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The samples in the training set are team agnostic - just home and away team stats and some interaction terms.
I experimented leaving out early season games but for some reason it doesn't improve the model. I know ELO models assume a mean reversion by 33% so I think there is some carry over signal.
Are your models hitting 55% on high conviction games or is that overall? Do you bet on your own or do you somehow monetize your picks? I also wonder how easily a sportsbook could detect algo betting. | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-20 | Z0FBQUFBQm9ORzh5T2Fkb0VpTVMxU0V3UjBUZTNQWlprSGZ5Wk00UU5tczRjbUQ2dm5uQVVpNmxIY2M4NUxvYkFjV1NqYW82U3VCYjZTR1hMWkttWElVT3RVczNTcjJrSFRHS3VXand3SU1TQUNfZHpadDNRUWM9 | Z0FBQUFBQm9ORzgxVXA3Ml9PY2ozUk40RWhWeFpEcWw0dWEzTFZNVnVEb3pKbml0dGZVQzI2cmhMUDJDeGZLSE0tVHRxSUNQX2R3QXg5d2w4QUtid2xNdGlad0lmWXE0R0JBQTdHYlNZdG5vWi1KUC1UN3o1Z3NwNUxFVVVmSzdaR2Z1Rk4xRmlPai1mQTRPbmhRSDUxTFhHVmNyOWFwQ1dkdU53YW1yYktlMXppTkJsNXJrcWljT2pzQjhiWE95UTZ3QnNQbF9mZ2FOQlU4a2RkVW9XS3YyeTZNRmVTRkZGbkJkenFsRFlyWWZ6U2tuNU5RX21vZz0= |
Might be a dumb question but can you stake BCH anywhere or earn interest on holdings? | r/bitcoincash | post | r/Bitcoincash | 2025-04-20 | Z0FBQUFBQm9ORzh5UWlQZkstY05tSmRkTFJWMkNmRGZ0NDJ0VFNPemU0UEpVQTZzNkpCWDMtUWZZRG1VZS14MlBsSHVDbTBIYzlZSUFVeUR5c0R0VWlYR0FoVWdOWmhoR0E9PQ== | Z0FBQUFBQm9ORzgxbVVSUmRpbXhyQmRDVUdmbTlPWF8tLXhkQ3VtemlPNG5VRXBSclFUN3BYemM3XzBkejFlVkluQU5ZVkphWl84VVBYNTJEYWtEU21aRzV0bUViYmQzYWNMeXNSOFZnVXkwRnVGSXNPZ0hPUzhUeTJGajJzcTA0NzRNWE5oWUFwRndjWkNJWGZmU3hvNGJqR1JfWjNYUzBnPT0= |
Yeah, 55% was only when I'd remove the marginal/early season games, otherwise closer to 53% for the good models.
My best models were either RNN's or XGBoost. I think the simpler you can distill down the features, the better. I found you can predict just about any team game, NBA, NFL, Hockey, whatever really, pretty well based just a couple of variables - you just need to know some general measurements for:
1. Offensive efficiency
2. Defensive efficiency
3. Pace of play/time of possession for each team.
4. Who is home/away
Then maybe a couple of sport specific variables. Fouls/getting to the line was important in NBA, NFL the penalties/discipline of the teams matters a lot. Little stuff like that helps, but I always found the more features I'd put in, the weaker the models would perform - using going closer to 51%-53% if I started just throwing stuff in there.
XGBoost is way easier to setup, you just gotta spend some time doing grid search to tune hyperparameters.
Using LSTM's/RNN's felt like the gold standard maybe 5 years back when I was really into it. IDK if there's better stuff out there now. The benefit is, you can sequentially feed in the previous games and discard the outputs, but the model is going to remember, or have a sense for things like "These guys got blown out as a huge favorite last game" or "They've underperformed for 5 games in a row, maybe someone important is injured". Stuff like that you can't easily encode in traditional regression models. Benefit is, it should gain a sense for when key players have been injured for many games without having to explicitly feed it in, and can capture subtle psychological aspects of the game like embarrassing losses as a huge favorite, and how teams perform immediately after, stuff like that.
Most sportsbooks don't care too much about algo betting in large market bets like Totals and Spreads. There's so much money on either side, they just want to grind numbers against a balanced book. If they do limit action there, its usually based on having a large sample size of you consistently beating Closing Line Value - I believe that is the only metric that will get you in limited placing large market bets.
I always bet independently with my own money. I never got limited like I've seen people bragging about on social media, but I exclusively bet spreads and totals, never touched any other bets. My main account did seem like they took me down from $5k to $500 bets at one point, but nothing like $1 max bets ore anything crazy. It was still workable for me. If they know you are sharp, it benefits them to keep accepting your action in a limited capacity. The earlier you get your bets in, the weaker the lines are. They can make adjustments based on where sharps are betting early in the lines, so they won't get hammered closer to game time leaving a weak line out there. | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-20 | Z0FBQUFBQm9ORzh5a01xODA4MkVUdk1GUFlodnA1dUxFWDdzYlpQV0NPeXFYQVFOXzNyRGktZFpCZGpxTHpFeFRBWkwwb2phdHZuMTlzTWpmY0VWSUNWNG8ydGNLbU9zWVE9PQ== | Z0FBQUFBQm9ORzgxZUVKSEJPanhrbEdRWDNMYzNzeENFMWY2VWdXYkxRcC15WWJhQXlZMkozS2FGbWtwSWVSNVJjMURxeEFoU01GTjhCc25lb3ZRX0o4dHdFTkpfZ3QzSVl5cmdEVFVhSkFRQTNTSmJGSzZoS21sblNsaG96OXg3ODg4S0haejJsdDZrVUVLdk42ZDJSdzkxYTlaWERLWkNVMUxJS2k2SEVndTRZc1JsMDJybFNkOEhxRFUwbU9vQTJBRHR1UC1remhibGhFZTRKQTdka2RueUlhQjdtR2pNdnJEQ1hTaDl3OFlmOHlUSU5iZ2NsWT0= |
In the middle of a bullish break out TAO suddenly became view only on my Coinbase. I can find better ways to purchase but still curious if others noticed this? I would assume it’s suppression cause they don’t own enough supply to lend out. | r/bittensor_ | post | r/bittensor_ | 2025-04-20 | Z0FBQUFBQm9ORzh5b2I2N2RkdlJpdnJJYUNGVXRxMFNuTU43bVdTeXJXWkJqY1Z3dUNDSlF6M1Z6VTlvVkhGbFk5UXRZdUhOYmRsRl8yZ2ROZTZIWnI1MW9tR3l6UmdEMkE9PQ== | Z0FBQUFBQm9ORzgxak1va0lDaFhqQXZxQkdhVUlFSnliUXlZZzlHTUFCXzIzY3Z5OThzU1RqTHJzVnBsVlVJNGRrTWJMcVdZRW1iOXlwZU82NDk5cUpXLTZRRmsxV3Z0d0NVOWtZQVR5c1Q2OWxQNzlCSm1Gcl9MOFVXYk1lNDlES2EyRWVlaVAzNThvNXg3YW1qdlV2US1FVGlSSzBnbHJJZGlKVWFmUDBodnVoemhpclpuN3VVWHNVRW56azFzS1dZOXJrMUx1MmV2 |
Could you guys recommend some well maintained and feature rich trading and backtesting engines? Not interested in HFT grade software. Some basic criteria below
\- Under 50ms to make a decision
\- Supports custom data sources
\- Broker integration (so even if I have to write a custom broker integration I wont be starting from scratch)
\- Python, JS or Typescript
Thanks | r/algotrading | post | r/algotrading | 2025-04-20 | Z0FBQUFBQm9ORzh5UU9oT0stazZQOE1hQl91Rm41UVhDSk9wMmtMZ0hlcVZXaWJobXgxd0pZNkFWLUdINUlWcUZnZmhwU0JUWHJSLVI2ci1tclJpUF9mcl9RdGRXYjRad2c9PQ== | Z0FBQUFBQm9ORzgxNzZ5U1ZsempKUjg0TnlVLU9id0tHNEtRdzg4VV9YVzNJX1dILXVIT01VaHBGY2NNTEFPeTZsMVBmRVFMNWg5R1BIZFdaNHhCRzhENHFocm1BcEFrdVJJM3VMYUo2MEVzcEtUVm1hVzVVYXpqVWtSeEJBeTdkWjZRYkkyeXV0bUdpbmxTczZQUzVSZkQ2UDRidURUbHRPdlVISXprbHBkU1AzRWU4YUE5Q3h3US0zdEZUWnhuMG14Ukw5eDBxa3A5c1RJQThqeVoteVdMSUQ1el9hMGs5Zz09 |
Please stay on topic: this post is only for comments discussing the uncertainties, shortcomings, and concerns some may have about Monero.
**NOT the positive aspects of it.**
Discussion can relate to the technology itself or economics.
Talk about community and price is not wanted, but some discussion about it maybe allowed if it relates well.
Be as respectful and nice as possible. This discussion has potential to be more emotionally charged as it may bring up issues that are extremely upsetting: many people are not only financially but emotionally invested in the ideas and tools around Monero.
It's better to keep it calm then to stir the pot, so don't talk down to people, insult them for spelling/grammar, personal insults, etc. This should only be calm rational discussion about the technical and economic aspects of Monero.
"Do unto others 20% better than you'd expect them to do unto you to correct subjective error." - Linus Pauling
**How it works:**
Post your concerns about Monero in reply to this main post.
If you can address these concerns, or add further details to them - reply to that comment. This will make it easily sortable
Upvote the comments that are the most valid criticisms of it that have few or no real honest solutions/answers to them.
The comment that mentions the biggest problems of Monero should have the most karma.
As a community, as developers, we need to know about them. Even if they make us feel bad, we got to upvote them.
https://youtu.be/vKA4w2O61Xo
To learn more about the idea behind Monero Skepticism Sunday, check out the first post about it:
https://np.reddit.com/r/Monero/comments/75w7wt/can_we_make_skepticism_sunday_a_part_of_the/ | r/monero | post | r/Monero | 2025-04-20 | Z0FBQUFBQm9ORzh5dG1WYXNfM2hoaXo2dk04eGVXTVBGZ0F4LW5RX3QyTUZUOWp6b0NidGJESjNfelRQQTJNX21mVEMtZHFDZWlKMFJtRWJrZk5EWHVac01HdlI5MWg2RFE9PQ== | Z0FBQUFBQm9ORzgxVUN4dTF6RlNTeDJXYTJMQy1oQjQxQUtJblMxR0hXdTl5cWE4NzhMdUZTQVpvUWJyclJMMnZncjdRWVlsNTJBSExvT3RCMTkybnJYUXQ5b3k3WHR2MG42eGN1VTE1TnhtdEljRFc5dDBFaTdkOTFXSUczMy1OdjhHblhPeVloVzV4UUFIUklWMlJ1dkpSREZPdHA0bERLM2p6ZjQ2c3NqdkNlQk1wMUpWQk55ZEpjZ3JBV0NUeVU4NnJHQWMwc005 |
A bit of context before going to my main question: Ive been coding in mql5 for 4-5 years now, mainly trading forex. I finally decided to try and learn python due to it supposedly being a lot faster for optimizations and backtests, and having full control of what I can do and how I do it.
I will focus on Indexes like sp500, nas100, us30 and some other like that.
I tried doing a small project yesterday in python where I download 1D candles from sp500 from 2015-2025 and plotted it on a simple candles tick chart.
Im having a bit of trouble of how to structure my learning and knowing on what to focus on. In MT5, The process was coding - run to make sure it works - optimize - robust test - run it live. Whats the process like using python? | r/algotrading | post | r/algotrading | 2025-04-20 | Z0FBQUFBQm9ORzh5Y2lkSkZMVzBlTWtNY05hTmdBOXVpRVQ1bUZPUElMWlJsZ1JEOUFPQllUM0NNYjRhbHRQajEzOUl0S21XYUF4eS1yeUFWclZIVTA1ZzUzd19IZWF4Rnc9PQ== | Z0FBQUFBQm9ORzgxRGJlbDhfV1VjdjVUd29TWElPM19XZFAtbEE2cHJmNnNDWFhVTzJ2TThvb2d1NkZPSWJkOGtpOTU4UkIzM21tRG14TF9jZk8xaXZoV2xRcVoyT3AtS0NJcjNCaHNlQy0wUGQ0YXlUcWpyT1F2cTExWTY2WDVCQkliSm9vWHZiMFcxTG1SaXZwS2E4MWxQRTRKMkktX2NSbVhxaHZ6QnVtU1dnRk4wX3VnTUpPQ3ZmaVdmbFdsUmpDUWxkR1lrMDAxcHMxRXFnZkd5bW5RTWUycVA1Z1dfQT09 |
I wrote an article about a mathematical side to ELO-based predictions in football - originally the model, having its origin in chess, accounted for wins and losses only, for football certainly there was a need for adjustment to predict draws too. I explain the details in my article.
I would really appreciate any feedback, whether is the explanation clear.
[https://medium.com/@aleks-kapich/adapting-elo-for-three-outcomes-modeling-win-draw-and-loss-8adcde60582f](https://medium.com/@aleks-kapich/adapting-elo-for-three-outcomes-modeling-win-draw-and-loss-8adcde60582f) | r/sportsanalytics | post | r/sportsanalytics | 2025-04-20 | Z0FBQUFBQm9ORzh5RjhneXBucHpGSVVoUUw2dWZ2eEQ1R1pWanpLWDBiUnA3VXpkcjViekhraTZtSWtZMDk5cUVPVEZ0elJnSmJkRlNDNDcza1Q5Zmpsc2lqeFNhWFFhZlE9PQ== | Z0FBQUFBQm9ORzgxcWtWNUY5S3hhNnNadFQ0YVlkcG0zX253TnR0Skd0RnJaZWl4UE0tano4dnNNdENJT1JCaXc2dFIwX25iMTA5cGx6bURiTmJsRlVUQ0RiZUdSMXBHbU42eTMyQ1pPQm1BYlFLX1JwTlpZQXBZdXF5OUFNWWI2ZFdUb0h5OWdHNWhfUmw3cEJqLUt5WXNBRF8yV21LZHhzc291eno0R0k1R2FSNWtFeHV0Y1AwXzN0Zmp1S0JCM01ONW14bzJkRlpGNVZBeW12cHRjMksweDBtcllzeHdWQT09 |
Imo if you're doing this, you might as well just use Poisson over goals (you can have correlation between poissons (by adding a third, common one), or you can also try correlated neg binomial). Goals are more informative than win/losses anyway, and this has a clearer interpretation over "playing well/badly" | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-20 | Z0FBQUFBQm9ORzh5WmtwZEFjeFVMOFdiYkx0OFlzUmljTHZQOW1hcThxY1RBVWxkS2xnY0JKbWo2SUJEOGZubTRDQnJLWWpfV1dyQXF6ME9UVUNQNldjdVp5MEItaERkVGc9PQ== | Z0FBQUFBQm9ORzgxVWRoUGUwXzJxWEJESXNFNVd2dXRYRUs4RExjTW8tVS1QR2pDcnA1S2c5YXVOQXdYVDlybTlUUGI0bVc0WUc0UklnQmdtQzFrRnFHY1lhNEEtZHQ5ZkNnZDlqWVItVGMxVmYyX3VSajFzSWotQ3B3NUhzRllZSmNBZFQ2WHhpWEtiTWF6S2lRYWdMc1lzMV9SX0w2aUQxMzdCdHJ6Zm12VlV2NnE3OVJ2ZlBRb0U2YjNkSnRMTjZZdVRUYlV0RTk3STNjSTFLckk5anlWR3F5c0hsZlptdz09 |
Depends what kind of data you are looking for and of what quality. You can always try something like Opta but you will probably go bankrupt :D
Used Highlightly in the past and it worked nice (live odds, predictions, stats, lineups, etc.). The only downside that they have is that they do not have player stats atm. | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-20 | Z0FBQUFBQm9ORzh5VkhtWkI3NWpoRXgzUXJNNVJXajdBdTlSazJleGs0TWRoZHlOZ1JMY19sMzh3VVZURnM5RjVTcFlsU3NGajdxazU2YkhtZzB6MVh6RHBlTl9GcXg4TFE9PQ== | Z0FBQUFBQm9ORzgxTXBsSTVwc2taMXpUSjBrOGtTbnV0WU9kX1FKeFE3NjdWR2h6M2xTaU9tOEJ5X01zREpIWHA3V0ZvSWUzeEFYWTRUTDduQVkwenpZS2FMY200R3hDQmJJZlVqQnJCdW5VQ0ZWSm9fcFFkWDNPOHBLZ2xYVThZRkxXazBQcXRzQTBvR1pOdzJ3WDBfYm9jSW5mODdxZEhLTWRyeGQtQWNFRGQ1QmtRME1CNWVLSmh5aGlKZXJtVF9Qdm51NGxweVQx |
I do a lot of automated trading with various strategies. Lately I have noticed that for spreads I am having more trouble getting orders filled with IBKR vs TOS. This has led to quite a bit of opportunity loss in the IB account lately with all of the volatility.
As an example, I will find mismatched spreads, TOS will get fills and not only will IBKR not fill but it won’t even fill if I shoot for above the price TOS is getting fills on.
CS/TOS seems pretty good. Neither will let me put in an order to open a put spread for a credit, but I have entered orders for 0.00 limits on TOS that filled for nothing but the commission for the trade and occasionally for credit.
So out of curiosity is there a better platform for what I am doing (automated trading of vertical/diagonal/horizontal spreads where one or both legs are mispriced)?
A few people have talked to have mentioned Lightspeed, Silex obsidian, SpiderRock and Sterling.
Just wanted to ask for advice as I would prefer to not spend over 500 dollars a month on trial and error. | r/algotrading | post | r/algotrading | 2025-04-20 | Z0FBQUFBQm9ORzh5QWlTcnZPT2I5Q1psY3RNMmtwVzVsaWNzREZBUFJheTV5SWxwZlFDNjZxYmgxcW8wWjdxSk9SUFliWmhua2lCbjQxMlF1WGZkNkRHbXRfZzhEUnZLbHc9PQ== | Z0FBQUFBQm9ORzgxdUlSZV90M1N6UFVKYXh5NVF3Z05IdmhsQ0VvS2VlQTlaVDllUUQzMjFvSDJKaFVzQXFWREUzbFptblFPalhLRFc3V05zOU5xZV9uZ1pXZUlBTWdBYkxRNmp1WmUxRVB4dTlaSE5KRVBGZTQ0cVRTc3BnTDZfemxHd3VVbEg0MnJkSUhhQzduTVRGNzFQUlc5bTdVYkk1bHBjZUZzMV9iSUE4eDdaWF84OWRrPQ== |
Curious to hear from others who have built their own trading bots from scratch. How many hours did you realistically put into your system before it was fully executing trades, logging performance, and running somewhat reliably?
Bonus points if you're willing to share approximate win rate or performance metrics.
If you consider your bot a success or still a work in progress?
Any hard lessons you wish you learned earlier?
I’m deep (500 hours +/-) into building mine (margin trading focused with SL/TP syncing, database logging, UI, etc). It's been a crazy roller coaster with way more hours than I ever intended and I've barely scratched the surface.
| r/algotrading | post | r/algotrading | 2025-04-20 | Z0FBQUFBQm9ORzh5R0dWc2xSQ2dySDZxQXFSZ0xvSE9GSlAxYktIRUJDd05QcUFMT0ZSNlEydlpRUkV5NldmajgtQXBvYktJa19GVXo2d3N5bVA3bXhJTGFXU3VIMlhrcmc9PQ== | Z0FBQUFBQm9ORzgxVk45NWRIQk1DU0ZqQzRZb0YyX2o5Z2JMbmx2SFV6SWs5WEJqSElfMGNtejd1Y3pQU21CTTN1bmV1T1puNTAwSy1nRXA4Z2toNEFTdFh6RXBZLURvWFRTVHA0OVlwcE5Xb0dMSm1veS1zOWdWdlYwT0UtVUp3OXo1MFp6VTBmMWg2MklabjFnekc1a0MwTENwbm1jcDg4ZUt0dWN4dmZlTl9Vc3VSc1V2RUxGYzRnbFI3UnE3NG51YUtHRUJmaXdUSkF4X1NpZng1WTNLdHAyQVBjODk1dz09 |
Hello,
I am a fullstack developer (Java/Javascript) and I have been playing around with MQL5 in Metatrader expert advisors.
Therefore, I do have coding experience, I am just looking for resources that would help me understand how to "think" in trading programming language. I struggle with converting trading concepts (say trendlines, ranges, series of specific candles, double bottoms/tops, triangles, etc.) into MQL5.
Some stuff I can attempt to do on my own but I hope there are some, at least community-based, standards or recommendations how to code these things.
So I am not looking for basics, I am more looking how to teach myself to transform charts specifics patterns/concepts into the code.
Are there any resources/tips that would help me with that?
