Quant Beckman

Does that ring a bell?

The argument is that human traders prefer round quantities while algorithms dont. The authors concede that aggregate data cannot distinguish the mechanisms exposed. Therefore, the evidence supports calendar-synchronized or automated-looking activity, but it doesnt prove that a specific class of trading algorithms generates the effect.

FX carry earns the interest-rate differential by holding higher-yielding currencies against lower-yielding currencies. The trade works best when volatility stays contained because carry can be wiped out by sharp moves.

I saw a tweet today saying that people rarely talk about research on X. Honestly, they talk about research all the time. What they rarely talk about is what isn’t actually research. For example, plugging an AI into a couple of platforms and getting it to generate a great-looking backtest isn’t research. It’s overfitting. Then reality hits, and the systems being sold perform nothing like those backtests. I’m not saying there’s anything wrong with doing it, but let’s not call it research, you need something more to call it like that.

Full trading pipeline in one line: Alpha discovery → nested validation → risk management → optimal execution

70.4% return and 3.15 Sharpe ratio? With only 3 stocks, 1 test year and no fees!? 😟

You know, that situation where you're talking to a buddy and just can't see past the end of your nose. Has that ever happened to you? Getting into an absurd argument like that?

Futures contracts have very different volatility, so equal notional weights create uneven risk. This method scales each contract by inverse realized volatility and targets equal risk contribution across the portfolio.

Different trading models can show the same performance metrics and still lose money in very different ways. Each one therefore needs a risk approach built around its own failure pattern.