Another way of thinking about comparing performance of a hedged algo like this one, say, to a benchmark -- and the SPY can work in this example actually -- is to choose a certain level of risk (i.e. annual volatility) you are willing to accept as an investor. For me, I think a value around 25% is sensible. Remember though that annual volatility is just financial lingo for a 1-standard deviation expected fluctuation of your algo over the course of 1 year. So what this also means is that if I were to suffer a 2-standard deviation event, I should also be willing to lose 50% over the course of 1 year. That actually seems like quite a bit now that I think about it, because if I lose 50% in 1 year, then that means I need to earn 100% on my remaining capital just to "get even." So, given that, I think I'll ratchet back the risk I'm willing to take down to 15% annual volatility (thus 30% at 2-standard deviations) which seems moderately more sensible...
Now that I've settled on sensible risk to take, I then divide my algo's annual volatility into 15% (using this algo above's annual volatility of 7% results in: 15% / 7% = 2.1), and then I do the same thing for my benchmark, SPY, and take 15% divided by the annual volatility of the SPY over the same period which I was backtesting my algo. The backtester doesn't currently report this for the specified benchmark (I don't think so anyway), but I just computed it offline as 11.2%. So to scale that risk up to 15%, results in 15% / 11.2% = 1.34. I then take each of these "risk parity ratios" and multiply the total returns of each by the ratio to get the returns per unit of my "risk budget":
algo: 26% * 2.1 = 55%
SPY benchmark: 42% * 1.34 = 56%
So on a "risk parity" basis this algo achieves the same return as the SPY. And now that I think about it, this is a much more rigorous approach to comparing the algos than the silly beta ratio comparison I did in the previous comment on this thread :)
FWIW allocating capital on risk parity, e.g. on a risk unit basis, is how many funds have approached the portfolio construction process for quite some time. Although some funds took it to some extremes and allocated capital to low-volatility instruments like bonds in conjunction to stocks in this same manner, and have "blown up" because of huge black swan events in the bond market where a bond's volatility has gone from say 2% per year, but then the bond's sold off 50% in 1-month, and because much more $ was allocated to the bonds because they were low-volatility and say the fund's risk unit was 10% volatility, the brunt of the losses came from the "low-risk bonds!" Oops! I only mention this example because surely these poor, unsuccessful implementations of risk parity are what would surely be at the top of Google search results if one would search for more information on the "risk parity" approach to building portfolios. But in the end, if approached sensibly it can certainly be a sensible way to allocate capital.