Thanks. | r/algotrading | post | r/algotrading | 2025-04-20 | Z0FBQUFBQm9ORzh5eXNZSDh1alJIVWVHejFvQXVJMFdPUmF4NmlKcnF6NEF0dVNsU19TZ09xdFZ6bjJHUWcwMm5GMjlDeFJGaC1HQVVvaWtPWjRLSTdzemduX0dRbWJCbHc9PQ== | Z0FBQUFBQm9ORzgxeDNLeVllbjdKdTU1ekw1NWxYWTBMT2xlMmctVEZvZzlCODNzU2VMWVR5WDR1eUtVS1pPQUZhQ0tuMGQ0TEN0NlF0dXJxZnREbUlRRDZGb3ZBMzlLMW9IM01CbWoyRldaNGMxeUdrbGdyM19naFp5bGRkRkNYeGcwUHI0VzU5bTBCck5TUkxQR1Qwc1dTdWhEeXV4SmR1dy1LcWdLUHFEYUUteXZpQlFRdVljdjRlbWJxR3hNbmZ1cHdkejlKd1kwV19tR0hZZW1hTDgxM0NhcWZsR0hmZz09 |
What are your opinions of subnets value coming into the summer? Do we see the prices retract toward 1.0 TAO, or do we see 1.5 -2 + and higher?
[View Poll](https://www.reddit.com/poll/1k3uvf8) | r/bittensor_ | post | r/bittensor_ | 2025-04-20 | Z0FBQUFBQm9ORzh5NkZUY083X0RGYnJNUTQzZU9hS1c2TUtHTHg1WGlld1hxaE1pSUU5MFE2MjEyRUVvMDZ5czNEWkN3SHh5ZHh4OTYxSWplcGtRd0xfeHlQdGtEVTFWY1E9PQ== | Z0FBQUFBQm9ORzgxdll3WFFEdWVfdzhkVy1WRGh1UGExRTY3RDA0c3dFUFpPTUw1bTVpRnl5T2gwU3dRRXM5SXhwUHhWcDlocHdCY2xmSVdmM1BUSnh2cXFKeHZ1cGduZGtTQkxXMWRBTXdBYnp3cGNBOXV0c1NwZ1ZGdXZ4OGlnbWFoWGhJd1MwNElWODdpcUk4aUtxQjljWlFxbFpJNnZDTmNhajlOa09LVGdTZU1GSGZMaFJZeVdRbVN4TGtka2FOXy1Na1lQVFp5 |
Shitcoin | r/filecoin | comment | r/filecoin | 2025-04-20 | Z0FBQUFBQm9ORzh5MTE4RUNySXJXd1pjWDBFd3dLN0I5RjJkc3BMQWpnOGpINzJScTItOUZ0a3JCc1AzWWRUemE5ckItdnRLWTVXazUyek1IUFV1bDF4czFneFEtRmE2SGc9PQ== | Z0FBQUFBQm9ORzgxblIwX1Y2NzRIalNRVWk1QmYtT01NZ2FqM1VYRFZUOVBJN0lDVnFiaEc4eFJidk5oVUh1OFlxZWJwQ1YyM2Y0NnhreXFnZUFRcUprMV9iUTdqTXFiZ2ZRNU9OQWtXcVhLVkFXS1NJWE9SejNTUVM2MzNfaEV1SzYzWFFoNjRpTzNqYW1HY2cxZHdmY3NFNHNTRGMzd1BvRnJWV214SWxLeC1JSjdJWm95UGxsaVI0VDh3THJqNG9VTURfcnJrdkM5a3prSkJkQkFMc2NuR05sV3M1MzhKZz09 |
Spamcoin 2B supply.. | r/filecoin | comment | r/filecoin | 2025-04-20 | Z0FBQUFBQm9ORzh5cmM1X29iakRteTZGbmVNNk5MTmlsWi1hbUFxdHo1VV9aeTFTZWxtYmNuVk5OU0R2aUF2eVZkU0FfaVdrYWItN25Eb1dtQTE1RC1kR1N1WUFtZFp4OVE9PQ== | Z0FBQUFBQm9ORzgxeHd0bEVmd294YUJvV0JyQ2xpQmo2QTdSMWdVQ002RU1JVC0yZnBxNklxWDBwN08xUDNtNWxkR1VfTldEbnFsYkFTZEhuTW0zMnlHTU9OdW12M1lLRFhvaUtiWm1yZ2prLU1qVFdSTXJVaVVVTm1vNno4UnkxSVh1akRmZXMwemdrMEpCVmV3TVNkeS1FV2JGM3N1NHdMRXZYX0lhWFREeHZERXFDNnQ2RXFOWVhfYS1ZSzRiTjZuWWNuX3R2UGNValFNV2E3d0lCUVdhWS1GYVRNNmlHQT09 |
How did you guys started? What resources (courses, programs) have been the most impactful for you? | r/algotrading | post | r/algotrading | 2025-04-20 | Z0FBQUFBQm9ORzh5aVN4anZKZm9HbXJzckd6Y0xraE5pV3BjVmhWeHA1NUVKQnlzZHRudXRxNzBPdkFPQTNuUEQ2RC12bnBWRTR5Umc2RVVvQlZ3TTBWUWlpYzJPNmZnNnc9PQ== | Z0FBQUFBQm9ORzgxZGdtSDR0YzRjQVl5NExfTUxnRWI4VmtUNWY5Q1luQmhLa1FlRERvMTlsNHU5WWhvTVBrZ3hTajVwYkl1ZTZQZk5xM0ZOUEdoQjMwQ0d6ZnZralRoaW5TRjdzTUkybXp6ak5yRnNnMmRHd1JvQnlZVWpCX2p6aDlvVG5xcENtSkRxd0pYdDhDOG5QeGkyWWNoSm44aGFVQXJzdWw1QzRTamJkdjVBNnc0VVFCN0FidGRIRHJLXzZ0THUydmlMOC1V |
Yes | r/ethereumclassic | comment | r/EthereumClassic | 2025-04-20 | Z0FBQUFBQm9ORzh5VjZsd2dod0tIM0pscGhJdXh1S2otWFhSdlN1Mi1kSWlvSC1jZ2ExVi1MQkVuUk1QeHIxOG11S0JoVG1oc0pRZjdrSFdQT0c4ZUFZVVYwMXpfM3pOZVE9PQ== | Z0FBQUFBQm9ORzgxYWRaOVhJRlc4QUNFZ21PVUptN2NFc2dTanpGYWFjUDJ2SFpDN0F4NEFKSnRZcDZmckR2c3lZU2hHcS1nSGViMTJ0cl9DTTJ1NkRDcnJ3Z0FNek45R3k3MW82cVREbURKUXUwamQyaFBNSHI1V25WdnhrVkRKRVktUzlJM0JIVTMzZldCWHVhUV82RGVVS1JPTzlFVWtzYVAteDFvOGd3d2tES1pBYXVqbFhwRGJOLXZTcHBZRU5VcUJvM0NhUy1rMERrdl9EQkMwSUlpY21aS1N3WEJOcmRpRm9HTkQ4UmJmQjdNbUVTUzBPND0= |
Solana or Filecoin? | r/filecoin | comment | r/filecoin | 2025-04-20 | Z0FBQUFBQm9ORzh5TUhGejBaSXdXWHhJYUM0dXhfMDhUbEpabGpKM3hyTS1XeW1LY2pFbVNSRlZDOFR0X0EyT0l5Q0F6SkdYRmdsRDZ2STFuYV9WR2lxX0FVNm93dGYyRlE9PQ== | Z0FBQUFBQm9ORzgxZDBlTmRPbTA5U2dyRXl0SnZtbXd3bVNtMjdPdHlKclhyZkFvbmdRRUE0blB3RUdDMFJ0OFg4XzFYZzVEY3ZDZVBLZF9oVE01aEt0bExqdnJlNmhRTnFkbnBfTUtlcnVvV3Jya1Jsc1dfM0diMjJuOXlxcWFxaEVoVE1FQnpfamhKTGN5eEl3Z1gzaERvWDdrSDM2U2RDR3VBVThYcW0yTmlnQnk5bWhkYjdUVWtlNERnYU9QQXdSVmtQUlRDLUZjRklzTXdMQUUycThnV3NYVklhN25LZz09 |
I don't have any expertise in algorithmic trading per se, but I'm a data scientist, so I thought, "Well, why not give it a try?" I collected high-frequency market data, specifically 5-minute interval price and volume data, for the top 257 assets traded by volume on NASDAQ, covering the last four years. My initial approach involved training deep learning models primarily recurrent neural networks with attention mechanisms and some transformer-based architectures.
Given the enormous size of the dataset and computational demands, I eventually had to transition from local processing to cloud-based GPU clusters.
After extensive backtesting, hyperparameter tuning, and feature engineering, considering price volatility, momentum indicators, and inter-asset correlations.
I arrived at this clear conclusion: **historical stock prices alone contain negligible predictive information about future prices, at least on any meaningful timescale.**
Is this common knowledge here in this sub?
EDIT: i do believe its possible to trade using data that's outside the past stock values, like policies, events or decisions that affect economy in general. | r/algotrading | post | r/algotrading | 2025-04-20 | Z0FBQUFBQm9ORzh5VDAtREZvaWhUMEZSZzFmb1pURWwwNE05bnZ3UVFMUmpRcHhXc0UtdHZGc1JjOW1TY255eVpwSmZfdVFxZWxCc1RVUndVRENwOV9VUHdFMS03SUhnZHpKRnd3Uk9pekpObzNyM2QtZ1Y1QjA9 | Z0FBQUFBQm9ORzgxSC1mX0NBZGdxUTQxRjB0eHllcEViNmxJXzJ5WkRNc0daNTdYMk9FYUgwQnZQaXp0MHlTVDNzdVgxTllYTUJJUE52ZWM1YUc4bXBNQ1ZSMzBKVVBISlQwR3JRSHNXOUhUTTFSRG9mSlVzT2hNaXBJNWd2QXVELXdnbURqZTE2UmpsNVREeXE1MENuV0tucHFDejZYZW9BdWk5bWtpOGU3S1NsTnVVaTBqN0JNMk1OMExYTmlTblBna3c4LXR5YXJX |
Hello am Eric from Ghana please need your help | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-21 | Z0FBQUFBQm9ORzh5c281aTZMM3FzSVM1YmhEVjFzN05UQ1N6NjV2dlR1dWNBSnNBUUU5ZHExdUE3UldYX1JLb2JRQ1kwa1NabVJxXzJ5RWtpNUUyRzIxMVEtYld4ZHhwWlloLUxiUWJGeHJRRTNhdHZUc180MFk9 | Z0FBQUFBQm9ORzgxODRKU3J1OWN1ZUFITHMyRlJWbzEzLU0tY3I0azBYRmtEc0FkdGxqUkZDRXY4TXhOcHJOVHhrVF9UcjdqR2J3bXh6bGR4SVI5SFZqbFZDVEd5cTVSZU42eTNzYVBTVHlIT01GODVLcVV1XzFQLUppLUV3YWl4THo1RThia0VMei1aYk05WGstSWJSVUREeEF5M3YzZllGWmNsa1NQMExfSXhWUjBqa1YtLTQ0Ml9nTktvRjluejZFQWtVajNIYi14 |
Little intro about me.
I’m quantitative trader for a crypto firm and I trade forex manually on the side
I’m looking for a great dev to work on Developing a Fully Automated Strategy with me in the Forex Markets
I’ll need help in developing the code , since I have less time on my hands.
In return I’ll teach you the strategy and the mechanics of it and how it can be used.
The strategy revolves around using some Technical concepts such as using Fractals - Deviations from Fractals and buying at swing discount and premium levels at the base level.
Rule based strategy
And already have a well detailed journal of a 100+ trades.
Would want to work with someone who understands the basis of the forex markets
GREAT in coding with any sample projects ( PYTHON / MLQ5 )
And Basic understanding of Technical Analysis- how to use Trading View
Will be a great project for both of us 😄
| r/algotrading | post | r/algotrading | 2025-04-21 | Z0FBQUFBQm9ORzh5Y0RWbTkxaUFYcXJvaHJDZDlOUldtOFVNTjF6a0hhZ2k2emRsZjEzVXN6ZWhtRWpYVkItckxoSWpVRXdJeVowNFQxQ2VkSXRmVkt2UzcyaWRaZGEyQ2haYnM5RUFyN0M1d2JKdmt5dFl1Z3M9 | Z0FBQUFBQm9ORzgxMXA2bm0tM2ZDRFBWUkpuR2V3MnNNX2Y0S0YzdDhFVTNHRzVDMngySjExWXNrQUt5NWlRc2VXemZ1dVlITGFmcXBJbzRaN2lRQTN1dVFNWDZHcHZyWlVHOXA4bGwwM1JEaUhUTjFTQmJXQmNjMFlFQjR1WksxTFFHcmFiemtXclFxZzNFUnp4LU9vczZiMC1ZcTZPUXFCb05yR3BLSnc4dTZabzg3N3RkT3BfM1l6cDNnTHh0aEUwUTFsanB5dW1K |
Chutes is 'serverless AI' providing 'instant on' AI model hosting (DeepSeek, Mistral, etc.) for 85% less cost than AWS. | r/bittensor_ | post | r/bittensor_ | 2025-04-21 | Z0FBQUFBQm9ORzh5M29NU0Z0dFJnekNab3A4d3FOYVdLaW5ORW5RWWh5Z2w5TnJJS3p0S0VpUXAzaS1RTnNqOTJsY0hfNmFycmdtNVFWdHV2bGlxTDNIdFc4ZDh0TzU2akE9PQ== | Z0FBQUFBQm9ORzgxRUZaYjhtelJDWE9kNWsxTVJRM3BRZDNwc1lqQy1weklBcjI5d043N0Nva3dVRG96Ny1SeWQxNTNjLTFSdFEyMHhEQkpKTklUcG9ZalM0ZTFrUjVEOEZYNmZuTllYeGpMVk5PMU1IXzNHd0U0RlFtcmM0alhNVGI5LVRGLVgxSVhCdER3TkVTMHlDR2FyRzM2Q2habGdvV2JURTg1SVg3a3l3UDVrMTVTTnRHRFVtbTBTUmpveUcxdmliX1ZOY0FpOEQxRUxibjRSVHhfeEFIaHppdUMzUT09 |
Funny enough, Highlightly NBA, College Basketball API has NCAA offered for free (not NBA though) but the number of available daily requests is only 100 (docs [https://highlightly.net/documentation/nba/](https://highlightly.net/documentation/nba/)). | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-21 | Z0FBQUFBQm9ORzh5eFdoWVhBZ0lMUkg5bHYxcVhabERiZXZWS05udTVwS2tncjY4a1NxYjBGU1hLY2szbFFqeVQyVnd1QTdwbERrTWJzc2hKWmRoaF81b09hUzJSS2djTWc9PQ== | Z0FBQUFBQm9ORzgxbGpNR01ta2U3YVNwRG9vWTJsZXBSaU9lTFRIOWdFV25yVDFPZWlhaHEta2FnUHhGcXhDVjFtMmZkMW5mVTh0WGhOZ2FlQUVQT1VfSGpmZVk0WHI5c2xKME92WEV5OG9PWXhMOU83aTFtQ0pURG1BY1Q2NmtHN2R6VzMyRWVoZVJsNllvX3ktaEV1dmZKM0tiLTVCYUtBVGJZQlZfNmF1dVFQeHFCbE5ETWpLZFctZE1BZ3ZYbGhpUXk3MDlraW1h |
Highlightly NBA, College basketball API is probably the cheapest option out there.
The data seems quite packed, but for me the highlights are the best. | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-21 | Z0FBQUFBQm9ORzh5SElDNXlDWEw1MkxYYXdob28ydXdJUU9RVUpBaEsyUmhmUEFhZUZhT216VmkyY3VyUDFrakplU29uVDJsRUlfSWZNZWczOU5CNTJNcUtJYmRmLUU2ZVE9PQ== | Z0FBQUFBQm9ORzgxdW5JS0tGNnNZQ0ZLaHl6bmYyckJqN2hUTmhjaHE2WVJvS0RrNkJqUzJzQTNhejlDbXpsWTBpbUR1bHpzdmVtM0VIVDVhYkJfYWZXMjdvQW9lZzRNeXZuYllIdjFyYldqd2d5NHdfN1FfMkU4UlJnT2dMNDZyRGg4SWxvRERId3c4TVV4Qy1RMkxXRHJaM3J5QXU4SUd0aENDNUlwdjJjR3U0ZTdpaWpFbkhBOUttOHQwWEVpbGJERkV4U0tlZXVYTXhGNHlacXU4UDdWYWlyR1FNd2Ezdz09 |
Given the success of the previous MAAMs ([see here](https://www.reddit.com/r/Monero/search?q=maam&sort=new&restrict_sr=on)), let's keep this rolling.
The principle is simple: ask anything you'd like to know about Monero, especially the dumb questions that you've been keeping for you every other days, may the community clarify it all!
Finally, credits to binaryFate for starting the concept! | r/monero | post | r/Monero | 2025-04-21 | Z0FBQUFBQm9ORzh5MzdVNm5YRXR0cmFYVlRMdTBheVJUWG0yREhtdUluR0tVY3RVLTVxeUFpcS1WM2xOT1g0UTVqOF90SEZIRFFnQ0NKNWprYU5scXVwUlludkducXJYbnc9PQ== | Z0FBQUFBQm9ORzgxM1RpU05iV3gtQnRWc2xXUmhsT2NiSzkwdER0X3JKOUItRkFTdGttTVdWa3dWMENSN3hmaG5Bb0hnXzY4X3dyODJDVTBTeTY4RTIwVnVEQXQzU2RNQWVOUHREOHRxWHhBYnZGTFIwNHlHNkFibkJCVmpPY1BGeGV1bDl0OE9Rb2NTZUtkS2hpT0psLWQteFRTWWxvLXFrdll4OTMyRjZMMWw5RDFQeWtLUmdyXzN0R0J1YWV5RDJoZVdwZ25qR3hf |
I have been developing algos on the side for 2 years now. I have noticed that most of my algos have performed better since 2016 on MT5 back tests and are consistently profitable - but underperform on data going back before 2016.
Various strategies fail from 2010-2016. These strategies trade the dollar major pairs on the 5 minute timeframe.
Am I right in assuming that the historic spreads were higher in the past - and trading conditions have improved due to broker competition and that this is reflected in the performance improvement post 2016 back test data?
| r/algotrading | post | r/algotrading | 2025-04-21 | Z0FBQUFBQm9ORzh5NGk0Y0M3VHVTY3F2TW5UTlJBa2s2VmhGTVpxeWkyUVVBYW8yMU51U3RHUkZGcFpuSnBmejIxLVZLM2pobW01ZExpcVlUZ0VINUZsclRReDhfZE44ZXc9PQ== | Z0FBQUFBQm9ORzgxaF9Fb1AyYkhBWmFUYjFMN214M0JoMHdGV0Fod0xtOEVSTXpzaHY4d0ppZVRlZ2dGU3Y5cUlVbkIwRndRWjNqaGtyWjlIRUpQN2F4ai15clRFYWFNTFlvdUdJby16Y2Y3d3dIQnNqTHBsNVo5cFBuX2lESmNaeDQzMTBKTld4Z2tuX0JoSkJOaVkyT092SW5ZOHZfaFhkV1haaWxFMmN6N1B1c0kySGpyVGVrNEFEeVY2N0o0ZkhZZDY3RDZvMkF2OWZCWDB2bFB5Y3VSOHBpRk5RdGhjQT09 |
Hi there, I am very new to algotrading but have years of experience coding in python, ML and data engineering.
I am struggling in the choice of broker / api to make a bot execute trades. What are your guys experiences? And is there one where I can do paper trades maybe?
