I have second-by-second stock market data covering the past five years, and I want to develop trading strategies that can consistently outperform the market.

I’ve already backtested one strategy that generated a total return of 169% over approximately 5.5 years. However, one of the years delivered a negative return of around 10%, which makes me question the strategy’s consistency and robustness.

As a Quant Developer, I want to move beyond implementation and get deeper into quantitative research and strategy development. Where should I start, what research process should I follow, and what key areas should I focus on to discover, test, and validate profitable strategies?

I’d appreciate any practical suggestions, research frameworks, or resources that could help me become better at developing robust, market-beating strategies.

Good prompts produce good results. For educational purposes. No investment advice.

An autonomous, multi-agent AI framework built to conduct localized security analysis, aggregate financial data, and backtest sector-specific algorithmic trading strategies.
By executing entirely on local Ollama models, this project ensures complete data privacy—your financial research queries, data, and strategies never leave your hardware.

i’m trying to get into quant at 15, tried to do my own research but different sources tell different thing and now i’m really lost. Could you recommend some books to read or videos to study, what degree should i get in the uni. Just got into 10th grade and want to secure my future job of becoming a quant