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, and we might even have market impact to contend with. A common issue in quant trading is to find an edge, only to discover that if you executed it naively, you’d get killed with costs. …

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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 might quantify their strength and decay characteristics and then combine them into a trading signal. This article continues our recent articles on stat arb: A short take on stat arb trading in the real world …

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How I use TradingView (and how to get 70%+ off)

​Disclaimer: the links in this post are affiliate links. If you use them to purchase a TradingView subscription, you’ll receive $15 in addition to the massive Black Friday discounts TradingView is currently running. We’ll receive a few dollars, too – so thanks in advance if you purchase using our link. I’m sure you’ve heard of TradingView. …

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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. The intuition is as follows: Imagine we have a 3-asset portfolio Assets 1 and 2 are perfectly correlated (correlation of 1.0) Asset 3 is uncorrelated with the other two (correlation of 0.0) Let’s say we …

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An Exponentially Weighted Covariance Matrix in R

Exponential weighting schemes can help navigate the trade-off between responsiveness and stability of the inherently noisy estimates we make from market data. We previously saw examples of calculating the exponentially weighted moving average of a vector, and estimating the correlation between SPY and TLT using an exponential weighting scheme [link]. In this article, we’ll implement …

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Using Exponentially Weighted Moving Averages to navigate trade-offs in systematic trading

Using 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 to validate (or more often, invalidate) a hypothesis about what might predict future returns. And one could argue that recent data is more useful …

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Beyond Stocks: The Surprising Volatility Returns of Oil and Gold

I’ve previously discussed the Volatility Risk Premium (VRP) and how it differs from the Equity Risk Premium (ERP). Probably the most interesting difference, from the perspective of the trader, is that the VRP may be somewhat amenable to timing – more than the ERP at any rate. In this article, I’ll use some of the …

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A Free Interactive IPO Calendar

I felt like doing something a little more lighthearted than usual. I’ve been deep in data engineering land these last couple of weeks, building data pipelines for processing a ton of options data for a trade we’re researching (the straddle-over-earnings trade). So I took some time out to mess around with something fun – building a …

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