Thank you guys! | r/algotrading | post | r/algotrading | 2025-04-21 | Z0FBQUFBQm9ORzh5ZXZNTXJZdkJ2ZHViWE1CSnR0M0ljTWFzV0kxVUpsa3NCNmZKSTZvWXJrZ2dLb09JWWY3dnJRcE5MZDVhUENWbUt5cThYcXBVNXE1MVZTYUNuVHc5NlE9PQ== | Z0FBQUFBQm9ORzgxQmFjb0dWOFZ1cFZYc19FUGpOQktaN3Rwa3c1NGdKWk93WTBJWGlOSWhDRTFKekJ3NlRyblJKcDM0ckp1Si0zckZfMjU5dEd2eG9OVW91SktvdjNVNk5yVXo0RDVVQzZOVFN0WEh5dW9XRy1DR3ZuZW5TLVpyWG1IcDA2Z1FCTEt5b3hnZlh0RnpJbmk5MkRvVUZXT295YV9ERV83UFdjaDNtaGcxMnVJZUVaSlRLT0F5eHpLRU9HajhtbWpTWWdp |
r/algotrading | post | r/algotrading | 2025-04-21 | Z0FBQUFBQm9ORzh5TXhWVjNHeW1zN3lYQ0g2c3pyTmZrSXRkeEFGbXBTb2JLNUNwaHlITUFaZGNKTTRtT01sVUxqYlFMZ2JQUEM5U3hRdFF3V1NpTFR3RndENmprbGFyNHc9PQ== | Z0FBQUFBQm9ORzgxbE5YZWJxamwwWmRSRG10SEdQUGVMYTNzUlRjLXdMUHgxMTBwbTBsUEV1QjliQy1lSTdQbXZ5cjZSZ2xtQnBoUTBOMFotZlZJVnV5T1llbjBqUGdGQU54X1pVYUFNMlV0OUpjT05GZjFpbzQxUFktajVhNm54Q0w1Y2hPQkJuM1czb1NpVi1vQTBZVUxBdTk0R0U0T1YzTi1PWWhSQk5SSWFFSFJOOFhDVEh3PQ== |
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How do you keep up with what to do with your Tao etc there’s so much going on I’m feeling lost 🙏🏽 | r/bittensor_ | post | r/bittensor_ | 2025-04-21 | Z0FBQUFBQm9ORzh5SlpwNDBYUlVZTlhvdVVFOEZKRXBrcGV6NXgtMWFWU0VvRTVQRDctNVRCZUpBamI4R2RBVWJJN2luZmFNejB5MW44Q1c3dDhiUkY1WVprNmZLSUhjcVE9PQ== | Z0FBQUFBQm9ORzgxOFFUaDg2Z1BhYlVUa0c0SW8xVzBJZ0pkQ2k5ME1XVXZwYnlScDZjQVJaWWZIVVgxWmFZVUhXYklaUkdONmpBYnBXVTdVbXlQTXkwWDBKUy0wSmthTlBpN040cTN5bUFkMTM5RDZkMHdYX1BFR1VqVzFoQVVKNTNQeGZXSHk2WnJBdTh6NVIweFJPdklKX1ZMXzBXNFoyTXJ4YkdWUlB4ZEcxZExUZ012NGprPQ== |
In forex you can get 10+ years of tick-by-tick data for free, but the data is unreliable. In futures, where the data is more reliable, the same costs a year's worth of mortgage payments.
Backtesting results for intraday strategies are significantly different when using tick-by-tick data versus 1-minute OHLC data, since the order of the 1-minute highs and lows is ambiguous.
Based on the data I've managed to source, a choice is emerging:
1. Use 10 years of 1-minute OHLC data and focus on swing strategies.
2. Create two separate testing processes: one that uses \~3 years of 1-second data for intraday testing, and one that uses 10 years of 1-minute data for swing testing.
My goal is to build a diverse portfolio of strategies, so it would pain me to completely cut out intraday trading. But maintaining a separate dataset for intraday algos would double the time I spend downloading/formatting/importing data, and would double the number of test runs I have to do.
I realize that no one can make these kinds of decisions for me, but I think it might help to hear how others think about this kind of thing.
Edit: you guys are great - you gave me ideas for how to make my algos behave more similarly on minute bars and live ticks, you gave me a reasonably priced source for high-res data, and you gave me a source for free black market historical data. Everything a guy could ask for. | r/algotrading | post | r/algotrading | 2025-04-21 | Z0FBQUFBQm9ORzh5S0FjdUx1aGNTQmtUOXRTckhOUnY3NlM3NkZnanRsdS1kZDdKb29MbkNVZDdVck1qNVVnX0Yyd1JCV2UzUFlfXzdqRWIzdFBEYUNaZ1lPaHEtN0oxLWc9PQ== | Z0FBQUFBQm9ORzgxRTJLMm5va0k4bzcxcmNPQ2ZyVzFOTU1VX1pXQzFtUTVQNWplMHk0a1I1MlNDYzdYM3YtM3dIcExRNlhfR1JWanBObDBhSjc3SF9XaVhkdkMxdlhtNktsaXhrNHY2SllIOFJoUFBkYmhQMFhyWjBhdnpnV01KMEtqNkRVc3dIaVpwM1hiTUlGTV9OU0w2cG0xNmZKODNGSHBvRWdSTTlGQ3FSZloyNk82M2tORFkwUEg0TGFhMTNwdnE2X2tjdTZUYmx4dTlGSTNqTW1SZXFsOW5Hc21tUT09 |
Thanks for taking time to take a look at the article, I appreciate that a lot. Thanks for the comment with hint.
Actually I've been using Poisson in my simulations, but wanted to use ELO as baseline to which I adjusted Poisson parameters. I described that in other article which I finished today:
[https://medium.com/@aleks-kapich/mathematics-behind-predicting-football-results-the-poisson-model-skellam-distribution-elo-bf50b8c5727f](https://medium.com/@aleks-kapich/mathematics-behind-predicting-football-results-the-poisson-model-skellam-distribution-elo-bf50b8c5727f) | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-21 | Z0FBQUFBQm9ORzh5WGRmc2tuSmh4YXhsSXFDZlhMWU1MUnhpeUNMeG1vVk5CeFlBVUZpdnFXOXpsalpoRGZKM21MaVJVTmlidkFaTk91bTBLQVotdGFzNVA4R19xMXFKV2c9PQ== | Z0FBQUFBQm9ORzgxWDh6WURua3p2NDRUcmpFTWdvQkJpc0VQZlI0WWd0ZDE5NmNTc0FIdEUtTkNmVER1a0tCLXdnaXRnSmM2UVMyZFBUYnBrRzRmTnc3YzNMYlJpTGhiOHFVaGUxWGhLb01lRDJpbTlnRmozVGJQdy1aM1pGR0JxQzhZaWJESVZic0IwejJVS0E2QV9nSlVXYXhlZjUxcjZBSEtHXzVQSTB3anRnSVVsbDVCTk5BcXhOb01EczZjeXp2UTkyeDQtSzdLUWFIVlhjUVBUUFNhbWVVZnNYc0w4UT09 |
I'm a beginner algo trader in the process of coding a small framework for training a python model. I'm using the TemporalFusionTransformer in the PyTorch Forecasting lib. I'm trying to build a sub-framework that allows me to declare various data pipelines that massage the data into a format that the model can use.
I've learned about all these different types of operations, such as filling, centering, scaling, various transforms like percent change and log returns, indicators such as SMA, and normalization.
First, I'm wondering about the terminology for all of these various types of operations. What are the terms used for each of them and perhaps all of them collectively?
Second, is there a python lib that does all of these things? I've seen libs like pandas\_ta that have some things, but I'm wondering if there's one or a handful that folks here really love?
Lastly, if anyone just wants to share transform pipelines that seem to work well for them, I would really appreciate that. I'm particularly interested in how more experienced traders handle different types of financial data (price, volume, volatility indices, breadth indicators) in their preprocessing pipelines.
Thanks in advance! | r/algotrading | post | r/algotrading | 2025-04-22 | Z0FBQUFBQm9ORzh5NS1DbXBlUkJyTkFpa0liMlJmd2hJSEE5aV8xQVpLbThyRU1HaldrTjNUNERpUzgwbG51X3dla3M3bGJmT3BQOVM1NkpkOE1GMVREUm1WeG5GbjhZTmc9PQ== | Z0FBQUFBQm9ORzgxVEZmanN2WU81Q0JmdjZKaHQ0aHh5WWNma2xMdlVVM1VpVmwwM3JmMm1aam9nWDdqS2RySlJURTRpQnB3eXp2UkY3cFRITEVDMzdIVkE5c3UwZmVKZ1FhaXJzbFU0NG5WSDhWUlpiZW5qcDJhLXlKQkVJOVRVbHRJdzFSSWVobWZkSnA2U3duSmNaQkoxQnpmTkF1YnBDdDN4UVB3dHdJa0FhbmNzT3RwcjVVUDVmQ2N1ejlhd21CSElMRWZuNmxqU2w2Wk93d0JNNGd2RTFWSXNqWkFtZz09 |
I've seen a couple of posts asking about storytelling resources. We just completed our *Data Storytelling for Sports* email course. Below are the quick-hit tutorials that accompany the newsletters.
1. [Introduction to Data Storytelling for Sports](https://youtu.be/zy2kAGRsNk0)
2. [Exploring Sports Data to Develop a Narrative](https://youtu.be/1SXQ88hWvME)
3. [Data Modeling and Analysis for Sports Data Stories](https://youtu.be/8m2iWX2_2lQ)
4. [How to Develop Your Sports Data Story](https://youtu.be/nw_KA8MdE8M)
5. [Translating Your Data Story Outline Into Content](https://youtu.be/T-2QspzzmsY)
6. [Leveraging AI in Your Sports Data Storytelling](https://youtu.be/ObALkTPqUNc)
7. [Creating Your Sports Data Story through Socials](https://youtu.be/8DaGofLyRgo)
8. [Creating Your Sports Data Story through Infographics](https://youtu.be/XxBmFz_yVZs)
9. [Creating Your Sports Data Story Using Power BI](https://studio.youtube.com/video/284p-F64jSs/edit)
10. [Creating Your Sports Data Story Using Video](https://studio.youtube.com/video/uN3j-R6b5V4/edit)
The above are all public access, and you can sign up for free for more content at [https://www.datapunk.media](https://www.datapunk.media) | r/sportsanalytics | post | r/sportsanalytics | 2025-04-22 | Z0FBQUFBQm9ORzh5MFh4MTkwRll0S09MVVNEOVBoM1BlNWN5SjN0d0ZsekF3WDNmbnN2cTJvSnpLM2ZtTmJFY1BKY1pQSHZBdnI4U21rRHlCLUozQXBGNXNtV09meFZzZVE9PQ== | Z0FBQUFBQm9ORzgxUmhTS0R2d0NhNk13dzlWM2tTYXhiLUc4XzNJNmtERlVXcGMxRDJnUDdFeE1IS25DSkFtX2ZtdUg1Sk1mMENldWNiVnZlSEJmSWVQVWotUnB6WkduQUR6dDBFWDRfeHlNNGJwM3NCUFc1Y3VYaE1qOVp2X21xZlNCQkppMVlZTUFmTjFLWFBudExJRGpKOEQ1R0h3eDJ4V0hFMTZGaUh5SUk4SVB3YXlFenlnYWtvdkY0THFQY0hQcDJYMURJZU5Fd1hOd0UtcURJVl93Q0t6bC0zLXRsUT09 |
Hi Guys. I am very interested in sports analytics. Should I major in sports analytics in college or major in something like Business Analytics instead? | r/sportsanalytics | post | r/sportsanalytics | 2025-04-22 | Z0FBQUFBQm9ORzh5cGtYcUFxeURaM2VrZkRQZEZYZWM3aFlqN3hyZDlISnhPQ2g3dndkc2ZoQ0xyanZoSngyOVkxTGR6TlcyVDN1NEJOSXNLd1ZwZ1VYUVZZM09FM1Baemc9PQ== | Z0FBQUFBQm9ORzgxOXJhWVhKbjZWRmZKVjRvV094WFNldkd5Y0hzZWxReG5CeHdjcVZNelc1SVpaRm13cEN4Vm9BMXRsM2xobk1EQnE5UmZVS0g2YjYyUmFFdllJeVlFOVVRWHhyaXZybTFTeEExalZzQ0xoc0lxbXN0U293aEUxRHVQdDBKUFhSWXJLLVdEY0RzZWxfdWp0WHoyNWJaTFZzVExlME14bmZ6Zkl6UGJlblpxclhCRmFOckM3bm5FSXF4QnUwUFRIZXhi |
Hello, [r/Monero](https://www.reddit.com/r/Monero/)!
After extensive testing and focusing on user comfort and privacy, we’ve created a Telegram bot that connects to your Monero Wallet RPC, allowing you to check your balance, generate addresses, review payments, and much more—all from your mobile or PC using Telegram.
**What does this bot do?**
This bot is not a custodial wallet, does not store your funds, nor interacts with your private keys. It’s simply a secure and lightweight interface that allows you to make requests to your Monero Wallet RPC, using the configuration you’ve provided. The bot does not connect directly to your node; instead, it interacts with the Wallet RPC as configured by you.
**Available Features (more coming soon):**
* /start – Show the welcome message
* /help – Show all available commands
* /config – Set up your wallet and RPC node
* /myconfig – Check your current configuration
* /removeconfig – Delete your configuration (completely removed)
* /balance – Check your wallet’s total balance
* /getransfers – View your recent transactions
* /integratedaddress – Create an integrated address (useful for payments)
* /getaddresses – List all your addresses
* /trackpayment – Verify if a payment was received (using Payment ID)
**What about my privacy and security?**
We understand that privacy is fundamental in the Monero community, so we want to make this very clear:
* We do not store any transaction history.
* We do not have access to your seed or private keys.
* Your Wallet RPC credentials are encrypted with AES before being stored.
* You can delete your configuration completely at any time with `/removeconfig`.
* The bot is not designed to monitor or store user activity.
We take the principle of “only you control your information” seriously. The bot’s code is not open source, but we use good practices to ensure that even on our server, no one can access your data without your authorization.
**Who is this bot for?**
This bot is intended for:
* Users who already have a **Wallet RPC** (e.g., running `monero-wallet-rpc`) and want a quick way to interact with it.
* People using a VPS, Raspberry Pi, or even running a node at home, who want to check or interact with their wallet without having to open the terminal or GUI.
* Projects or services that want to monitor payments using integrated addresses or Payment IDs.
**What do you need to use it?**
You just need three things:
1. A **Wallet RPC** running (either locally or remotely).
2. The username and password you use to connect (if authentication is enabled).
3. The URL where your Wallet RPC is running
Once you have these, just use `/config` to set it up and start using it.
**Why did we create this?**
Because using Monero shouldn’t mean losing convenience or sacrificing privacy. We want to bring simple, useful tools to users who already have some technical knowledge but also value the accessibility of Telegram to check balances, addresses, or verify payments.
**Interested?**
We are opening up the bot to more testers and users. If you’d like to try it or leave feedback, feel free to leave a comment or send us a direct message.
You can also help us with ideas for new features that you think would be useful for the community.
Bot: @@XmrRpcBot
https://reddit.com/link/1k4v7jd/video/qb3wpvcooawe1/player
| r/monero | post | r/Monero | 2025-04-22 | Z0FBQUFBQm9ORzh5V2tIWFRZVEdRbGFuS1F6RHRaSEZvMkxsZVVhbksxVXNtMTIzV0liNWJJQ04xX2hSWnRLMm1lV0lLNjRPbF9aQ1c0MmxTand1RVh3WUVOeGV3YnZYa0E9PQ== | Z0FBQUFBQm9ORzgxdURNVjZmVEFFSVgxZVZQNmVQTnNoeDVnNEIxWE0yMXc2Z0I1V2IwcUpJcFRvaHR0TGMxRElzR1ozTXp0cEVWZVk3VjJzLThobTFEdGllLUJUamd0SkxhcXZzSFI5Y2J6WHFkeTZPRGlCZ1EwSmlCU01WRjJfLVE3WGZsamtETndrQzhrVzUyaldfcE1RaDJ2YlpxS3ZLSlZSQUhFWHJDT2NFYktZYmN2aHp0U3dpMmMyRlNhRFdiTm9nLUZ3b2M2RzR5d2NfamE1WnVFdlZXZElwa1ZIdz09 |
I'm quite new to this field. Can someone help me with these following questions:
1. How much data (number of candles) is a minimum for an acceptable strategy especially for intraday. If it's too much, PC could run for life.
2. There are 3 main params
\*EntryThresholdTicks: Max distance from a recent swing high/low to allow entry. Prevents chasing.
\*TrailStopThresholdTicks: Tick buffer from the latest significan bar to trail stops.
\*StopLossThresholdTicks: Buffer in ticks added to swing-based stops.
Currently I'm throwing some magic number. How do I optimize for a specific instrument and a specific timeframe in a professional way. Btw I'm using ninja trader. | r/algotrading | post | r/algotrading | 2025-04-22 | Z0FBQUFBQm9ORzh5VnQyRFI1cm5nZ3JUdE0wYUdTZDR6ejd3ZzJqbU5mdXdxZ1kwZzB4d0hNRDliTFRqXzRzYjBxRld4Ujk3bkpVa3d3X2hEcWVuSmFEaDF5NnlPTVhzVEE9PQ== | Z0FBQUFBQm9ORzgxa3lYQ2FZVGYwVlN6MzRJc282cTMxb1VtbTQ5WjdObHVHMDh0RjNXdk5DNEdYdGdzbDNBYnhBcEx5Tm1IdWVDeWpBSThzS0R0UTZGTzJCSzNkV1FNd2JBcnEyV1NNcVk4MjBQVG9sX1g1dEpjLUxQanJCQ0lzbk1pcVQ2TkNITDJfY3o0UUxhRWpTWmZzbXFVektSWnFXZFBjX0hzbGxnWUZTckdtRXA1RzcyLVBkQ01tYkMzZWR5XzV4eWdLc1llTThOZDZhU3pvODlvRlJHeFpUNVc4UT09 |
If you’re serious about working in sports analytics then major in some combo of stats, math, and computer science. Learn to code in R and spend some of your free time working with a sports team at your school or doing independent sports analytics projects. | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-22 | Z0FBQUFBQm9ORzh5RW1jcENvVExWVE1iVmFqZFdpMUNvR0lmbV8zQ1FKNkRCZzFTQnFtZzNoZE5XVFpKU193R1FyLXROaWdQTTJTOUtqQngwbnUzcnNCSGluWUpLYzFiNHc9PQ== | Z0FBQUFBQm9ORzgxV0dDOW1zSVpSTlB4YmRfcXpTWkRmTGo4MFhpSkktUzBLZmhQS05OV3BOazJOclozb3EzRjRXWUZzd0pTMThuY0oxVFE5RnVtZUgwaWduSTZHVEsyUXA2cmdlSUxlWTF2NlhEalBYSU55Mk16TWZudU43UkQ4cDE4M2hTVkFSMEQ5R1d0UGNjRnFDYy1mM0s3bi1ud3UxQmo5X1RjVzFrbWhONnhDOXVDRGwyZ1d6eWRhajA4dl96Um80OFo3NVp3 |
Why computer science? I’m a cs + math major but I feel like the cs we do doesn’t translate to the sports works well. I don’t usually work in R, and sports analytics seems to be behind the AI trend.
Granted learning to think like a computer scientist might be valid, but just curious as to the jobs the pure cs people can get. | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-22 | Z0FBQUFBQm9ORzh5VUltTE1uWlBsRVZmRWVaR0JVQUhIeXVObTlMQVZUTkxNSzdQNzl0anRKYzY4S1hqbFY2Zl9sUHVBUk9UVXE0ZzVrNmFULW5oY0JNRWxQci10VXBtb2c9PQ== | Z0FBQUFBQm9ORzgxeldmVVFjaW9jc3ppeEN0akpnbWk3dUJ4Zmw2U0VpdnRaOUFnaTNrSVZCTFlsZy01d2ZWUmhaT0lTTmc4dEllcm1PTG1MdUU2ZWVveVpNMC14eEFRUFhHcUtoeEpLZUwwSjFNTmhkeENuYWt0SjgxXzBaTXFJbE1nRFhyanlPR3JRc0Y1Tmc1d21nbWFEa0cwbEpxckk0eFRUTF9GLVc5TzlDVnBzYjBlalZMX3RGaGNCTmRPMTBzd25TdXROQ0dh |
I wanted to start a discussion about the different ways to use "AI" aka LLMs in developing trading applications, but instead I came here to rant about how I'm continually surprised at just how *bad* LLMs are.
The way I use LLMs is (maybe?) different than a lot of developers. I don't vibecode, and I don't use the API as a code completion service. Instead I actually prefer the chat interface, because prefer I have conversations with the AI. I'll say something like "I'm noticing a bug where bla bla bla, here's the function that computes the thing, here's some console logs, can you help me debug this?" And then the AI and I have a back-and-forth. A lot of the time, it's pretty good, but even the newest (paid) OpenAI models still make surprisingly bad hallucinations. You simply can't trust them (which is why I don't let them write the code for me).
Example:
A while ago I had a problem where my pricing model was consistently giving bogus greeks for puts. I put some debug print statements in my code, and tried to price an in-the-money put and got something like this:
S=509.69, K=547.0, T=0.0035 (≈ 1.27 days), sigma=0.2543
Model says for strike 547.0: $37.31, delta = -0.0000013
Interestingly enough the price was pretty accurate but obviously that delta is incorrect. So I asked the LLM to help me debug, and it very confidently told me:
>You're pricing a very deep in-the-money put, with:
>Short time to expiry: ~1.27 trading days.
>Strike = 547, Spot = 509.69 → ~$37.31 intrinsic value.
>Sigma = ~25%, but over just 1.3 days.
>Almost no chance of expiring out of the money.
>
>So in risk-neutral world, the probability the put ends up out-of-the-money is nearly 0.
>⇒ The put behaves like a bond payoff with a known cash amount.
>⇒ The sensitivity to spot (delta) is almost zero.
>
>Hence, delta ≈ 0 — this is numerically correct, but…
Uh yeah no thanks, ITM puts should have deltas approaching -1, not 0. This was ChatGPT4o1, or whatever was the latest at the time.
