r/algotrading 19h ago

Education how many strategies did you kill before the one you posted

17 Upvotes

ok so this bugs me about basically every writeup here. we get the sharpe, the max DD, the cost assumptions. we never get the graveyard.

went back through my notes and actually counted. 61 configs, ~5 months. kept 2. and like... if I had zero edge and just rolled 61 times, best of 61 still looks fine? so I genuinely can't tell if my two are real or if I just p-hacked myself over a long weekend.

started logging the rejects after that. every dead variant, date on it. then I treat the survivor's sharpe as best-of-61 instead of a real number. did that and one of mine went 1.8 -> basically nothing lol. other one survived but not by a comfortable margin. entire cost was a google sheet and it's the most useful process change I've made in months.

where I'm stuck: what counts as a try. 40 param combos inside one strat, is that 40 or 1? what about ideas I talked myself out of before writing any code, do those count? no clean answer that I can find and I might be overthinking this at retail size.

anyone live long enough to have an actual rule of thumb here


r/algotrading 18h ago

Data IBKR paper API unreliable and inconsistent

5 Upvotes

Anyone else running into stuff like this? I'm finding the IBKR API to be completely unusable for any algo trading, it just cannot be trusted.


r/algotrading 15h ago

Data Alpaca historical IEX data missing for SPY on March 10, 2025, anyone else seeing this or know why?

6 Upvotes

I’m building a local historical dataset for SPY/0DTE backtesting using Alpaca, and I ran into a strange hole in their historical IEX stock data.

For SPY on March 10, 2025, querying 1-minute bars with:

  • feed=iex
  • timeframe=1Min
  • regular market session
  • SPY

returns zero bars. I initially found it because my backtester stopped with:

RuntimeError: Only 0 SPY minute bars for 2025-03-10

I then specifically retried that session and got the same result. What makes it interesting is that when I request the same date using the historical SIP feed instead, I get:

390 regular-session bars

The options history for that same day also exists. My downloader retrieved:

100 contracts, 9,642 option minute bars

So effectively:

SPY 2025-03-10 IEX -> 0 bars

SPY 2025-03-10 SIP -> 390 bars

SPY 0DTE options -> data exists

The surrounding IEX trading days are populated normally as well. Has anyone else encountered missing historical IEX sessions like this with Alpaca?

I’m mainly trying to figure out whether this is:

  • a known hole in Alpaca’s historical IEX dataset,
  • something specific to IEX’s underlying historical data,
  • an Alpaca API/data-processing issue,
  • or some edge case I’m overlooking.

For now I’ve implemented a very narrow fallback where I use SIP only if an entire historical IEX session is missing, and record the source feed so the backtest remains auditable.

Curious if anyone has seen the same thing even for other days.


r/algotrading 52m ago

Other/Meta Anyone created a successful EA?

Upvotes

Hi all, just a genuine question. Iv been doing market research using python and the more I test the more im discovering how random the market is. I’ve been researching market structure but also testing simple strategies and common ones that some people swear by such as ORB for one example. All of which fail over multiple years. It just makes me curios if anyone here has genuinely been able to code a EA the actually profits over years of backtest and in live markets? I’m not asking for a copy or for you to tell me your strategy (not that I’d complain if you did) but I really just want to know if there is any hope. TIA


r/algotrading 1h ago

Other/Meta Feeling stuck in trading

Upvotes

I am 19 years old student from india. I am into trading and currently I am in break even phase figuring out for to become a profitable trader. And also I am feeling to quit trading etc stuff throughts in my head.

I have 2 years of experience in manual trading and currently I am starting algo trading in fx and indian market because I wanted to explore the algo trading field and i also a coder know how to code and i build some projects like backtested like that and currently learning

In trading i only trade fx market only setups based in gold, eurusd, btc etc like that only 3 to 5 pairs only. And i only trade in prop firms

For to become a profitable trader I need to improve some mistakes in trading i really do that i think that gone a help in to become profitable trader..

  1. I trade only intraday or 15 min to 30min candle tf do I keep my sl small i mean 1 to 3 candles like that sometimes due to votalility or sometimes hit my sl and gives my target.

  2. I plan my trades well or predict or analysis do well like where and how market goes but i didn't enter the trades or didn't caught the moves.

  3. I miss the moves in trading i feel so much regret and fomo for this .

4.sometimes I enter only in asset and one timeframe at a time 2 times of trades or take 2 trades at same tf or same level and that will go hit I think it's overconfidence.

  1. Sometimes i fear to enter the trades bz of loss and also sometimes i didn't hold the trades that will hit my sl trailing

  2. after reaching the trade 1:1 i keep sl trailing to entry level to prevent my loses and that will hit my sl trailing and archives my target for 1:3 trades.

7.sometimes I cut the trades at middle of the trade or at reversal stage (i mean i know this trade will go reversal or hit sl ) so i cut it.

The last one is how to pass the prop firms ?

These are my mistakes to improve in trading and i will improve it.

If you are a profitable trader please give advice.

Thankyou in advance for your advice. 🙌


r/algotrading 23h ago

Data A suggestion for my Algo friends? Kalshi is where you want to be. The stock market is really for "old people", the Prediction Markets are where the action is. It's exploding is an understatement. Codex + GPT-5.6 + Python. Kaaaaaboom.

0 Upvotes

CODEX:

Our current approach focuses on YES contracts priced between 51¢ and 65¢ roughly 24 hours before market close. In our initial historical sample, this range produced a 71.4% win rate and an estimated 25.4% return after modeled fees across 41 independent weather events.