FactorsQuant tradingRTime series modellingTrading strategies
How to Model Features as Expected Returns
Modeling features as expected returns can be a useful way to develop trading strategies, but it requires some care. The
Quant trading
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BacktestingFactorsQuant tradingRTrading strategies
A Simple, Effective Way to Manage Turnover and Not Get Killed by Costs
Every time we trade, we incur a cost. We pay a commission to the exchange or broker, we cross spreads,
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FactorsQuant tradingR
Quantifying and Combining Crypto Alphas
In this article, I’ll take some crypto stat arb features from our recent brainstorming article and show you how you
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FactorsTrading strategiesIdeas for Crypto Stat Arb Features
This article continues our recent articles on stat arb: In this article, I’ll brainstorm some ideas for predictive features that
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Quant tradingTrading strategies
General Approach for Exploiting Stat Arb (Statistical Arbitrage) Alphas
Last week, I wrote a short article about statistical arbitrage trading in the real world. Statistical arbitrage is a well-understood
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Think like a traderTrading strategiesPairs Trading Strategy: A Short Take on Real-World Application
InIn textbooks, you often see pairs trading algorithms starting by regressing prices of Asset A on Asset B to calculate
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Quant tradingRTrading strategies
Exponentially weighted covariance in an Equal Risk Contribution portfolio optimisation problem
The Equal Risk Contribution (ERC) portfolio seeks to maximally diversify portfolio risk by equalising the risk contribution of each component.
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Quant tradingRTime series modellingUsing Exponentially Weighted Moving Averages to navigate trade-offs in systematic trading
A big part of the job of the indie trader is data analysis. We’re always looking in the past data
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FactorsQuant tradingThink like a trader
Quant Signal Trade-Offs in the Real World
I want to discuss a couple of simple trade-off considerations around quant trading signals that may not be obvious. Here’s
