At PortfolioEffect, we use high frequency market data to calculate intraday or end of
day risk metrics. This involves a new methodology for the calculation of risk that was
developed through 5 years of research. The results benefits low and high frequency
traders and researchers. We offer risk metrics data on volatility and risk factors for
8,000+ financial instruments, including stocks, stock indices and ETFs. Our end of day
risk metrics data are available on Quandl: Vol & Risk Factors, Risk & Performance Metrics.
To illustrate the potential utility of our data, we have built a sample algorithm that uses
it. Using the end of day Sharpe ratio calculated by PortfolioEffect, we compare the end
of day Sharpe ratio for the last day to the Sharpe ratio for a 1 week window length on 10
stocks: ‘IBM’,’GOOG’,’C’,’F’,’GM’,’GE’,’AAPL’,’AMZN’,’CSCO’,’GS’ since 01/04/2013.
By 1 week window length, it means the window length for calculating the metric is 1
week. Weekly Sharpe ratio is calculated on 5 days windows length. Therefore, we look
at the Sharpe ratio of the daily vs weekly rate. If the daily Sharpe ratio is greater than
the weekly Sharpe ratio, we take a long position, otherwise a short one. At each step of
the algo, we buy and sell. For example, we have 8 shares to buy and 2 shares to sale, we
buy each share with a quantity of 150% / 8 = 18.75% and sell up to 50% / 2 = 25% of
the portfolio. We are creating a changing portfolio containing long and short positions
at any given time.
In summary, we buy stocks with good Sharpe ratio through the sale of shares with
poor Sharpe ratio. Take a look at the attached backtest.
For more info on our end of day risk datasets, see attached description.