So, question for the community, because I'm super bearish on AI in the short term (because it sucks) but bullish long term:
How are you all using LLMs? Is anyone actually brave enough to incorporate it into the trading loop? Is anyone trading significant capital with a vibe-coded algo? | r/algotrading | post | r/algotrading | 2025-04-22 | Z0FBQUFBQm9ORzh5LUoySElvOGRVVTlWTVFSdVEwLXVreHZYQk1OLXV6dHlqSnI1aUxVcUxfSy1ERUVsbVZhRTZoVVFGZGJUekZNU3ZyMDZqMW5YVmJ3cXZ3OHhjQWRWbnc9PQ== | Z0FBQUFBQm9ORzgxd05YdHJKRURHX3V5X19BQ1FpUThNeF9ueTBOOGpZVkw4RnYxb05zSldCSG1ZX0Nld2JXRWljZjdCenVIaWp5ei1qTHA0Yjh3eEFnaGxPeEpTSHdWNXBfcjliR0JvaURGUTNTT3g0eXFUQU9mLS0zM3NIZTJwZHE3Z3RKdmtjdC1KUjhuLVYybTNyeEJQTld0RF9iYkdoZnBkajBRVm00S2JqWlh6aGgzYzE0UjlFQ3hWMFgxUXVaZUg2dkFXeklu |
Hello.
I'm trying to do some tests on portfolio sizing, my goal is to use FTSE All World or MSCI World indexes, but I need historical constituents in order to do my testings.
Does anyone know where I can find this data in a relatively cheap way?
Thanks | r/algotrading | post | r/algotrading | 2025-04-22 | Z0FBQUFBQm9ORzh5NHJGNFRxWTN1d25IMWNNbU5lalJPLWNZbVFzSW1qbzFzN3c0YUZSaGVCbDFCQ3dKMFhveGNqdnVjczZjTEF4QnY5TzM0Q3puN0VodlFXMXRBYmp3Mnc9PQ== | Z0FBQUFBQm9ORzgxSkpQQkR3WDBUazBGbERIdTlHMkNHSkVSbFJkb243aGZsdUN5Tlhzc3RlYURCZUQweUc4V1BiOFhSZXVWMFAtck56VDJFakxRRk9oOWJzVWtiOU1BOTZkTjJOTDZUNVc5NW5hQWdPM29Gc1VLZHBPaHpwRUxGOGE0LWdpT2psWU5YdGZkX3ppUEFFWDJsSjNWeE94WDhJLXZyUzlENUhrODh3Zkl4VWJ2dmdPLXFNM3RJOGZVLTBuSHVST2g1Z05KWEJCY3hZc0E4Ukt5akJZazYzNm5vZz09 |
tx to https://x.com/taoinsider/status/1914603936595538131?s=46 | r/bittensor_ | post | r/bittensor_ | 2025-04-22 | Z0FBQUFBQm9ORzh5SHByU1NiSlpCbHllT1h5YTZWMF9YNEFqMi1teFFNOFUtT0tZclhtU1BtaHBmcWdMVXRORmthRWFrYWhxZm04dVNzWGdLQS1DMGFjRFBFVEpNX2xxWVE9PQ== | Z0FBQUFBQm9ORzgxZDFaMkVFQWZpdHRCQzE4UzRfeng5d3F5NkhYSncxSm1TajhrTldfYklWOWlLWmc0Zmdvc184YVZhbkFBWFlUcFlBX2ZfcVBwTVZKaktadGZwSjZaU2V4bUhLelRyZEQ5ZXJrRHM5ZDNhb014VnVkWHNZNTF3M1hVQjRsZE1TOGthN1ZlXzdVdVRISmdFaE5GdnAzQU9MdkZ2ZnVmbnFiUjdSdjQwQ096aXFvPQ== |
This is a dedicated space for open conversation on all things algorithmic and systematic trading. Whether you’re a seasoned quant or just getting started, feel free to join in and contribute to the discussion. Here are a few ideas for what to share or ask about:
* **Market Trends:** What’s moving in the markets today?
* **Trading Ideas and Strategies:** Share insights or discuss approaches you’re exploring. What have you found success with? What mistakes have you made that others may be able to avoid?
* **Questions & Advice:** Looking for feedback on a concept, library, or application?
* **Tools and Platforms:** Discuss tools, data sources, platforms, or other resources you find useful (or not!).
* **Resources for Beginners:** New to the community? Don’t hesitate to ask questions and learn from others.
Please remember to keep the conversation respectful and supportive. Our community is here to help each other grow, and thoughtful, constructive contributions are always welcome. | r/algotrading | post | r/algotrading | 2025-04-22 | Z0FBQUFBQm9ORzh5WHl4OTRQVzgxNFVUaVBkdWRodWxXYklfR3B4Mm92S3Y3LWZKNFJBcmJWT1V3OG9RbzRqc0lTcDZyaVdQRFhKcDcyTS1VVnJISVU2MmZmUXM3M3NvdEE9PQ== | Z0FBQUFBQm9ORzgxY1I0ZG54dFA3Zm9SMmlqYWF1dk1UeDBKZGVKTjVJTDhOOE5wMVpqTTBwTXljZjJIbTBxM2hycWk2bVpEbzM1Z1NuZVdQd1JIWkNuM1kyR0M0NktYSVdxQnRQaFFCUUhOQU1JeExDdHc2eXJPSFQyNUxVNUlueU1mSFZ6NGVrSWZTcXluNU1XTmR1cTYtZFpDVUJENHpBb2RmaVpZOVhjYXI4YWplVW9RZ2ViN05yUVIzTWF5Um5wWDVzaXBYSWZl |
A lot of any analytics job is writing code, and as long as you can demonstrate reasonable stats knowledge CS will be relevant. You may not work in R, but knowledge of data structures and algorithms carries over from language to language. Maybe more relevantly, most sports teams also have teams of software engineers who build out websites for all of the internal stats, etc. | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-22 | Z0FBQUFBQm9ORzh5WU1VUk9seWtYWk5OY2ZpcDZudElDSHpZRVdTOTloVlpVVFpvRUotYXo0Rm53SHQxSmk4bC14SmZZUjBGc2JuaHBwYW9vMGRLSjFKT3BQMzBYV1pWOXc9PQ== | Z0FBQUFBQm9ORzgxbEVzbncyUHFWMllOdFNwaTRoVGxoUWlOX1NRMGE1Ry1JWXR3QkxGcFBDSHBlal94LUItak1rTlZNNlRZS29URElpcXZRTkZneFFIN3B3d3czWWdGMks4WGFyQXBRTV90YmVnMTI0SFlLdm5nNUd0enF3OEpCRmoxbTNkOHRLWF92NWZZR0V3akFiOW9BNWkzWkxXVU1aZGtuWTBCZl9falZiVnUtVl9mZ0FGUGxBLWRqb18yZ1N1OXl2eHBXR0dD |
monero currently is one of the most (if not THE most) private chain in crypto. but after [vitalik released a blogpost about why privacy is important](https://vitalik.eth.limo/general/2025/04/14/privacy.html), its like every single blockchain now is suddenly focused on privacy... AVAX is launching eERC-20, Solana is getting confidential balances, ethereum is focusing on private L2s and privacy pools..
i know monero basically has a perfect distribution system (ASIC-resistant CPU mining), but will these privacy solutions from other blockchains pose a demand problem for Monero? | r/monero | post | r/Monero | 2025-04-22 | Z0FBQUFBQm9ORzh5Mlp0UUQ3SHhqNWNNZEFYTklJdTdvMGVFcW9sMXU2ZGYzT1QwMWNZUl96YWxGZnk2eXFDSTh1TE1uVGcxdmQ5emVMY29sWm5yVDBWbllaSEw0alo5NXpVWUdWd3JxRFNQMXVPN0ZQU2JuNmM9 | Z0FBQUFBQm9ORzgxUlg4NmRoSnNXYmdUejJ2a2ZLVVVxcnA0NzRxU0M4MjlIa20zWEJwYzRsYnllRjVFVmVDMmUwang4MFI4S1F5WXhqMXZhQ1d5QUV5MUNhYk1NcWNwckktcEVJaGk5ZThHc041OU1VR3JoWmc4OFFfczhGaDg4UE8wQk9vVmFaUXd6NkZmMlQ4bHdBd1JpbDc3aDVSSmwzYldJcG5xaXFKRUJqSjNFRTJlaVhtVnhCM2N3cmc4am52UnItMTNiLW0x |
While I am vibe coding so perhaps that is the root of the problem I am having issues with Dust as well as state management. I buy x amount. Verify I have x amount then when I sell I have y amount to sell. Same thing happens with money. Buying power seems to change and not reflect reality. I am just wondering if backtest crypto is a no go in QC or what. | r/algotrading | post | r/algotrading | 2025-04-22 | Z0FBQUFBQm9ORzh5WmRrTldoOFRqVkcyaGVfWG5EdkNFb3prS2lDNFozaGJBMWhST2pHLVMwTlZJOGtxVGlJZjM0TzJ5LTFzOTZKa3hwV0F6cnpEQy1ETHFST280VXc1cGc9PQ== | Z0FBQUFBQm9ORzgxOFN5M1k2UW9LUV9xdXU3UVgwUklXMUpQUDY5VW1UTVN2aEJ0TW1scnlVaTJIS05rMFcxazdrYlpFZklzYm5MdWVRVjJ2bUctVDY1OVFFOFdWNE15WWZLSmpDQnpKZWJCWlNyZzkySEtjQkJOc3hwdnJmZnhoU0tidnpQSzlxeTZhWmNEM1dvcnlZLWxTTGx6WXUtc3JERFBIc3JUempFcTQ1WHAtbFdpaFdVMHRfUGt0a1czbkdjR1p2MDdZOXFEQVJKN1VXaWRBcHZuSzc3ZFBOM19MZz09 |
TL;DR: The market for BADGERS is getting exciting.
Here's how to interact with the markets:
- Divide current the price of BADGERS (in sats) by 20.
- The above number is the effective annualized staking yield (APY).
- If the yield seems high, stake BCH for BADGERS to sell them.
- If the yield seems low, LP stake BADGERS on cauldron, until it's higher.
- Active users of BADGERS markets can reliably get more Bitcoin Cash.
Example:
Today, BADGERS [are trading for 70.4 sats per token](https://app.cauldron.quest/swap/242f6ecedb404c743477e35b09733a56cacae34f3109d5cee1cbc1d5630affd7). So staking BCH to sell BADGER would yield a roughly 3.5% annualized return, with minimal risk exposure for the underlying Bitcoin Cash principal.
The yield for Badgers is **higher** than the current rate for FBCH of 2.1%, and higher is generally better for yields with comparable risks.
This is hard L1, fully-collateralized, always-auditable, time-deposit, low-tech staking with NO LOANS an no funny business with the underlying capital.
## Intro to Badgernomics
Over the last six months, the market for BADGER tokens on [cauldron DEX](https://app.cauldron.quest/swap/242f6ecedb404c743477e35b09733a56cacae34f3109d5cee1cbc1d5630affd7) has crashed from upwards of 2000+ sats per token to roughly 70 sats per token now.
Typical pump and dump... right? Well, nope, not so fast.
The market for HoneyBadger tokens (BADGER) is about to get interesting, because it might be the **ONLY** active open intrinsically-priced decentralized token market on Bitcoin Cash. This is a fair market that users can affect, individually and collectively. And the token price and staking APY are closer to where they may be long term.
Another interesting, or boring, thing is that: a million people could lock a coin in the badgers app for a week, and they should **ALL** get their whole coin back plus 1000 BADGER tokens. (This isn't a Bankman-scheme). And since the BADGER tokens will always have some non-zero monetary value, there could be a million winners. And they can all know how and what they'll win from the outset.
Like bitcoin's issuance, the "Badgers Test" is a simple checklist:
- [ ] Total token issuance was contractually controlled.
- [ ] It has a fair distribution with issuance not directly benefiting the project owner.
- [ ] Token price is allowed to float based on intrinsic open market forces (not pegged to an extrinsic oracle or BCH itself)
Very few CashToken projects check all these boxes. Badgers does with Fungible tokens. The [Emerald DAO](https://emerald-dao.cash/) was an NFT project that passed the "Badger Test". But to date, I'm not aware of any other token on Bitcoin Cash that meet the above three features as cleanly as Badger.
WBCH and FBCH obviously peg to BCH, which is less interesting because we know 1 XBCH is (or will be) 1 BCH.
While there are certainly meme coins or NFTs that have contractually controlled issuance, and lots of token derivatives tied to other assets, BADGER is interesting because supply is NOT controlled by a single actor, and it's NOT pegged to something outside. It's firewalled. It's a realer market than a derivative. People in BCH can actually impact the price in a decentralized way. And it's not like the issuer kept a bunch of tokens to cash out later, meaning a single party could dictate the price.
## What is the Badgers Dapp?
[Badgers.cash](https://badgers.cash) is a decentralized finance app to get token rewards for staking Bitcoin Cash.
What do the tokens do? Well, for one thing, the token price indicates the prevailing rate of yield for people to stake BCH without impairment losses. So not only can users get a *yield* on locked principal value, which is huge, but everyone can also see the *market rate* for that yield, which is bigger.
Badgers uses the [BadgersStake](https://github.com/SayoshiNakamario/BadgersStake) contract, which anyone can view, interact with, or audit. And the total initial supply of Badgers was held by that contract. Anyone can stake permissionlessly. There is no way to withdraw that BADGER token supply except through staking. There was no developer reserve or Badgers Foundation.
[Badgers.cash](https://badgers.cash) has been around for a year, it was released around May 2024. The contract address can be viewed [here](https://3xpl.com/bitcoin-cash/address/pvgcl3xk6nwqlngkk09e7g67x5vxs57jv6v2q4qm4ct5yv4d3ppfgl3tq982v). And the tokens can be [swapped on cauldron](https://app.cauldron.quest/swap/242f6ecedb404c743477e35b09733a56cacae34f3109d5cee1cbc1d5630affd7).
Badgers was the second dapp on Bitcoin Cash to pay a "safe" yield. Along with the first app (EmeraldDao) & FBCH, it's "safe"er because staked coins aren't loaned out for interest, principal is simply held on the contract and released later with some bonus. In contrast to protocols where coins are loaned out to a succession or riskier parties, badger staking has less risk in practice, because it's always fully backed and easily audited at all times―like bitcoin.
It's very easy with BadgerStake to see that all the coins are on one contract, and that everyone who staked in the past year got all their coins back, with token interest. There's been about 1500 transactions, with 75 active stakes at the time of writing.
## But we had open defi markets already.
Ehhh.
There are protocols on Bitcoin Cash to engage in *currency swaps* tied to an extrinsic oracle, which risks the principal of an investment and doesn't directly impact price.
A swap is not a timed deposit, the risks are very different.
It's simply not a market if there is no price discovery. It's an unplugged controller if orders never really go to the lit market.
Additionally, there's a risk of loss of principal. If someone hedges 1 Bitcoin Cash in a swap at the rate of $350 for a pre-rebate or coupon, they're risking a fraction of their principal in coin denominated terms. As an extreme example, if it was revealed tomorrow that the President of the United States promised all national stockpiles of gold and weapons to another country, and the price of Bitcoin Cash shot up to $350,000, a hedge position might only get 0.001 BCH back in principal, for a couple percentage prebate.
It's not really a straight yield on principal, if the principal can be lost.
On the other side of a currency swap, someone can take a leveraged long position, but they aren't really participating in a market if the strike price for the swap can be determined by a single party with a lot of dollar tokens and advanced market making capabilities. So someone bullish on Bitcoin Cash can risk all their principal and not be participating in a decentralized market, if they enter into a leveraged currency swap settled by an extrinsic oracle.
Places to speculate on asset prices in ways that don't impact the markets have existed for hundreds of years.
## But there are lots of token markets...
It's also possible to "stake" assets (BCH+tokens), but again, there are risks.
Automated market making on BCH involves placing both Bitcoin Cash and some token in the same output or vault.
If someone mints 21M scamcoin tokens and creates a market where each one of those tokens starts trading at 1 BCH, it's not really a decentralized market if one party starts with the entire token supply and can dictate the initial prices.
To provide liquidity for a token that a single-party issued is risky, because the LP staker must hold the token on their books. In practice, the issuer of liquidity creates considerable downside risk for any party that didn't control the entire initial supply of tokens, unless all the tokens are provably issued to a permissionless contract.
It's trivial for someone to begin an AMM market high, and harvest value from parties trying to state liquidity at inflated rates. When someone stakes a token at a high price, they're essentially offering to buy more at that high price.
## Moving Onward.
Badgers.cash has grown over the last year from an app with 10 BCH TLV, to an app with over 150 TLV (at times). If Badger Staking offers the best yields in Bitcoin Cash (better than FBCH), than liquidity should go to Badgers. Some kind of positive yield, no matter how small, is higher than staking in an app with no yield (like the HODL-EC plugin for example).
With the way Badger works, the user chooses a predefined future locktime to hodl to in advance. One of the nice features of this setup is that locks can "auto-complete", anyone can execute the code to repay the staker their original funds and BADGER tokens. Which is great for getting everyone paid back.
A competing app could be more responsive. Markets could be more responsive, and users might stake more liquidity, if a dapp offered the flexibility to unlock at any time. So someone might choose to keep the bulk of their reserves staked and simply wait for the price of a token moved slightly higher, then they could unlock and sell dynamically in response to the market. Or if the positions were tokenized and could be released for liquidation as NFT keycards in response to the market.
There will soon be new dexes, new auctions and new uses for BADGERS in vox.cash. It will be possible to create transactions arbitraging orders across transactions. It will be possible to subscribe to apps using BADGERS tokens.
But for right now, anyone in Bitcoin Cash can collect some free BADGERS by staking. Anyone can put in a little money, see that it's locked, and see that they get it back with some positive reward. There is no outside lever to rug or liquidate everyone's claims.
Right now there are 75 locks on badgers.cash. There could be a thousands locks, or ten thousand, and all the money can be seen and accounted for at all times. And everyone should win something, individually and as a group. | r/bitcoincash | post | r/Bitcoincash | 2025-04-22 | Z0FBQUFBQm9ORzh5UFc3a1pST2R5UHE0OENSWGNOZWttLTJlcEFPZnBlajhwUWt0UFFCMzY5eVlITEdjWVRJZHBINHpxdTBIOV9pMG02cTlsSEpPVG80YTh3VjJRNURTYkE9PQ== | Z0FBQUFBQm9ORzgxS0loTzVQdHRGS2tLNndFQk1DX2NkS3oxMWxZOGw5V3ZDbHU2ZWZiVFpSU2RPS3Nza19WRURVRldpMHJHdkJTOF9od19qU3J5am1sVHVTeWxwZk5WMk84ZktzekYyajhFMV95bDZESml0N0QwNVFwRlBsOEVVWWVhUENzUTNNNmxiRE82S21NaVJjUVl4SVRvMGd0VlNNdnVpRWZZODhWQ19uWWxWTzdUZlBMZGxxT3RtYWduenp0UGszdVBCU3FJdEdIR2FvTUkySEdtMmNaTWEtX2xWQT09 |
Everywhere I look on the Internet, people seem to be saying that Statistics is more relevant to Quant Finance than Mathematics. The quantitative tools in quant finance seem to be based more on upper-year Stat topics (Stochastic process, Multivariate analysis, Time Series Analysis, Probability, Machine Learning) as opposed to upper-year maths (group theory, real analysis, topology). Except for ODE and PDE, which is not used as often then when this occupation first became a thing nowadays anyway.
Dimitri Bianco, the famous quant YouTuber, also said that the best degree for a career in quant finance besides a quant master and a STEM PhD is a Statistics degree.
The similar jobs that are often compared with quants are data scientists (vs quant researchers) and actuaries (vs risk quants), which are obviously more stats-oriented than math-oriented.
So why are most programs still called "Mathematical Finance", not "Statistical Finance"? And why do people still have the impression that quant is a "math" career, not a "stats" career?
I'm just a first-year undergraduate, so there's a lot I don't know and a lot I'm yet to learn. Would love to hear insight from anyone else with experience/knowledge on this topic! | r/quant | post | r/quant | 2025-04-22 | Z0FBQUFBQm9ORzh5T0hyYzgzbFU1VWs3Vmg3SWVtdzRHVUk2X3BRZkkxOW55T2VHNUZEUGtHcEhxaERudjNnOFRQQVpFRldibXFPN2Fmc2ZXZzZ1UnMzYlNXUmtabkVxQXUweTRET2tTSzJ6RGdMTFY5RVI5VGs9 | Z0FBQUFBQm9ORzgxbGFFLTQzSTlBOXB3U2ROZjZIVGxrLVk2YTd1YXZMMlE0LUdXTWRiNmYwUmpQc015eC0wLWR4WWtySS1DbDJ6LVZvWDdHcEVyWWp6Tm5DbkRqc0dVUDIwSU0tLWFuUld4aFU2U0RsdzhuMDZsQmxtUlJKTGR0MUFFRE4wVGJRNUtRUmdpYWxPQUlBb2x5dE90MlExb3ByN0U3ZExQMDlxel9NdUtiNktVUExIOWtjb1pPS2ppUGVmUWVLejJZS0tX |
About the idea of a "Quants".
Everywhere I look on the Internet, people seem to be saying that Statistics is more relevant to Quant Finance than Mathematics. The quantitative tools in quant finance seem to be based more on upper-year Stat topics (Stochastic process, Multivariate analysis, Time Series Analysis, Probability, Machine Learning) as opposed to upper-year maths (group theory, real analysis, topology). Except for ODE and PDE, which is not used as often then when this occupation first became a thing nowadays anyway.
