Preface
In the previous article, we have shown that the simplistic approach to covered call does not work all the time, we have suggested a new approach and observed a significant improvement, in this article, we will improve even more and then some…
Let’s dig in.
Trading price and volatility
When trading covered call ( or any option strategy ..) we actually trade 3 aspects of the underlying – price, time and volatility. In the previous post, we put our emphasis on price, which is only a part of the trading plan, in this post we will focus on volatility which is a substantial contributor to the price of an option.
A measure of underlying volatility can be expressed in many ways – standard deviation (which is used in the academic option price modeling by Black Scholes), Bollinger bands width, ATR, and more.
In this post, I will use standard deviation to measure current volatility and volatility trend.
Flat volatility strategy
The first strategy we test is a strategy that sells calls once the volatility had flattened out after a significant move, we measure how flat the volatility by using linear regression of the standard deviation in the last 21 days, in case the volatility is flat and high, the strategy sells calls, in all other cases the strategy stays off the market.
The strategy uses the S&P500 as underlying, selling OTM calls with 30 days to expiration, this means we are trading with the following conditions:
Entry: Buy and hold SPY, plus, every first day of the month sell 1 out of the money(OTM) call for the next 30 days, OTM strikes are selected with delta lower than 20.
Sell a call only if the volatility flattens after a significant move
Exit: when the price reaches the strike or on expiration(end of the month)
When trading this strategy, these are the results:
Alpha= 0.182
S&P500 Sharpe Ratio = 1.06
With CC Sharpe Ratio = 1.11
S&P500 CAGR = 12.71%
With CC CAGR = 13.6%
These are very good results, this means that selling calls should take volatility into account when calculating entry condition.
Examining the losing trades in this strategy demonstrates that this strategy loses money when the price makes a significant move to the upside( same results as shown in the previous post) and this is, of course, the biggest disadvantage the strategy has.
Using RSI to normalize volatility
So how can we tell if the volatility is too high or too low? We may use RSI to normalize the values of the standard deviation, in this way the absolute values of the standard deviation are not as important as where is the current volatility with relations to its history, RSI is a great normalizer and we use the RSI of the volatility to decide if the volatility is overbought or oversold, to use the RSI jargon.
Using RSI, we use the conditions below:
Entry: Buy and hold SPY, plus, every first day of the month sell 1 out of the money(OTM) call for the next 30 days, OTM strikes are selected with delta lower than 20.
Sell a call only if the RSI of the volatility if below oversold threshold(80 in this case)
Exit: when the price reaches the strike or on expiration(end of the month)
Trying to use this approach yields these results:
Alpha= 4.42
S&P500 Sharpe Ratio = 1.06
With CC Sharpe Ratio = 2.1
S&P500 CAGR=12.71%
With CC CAGR=14.3%
And this is exactly the purpose of the covered call strategy, first, it enables us to profit when the underlying moves up and second it is a cushion in case the underlying goes slightly down (in effect reducing the drawdown to a minimum).
wpDataChart with provided ID not found!In Alpha Over Beta, we use a variation on this exact strategy to generate trade decisions in one of our portfolio, we actually have another ingredient that we use to scale up the risk and improve the strategy performance even more, you may use the website to follow the trade alerts provided by this strategy and more.
Trade safely,
Alon