Research Article #41 - Long/Short Crypto Trend Following
Finding better returns for unit of risk with a long/short crypto model
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In today’s article we’ll be researching a long/short model in crypto, with some volatility targeting added to it. We need to update our backtesting code to make this happen, so stay tuned to the end of the article where we achieve that result!
Also I’ve started this new series, where we will be deploying models live to the market, and a variation of the strategy we talk about today, will be the first one I’ll be deploying.
Today the goal is not to have a super efficient trading strategy, but to demonstrate the effect of the short side in a simple trend following approach.
We want to know how much benefit it adds, and if it compensates for us to have it there. At the end of the day, we’re paying for that exposure, and we need to know if it is a favorable thing that we pay for. Trading is like any other business, we are here to make a profit.
There’s something interesting in today’s article. Shorts in equities seem to perform very badly compared to shorts in crypto. There’s a few reasons that I believe causes this, and I’ll be laying the case in its appropriate section.
Let’s start!
TLDR Summary
Emphasis on the importance of understanding uptrends and downtrends.
Trend following can be hard on the short-side due to “up-only” market tendencies.
Bitcoin Long-Only Model (Not Volatility Targeted): Outperforms BTC's buy-and-hold strategy with less risk, despite significant drawdowns.
Multi Asset Long-Only Model (Volatility Targeted): Aims for 20% annualized volatility, but underperforms BTC’s buy-and-hold in terms of risk-adjusted returns.
Multi Asset Short-Only Model (Volatility Targeted): Provides diversification during negative BTC years, but underperforms in general due to the sector's upward tendency.
Multi Asset Long/Short Model (Volatility Targeted): Combines long and short strategies to enhance risk-adjusted returns, achieving outperformance of BTC buy and hold, although performance has declined in the past two years.
We need to be careful with our assumptions when using fluctuating metrics like market capitalization as a filter.
Plans to acquire better equities dataset, to address these biases in future articles.
Index
Introduction
TLDR Summary
Index
Strategy’s Thesis
Bitcoin Long-Only Model Performance Analysis - Conservative Risk Tolerance
Multi Asset Long-Only Model Performance Analysis - Conservative Risk Tolerance
Multi Asset Short-Only Model Performance Analysis - Conservative Risk Tolerance
Multi Asset Long/Short Model Performance Analysis - Conservative Risk Tolerance
Edge Effect in U.S. Equities
Parameter Settings Overview
Conclusion
Python Code Section