Dimitri Bianco, the famous quant YouTuber, also said that the best degree for a career in quant finance besides a quant master and a STEM PhD is a Statistics degree.
The similar jobs that are often compared with quants are data scientists (vs quant researchers) and actuaries (vs risk quants), which are obviously more stats-oriented than math-oriented.
So why are most programs still called "Mathematical Finance", not "Statistical Finance"? And why do people still have the impression that quant is a "math" career, not a "stats" career?
I'm just a first-year undergraduate, so there's a lot I don't know and a lot I'm yet to learn. Would love to hear insight from anyone else with experience/knowledge on this topic! | r/algotrading | post | r/algotrading | 2025-04-22 | Z0FBQUFBQm9ORzh5ajVMYlREMUFOY25uYWg3aWk5WXBrd2hyRzNLWWJrdnE4OVFBeDFCZTJKNnR1RENZajB6aDVFQTlVMHhUbXRGQ2xMRTAwY1g3QUF0RmFCUmNoa1haaW96Uk9WX1lQcWtkbERMUDJGbFpzR0k9 | Z0FBQUFBQm9ORzgxMGJxSlllLVU5bUR6QVc1RndsQ2RnODQ2RFNySUZKaFRyZVJ5RXE1Wml3VVZnTGVWRTdDZTl5RkhOckRYRXRQZlpmbmtnQ2laWGVpU2pvUjNNNmIxM3FOZXlYMlAyaGxxLUNqT2J1RnRNRnA4ckFzOGNkb19adm1SY0dkZWdLaDJRYVZLMUNJRUc2RGRWQWtFeDg1bmFuRVpYNzJIM1ZnZm9OdktSd2JUQ0QtdjlpbHpwNlRLYTFMaVE3bnpsLW42UTdiTDlMd3pEVHZfWDNqX1FPMXI2QT09 |
I have a bot which in backtesting did very well, however it is very high frequency, trading >300 times in 850 candles. If I were to trade this with Coinbase the fees would delete my wallet in an instant!! Ideally this service would also have API calls for buying and selling and decent paper trading so that I could test the viability in realtime markets. Am I better off just trading an ETF with lower fees on a normal exchange? My concern is that it is not 24h like Bitcoin itself | r/algotrading | post | r/algotrading | 2025-04-22 | Z0FBQUFBQm9ORzh5UWpCdHhLZnh5aVRrVzNoSENDSldSc1d6M0pKR29CVmw5WXpOczU3Rl9qN3hZZVF0MTZjUXdSQUdFOXNEMXBDMzIwN2ZvTjNRVkFWdDRmV3dlaUxhc0E9PQ== | Z0FBQUFBQm9ORzgxY2gxUjR0T0FwZThjU0ZSb3JjaEFiY1VoQzM2SWhpUTBReG0tOUtYdjlfajNRUHZFck9XWWRQZG5LVGxMRUt3VUVJZ1IydlNrc0c1TUZ0dEJhZnZWZi0tUzZiaW9RSl9SVS1JMkw0NDhaOGlCREtWbHpsaVV4UzJZbnlUcm5CZUZveFZpY0ZDam9id2FEaVRVNDJrV19PVzlYYmpxMmQ3QURPM1FvaGV6anFfci1zY1hTcEJSLTZkT0FHS0tZVlE2TXctMWxQZHBpN1ZIUjU2UmpoZUEwUT09 |
u/EstimateHumble118 we have all D1 men's basketball games and teams. We also have a program for early stage companies to access our data while they build out their product called the Breakaway Accelerator.
[https://rolling-insights.com/breakaway-accelerator/](https://rolling-insights.com/breakaway-accelerator/)
It was born partly due to our own experience trying to find data for our product, especially after speaking with some of the established data providers.
You can also generate a trial token from your account and start using it right away.
\- RI | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-22 | Z0FBQUFBQm9ORzh5R21xN0hEMGZQRGdiMGxlLVE5MUt3Q3VqR0l4RFc5dFRoQXY4MlUxdThsUUNiSkI0SnRXR2hFTWRTNGZmRDdBTHhEeUNlQ3RVcExlWFVUQVg5bUJKT1E9PQ== | Z0FBQUFBQm9ORzgxMkJBZXZDZm9IaXNZeG4tTENKc1RfNVRuT3dQN1JBRkdJLUZUVGtPQkJDYXFyalpSa2JFQk1MWG9WR2Ztd0NFNVJMWmJUR3ZfSXFNaWlEZGVIempEMlp3QVhNelc3eDVid1RtcmJYS01QQ0hFSkxaT0ZLUF8ycFZUbnpkQlRyTXNVdDBpSGtkNkRId2pnQUIwVXdrdUszZ0pOcTNrNE5wVi1nLURtZjdWSkpPNzMxNkZnTF9zYUNwcjZNMW8xYWhyRlhnejV1My1DQlJPLXRmTV9VWmY3Zz09 |
Getting set up to sell BCH Global Lotto tickets to get paid BCH instantly is super easy! Selling tickets is even easier when you break it down to the simplest concept that anyone will understand - it’s only $1!
Let me know if you want to get set up selling or you can head over to the “Ticket Seller Rewards Program” in the menu on the site: https://bitcoincashgloballotto.com | r/bitcoincash | post | r/Bitcoincash | 2025-04-22 | Z0FBQUFBQm9ORzh5ckFsOTRIRGFybE00eVVrQ213YkRiQndYZjAydDM2LWNwVHZXRkNtTTBRTTFVNFBCeWFVenRsbko3U0FfUHpxM0lrcWJZdVpzZFBBWkYtU2l6RElES2c9PQ== | Z0FBQUFBQm9ORzgxbmpyenZ4cGVDYjhzT2ZaUGZMTWNVbTVEM0dxMDBzd1ZsLXd3N085aUtfclFnbHA5Q2RReDdWUktlYnRBNm16UkxkWHBSX3BwSThnV2JnWDZ6aVh6N3RoZnA2OEZid3ZPd1NTTGdVN0E1TzRQWXVSdkpnb3AtZE5TTTVpTTRwcDVHSTFwcndBdXRBTnhsX1o3SEc3cTVIeS01TXdnai1BVXJqYmtSdGNLM2M0TksyTWNNWEVuQTNQSGsxOEJRQkYwSjlaNlJqQU9oQnNnZThsRjBTUTJjQT09 |
Did he sell his 0.2 Tao? | r/bittensor_ | post | r/bittensor_ | 2025-04-22 | Z0FBQUFBQm9ORzh5d2l2cEZWOE1BOXlMUW5jTnVHRHp6MURUbHY1NDRLZXk2QjF2MFZkMko2YzlmMEhONE5qN0FJM0szVjltcVdkd2I0V2tHaWNPZ2tvMEpETVdMTDZWZnc9PQ== | Z0FBQUFBQm9ORzgxNmtGT2ZtWFZyS0g3cWdDWlVCZEZlSVc0RGZ2RnlNbHd1em1CNFNwSTdlOFowM3NfS0RadWdHTUI1M2k3NXhxeGVWYmY4TDJscnY2QTJfeE94RlF4WFpYTGZzWHBkS0ZFWG9Gd1BfMTVZb0hwTjNpNjctVzRSbkFFNE91ejlhVDMtSWM3cFI0UXNmbVhOZW1Ia25nRkYwcDg2aWRfdGhKeUNyTUpLSlVMWnNRPQ== |
What’s everyone’s take on trying to accumulate the highest Tao return on their subnets?
Originally I made a nice amount by spreading my Tao over quite a lot of subnets but now with this big pullback I’m not sure whether to just stick to maybe the top 5-10 or still try to find low market cap subnets and be invested in nearly 20?
What’s everyone’s take? | r/bittensor_ | post | r/bittensor_ | 2025-04-22 | Z0FBQUFBQm9ORzh5bkVaQ3F2eHM4Z3I4NHRQcUl3UHNveXVZZl9rZzJPWWJKZ2h3bHgxUmRsNEFMZGF0dHZkSk92MWZva0FuQkNSbndKRC1kQ3RzZXA2TnU2YzFNSXd5SUE9PQ== | Z0FBQUFBQm9ORzgxNWQ5bzlsS3JTVm4zU0pzU0JKNkN1clJUSVVtYWRTeE5WTTVlQS11NnRKTUg5d1J1eENoQXdVODBFa3piMVlmYmhCbTNJdzU2UDRlbTlQZWtnWk96eVJJcEpQVXBpRW53ZDlFUE45dUhKUWkwUk95NEFSUFZZc0ZiZkNSQXVONnR1SGlWVzZTamI3UTN2OWFJTzhlOER1b3FRNXQxLWtKWEVfc3N5MTZRMkhvS2tPQTZxd2x1NzBMcF9XalEtTEtqU1ZwcmZvSHkzT0lhQ29ONFlWVkhmQT09 |
Plus exploring the paradox of the "buy-the-dip" factor | r/quant | post | r/quant | 2025-04-22 | Z0FBQUFBQm9ORzh5SHJGMmxqMWJxemp4UGUzb3hnVXdRdFdxZng2clBFUXJWRXJuZU5WU2hIT09FLUJqX21NOTNDekxIeS1UWkVkd09kUVloYURCQ2FjTlRRX0dmZ0hOS3c9PQ== | Z0FBQUFBQm9ORzgxXzRndXc0OU80aG15dm5lbkx5ZmFSNnY5ODRsWGxOdzNzVXBrQVdqQklmNVNuUkpTa2RrdzhjOU5iOWJ0YVo2M1EtM0lHTDVUaGJaSHo4azhZOVBOeVFtQURwajdrMk9ycHdLN2xSTE42d19DaVR1WkMzYTZNbXV6SXpaZUJ2TWJHNWQweF9TQTRnMzRCMXJtbXZQWnVQVEJVUEJiY1lNZ2lUVXdMOEhuUWxxRTRvdjBkNVZIdUk5bENtX2tOelBL |
In my opinion, one of the biggest stoppers for Monero adoption is bad user experience. Having to write down a long list of words (seedphrase) without loosing it, is complex for the average user. And the risk of using a hot wallet or additional complexity of setting up a hardware wallet that only connects to PC, adds another layer of bad user experience on top of the seedphrase.
This two problems would be solved by using a plastic card with a chip that allows signing transactions. Such a card doesn't require remembering the seed phrase as you can create multiple clones and simply store the cloned cards. You would then only need to store the cards themselves as backup. [Tangem](https://tangem.com/en/) has a solution like that but they don't support Monero. My understanding is that [some extra compute power is needed to sign Monero transactions that this cards lack. ](https://www.reddit.com/r/Monero/comments/117hopf/tangem_wallet/)
I'm sharing this idea because it seems like an important gap pending to be filled. If we had a seedphrase-less hardware wallet in card shape, it would make user experience greatly easier. The card could have a PIN for a spending account and an extra password for the savings account, and support NFC to make transactions on a mobile app or make payments to any vendor device supporting NFC. Then, it would be as simple as using a common credit card. | r/monero | post | r/Monero | 2025-04-22 | Z0FBQUFBQm9ORzh5bFZSeVNibGVobEZMWTZrS2Z4RFhtUDYtekJTTGdmNmpwTzNNRkJBWDRXaU0wMjBqTi04b1MzcGVmVm9zdnpYRUNNcndNcy1MNmNIc3lWUTViNFZLVmg4WlYtNXpkVjd1eWxMOTRxUFhmUnc9 | Z0FBQUFBQm9ORzgxaVpfbnNjejVTbjB2enZxZ2RlQVgxVWlNdGo4MHI2RV81cDVKel9pcnduY1ZDVkZvRnNYaVpBc2pWdUV6US1jVkJiQ0hSclB6a1VjYTQ5LWFzVVUtQUVYRlVheThpOWt3OVhmemZMZnNrVmZNNDJ4bDZiT3NGR1p0ZnFnWEtpZzZfVDljSTVJX08zNE9RcEJCT0FNQTNBRWpVX1FldFNGbmJkOUpzcHJOWFRWNEZzZzlBZ09DVFhsLV9jdjRfeVlFMGl6WGk3OE9NYUZqb0RjbldoMDhLdz09 |
Hi so i'm currently working on quite a few strategies in the Crypto space with my fund
most of these strategies are coin agnostic , aka run it on any coin and most likely it'll make you money over the long run , combine it with a few it'll make you even more and your equity curve even cleaner.
Above pic is just the results with a parameter i'm testing with.
My main question here is for the people who trade multiple pairs in your portfolio
what have you done to choose your universe of stocks you want to be traded by your Algo's on a daily basis, what kind of testing have you done for it?
If there are 1000's of stocks/ cryptos how do you **CHOOSE** the ones that u want to be traded on daily basis.
Till now i've done some basic volume , volatility , clustering etc etc , which has helped.
But want to hear some unique inputs and ideas , non traditional one's would be epic too.
Since a lot of my strategies are built on non- traditional concepts and would love to work test out anything different. | r/algotrading | post | r/algotrading | 2025-04-22 | Z0FBQUFBQm9ORzh5dmo3VXJpU2NEVTI3RGtNam9qNXlrV3ZOMDhhd01XZkJsb285X00xcUxNbWpNRkV1TFpHbFlkS2pqZEZvLTJKcW9oUHdXdTdqZUVWLWxJdVFZanA2QWNTUlZhR3FGdlhVZ3RZZ21xaEdRME09 | Z0FBQUFBQm9ORzgxWDA2TjNGd2xzOE9qUDlyWU9RSC0xaEF2TXQwcHRDRDVVMGlWdXJUWEZwblRJMFVnM0FodXd3Y0NTT2labUxEQl9NUHc5WHM5Um0wX2w4d3pmTW1WUjZzaTdiaVR0WUFGSW9NLTVLSWQzM2NXTlc1SEpnWWJBbUpLa19NbjZDQXFIc1RXQjA2cU9HZHVzQlJkZzR4alprYkU4a21wNXd5T1F1LTZRVXl1aW92RExybldRWHp2Q0xTZmRXLWhZRXFIc3RPc3FBYTlqb0hjRHd5YmViMnV2Zz09 |
The Taoshi team is headed to Austin, Texas this week! Thomas Dougherty, Taoshi's Director of Research Development, will be speaking on two panels this weekend - “Building Alpha Generating AI Trading Agents” and “Code of Capital: Building the Future of Finance on Bittensor."
We hope to see you there! | r/bittensor_ | post | r/bittensor_ | 2025-04-22 | Z0FBQUFBQm9ORzh5ZWJFc3pMc2JzbHlqdEhOQlJHZ1FjSHBVMnh0TzlZV3RHblJnWkllM1hjYWhDZWFpMTlFcGJ2SXlMdTctdmFUQjkwYURfUkJLZWxOblRBZVN3YVMtNHc9PQ== | Z0FBQUFBQm9ORzgxUHRNbVBsT2VURXRMS01MNkU5Z09fUjVNUndiTW8wQmJodFlDU25VYjZkSkR2c3owSzRaR3E0SFdUcTBXX0haREt4TFlGdGlfQXJ0NjlobFlNWEZQV1pfRlhHSXBVOUdibVVWRlJ6aU81ZEZyV05fX1RYZ0hmbUY1OU5sYXo3TThyR29mWXNZaGoxaUQxd2t3U2JZM1VELWhOdlZvclBqS2VpSEtWQUVISnVxTnBhbTVfVFYxUFVWNFFSX25rZXQ3 |
Have a small group that is looking for strategies funds to allocate to, current focus is obviously everyone’s favorite past time Crypto, but open to all.
If you have experience and have something worthwhile:
1. High Sharpe > 2 most importantly low drawdowns compared to annual returns > 2:1
4. Scalable
5. Live track record 6mo+
Reach out if interested in exploring.
Edit: updated requirements from feedback here and the allocators. | r/quant | post | r/quant | 2025-04-22 | Z0FBQUFBQm9ORzh5Rm1UMC1LZzVPbTVTM2pWZG91amQtVWZOanU2eTBmY3E1VzBOSmZodzdGamN6U0xza0Y3dlVBa0lfSi1vX2d6MnpwMEI3SWRvQmFpaDU5MWRmV2VMNlFVNC04bG1vZ0dwbkcyd3ZzUnh2S1k9 | Z0FBQUFBQm9ORzgxNmVMWVNPb1ZCVHh0VkNjRE01cl9vRDFDS2xhNGhXekRsNU9hd3o1MHdqNHV3Mk83MXFfb2FXanVaSFRyZDI4YVNfOUJfZklUeVNyNGlSdjhvR19nSjBxLWtEc0liZ2VsaXN2dlkwSDFKSGRTbEV5YWhSNTBMQWYxM0xTZUUwdGxBOWthLVFENElxcnBUVTllU2t2U0hQZGRWaXI4cWM4ZmtwVVJ3SGoyWEdoRFl6TG1ORFJUTHNGSS10UmduSXFU |
Hey everyone. I’m building a personal NBA project and I’m looking for a good API that provides career stats by season for current NBA players, including both regular season and playoff stats.
I also need basic player info like position, team, age, nationality, draft pick, and ideally their awards (championships, MVPs, All-NBA teams, All-Star selections, etc.).
Willing to pay for a solid solution — just not something huge like SportsRadar. I’m mainly focused on current players, but if historical data is possible too, that’s a nice bonus.
Would really appreciate any suggestions! | r/sportsanalytics | post | r/sportsanalytics | 2025-04-22 | Z0FBQUFBQm9ORzh5YjRrOEVHSkpCNTlrSjdwU3l2Q05IUThjbWJxNkJHWjc0TDZmOXhmcGJRbjgwTE1qREFSZXVBaTQ5b0ZnQVV0eWQ2VXBhSU4zekdtV2dnNXdCQ0FKREE9PQ== | Z0FBQUFBQm9ORzgxV0tVc0FVSElsandsaldFZEFRVWR2Z0JuQnFqUFB0NEF4aHNuTUJCZzhkbURvMDlzRkdHbWhoMVJHM1VSX1UyRlU5VWJsTVdudWhjUXBHNl9WQWszajRIc05IMFh5V3I1MWZjdFdaZnJkRTdpTFhIOFUxMWZtOEVLT1BhNnNrTEZENVdmYVhHT2cxeHJ0VFpXeWlSWG92TlpGa2F3aF9pQm1CaVVia2NLb2dxRWV2OV9OVUFVcmFsUWd3V0dNMEVQeFFIQnlPcWxCLW5EbzhaZURPMG1zUT09 |
Is it possible to store subnets on a cold wallet? | r/bittensor_ | post | r/bittensor_ | 2025-04-22 | Z0FBQUFBQm9ORzh5cm1zNHY1QW1zckNQMnB4SDhJMlF3S1BzNi1QQlhRX2ttNkU5aGVlbDVFVmMwQkRjblByM2c5aklicDBBbGFiaDJxME85RllGUDdETGtER2NuLU1TYVE9PQ== | Z0FBQUFBQm9ORzgxTmZnQllRRy1ySGNLbE12S0tQNmQ3aUVKWWJNYlNVRVlEeDB4dFdYcXM1Rk1FejJ2T1JiMDVsWDlUbjl3TW1hUHB1SnlqOGZmeF9oZnhzeEZEQ2xQLXVka2l4all3b3Qyb2hXaUc2RllzUk5ualB2aGlBQUxDYjlHeUNFY05VZ0FKSkU0Q0lWb2xRY29VRlFzcF9JR3puVGNybmxTdXN3UnJZdGxrSVdYTWV6UTFDTGVfSWFHbEhhVXpZSlRPV09I |
RapidAPI, ESPN API (I recently learned that this is free for non monetization use cases), I’m sure there are some NBA Python/r packages. The award data will be tough, look around for some tables or information where every award for the year is listed and learn some web scraping. After you collected all of the data, come up with some type of player ID and merge all of the information. This is a true data science project, enjoy the journey of it all! Let me know if you have any specific questions. | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-22 | Z0FBQUFBQm9ORzh5Z3pTNUtkNUpRNW82MHBxU05PNjNnd3pKeGRZeEMxNHp4NXl0VjJNUXFyVHJ4RWx5dFFXR3ZLWUUtR1JKenlCTEJJNE1QZDBfVUhveVBTMUtFSVRkQ0E9PQ== | Z0FBQUFBQm9ORzgxTzhxUmVOM0JXSl9xMFotRlVPN2Y0SDdObmxXX3RYQ1VOYkJxdTduaXYwQXRuQzVyVUhMaG9wTzRaUk4tbTFKWFFoZVJubU1RWHVwTTFDVGhDYTlHQlAtWVhrcFNHejNVTnRGUld6Y0pkRUZQaTBQWnNPRzRFY0loWUZtRnlXV1UwSURYSW4wenI2S3h1UFJ4VVRXQkVNYlVSTG92Skp3VlM1ZF9yR282ejlQbGVGSGg0Q3UwNm4wWXZlb091Tkh2UW1WbnN4dUlmaDVkX2dIakp1X01lNWVQVU9mMFZFM1ZkYUppeU9mZ1BIbz0= |
This is great | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-22 | Z0FBQUFBQm9ORzh5WnNsMFFIbFJSSmJEeGJpM0VpUUJiM2FuTzZ2aG8tZXE4b21faTZYZERDcDh0WUkySUE0Vk1mOTJNc1pBU3djbWJZMmgySW5fYVNjSnY3SjlSd0FIbENCSVZlVExKSXBuc2tqTV90Z2tubmM9 | Z0FBQUFBQm9ORzgxWHU5WjRjM0w5SC16amI4T04teXVGYjNSYktaeGdkMUdNYWNhRHpiQnVNcGQxdkVPSDhSMTR5cUo1V056R2IzZ2pFZ0dHTUhYVEVjLTYyQklkWFFkVzBpOWtMaWF0LW9UUVhRYUZZbDhXZW1NNkZPT2xzZFFhT1VZT3kycVo5QURRX2xiU0JDd2NOSjBOVklyZjZZTnFJM2h4R2NKc0RMbWJTU3NhMTkyWTI5M0hSRUpsSEU3elV3ZWJ2by1CbFlrVnI2X0NvODAxQ1NvQndPRWpiZmJfQT09 |
No need to pay for anything just use the nba api. I’m pretty sure it should have endpoints for the info ur looking for.
https://github.com/swar/nba_api | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-23 | Z0FBQUFBQm9ORzh5Mm92NkZUM0Viai1BNVppYm5zcmNXQ0llUFBEYm1SRnliTjZ4bWN3ZTdUdnB4WkNyUVpjT0hlUHFhTHYxZEpOelVtTzRZSHA3eHd4UXZ5dmpWYVdnNHc9PQ== | Z0FBQUFBQm9ORzgxakVrSFJoOFktSUFrcTIybEpJaTZwRVFTWE9BbUNXd0Q5clI2YUNwel8zX3VKeld3RmJkVFcwaTcxN2QzSzNjOE96Q09rV21SX3VxQ1FHR1V1eTdTbXRMN0Fuc25DX2FENU5EZTV2TE5BUHpQZC1ObTJkZXd1d1UzUEhJOXhDaF9DMTJnaW5NckE3bXA5YUhJX0VCNHFDZTJfYlhzRXV2U0FVLVA2TWE0Q3FMMXI0T2ExOF9yNlpYTGZ5bEhFNXloRnRVdEk3M044VVgtOEh3d0RZMEJSNnRwN0JDMnRrOE01SV9qeTNuM3VaRT0= |
**TL;DR:** Working in a risk management and valuation company in the energy markets. Confused about what roles I should be targeting next.
