Building a Quant Trading Firm with Diversified Strategy Types

Summary

Sourabh Sisodiya describes moving from discretionary trading based on technical analysis and candlestick patterns toward rule-based strategies after questioning whether his approach had a reliable edge. He presents backtesting as a way to assess a system and outlines a development sequence: define an idea, turn it into rules, test it, decide whether to discard or deploy it, then optimize and scale it.

At his quantitative research firm, he reports trading mean-reversion strategies, trend-following strategies, and option writing intended to capture theta decay. He says the strategies are uncorrelated and that this helps limit system drawdown. The article offers no independent performance data, implementation details, or evidence for the stated correlation and drawdown effects, so the account is illustrative rather than a validated trading study.

Key ideas

• The interviewee moved toward systematic trading because discretionary chart-based decisions left him uncertain about his edge.
• His proposed workflow turns a trading idea into explicit rules, backtests it, then determines whether to deploy, optimize, and scale it.
• His firm combines mean reversion, trend following, and option writing to seek diversification across strategies.
• He emphasizes limiting losses rather than maximizing the percentage of winning trades.
• The article gives no performance data or technical details to verify the strategies’ behavior.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.