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Comparing Some Strategies from Easy Volatility Investing, and the Table.Drawdowns Command

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This post will be about comparing strategies from the paper “Easy Volatility Investing”, along with a demonstration of R’s table.Drawdowns command. First off, before going further, while I think the execution assumptions found in EVI don’t lend the strategies well to actual live trading (although their risk/reward tradeoffs also leave a lot of room for improvement), I think these strategies are great as benchmarks. So, some time ago, I did an out-of-sample test for one of the strategies found in EVI, which can be found here. Using the same source of data, I also obtained data for SPY (though, again, AlphaVantage can also provide this service for free for those that don’t use Quandl). Here’s the new code. require(downloader) require(quantmod) require(PerformanceAnalytics) require(TTR) require(Quandl) require(data.table) download(“http://www.cboe.com/publish/scheduledtask/mktdata/datahouse/vix3mdailyprices.csv”, destfile=”vxvData.csv”) VIX <- fread(“http://www.cboe.com/publish/scheduledtask/mktdata/datahouse/vixcurrent.csv”, skip = 1) VIXdates <- VIX$Date VIX$Date <- NULL; VIX <-…
Original Post: Comparing Some Strategies from Easy Volatility Investing, and the Table.Drawdowns Command