Longer version:
After a brutal job market, I somehow landed a role at a risk management and valuation firm that operates in the energy markets (USA). There’s no real title for what I do—it's a mix of dev, research, and modeling.
Over the past two years, I’ve built valuation models to price books for major players and utilities in sectors like batteries, power, and natural gas. On other days, I’m building data pipelines, SaaS platforms, or internal applications. It's been a pretty broad role. Being paid like $120k all In + $100k paper money + 1% company pnl (around 10-20k).
I also have a strong academic background in stats and stochastic calculus from prior AI research work.
Now I’m trying to figure out what roles I should be aiming for next. Quant? Data Scientist? SWE at a product company? Something in energy again? Curious to hear from anyone who's made a similar transition or has advice on how to frame this experience.
Additional Context:
I worked as a Software Development Engineer (SDE) for 3 years before going to grad school. After graduating, this was the only place that gave me a shot. I had no background in energy or finance and still don’t fully understand what roles exist in this industry. I am looking to stick with industry as it's more simulating mentally than a SDE/ML job however I do not foresee how my next 20 years would look like.
# Why I'm considering a switch:
**a)** Every year they give me "equity," and every year I end up paying taxes on what feels like worthless paper.
**b)** Uncertainty — If this company shuts down tomorrow, I genuinely don’t know where I’d fit in the broader job market. I look at typical SDE paths like SDE1 → SDE2 → SDE3 and wonder: what’s the equivalent in the QR/QD space?
# What I’m struggling with:
* I don’t think I’m a good fit for **Quant Dev (QD)** — we don’t optimize for latency or performance in the milliseconds.
* I’m clearly not a **Quant Trader (QT)** — we don’t trade, and I have zero formal finance background.
* I don’t feel smart enough (no PhD) to call myself a **Quant Researcher (QR)**.
All this is starting to weigh on me. Sometimes I just feel like switching back to being an SDE—be a cog in the machine—because at least that path feels structured and stable. | r/quant | post | r/quant | 2025-04-23 | Z0FBQUFBQm9ORzh5VXhuVXNJbHJpNjR2YkkxRjJ0ektzUmRoT0cwMGU4S0pTLVd6blhsczVGSU54ZnhBWFFLczNHUTBJZ2RibmdQNzY2LS1zX19idTd2S2F3R2VWcFpPTkE9PQ== | Z0FBQUFBQm9ORzgxVVZqZERnMlY4NGZMRE5MQThtYTc5dmtwb2d2Y1Y2SGx0LVdvT2xwTzRkZXpvbi1KQ3VVQzRsUTBCR2dOT2tLZHBsb0pWdlM5NlhYQmdvTnExSTJhd3Z0UUdfdW9sUUg2bllzenJZRkhQYWFScVd0dWt3a09nYTZXNDhack9mMFRtV1BWVFRwN3lNeXJwcGFnMHN5RG9ENHFwUDZCa2hoTmxZUzhraGUzaHJhVnJKMEFPS1c4QVdYRU5QSkZ1Tk0zNmloZ1NPNk8zNW1RMmxMTGJuUS02QT09 |
Anyone have any good recommendations for books on options and specifically vol arb? Trying to find some good stuff to have some of our junior traders read. | r/quant | post | r/quant | 2025-04-23 | Z0FBQUFBQm9ORzh5ay1SZnJuTWxPdUREZzAwb0ZzVm9Hc0FHUEdXM0tLU0U2cHAyUXRvWjFkN29WRjdMN3JtZmMzNjhuLXFlQ2dIZFRPQWJGNndvdTlrMldjRlhESTFzZkE9PQ== | Z0FBQUFBQm9ORzgxYWUxRHFsQ1lRSTd3OFJIWk94OVdPZUtGVU9Kbl9GbWtkMmpEaUhxZU5XbjQwaG5ITU50QXZPWXlKLTg2UW5ETDNYWHNvUnJIOWVpNkJHbHVPdExPTG9jdmxUSkk0TUotY3BpckJjXzMwYXhWNjlwdHowRGxNY2ZXWTFWajE3aFpVU1ppblh1UC1tMVdVeDZpOXZfdVFRPT0= |
Code reviews and 2-person reviews are important tools for preventing mistakes in software engineering world. I am wondering if anyone has experience implementing a similar system in trading world.
The basic idea is that a trade cannot be executed unless a partner also approves the trade and there is no possibility (or a lot of friction) to skip the other’s approval. | r/algotrading | post | r/algotrading | 2025-04-23 | Z0FBQUFBQm9ORzh5VGIwWHZHcUZrd2xzbFc4TmtxY3JrUTBXWmxDeDVrMkp5MVNnRnhvTTZ6cnEtbDc3RlhMT3VSWHozb1d4YjlUZlp5TkVTOGF1ZHppc3k4SVI0czd1bVE9PQ== | Z0FBQUFBQm9ORzgxV1BGbl9FcEpib0pIUUZOOURGYVFOci0yS21KdDNqVjB5TXBxeWVzS2xTR095ZDl0X2dJdlRoa21odlc2NGxWaFVtYjdmeEJFaUpUN3kyYThzRWpIb0haRXdQUDF5Mmp5SHRkZWlyLV9xMkY0YndfRFZTTEtySmlmUlprUkVvSk5xbXN3NFZnaUY5SFhQQjliMnVNWkFla1F5VXBqZ2VGbVpEWGNFX2RBV3B2d2Nnd0RFVmFac0NGNURaU214dGdmcEVOUmFEdkRSSVUzbjRhLVRqOVlDQT09 |
can anyone help me navigate the bittensor app? i have some TAO staked on there but i have a few questions :) | r/bittensor_ | post | r/bittensor_ | 2025-04-23 | Z0FBQUFBQm9ORzh5TURhSjZVNWpQYW9sRzF2Q2VHdkFIR0FGejRpSEY3MTBuc0hDZkd1cU9FU09YYmdNa2NLbkpEbFhoWU8zSlllU1A3bkIzY3lrYjNuOUlpZGE1ZkhiQlloX1pfS0h6RVNlNUhlRm1vTlFRTHc9 | Z0FBQUFBQm9ORzgxcjVMTFRlYWlPREdCR0lLZ0hYeTl3c1lUa0VWb2I4VDBnU1FtdklScnpyREY0OUNCdWtsZjhBMmhMRWYzSnJ4OVhjT2dIbmIxTjRWWEE0U3hpazljYlRCV3ZjSUpVbzZWa1BNc2tnOTJWZ0FXTTJQNXpxWTF6MWIzbHV0QVRYZnVOVVA1QmJIYkdMM0tEZkNIM0VtWU52aWEzWGdEWG5uUkNlRlpBSXRrN3pZPQ== |
What software or programming language do I use to create visualizations like this? | r/sportsanalytics | post | r/sportsanalytics | 2025-04-23 | Z0FBQUFBQm9ORzh5T2FUdkxXby1sdUFma2xCTU5ZajBaTkttN3ExN1gycU41TFVYMnFXRHoxa1UydzdSbmJEdl8yWnduUTlraWdLQTZmd0xqbkdpZ0lrZWFnVFFESHd3bGc9PQ== | Z0FBQUFBQm9ORzgxZXVmbThpREJVU3JUX0pjSmxiSHZqNDN5T0hVSDB5ZS1mZkRxZDFVcUNUSmpfYzR4eUltbFIzYTJzUk1VQmhNVWxqVzRMYXhWZWI5MTlXYmhvVmNJTEtfTFNBd1JIMnhFdEpqeFVkUEdzaGZUX1prODhpSmVBZ3R0VklvbmYyVFdZRnItMXd4OVB2S3dmaWduSFhXSlhXQWZ0VENFWHFzOF9GVjJqeUhXVDljPQ== |
Photoshop? | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-23 | Z0FBQUFBQm9ORzh5alR6cXlNOElQUWZOZkFXcUhwbkxvdm1HZmwyazhIWk45Ny16T0Q3Nk93OTJQM0xuQ3FDaGJBbnRSald0U1dxckVoa0ZFbW05RGtTRThoMlBoWkFNOEE9PQ== | Z0FBQUFBQm9ORzgxN2JIamFkTklyUE9MZTdreEJMVTJGMzgwVk9CdFAwellLUlkyaG1GNjFoTTFqbS1uY0xNNG5LcHZyZ05MVkJNRmRPaUZjQWV3QWN2YnVZSzZ0MS1Tb0NTREhLVHNaOWdjdFl2YUZMM3FkVFVpb3dxTjdsSkRGYWx4REtVb3BaTEZvN2NnSlRPU00ycGEtU3BvdlFmT1g2SUhXb0dyeWdKMjFIOVU2ZTN3YnROUTFwTDlNQTZLVFhYMks4WEM2dGcy |
Hi all,
Would appreciate any thoughts from anyone who’s been in or around this situation.
Quick background: did my undergrad in pure math at an ivy, spent a year in S&T before getting a QR role at a large multistrat, where I’ve been for ~2 years. Overall, I find the work rewarding, only catch is that the markets I work on are fairly niche and illiquid, so a) QR doesn’t always translate well vs just trader instinct b) the domain knowledge I’m developing feels too narrow this early in my career.
I’ve been interviewing externally for desks with different/broader mandates, and though research skills are always transferable, in the end they (understandably) prefer candidates with more direct experience in their markets.
I’ve been accepted to a few masters programs, all in applied math and CS with a focus on ML and a research component (T10 in US and oxbridge/imperial/ucl in UK). My current firm is also famous for enforcing long noncompetes (12+ months). So: would it make sense to quit without another role lined up and and do one of these programs during my noncompete?
Main questions:
- Would this kind of degree actually give me a better shot at pivoting, especially to markets/strats that are “more quantitative” (as QR exists on a spectrum depending on market)?
-Would going back to school after being in the industry be viewed as a negative signal (i.e. couldn’t cut it in industry)?
- Are there alternative paths I haven’t considered? I’ve interviewed for a while and just seems really tough to switch directly
- Am I overthinking this niche market thing?
I do think these programs would address certain knowledge gaps and make me a more mature researcher, but wanted to sanity check. Appreciate any insight. | r/quant | post | r/quant | 2025-04-23 | Z0FBQUFBQm9ORzh5aHp5ZWlJa1pSNGFackNBVE5TT2ZYb2stSkc0RlBUTTcxcHNRcXVkeEZ4dzgwRWNxRGZqU0FLeG1PdzlocjUwSlhuYkhmRkRYQTBxcjlWbzhHSHQyR1pCTlRwam1ORUhJMHh5WEV5QWdXQzQ9 | Z0FBQUFBQm9ORzgxandsdkt5WDk4VlZaNnJLVzZ0Wld6ZUw4a2lXYTBOU2IyVnhwelktNnI5NHB6NTdHNkk4Q2pKY2R2QUZxMjI2LWFoYUdSV2ZYNXMyVEhpRGNvSDY4TlFZZDBQYnpJVnZKOHIwT0Rob1BDWFVXUC1rM0NhdnpIdnV0dy15T2JkZ0VmMkg0MjBSYnQtSkx6RWlNZjlYZ3FiY00zNnhaWl92REFycVEtZWNDOGhMYklIQldFNUliTy03TkJ5NHJDRVNDWWlGMlcxa2pHZVVSbzJRQUoxc3RkUT09 |
I'm not sure about this specifically, I've never seen anything like this with a blue background. Most of the viz I see for sports is from R. | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-23 | Z0FBQUFBQm9ORzh5amNqLVVtcHVCeS1wSW10bEQ2S0VzNTh0d2xuekwxNUpzRFFZeFoweDVMVzdILUlQYnc3RHJGYUcyUWFKQTB5ZG02bEFLemcwU0x5OUp1T0JBNVo1NWc9PQ== | Z0FBQUFBQm9ORzgxVXRVRmExQUxrdXFiZml3b3BJTUJjN2VHZlZwOGptaHhvSm0tZG1KS25YanZnV0NLYVRBWW1YQmNuZGR4NkNlQnZqREZ5alZBMG4tSFBqNnhOaXlVcnM5ZmthNGNLZGYxV0xVTk1sZE5pQjM2UU14OEk4QWtjalItU2hnTmJfNjBUSkQxR01sMGVUeTVqUXQ0NU10RUlnQXN0SEloak9LOVJCYlBDWUdsb2tQV0dVbVYzd1F4Q3ZPMjdFQzg2WHkz |
Building off this there are people out there that have automated grabbing data from the api and storing it in GH repos like this one
https://github.com/shufinskiy/nba_data | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-23 | Z0FBQUFBQm9ORzh5ZXROOGRYZTJNaVBxLTJRb3V0R1NjRjYwZGFiTmI1S25oUUhXdEgxZ3MxaWVZdzJJTllXRzJMOU1xVUJzdUVXai1jeTZyMTFJejB6aFdEUXdWbkNRcXc9PQ== | Z0FBQUFBQm9ORzgxUllscXNHN2JlLWpkWWM4b3RKUENTZGgyVzE0TXhza0NJRk9pWDN5d0VMQ0tsWHExWFBaNFFaazlGQ2hOUHRUdnZ0ODExem5IbHFwZXZLVFJYNFpnWENLN0lvaEEtTG1wNFJad2NHaFludWREaEl3Y0NKaXFEbUhrWlR1dEJGXzBiU1NXYmpHeFNXMjV1XzBLbURIMUlTUUpkbU5HbjI0MXRVbDFLclBYa1RXWHV2M3g2SGd5NldPUEFzZ0N1cDlQeXhEX2JFQVpzWVlMbnFOcFZxVGtTenBuSTZlNXRqbGVVWC1lMWRDdUdHaz0= |
why is everyone so mean, if u dont like or understand something a fellow fan of the topic spent his own time working on then scroll on
neg comments say more about you than the OP, unless someone got a g\*n to ur head u got no reason not to scroll past unless ur just the 'type' of person to put someone down in a way that isnt helpful aka the top comment im seeing below
its sad, i work for the NDIS and so many clients 'appear' unaffected but its internalized and some stupid interaction youhave like this could have them getting upset all day about it, plus for all you konw the OP lost a fam member and is using reddit/this anylsis etc as escapism, there are a million reasons NOT to be a dkhead
and very few to be a dkhead; insecurity, personal issues you dont knwo how to deal with like for ex having to live at home as an adult etc, a feeling of moral insecurity, or ur own undiagnosed or diagnosed menal health issues....in all sincerity, look in the mirror...unless ur under 16 then i get it we were all dumb kids...but if ur over 21 most psychiatrists starting with freud would say you got at MOST 5yrs to get ur personality on pointbefore ur 'locked in' as an immature dkhead
consider this wisdom ull hate reading till u stumble on it ten years of now and realize you'd say the same with more life exp and im only 36 tho ive lived and worked all oer the world/4 pssports etc | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-23 | Z0FBQUFBQm9ORzh5czhKeHpGTzFFTHRIUFZxeDFYazdINDZaMWM0d1VTMnJkQ3hkOGZfZTFJam9rbWIteXRXc1FINkhud2NkVXdnenZWMjVLOXYzSzhjN2V6NnZfbllCWkE9PQ== | Z0FBQUFBQm9ORzgxLS1JN3hJZmtXTTZ0ekdWbUFDeEZOOVZ5RG1POWZIUC1INFhGZU1oX1hsVUE2V0ZJb19nbWxOMHUzRE1aaWoxNHUwRzdfeFFPbTNiMmFxTTVMRnZUN19zbWJ5dzk2SjV6bVFGc3VhUUZfZEdaYS10R3JzS1JQcU1UOVUzMDBERHNuUmVXM29hM3JRX0ZpRFR5LXBFRzVpWFh6X01Jd2I5WkFyRjdVak1SVDcySUpfZnl6cFZJUG00MndZOGNFZ1hmNjU3TTRRLVhEclYxN1I1aDZJeGpjZz09 |
Hey folks,
I’ve been working on something to help athletes better track their training, recovery, and overall performance—especially for those who don’t have access to high-end systems.
Not here to promote anything, just curious: How do you currently track athlete performance? What’s still annoying or missing in your process?
If you're into this kind of stuff or want to chat more, feel free to DM me. | r/sportsanalytics | post | r/sportsanalytics | 2025-04-23 | Z0FBQUFBQm9ORzh5UG9FSU9TNl9EcHptZlFrYnVQakV1U0pDdU9rV2hVSGt0OXl0XzZ6QkFTWWI0VnVpVXFJZWRGSUJjd2RkNk0zRlJfM3dGLUJORzJyUDM5djdSVWY0cWFNOHpDY2l5elR6SVl5R1VaQUhoalU9 | Z0FBQUFBQm9ORzgxUVNhdHA0V1ZlYkhUeXFzWFUwMV9qZkV5eC1ZZDc4dURVc0NtQnRFaTgxazh1MEJnenVoZFRaUzFvalpjU0VXU1hqUl8xajR5Q3U4aW5COS02QW5Fc0hkS0R2RW16eHFxUUdpY0htTGJkN0ppZlNYZjJCWG5PQXpWVzVyR052MDZDUHVMeUZ0Mnc0b1h1ZFM0aE1CYkQ2a2MzR1R3aXlUdVJDbVV3NzYzaFJkM3BzLXJNNkZtMzRVWDJQRHdhVXdXR3REZ19BdnlPVEpMY0hCaXo4TlVNQT09 |
Not a maffs guy sorry if i make mistakes. Please correct.
This is a correlation matrix with all my fav stocks and not obviously all my other features but this is a great sample of how you can use these for trying to analyze data.
This is a correlation matrix of a 30 day smoothed, 5 day annualized rolling volatility
(5 years of data for stock and government stuffs are linked together with exact times and dates for starting and ending data)
All that bullshit means is that I used a sick ass auto regressive model to forecast volatility with a specified time frame or whatever.
Now all that bullshit means is that I used a maffs formula for forecasting volatility and that "auto regressive" means that its a forecasting formula for volatility that uses data from the previous time frame of collected data, and it just essentially continues all the way for your selected time frame... ofc there are ways to optimize but ya this is like the most basic intro ever to that, so much more.
All that BULLSHITTTT is kind of sick because you have at least one input of the worlds data into your model.
When the colors are DARK BLUE AF, that means there is a Positive correlation (Their volatility forecasted is correlated)
the LIGHTER blue means they are less correlated....
Yellow and cyan or that super light blue is negative correlation meaning that they move in negative , so the closer to -1 means they are going opposite.
