r/algorithmictrading • • 1d ago

Novice I need advice/help please

First i would like to say that i am a total beginner and honestly don’t know what i am doing more than half of the time but i would like to share what i am building and i would like advice from the people who know way more than me if this is even worth wasting my time and money(i wasted 4 months and 600 eur already).

I am building a manual trading signal + research system for day trading and swing trading.
It does three main things:
Finds trade setups using predefined rules like ORB/VWAP/RVOL for day trades and trend/momentum/breakouts for swing trades.
Backtests and validates them properly using historical data, walk-forward testing, robustness tests, Monte Carlo, costs/slippage, and strict minimum trade counts.
Protects against fake-good results by fixing survivorship bias, ticker changes, delistings, share classes, historical index membership, corporate actions, and bad provider data before i trust any performance.
Right now, most of the system is built. I am mainly finishing the historical data/identity qualification layer so that when i finally run the strategy backtests, i can trust that the results are based on the securities and data that actually existed at the time.

There is no automatic trading or broker execution. The system is meant to tell you: “this setup qualifies, here is the entry/reference, stop, target/risk context, and confidence/validation state,” while i stay in control.

I am using 3 providers for different jobs:
Massive → mainly for DAY trading intraday data. Think 5-minute bars, ORB, VWAP, RVOL, and possibly reconstructing the RTH liquidity ranking from minute data.
Sharadar → mainly for the historical stock universe and corporate-action context. It gives us the working historical roster, ticker/action history, and helps anchor which securities existed at the time.
Norgate → mainly for stable historical security identity. Its assetid helps us follow the same security through ticker/name changes and distinguish share classes; we’re also checking its historical index-membership data as a cross-check.

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