Weekly Discussion Thread - August 11, 2026

Hey guys, A bit new to programming, but not so much to trading. So far, I have created my first momentum-based trading bot, and from here I am transitioning into programming my own backtesting engine. I have done most of the work from scratch, but here and there I will use AI to discuss implementation options, write monotonous code, or help out when I have no idea where to start and am just staring at a screen mindlessly. Here are some details on my trading bot: * I am using moomoo's API through Python. * I intraday trade a basket of stocks that are "hot". My strategy scans for volatility and enters on continuations. * I store trades in a dictionary with the ticker name as a key and a list as the value (e.g., orders["US.AAPL"] = [trade1, trade2, trade3]). Each trade element contains info like child orders, shares, decay, etc. I log trade info as well. Here is an example trade that the bot took so you can see where in the market it executes: Plaintext US.AMD: pending entry: 473.68 Ask: 473.24, Bid: 473.19, Spread: 0.05 US.AMD: SELL order filled at: 473.28, STOP LOSS: 473.96, Take Profit: 472.6 Shares: 31.0 Time: 2026-08-10 09:34:15 US.AMD: take profit order filled at: 472.5 Shares: 31.0 Time: 2026-08-10 09:34:21 PnL: +$24.18 Currently, I am just playing with ideas. I do not expect profitability from any of my strategies, but I have a lot of things I want to try. This is my first Python project as well, and it's been a lot of fun. I have some questions for the community: 1. **Do you think it is worth it to learn C++ for speed?** I know location is the bigger concern, but I can't help but feel like I might miss out on some fills. 2. **How do you deal with rate limits?** As you can see, my bot is very fast and the API has rate-limited me before, which has me holding onto positions for extra time. (I was thinking maybe I could source shares from another brokerage). 3. **Would you say tick data is required to get okay backtests**, or is minute resolution good enough? 4. **I don't know what I need to know.** What concepts should a noob learn about?

Does intra day mean reversion using RSI actually work? It’s too early for me to tell at this point.

Not enough info to answer you as there is an infinite number of ways to implement that idea. You should flesh it out and backtest it. Personally, I think that mean reversion is one of the easiest and most reliable way of being profitable, so you seem to be on the right path!

Thank you for the encouragement. I’m just starting, so I’m having a little insecurity about not knowing what I don’t know.

I’m also struggling with getting good performance correlation between in sample and out of sample. Win rates work but profit and loss is all over the place. This gives me zero confidence in any of the parameters that I’ve selected.

I’m also struggling with getting good performance correlation between in sample and out of sample.

That's pretty normal, sadly.

Win rates work but profit and loss is all over the place.

I would look at Sharpe, Sortino, Calmar, and Omega ratios too. Oh and my favorite, the SQN, or System Quality Number created by Van Tharp. A rough passing threshold is to have an out of sample sharpe higher than 2 and a SQN that's also higher than 2.

This gives me zero confidence in any of the parameters that I’ve selected.

What are your parameters? Like numbers (ema 10, 20, 50, etc), indicators (ema, ma, tema, etc or rsi, w%, stochastic, etc), patterns or market regimes?

For tqqq, I’m using RSI 9/OS 40/OB 85/EMA 60/sell stop at ATR*5.0/1 stop per day.

Stable win rate with jumping P&L is usually the shape of the strategy, not the parameters. Mean reversion with RSI exit and ATR\*5 stop gives many small wins and rare big losses. Win rate is made by the frequent small outcomes, so it converges fast on any sample. P&L is decided by how many of the rare big losers landed in each window, and different windows catch different amount of them. So P&L can jump between IS and OOS even when nothing is broken. Quick way to check which case you have - remove the 3-5 biggest losers from IS and from OOS results and compare again. If numbers get close, parameters are fine and the real variable is how often stop-out days happen and in what conditions they cluster, so count those days, not trades. If numbers stay far apart even without the tails, then it is the parameters, and RSI settings on 1 minute bars overfit very easily, small change moves every entry.

This sounds really useful. Thank you!

What libraries do you guys use for data visualization, especially for backtests?

Depends on what you want to see. What do you have in your tearsheet? mplfinance and matplotlib have been great and easy to use! Easy to plot stuff like signals, equity curve, rolling sharpe, and monte carlo simulations.

Just the basics, not really sure what people are actually using. Thank you!

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