I likey this cuz lets say i have a portfolio of stocks, the right model or parameters that fit the current situation will allow me to forecast potential threats with the right parameters. So I can adjust my algo to maybe use this along with alot of other shit (only talking about volatility) | r/algotrading | post | r/algotrading | 2025-04-23 | Z0FBQUFBQm9ORzh5TEdKaUhTUTBacGxLMVZPY0MtdTROLWlMRjZXalB5SVVNWlRMVzdMY3R3dGRGTjl4d3lJTlo0QW5OYWNGdDhGQ1RScVlhVUFxbkxIWDRMWG5FQS0zb29uNXNUbHJnQ1ZiVDJvR24ySkpjdk09 | Z0FBQUFBQm9ORzgxQTFuR01PUW1Ka1Niak9YSF9hODdONlhPLUdieFpaVTVZN0tjM2hkUGc5aExsbHd0ako3Vnc2OVZ2MzNoQkpMdXJRbVd1ZmtZZV9ob0k0b085eGtCbElLek5EeEczSGQ1RGNscHlaWmpmcDZGZ3JLOEl6ODdYRkVfYktabXVubV9TRTdBc0RBWnoxeFNOa0Z2NWZKODBPUUZsZDdpQmdHdkxrRDZ3TXRPYnRSWEZYRlZrQUdLY2lZYVFRT2FMVHhVRFpvNHh2dnFFSGU5TUFhN2htYTV4UT09 |
I'm running a production-ready trading script using scikit-learn's Gaussian Mixture Models (GMM) to cluster NumPy feature arrays. The core logic relies on `model.predict_proba()` followed by hashing the output to detect changes.
The issue is: I get *different results* between my Mac M1 and my Linux x86 Docker container — even though I'm using **the exact same dataset**, **same Python version (3.13)**, and **identical package versions**. The cluster probabilities differ slightly, and so do the hashes.
I’ve already tried to be strict about reproducibility:
- All NumPy arrays involved are explicitly cast to `float64`
- I round to a fixed precision before hashing (e.g., `np.round(arr.astype(np.float64), decimals=8)`)
- I use `RobustScaler` and scikit-learn’s `GaussianMixture` with fixed seeds (`random_state=42`) and `n_init=5`
- No randomness should be left unseeded
The only known variable is the backend: Mac defaults to Apple's Accelerate framework, which [NumPy officially recommends avoiding](https://numpy.org/doc/1.25/user/building.html) due to known reproducibility issues. Linux uses OpenBLAS by default.
So my questions:
- Is there **any other place** where float64 might silently degrade to float32 (e.g., `.mean()` or `.sum()` without noticing)?
- Is it worth switching Mac to use OpenBLAS manually, and if so — what’s the cleanest way?
- Has anyone managed to achieve true cross-platform numerical consistency with GMM or other sklearn pipelines?
I know just enough about float precision and BLAS libraries to get into trouble but I’m struggling to lock this down. Any tips from folks who’ve tackled this kind of platform-level reproducibility would be gold | r/algotrading | post | r/algotrading | 2025-04-23 | Z0FBQUFBQm9ORzh5V3B6Ql95ZGVsbnQ1eTRtMktVc2lqOTNRbFF5TktuYzI5LTZBYWl1YllZQUZCNnp6b1l1alU0SFVlNHpFa0s5d19pOHFTVEMzWGFzNmxxV3hqVF9yMFE9PQ== | Z0FBQUFBQm9ORzgxTFByem52S213WlJuYnZsenktR3VPeFhud0diZWFXT2ozNkpMY1JhaVFIRUFYaXNlc3htdmtyYzI0ZlFhb1BhYTZyRmNBb1BxWFl0Q1dXUDBJcjFXN3U2cklkcnBmQll2a1plZ0NfLWdLQ2tvbGFIemxIR2VjMkpLcGV0X2t6Rms3dWdRZVRSVDYzem9YeklQVml6WkF5S3B3bGMzXzV5V2RKaklnUVJyWnZoRG9YOUtzMS1qajEzT0xfZExlWFlZV2tjcDZxbnM1S1hwTE1oRjZ4OWRJQT09 |
I'm running a production-ready trading script using scikit-learn's Gaussian Mixture Models (GMM) to cluster NumPy feature arrays. The core logic relies on `model.predict_proba()` followed by hashing the output to detect changes.
The issue is: I get *different results* between my Mac M1 and my Linux x86 Docker container — even though I'm using **the exact same dataset**, **same Python version (3.13)**, and **identical package versions**. The cluster probabilities differ slightly, and so do the hashes.
I’ve already tried to be strict about reproducibility:
- All NumPy arrays involved are explicitly cast to `float64`
- I round to a fixed precision before hashing (e.g., `np.round(arr.astype(np.float64), decimals=8)`)
- I use `RobustScaler` and scikit-learn’s `GaussianMixture` with fixed seeds (`random_state=42`) and `n_init=5`
- No randomness should be left unseeded
The only known variable is the backend: Mac defaults to Apple's Accelerate framework, which [NumPy officially recommends avoiding](https://numpy.org/doc/1.25/user/building.html) due to known reproducibility issues. Linux uses OpenBLAS by default.
So my questions:
- Is there **any other place** where float64 might silently degrade to float32 (e.g., `.mean()` or `.sum()` without noticing)?
- Is it worth switching Mac to use OpenBLAS manually, and if so — what’s the cleanest way?
- Has anyone managed to achieve true cross-platform numerical consistency with GMM or other sklearn pipelines?
I know just enough about float precision and BLAS libraries to get into trouble but I’m struggling to lock this down. Any tips from folks who’ve tackled this kind of platform-level reproducibility would be gold | r/quant | post | r/quant | 2025-04-23 | Z0FBQUFBQm9ORzh5VGQzdF9pOGRNYmpKQXNfU3lBekRKUkVlR0NUSlRwY2h6VC1teXpEWUlWbk5salM5WFFVdHB2MGR0MktyR2FCV2xUQkNiSUxwOGJQajBNM19fSTFadGc9PQ== | Z0FBQUFBQm9ORzgxdTFsejVRNjZOZmZOTlpYLWVDaHh5SFlsSjZIbm1pSHl2blhKTW1USWVTeHJuU0tLakM1VDNIU2RxQmk3YmRmck1WUmJLbXBoNWlJVXBCR0w1S3l5S0dKclVFQlI3NEFTSE9LUmFLX21EbmczXzhyVFlobFYzbFcyTXZ5YjY5Xy1iLUx5aEJSY3VoNlhJRzBzekNWb3hsaGJPZEhxRGROa2NwVzdid3EwUkRVYk5nTHBXc2gzV3dpLUpwUHV4MHJ5 |
Let's say somebody develops a quantum computer at some point in the future, after monero has become quantum secure.
What information can they get from existing transactions / outputs from \*before\* monero became quantum secure? | r/monero | post | r/Monero | 2025-04-23 | Z0FBQUFBQm9ORzh5dGV5QXktREJXTGh3amNDU0FybHd2dWhGQm9VV25nYWRkNzlhbl83OWVsVHB4VTJuQ3dVMWxjRnNOZkZhYXJEUjJ4TGtsY1VaS2MyeHJrRmZsbG4wMHc9PQ== | Z0FBQUFBQm9ORzgxMkNIM1liakJSODc2WkFTaVdnZ0NWT21ZTWlISG5mNVE4OEtnU2JiVnBwVVI5QnNyZ0VlSGpYSGVKNGtYMWNQR0VSblc4bVJCNExKQUo4VmczYnBUSk9UWmgwZVhQMHU4OXhha3ROUGZxTmZyaXF4d3JvZHlRY1VlY3lMRjgyODNRQ2lZanFnN2xJZUtZZWFHU1JxMmZQQ3FKR1ExWWoxbjVsMnB3ejhXcUxnZVYxZEk2QTByaFRNZzdaYVpYd2J6STZyOEdnTHVCdnVPeE5iTmpLQ2pVdz09 |
Probably plotted normally with dots labelled with the player names or player_ids, then the headshots are overlayed in photoshop or something similar | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-23 | Z0FBQUFBQm9ORzh5WVhyeGd0dkRNb0xvSnZoSGJtcXN6MENmaDdWNnoxMWNoOVFjalY4QnlNcnE3VVdQMHF3S0NRMGtmejJ6OXY1Ul9LYTlZNlE4NWlIaVZndzlmc1V2anc9PQ== | Z0FBQUFBQm9ORzgxdTFxdldibzhDbmFISk5jTWk5bzNEVVRDMGYtR3RrWGN0WmQwcV9PQ0tucThhdmlXdnctNDVXOEQ2b2JQQmdZVGNiV2tGc3RLUkxMTFRVYnZoWFl4cWFqZmttd3dLT3A3NXc5ZnIzZDRTNzVoSGpSV1Z5blg4RDF3SnVDNVI5VHYzelJOVzFSdHVyQXJYR0NuUzQ4NUhtaGl6SUdMYTZDLWlOc1lydHppeURROFA4NFF3YmJSbmhINm85Y1BqeGNx |
You can use R to do this. You could also use Power BI. I believe there is an enhanced scatter plot option that you can use. You could also use the R or Python embedded controls in Power BI.
It may not look exactly like what you’re after, but you could get a clean view with images instead of points on a scatter chart. | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-23 | Z0FBQUFBQm9ORzh5Ym1hZ0p4RFdfRVhiTkd2dmNkcnpXMGRubFhBdzlJd0Y2TXRvaV9rLTEzNW1ILUFaNzJCSEwwR21LSzdJSzlLTWFFci15MDhfRElzczdwM0xCbnVwR0h0MUZmT3JjMGo0LUFIX2lLajJXMEU9 | Z0FBQUFBQm9ORzgxM3pfb3RtcU9HTXpSSGdtY3dGbFRBQU0wNC0zb19xcWlFa25rRnR0UnVITlhDWFlRenZESURJTVpQc3JEODh1cXd0UEtQZF80VDhfcDZqdHQ2TjB5VnI1bi12Nlc0bDhFZjdCWGtPZ2J5cTB5TXItZnRNWE5uUmVzWlBpRHc0T2NpSmQ0cnBpQll1TG50V3ZiSFlsY2VsbmFXd09PQld0eTBWTzVWSmdzeDMwTjBFeGFZeEZ4YzRLX3RuZkdwei1q |
High-net worth financial advisor searching for some useful course or book up to date with the recent technological advancements in AI to learn how to exploit the various GPT APIs out there for financial analyses, client and portfolio management. I'm ready to pay for it with no specific budget, any idea? | r/algotrading | post | r/algotrading | 2025-04-23 | Z0FBQUFBQm9ORzh5aXA1QlN0SFYzbFFqZWJkUllhWUI3OWt5b28zdWpVNWRlU3dxWl95czVISEtzbEl4cTczbVp6YVNiWTZGMmV3c1dLZUJIRGxjVks3NUw1VDlUeFdhRWc9PQ== | Z0FBQUFBQm9ORzgxd3phRDliRWJJVmRnQ2NkZlBaQlJNdkx6MTZXdkJ2TnBFS21LUF9kbjNZeEJMY3RBZ2p1aWVMbjRTTDlWZ1RBWk9ac0tlem9FQXljSFN0bXFMVGZxTEFXMmZjTWJ2QV9xRkVuUDVRcUtiTXhxWDJxaDNEQlZpZUtrLUhENE5mWjAxa0x5OF80a01BTVJ5UzM2X2I1dGt6cGkyb2RGQjljdF9KNFB3NnByRGFEazFlbVk1VnJpNmhFWEhTUWlVYVpQSjhncng0RnlSeFU4a3BrZ1JpRG54dz09 |
I just came back form one of the big alt data conferences. Based on sessions and customer conversations, here’s what's top of mind right now:
https://preview.redd.it/49mtc5ukwkwe1.png?width=1050&format=png&auto=webp&s=9b7527beda7bef989e6caa522612c0448a85f185
AI is definitely changing the alternative data landscape towards more automation and processed signals. Information is every fund's competitive edge and has been limited by the capacity of their data scientists.
This is changing now as data and research teams can do a lot more with a lot less by using LLMs across the entire data stack.
But even with all the AI advancements, the core needs of data buyers for efficient dataset evaluation, trusted data quality, and transparency remain the same.
Full article: [https://www.kadoa.com/blog/alternative-data-trends](https://www.kadoa.com/blog/alternative-data-trends) | r/quant | post | r/quant | 2025-04-23 | Z0FBQUFBQm9ORzh5YlRFOGVRX1BlajE5bGtvcmp4ZWY2Uk9ZRDFrSHBaMXgxQkU3WGE1Q01icFlvNll6RndmU2dLN0JIMjkzUW5uY2FheHBZYThWcXFmallYWTJibTJqLTJsRWlTQlZPOTJ2ZWZsYS1WTHluNVE9 | Z0FBQUFBQm9ORzgxbER6aTNaV2pCOWN1dzBRX1JmSUx0SzlJQTc1S3BPdjBJblg2cWRiNEVHTHI2LVltZ0N0RWRGMm9UX2RkSlBINFZnNk12VlRZZFZlRTRSSmZlbkV0RURLNldrYkhycmZJcldLREo3SWh6Tzg1bGYwc29Wb0NfZTFTZWRmMEgwazNIWExWSXhPRVhQUF9laWxZdGVXNk5FWWdOa0RUUHNsQll0VUhjODFZczFRPQ== |
[https://forum.zcashcommunity.com/t/monero-everywhere/50689](https://forum.zcashcommunity.com/t/monero-everywhere/50689)
>*You don’t like the title? Me neither, but it’s true nonetheless. Everyday I do something involving a payment online, more and more places accept crypto, more and more places accept Monero ...*
* *Yeah, almost all payments accept XMR, but very few accept ZEC.* | r/monero | post | r/Monero | 2025-04-23 | Z0FBQUFBQm9ORzh5WlZJUHhoRTV0clpzZVhuZGNkcjVVbVdBZW40WGZvTWxFZ1dZQW1lV29sSUh3RXV4amV2MmZpTmNuYWhRT2JHbkM2UFlCOHJ6VGduZlJCejhhajExWmc9PQ== | Z0FBQUFBQm9ORzgxd1VKaGkzYnlZRE1rdW9oTHZUYmtiQXI1UV9jYk02RHlJaHBDNWVTMEI4QXBmbFJvV3BwSXMtOGNSM0d2UmQtSWdnRXFONWE0aHdyWDkyYlhtbVBDTlpwOWtpVWxxcnQzSzBmTTh4enJ2dmJ0UG5POUo4YU5PZU9LMDFkakdLUl9DMkozSnBQeDdwVUdVakxVUEhvdjcyNVo5Q3NFUUVWRVZpRC1weW9CUmcyUk5LZjdqV3pReUlUelV6aUVwRmZh |
I currently have a temporal cnn model that predicts daily close prices, but I am planning to creating two other models to go along with it. The three models will model the long term (past 63 days, daily prices), middle (hourly prices), and short term (past 1.5 hours, minute prices) tcns, then combine them into an overall prediction. Is using multiple architecture the norm? My overall goal is to create a sophisticated intraday model and do not know what is considered standard. | r/algotrading | post | r/algotrading | 2025-04-23 | Z0FBQUFBQm9ORzh5cl8wdmk5cDQ4UzFrLXR6bWhMbUViQ0wtem9sT3ZSd09XTGZibTVRUnljQXkwYXVYQ2ZORjNjTlVDaUFpMDVLX1BwRkJaOFBKc2NVa2h4X052cGlfdVE9PQ== | Z0FBQUFBQm9ORzgxWVJycTc5aS1NcUpqVUhzVVFnUWxYeUFrdzFSVjJvRHNYS21qSHRmRUpzNVZ4ZkhVcWNnYXJXMktDUnpnZmFybmFIWWRMaEhTWUxRamFGdWxONGpZNmxOLWNjWHVXclFwZWozS2hYcUtkYzlqNUt1WXBaUG83dG1OS01RWTc3Y2djb3ZRQjdrOFFRM1ZhUmVpUllHMzV5VDFPQjQ2bC1ZRUdkVGx2ei01dHlNV0RNTXdhS1F4c3hFemhHU25zNnc3SGVJNjRJVWpRWjhVYnJ3ZTVIZE5GUT09 |
You could also ask “what is a successful strategy”?
When do you say that your strategy is successful? Do you claim to be better than the market, i.e. better than the buy & hold yield? Or do you measure success by a certain percentage?
I trade cryptocurrencies myself using several strategies (mainly DOGE). Unfortunately, I rarely manage to outperform the market. After all, I never make a loss, not even in a bear market. I am currently trying to figure out how I would define a successful strategy for myself. Can you please give me some food for thought?
Personally, I would like to generate a steady income. It doesn't have to be my main income, but simply regular cash flows. However, I am now asking myself whether it makes sense to continue with my algo development if investing would be a far more successful strategy in most years.
Thank you very much. | r/algotrading | post | r/algotrading | 2025-04-23 | Z0FBQUFBQm9ORzh5QXRjMWUtOWQ4cU52d0lpOHIyc0VWeEY2X3ZkRzdZNm5zQkoxNzJ3c3VQYjVwNFNIRFJPV20yQXdFUEhvM200VDY3Wkc3MWVRTGJDRUFLcWlQTU1wcEE9PQ== | Z0FBQUFBQm9ORzgxZm1YV0xWckV2VGdGdTgzLTBMZHRPZUxPYzBtb1lHMUpNeTJ6NmJCVWtRZm1kX3NUM1lJX3pQZGNKbzN5SGhqc1FEX2dJMnFQM0hvOUZTcnptZFhESU5VN1J1dGFURWFSM0dTN0VkQm5waUV4RzkwUEpuZU1XalVid0l4N21wNkFPeHZSZkRHYzZ5TXVFTFdDeDNNeklTSU5jRnBhZFMwWWpPbzRNRmY4QUpGTnJmckEzWnVEWXVTX3JrZ0JsUTgzUUpmU01YeEgyQVJkd0ljcjVrLU90UT09 |
https://youtu.be/XoqdTfKQCjA?si=Mg94qW7TUIroi9M7 | r/bittensor_ | post | r/bittensor_ | 2025-04-23 | Z0FBQUFBQm9ORzh5V3R3R0N4QW9iZk9nQUNaVUhJUTdJNkxpR1RJc3o4RTdkY2tLLXkyOUVFN3dyWjBPb1cwek9LZ2VYXzhoMkQ0dFZucjF5dW9tN0hnUHlWYld3bEZaTzgxMXpOLWhOeGo2bEx6ZmowWlhQMVk9 | Z0FBQUFBQm9ORzgxcjFGemwzeWlHS0hIYnBjWWFpU0pqT09TUVhMbFp2eTVkVFU5QjI5ZFllaF83bmVzMzBlUnFyNFRVNF9mdVowdkNiMlJhVGktRGRZVmhHT2VaYU5obWVPX0NDZUd1ZGZaSU90Y25PS3pkc0J2YXFXZTBBWWE0NkVMYWtpQ1F6X3Exejk1Q0o3VURLNXVrajRsMEdWeExrT1NTY0ktOURiU1FnNHE1eGRPblBsSUFmaHB2b0gxd3JNWW1XV0liOXBBeVUtWmloNTZ5VHZCLUZUU0FBeVMxUT09 |
Hi, i’m an undergraduate student working on my bachelor thesis, which will be about the mean-variance markowitz model considering stock borrow rate for short positions.
I’ve had trouble finding any historical data on stock borrow rate without paying and exorbitant amount of money, we even have bloommberg terminals in my uni but we don’t have the required subscription for that kind of data.
Does anyone know or use that kind of data for modelling and if so, able to help me in this case? | r/quant | post | r/quant | 2025-04-23 | Z0FBQUFBQm9ORzh5cG1LYUtoVGpFRUlaVTFpdWpVQjU5Z0VNcGpReFNHYTZNdVZPVlF3YTdyZUhrV2cxM0h5aXdXbmV1dGZnc2JtNW5zc0NscXNtZEJUc1I5SjM4NmxVVUFFMUpyeGlYVVZUTHRmVHloMURFQUE9 | Z0FBQUFBQm9ORzgxNFVVUzFiUm5TUmhjV0lFUFlVcWFza19qOWcwTkRraGczbUtCX21nVm9VcXhPSGRtY1VhNGs0WndfX2IwZkV1bWhMOXJuV090TGJWY1VVNFZta3huMWNxTGIyRGtDNktPOF9ROFMtTGYzcllSMGp4MjNiMFNDNzBXSnBBYko5MGg1Y1kyd0dCVks3WUZoWTZKME9tU1VDUHAzbC1ZaG5fVzJ5bkRneDVXNFMwPQ== |
Bullish. | r/bittensor_ | post | r/bittensor_ | 2025-04-23 | Z0FBQUFBQm9ORzh5dU05dlRQVlJ0U25pNVVucjZLN0U0Y1FBSnNhSlBTN0NJUjJBcVZ0Zld0VmxZYkd0Y1QzdWY5bVZMV2tMOWVIN1VkbnhKWWxwMXBVTU1zZF9uVFB5c21SWWxjNFJkYms2VXBWdkJXandWdzg9 | Z0FBQUFBQm9ORzgxNVpHejFDY0tTYW9hWFpIWlR3XzhPWjdmb0xXWHEwSk4xSXJDRnVDV2RkVk1seEVOZGItMDM4bGUxUjF2OFVJdFhoc0hLeUlyRDhPaURlVXRmWktoV0RVYkhmZk1Ma2NTc3h2LUp6RmtORFZQQmNXUi1WeDlvaTZaUVNocDMxcUdhZV9reTVrMHFwdTU5MkxQWE16QUVzS2JVSTVXT2pXRlRRcnZndUpBNHM0TE11TEsxeVNNdW5sd191VWJ4QmJoWnZnWjdSeC1WVWR0QW9LX0JFaDQ5dz09 |
Why is the number of trades per day relatively flat on [https://haveno.markets/](https://haveno.markets/) retoswap, yet volume seems to be increasing so much?
