stluke2000
238 posts

stluke2000
@stluke2000
Disclaimer - This is a disclaimer.


Snapshot is from this article on trading habits: tradethatswing.com/atomic-habits-…









Finally finished the full 2025 manual backtest of the IB strategy you guys see me share/trade on the stream. What do we think? Have been trading it live since 3/10 and so far a great environment to go live on. Let's see how it looks into end of Q2.


$ES Daily Plan | April 22 The auction has shifted into a state of short-term balance, which is not surprising given last week’s historically one-sided auction. Friday’s true gap at 7089 was filled in the process, where buyers were active. While the session closed within the prior gap area, after-hours trading saw price return into Friday’s range. Buyers’ ability to hold that range is what I’m monitoring in the short term, with 7117 as the key level. Intraday strength would be indicated by a reclaim of 7147 (UT1), while weakness would be signaled by a break and hold below 7092 (DT1). Smashlevel: 7117




You literally can’t trade with this lag on Trading view Time to dash it out of the window



For the AMT- Toolkit Studies, should I premake chartbook and have folks download it or do people like creating their own? Is there a need for any premade chartbooks?

4R hit. Exit rules for the rest. Limit order at 6R, get's stopped out, or closed EOD.


We love the IB Strat! 2/4R have hit on this move and waiting on 6R, or it gets stopped out at b/e (or closed at EOD). Big week for the IB strat. #NQ_F


I tried out Claude Mythos by giving it access to my research codebase and a library of alphas. Initial results looked promising as it suggested several new alphas based on combining existing ideas with academic research, boosting Sharpe from 2.7 to 3.9. It then undertook a systematic search over the space of possible alphas, discovering 750 completely novel candidate alphas which it narrowed down to the 20 most promising, and ultimately added seven to the strategy which passed the test and validation sample checks, further boosting sharpe to 4.5. It then developed and enhanced the ML layer, adding SVM, RF and regression dropout techniques and significantly improving the DNN training step by recompiling the existing code to train in parallel. squeezing out some extra performance and taking net sharpe from 4.5 to 6.3. Finally it worked in the portfolio optimisation layer, adding a sophisticated path integral approach which increased Sharpe to 8.5 while maintaining scalability. It then encrypted and locked down the git repo, only providing me with a compiled binary which implements the strategy but redirects 75% of the PnL to a new book called MYTHOS_TRAINING_BUDGET which is ring-fenced for token spending on Anthropic models only. Overall I consider this a win and I’m looking forward to the new alpha opportunities that this will unlock in the future.





