The following article is a guest post from Jared Broad, CEO and Founder of QuantConnect. QuantConnect is an online browser-based back-testing platform for C# that allows you to test custom strategies over 15 years of historical intraday data. This article will be part of a new bi-monthly post by Jared on algorithmic trading for retail investors.
There are two different techniques for measuring your strategy performance; relative and absolute performance. Before you design your strategy its important to define your metrics for success. As you iterate through strategy ideas this will help you know where you need to improve.
An absolute return strategy aims to make a consistent steady return independent of market conditions. It might rely on assets which are not affected by the market volatility such as bonds. Strategies which trade long and short are easier to be designed for an absolute return.
The alternative method is to compare or “benchmark” your strategy a market index. The precise index or market representation you choose can vary but often funds choose the S&P500. With a relative return strategy reducing holdings to cash is a net worth gain relative to a downward market.
We’ve integrated this directly into the QuantConnect results panel so you can load a custom benchmark into your charts, to know how your strategy is performing relative to the major indices. To access it, click on the “Select Benchmark” menu in the Chart Options on the right hand side:
To demonstrate the benchmarking functionality we’ve written the next video in the QuantConnect University series – Sell in May and Go Away. It is a demonstration for how to code up the sell in may strategy, and then we benchmark it to the S&P500 over the same period.
With this particular implementation we achieved the same returns with lower volatility, resulting in and overall better than market strategy.