Transactions per day have been consistently between 20-40 per day. Volume has gone up by nearly 10x in the last few months it seems. | r/monero | post | r/Monero | 2025-04-23 | Z0FBQUFBQm9ORzh5RWRjRG03SGhTUnh6VzNUOWx3WF8zMWFxcngxR2dJNklTenEwc3F2ZWExc1dxTUVOU19UWHEyQldGaDdReWVYa3lEYmpKOW9mRExKdHJZbXE5ZzE5d2c9PQ== | Z0FBQUFBQm9ORzgxMll1bFhJR0JTZ0l1UVZnS2NINGtXQ1l5YVdXVTU1VS1IN1hEQktEUmF5THVLanIzSURHWVpwNld3c01ZZGNMcm9FWDFqNG9UMlRSX2RvSnJ1bmhsSlBqOEM3UkF5MlUtYl9wX2NmeFdqVTBZM0FKZUNTZ0xmSlhzV1dsWlozMTFrcFhWZENfZmRMYy1GQTQ0R2k1NEp4MnBuVVNlcEo4bUI4Q3pRdlhLRktZPQ== |
More deep dive
You will need some analytics. R or python.
Some solid graphing
The nice thing about the graph is the headshots. So you will have to tie into a library that has them. I'm assuming that they come from NBA or nba_api.
So I would use python to brag and aggregate the data. Then use echarts or plotly to visualize this.
Throw comment in a llm and you will get some momentum. | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-23 | Z0FBQUFBQm9ORzh5TGxGRllSZUpJeFYtdktJQW9IRDkwdnVGVmdiRnJvLWttbEtQUmtySmVadXpzY2V3SGxpU3lJUURFZEVqV2d0eGU4dlROakF6T0R2YlpjSDkxWFRWMHdFcXZfLWZQVktKbkgyaVl3TlF0Z2M9 | Z0FBQUFBQm9ORzgxWWUwU3hNQTE3eXNQcnp6OGRXVmE0b0tkMUdjbFFOMmloSWhBMXdUM1BuRkNrYnRlNGlOZ3RobS1DLWVmYlB2VWMzR195dTN5aVVTVzJXaUVKejBXMWVha2h3cEEzSGdVZV9xZjdtQ3lCamV5Wl9GMTJWM2UtTm9BRTZMSlpmNEpIVG42dUFCNHlXdkJsZjg5UDlkNU1EY0gwTXRhTkV3U2JERTRhc2JndEd6eEJzVDNTNjdSV2VqZXhkdk5sZWR2 |
Hello,
I have built and tested an AI options trading bot that handles strangle options trades throughout the day, it is profitable every day! Using ChatGPT 4o model. Basically harnessing capabilities of LLM and the newer vision/image reading. I figure if AI can understand the difference between very similar looking dogs, why can't it understand chart structure. Turns out it can.
This seems way better than ML... I'm not even going to use ML anymore. I was so impressed by this, I wanted to see if anyone else uses REAL AI for chart reading, data analysis, decision making, etc. and not just trained ML models?
https://preview.redd.it/w74q6xuohpwe1.png?width=2046&format=png&auto=webp&s=120af698adcf90dc259b189e2bf0a0ee1bca1e24
https://preview.redd.it/j33iwb5ugpwe1.jpg?width=1280&format=pjpg&auto=webp&s=229625e40a61f903299f300758730dde56a69462 | r/algotrading | post | r/algotrading | 2025-04-23 | Z0FBQUFBQm9ORzh5M2ZnTnRWU3NBcnJraW5sRTh5X1RKUnZMd2hvZzhmdFJkYXpxZVQ4eXBvY1RrZDdrSTVlUWFQUWIxRXNFZjFYNlJNRjZtZjdmWUpHTGdTTXMxXzJ2dVE9PQ== | Z0FBQUFBQm9ORzgxbC05eVRGS25WTndITzFCOW1QWXVDd3dOc0VyMjhvUEp1OTRvdWhGSVYydEVxdV9aeWFqblU2SGdHOEhGZ1U0WGwwOU9mWTlkc1dKSzdOWUh0THk1cTV0SDFzQVh2SW1aVHJYdXp1Y09JaUFmU29mbFczaVNERWx3bWpQUVMxVGZfVFBTNlA5Ym1fOFIxMDRLelNlQ2tVU2Y0V3JzblM0MXhCd0RmbDJIM1lrPQ== |
TLDR: I'm currently building a web app that:
* Automatically loads videos from a source
* Allows users to directly cycle through the videos there
* Timestamp particular events by just pressing Enter, which is saved to a database that can be exported
* Mark or fill in any additional parameters that are needed
* Add or remove the parameters (custom fields) as needed
* Has auto audits and field restrictions that prevent misentries
* Creates a dashboard for statistical analysis of the parameters afterwards, based on the user's needs
The problem that I'm trying to solve (for a particular use case which I can't disclose), is that currently the users are operating as such:
* Having to juggle through multiple video links that are all on a spreadsheet
* Go back and forth between the video and Excel or Spreadsheets to write in data
* Often missing key moments as they can't just capture the exact timestamp
* Assigning the videos for review through the spreadsheets as well
This is obviously quite inefficient and prone to user error, whereas the system that I'm designing minimizes the mistakes while making it much easier for the users to organize and use their data afterwards, instead of juggling many spreadsheets, video links, and generating their dashboards.
My question to everyone here is, do you know of any use cases or particular industries where these types of operations are active (i.e. video reviewing in this manner)?
If so, what are some industries that use them, how do they use them, and would there be a potential market for a tool of that type (or if you run this type of operation would you use it)? | r/sportsanalytics | post | r/sportsanalytics | 2025-04-23 | Z0FBQUFBQm9ORzh5N2tHWWxxWGx2UXVjT0hQR0xRYVVhVE5HR0UxazYxUkx1dzk4R0Ezc3AtT0tmdTNTV0h4ZXNUQTRCTThLZk1tdHFLall0MmRhQTY5dHNmajQ2dlhPdWdSdkVJZ1RNbDF0UHcwellPdFRSSE09 | Z0FBQUFBQm9ORzgxWWtlZzE1VWVmQWhXMUhobEVaU0RYMGx6dTI4WGkxTUJZdnpSWTdWUmV6M0tGOEI2X2pRR0s3b2RBTExmRzVRQ1RiaUxIRFFPa0owTWJ4WFkxbjdzSFdCOUVaM0NfazdYZXQ4LUtFNFNPS3ZIZkkzSF9XUEIwbEU4SGdIWTBtTHh4S0tEaUpmc3hxUmZNMjMwcTFsTXgxTDdJRUstUGtXLUdoMEV6bk5ud3lmYVhzMkU1YTZQYkJfNXdrQVJnTDVkY2xKNEFRYlZnR29rU3UxQ29sMnlLUT09 |
Is this post just.. an image saying the same thing as the title?
Figured there'd be an article linked or something.
I like filecoin but this seems like self congratulations for an imaginary achievement | r/filecoin | comment | r/filecoin | 2025-04-23 | Z0FBQUFBQm9ORzh5cEEwRUc0Umgtb2VockJ4ZE5TbGNIaE9hR0F0VnpYMGJPSXB2UFB6eHJpWEp4cWlaVDhBeWxvRXhYM0JmNnJ4SWtJdnVnVFktbFJKaVg5MXlEZ3FvcG1XU3BkbFduaGE4WjN1dlFFVUJEYVE9 | Z0FBQUFBQm9ORzgxRkdrZXhsNHdNTjlZR2VSYkdWSHdtV0RIZDhuVFdOeFFqbjFPQUxoNFJFQkp5aS1NZDBTUlVURWNiUzNXNnRycm54eE04ck5lNC1wXzNZZWo0TFdWNzUwNDBuNTZVWXg1T01fS1ZtVndnR0pfYzI1U0hvYlZkZWRfSFNzQ1Z3UXk0YXY2TUw1bHpiOG8yLVRXTHJzZVlnWjF3Mm1VWktsS0RwMUpZV3Z4Y0NTXzNueGQ3eHB3cTVhUVAzNDJScWJKRmFJRG1FSkFIZ0tlU2FkLS1iSjhZZz09 |
Hey folks,
My earlier post asking for feedback on features didn't go over too well probably looked too open-ended or vague. So I figured I’d just share a small slice of what I’m actually doing.
This isn’t the feature set I use in production, but it’s a decent indication of how I approach feature selection for market regime detection using a Hidden Markov Model. The goal here was to put together a script that runs end-to-end, visualizes everything in one go, and gives me a sanity check on whether the model is actually learning anything useful from basic TA indicators.
I’m running a 3-state Gaussian HMM over a handful of semi-useful features:
* RSI (Wilder’s smoothing)
* MACD histogram
* Bollinger band Z-score
* ATR
* Price momentum
* Candle body and wick ratios
* Vortex indicator (plus/minus and diff)
These aren’t "the best features" just ones that are easy to calculate and tell me something loosely interpretable. Good enough for a test harness.
Expected columns in CSV: datetime, open, high, low, close (in that order)
Each feature is calculated using simple pandas-based logic. Once I have the features:
I normalize with StandardScaler.
I fit an HMM with 3 components.
I map those states to "BUY", "SELL", and "HOLD" based on both internal means and realized next-bar returns.
I calculate average posterior probabilities over the last ~20 samples to decide the final signal.
I plot everything in a 2x2 chart probabilities, regime overlays on price, PCA, and t-SNE projections.
If the t-SNE breaks (too few samples), it’ll just print a message.
I wanted something lightweight to test whether HMMs are picking up real structural differences in the market or just chasing noise. The plotting helped me spot regime behavior visually sometimes one of the clusters aligns really nicely with trending vs choppy segments.
This time I figured I’d take a different approach and actually share a working code sample to show what I’m experimenting with.
[Github Link!](https://github.com/tg12/2025-trading-automation-scripts/blob/main/feature_selection_with_hmm.py) | r/algotrading | post | r/algotrading | 2025-04-23 | Z0FBQUFBQm9ORzh5dkZUaWtwdmZIbGhOV3poYVQ4NHRjbGNrbHV1VDNwam44TlFJZEgtcGxNWWNYN2hNMm1NbV9TX3g1UktyTENpa1pGZXV0U29XcTdTUEJhNmlnbS0wT0E9PQ== | Z0FBQUFBQm9ORzgxTWpiT3AxYlpwZUxILUQyUXpsYU5ma05nd0dkSDNINnJkOF8xTXRwazQ3SEQ5Q1dxZnR6U2dBSDlGOUV6TkVmX3pYNzVOSVlFNHFMY29vdF95T2h1QlBzZ0s0X2NrVmhIemVLcjF2SndGZkhtcmhlSTZZUjIwNmJ5OEJDd0RoYURvUllGMkVBVjVSWFNFTkV3aHhfTElUdkZvVWo2VHYySFc1Wk5iREZCR3YybDF1ek1HTy11R19IY0Ewa0FWXzRaUzlUUV9TVU1YNmFXd0ZOSTNmbEZtZz09 |
Hey folks,
My earlier post asking for feedback on features didn't go over too well probably looked too open-ended or vague. So I figured I’d just share a small slice of what I’m actually doing.
This isn’t the feature set I use in production, but it’s a decent indication of how I approach feature selection for market regime detection using a Hidden Markov Model. The goal here was to put together a script that runs end-to-end, visualizes everything in one go, and gives me a sanity check on whether the model is actually learning anything useful from basic TA indicators.
I’m running a 3-state Gaussian HMM over a handful of semi-useful features:
* RSI (Wilder’s smoothing)
* MACD histogram
* Bollinger band Z-score
* ATR
* Price momentum
* Candle body and wick ratios
* Vortex indicator (plus/minus and diff)
These aren’t "the best features" just ones that are easy to calculate and tell me something loosely interpretable. Good enough for a test harness.
Expected columns in CSV: datetime, open, high, low, close (in that order)
Each feature is calculated using simple pandas-based logic. Once I have the features:
I normalize with StandardScaler.
I fit an HMM with 3 components.
I map those states to "BUY", "SELL", and "HOLD" based on both internal means and realized next-bar returns.
I calculate average posterior probabilities over the last ~20 samples to decide the final signal.
I plot everything in a 2x2 chart probabilities, regime overlays on price, PCA, and t-SNE projections.
If the t-SNE breaks (too few samples), it’ll just print a message.
I wanted something lightweight to test whether HMMs are picking up real structural differences in the market or just chasing noise. The plotting helped me spot regime behavior visually sometimes one of the clusters aligns really nicely with trending vs choppy segments.
This time I figured I’d take a different approach and actually share a working code sample to show what I’m experimenting with.
[Github Link!](https://github.com/tg12/2025-trading-automation-scripts/blob/main/feature_selection_with_hmm.py) | r/quant | post | r/quant | 2025-04-23 | Z0FBQUFBQm9ORzh5WmtGb2NvTEZ2WF9tUmJvbV9ILUZPdzhNbDJyeVYtMm1iWkZpNXVmUDVWcmJXbjQyYzVqWXIydlVXLXI4M3hfbV8yMFpzNmhEc19zd1BITTFIb2J6NWc9PQ== | Z0FBQUFBQm9ORzgxQlJXeXl3bUs3ME1DUWphSXJxems4ZW1VOGluOVhlUk5oNG5TUGZlWXN3Z190eVNUU3FqLXlZeEkwU0xEN3Rib3FMMjFabllLNXdEcDlyU2g3ME5XbmhBbjhoU0NUZUdfaEtnTjcwdkctcHJMQ1VIVC1FbUE1RzVRS2pvX1owczEtcW1XTlNOTFNieno3dWI3N0JlLWlibUFLZzJPVC0yWjlNeXhNcmFCUl8waGtwWDd4RW5yQkJON3hsdVN3LVE4X2lzNzVWYktuNS1GaC11LUNoeHFMQT09 |
Was kind of a dick in my last post. People started crying and not actually providing objective facts as to why I am "stupid".
I've been analyzing SPY (S&P 500 ETF) return data to develop more robust forecasting models, with particular focus on volatility patterns. After examining 5+ years of daily data, I'd like to share some key insights:
The four charts displayed provide complementary perspectives on market behavior:
**Top Left - SPY Log Returns (2021-2025):** This time series reveals significant volatility events, including notable spikes in 2023 and early 2025. These outlier events demonstrate how rapidly market conditions can shift.
**Top Right - Q-Q Plot (Normal Distribution):** While returns largely follow a normal distribution through the central quantiles, the pronounced deviation at the tails confirms what practitioners have long observed—markets experience extreme events more frequently than standard models predict.
**Bottom Left - ACF of Squared Returns:** The autocorrelation function reveals substantial volatility clustering, confirming that periods of high volatility tend to persist rather than dissipate immediately.
**Bottom Right - Volatility vs. Previous Return:** This scatter plot examines the relationship between current volatility and previous returns, providing insights into potential predictive patterns.
My analytical approach included:
1. Comprehensive data collection spanning multiple market cycles
2. Rigorous stationarity testing (ADF test, p-value < 0.05)
3. Evaluation of multiple GARCH model variants
4. Model selection via AIC/BIC criteria
5. Validation through likelihood ratio testing
My next steps involve out-of-sample accuracy evaluation, conditional coverage assessment, and systematic strategy backtesting. And analyzing the states and regimes of the volatility.
Did I miss anything, is my method out dated (literally am learning from reddit and research papers, I am an elementary teacher with a finance degree.)
Thanks for your time, I hope you guys can shut me down with actual things for me to start researching and not just saying WOW YOU LEARNED BASIC GARCH. | r/quant | post | r/quant | 2025-04-23 | Z0FBQUFBQm9ORzh5anROSVdnRThVSVFWaXR1RDhRZzFMSVg0cjlOOWVfeUx4Y08yUDR0b3VkaHB2eTlIRzVtX0RWOXZEQ3dHVXg0X0tzZXJ2anlFbEtuajBtRWEyMjBCbV9wMHVYTkxKNkhuMnZBRlFHRVhqaWM9 | Z0FBQUFBQm9ORzgxLW1HQ3RSYWNVN0gwR1FKa3lGSTVJcjVqeXY1RV9lVklkNXlkalJpTk5uTGpmQmhWY1V2LTRXWFM4WkgySThDNGVoWEtqTjRlUTJwZlVLZE5WXzRFSlJWNlpINjQ2S2p2Vm15ZjY2QnBmdE8yUENxWkthNmlvSzBma1VSWGlCRHdwYVZCTVRMZ2xZXzdEWng2QmhwVnEwRXFLZ1NCWVRNRVVfRFZzM0dWRUJMMGM3TXFQWEtYTlk0WjF4MDVnblBO |
Things like this exist for the NBA already. Teams use them in video rooms. | r/sportsanalytics | comment | r/sportsanalytics | 2025-04-23 | Z0FBQUFBQm9ORzh5OTFpQk5yQlN2YzZGYndwNDhxRnptQnlpN0RCbVEwV3JRc05CRDFUSjFQVnlFZVNMUzVBWG55dXVnQ0JnSU9fWXU1Q2lyT3RCY1VxNG1NMzc5S0o4ams4d1RtblpUUmFmZjZxX0ljMlBzLWM9 | Z0FBQUFBQm9ORzgxelJBZ1BGTGMyMURraDlEMjdfMUE4SGplQ0ZsQ0NiM1Jwd2Rwb3R5RXh3QXI2ZWkyV1FORm9yTXp5OWhmNnhpTUVQRUlQWGtrdk5RVHV0blNncGQ0THVsWXZqRk5CSDg4UXU2N1Z1a19IbFlOVDZPT2ROeHN6SXFvRjRPTnNTRVF6emxxSElSRFM4ZzNzRTdTVG5wZVRTMFJCdnhxREhYZlFCdXFfTmtXbE5HcUNXV1JjSWluakp3R3h4VDNTRC1UOWlvLUpnRC04dVlNejcyZTZ6eVRKS1BmWS15VHcxSzQ0QldqeU1QcGVnbz0= |
Hey guys, over the past few months, I have been developing my backtest using Polygon. It's a simple shorting large gapper strategy.
I am at the point where it is finally time for automation. For this to work, I will obviously need a scanner that checks for the top % gappers for that day.
Unfortunately, Polygon does not have a built-in scanner so that is what I am currently looking for. I was wondering if any of you have had similar experiences and have any recommendations.
Thank you for the help! | r/algotrading | post | r/algotrading | 2025-04-23 | Z0FBQUFBQm9ORzh5NUZPb3I1STFmSzJfa3hEOFZfZE82OFhrdzQ3aHZIZXU3QWdicERFand5UmtHdnU2QkVkTlNsTTRQdmNCd0ZoT29Td0NJTFV3VVVLWXBpS0Jmbkc0ckE9PQ== | Z0FBQUFBQm9ORzgxX1E2VENBc0dYRjhKdlNwakF2X3RlQ1JWWHhLTEo5V1h3MEt2NGhrMW4tQXFkTVVjUnpqRFJ4aUE2Qk5uNks0dXpaekNjYzZZUHctcVRnNXR5Q0NRVncycFQ2SVhBMWZmYkNzaEh5SEZsTjUybjBfdEk4dzVWWVdIb3BIbUd3MENPTDFJRHVEdDhITU9YX1ktY2NuWUtKY2dha2FjQ1R6ckNwR3ZuanpwYURzQV9BQ1VNMWN4UW9sdFBYVXR2UGVQWGxyVGp6bjBiX3ZVQm5VVmstSk5Tdz09 |
Like it always give some ideal performance and then when you try it in real life it looks like you should have juste invest in MSCI World... Like this is a fucking backtest, it is supposed to be far from overfitting but these mf always give you some unrealistic performance in theory, and then it is so bad after... | r/quant | post | r/quant | 2025-04-24 | Z0FBQUFBQm9ORzh5aGhjcnRCb0tEa3FGTjVrbUZtREFzUDhzUTNza1RIdTFxczVBVHRKb3RyemZSWUhEdjM0eDZkTWNqaEI1T215Q2U5TFVjZlNvZ0R3WVBveE1KVHJ1dUE9PQ== | Z0FBQUFBQm9ORzgxb1pDWDdvM1BYSFRzLWhwRzZuYmpfSE1nVFpLUzJycE9JYVU3R1h3dnE1dlQzS2U4RFE0UUp1aU83R3JDMDY1M0ZSOUdBaGRpMFdPTUhwdGZmWXljNlp3ZzZGdVZKb3JrWDVqZDFJbm9qejlDdmEzSWZWSng4bEdlOEpVQ0JmenpZSGFJZFhSOVh6QmlLbnhoQVpsenp0ZGI2bVlyYktJcU1iVzlyWmN3M3V5Vnh2VE9RWGUtejRUSnRXbzBwczBT |
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