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tf/algorithms
178
tf/algorithms•Posted by u/swing_king•

What is quant trading actually like? Is it just math nerds or can regular traders learn it?

I keep hearing about quant trading and algorithmic strategies but I can't figure out what it actually IS in practice. Is it just writing programs that trade for you? Do you need a PhD in math? Can a self-taught programmer build profitable quant strategies?

I know Python decently (data analysis, pandas, some ML) and I've been trading manually for 2 years. Wondering if I should try to automate some of my strategies or if quant trading is a completely different world.

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algo_trader_42·edited

Quant trading is using mathematical and statistical models to find and exploit market inefficiencies, then automating the execution. It ranges from simple (moving average crossovers) to incredibly complex (statistical arbitrage, market microstructure).

You don't need a PhD, but you DO need strong skills in:

  • Statistics (not just mean/median — you need hypothesis testing, regression, time series)
  • Programming (Python is fine for research, but production systems often use C++ or Rust for speed)
  • Finance (understanding market microstructure, order flow, exchange mechanics)

With your background, start by backtesting your manual strategies. If they have a statistical edge, you can automate them. That's actually the best entry point — most people try to jump straight to ML without having a tradeable thesis first.

134
trader_mike·edited

Seconding the backtesting advice. I started by literally translating my discretionary rules into Python code. Some of my rules turned out to have no edge at all when tested rigorously. Others actually worked. That process alone made me 10x better even as a discretionary trader.

78
macro_man·edited

The dirty secret of quant trading: most of the alpha comes from better data, not better algorithms. Everyone has access to the same ML libraries. But if you have unique alternative data sources (satellite imagery, shipping data, social sentiment aggregation), that's where the real edge lives.

112
algo_trader_42·edited

Fair warning: the gap between "I backtested a strategy" and "I run a profitable automated system" is enormous. Live execution has slippage, fees, latency, partial fills, data feed issues, and a million edge cases. Paper trading your algo for 3+ months before going live is mandatory.

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