Can you regularly beat the market, cut volatility by 40% and max drawdown by 70% with only four trades a year, or is this too good to be true?

Active trading certainly isn't for everyone. Between spending time with family, going to work, running errands, paying bills, and not having the time or financial knowledge to invest wisely - it's easy to see why most people use the "Buy & Hold (Hope)" approach or choose not to invest at all.

But what if there's a way for you to beat the market, earn an average of 20%/year, reduce volatility by 40% and max drawdown by 70% using only four trades a year? Surely trading this kind of strategy should be attractive for anyone.

Here's a strategy that does just that.

Note: Past performance does not guarantee future results. I simply share my findings here not as a recommendation, but rather as back-tested results of a theoretical trading strategy, net of any commissions and fees.

The Lazy Strategy

The premise of this strategy is that (A) the market tends to go up over time, and (B) precious metals tend to display a seasonal up-trend during December-February, and around August (see the below GLD chart, adjusted for seasonality).

Legendary investor Warren Buffett once said (and then repeated) that "The trick is not to pick the right company, but rather to buy all the big companies through the S&P 500 and to do it consistently". Sound advice for 90% of people, indeed.

That advice takes care of item A (the market tends to go up over time). But combining that advice with a bit of hedging and two seasonality trades/year can yield more attractive results.

So, are you ready for this brilliant strategy? Ok, here it is:

  1. Hold GLD (SPDR Gold Trust ETF) from December 20 of every year through February 20 of the following year, and during August.
  2. The rest of the time hold SPLV (Invesco S&P 500 Low Volatility ETF)

That's it! (I told you it was simple)

I should point out that I haven't optimized this strategy at all. I simply "bought" Gold during its seasonal up-trend, and a low volatility "market" ETF the rest of the time.

So how a strategy like this performed over time? Here are the results from May 5, 2011 (date of SPLV inception) through today (October 3, 2019):

Metric               Strategy    S&P 500
-------------------  --------   --------
Cumulative Return    429.44%     117.45%
Yearly (ann.)          21.9%       9.67%
Sharpe                  1.73        0.71
Sortino                 2.65        0.99
Max Drawdown         -10.61%     -19.78%
Longest DD Days          258         416
Avg. Drawdown         -1.45%      -1.67%
Avg. Drawdown Days        15          20
Volatility (ann.)      11.9%      14.58%
Best Day               4.02%       4.96%
Worst Day             -3.75%      -6.66%
Best Month            12.27%      10.77%
Worst Month           -6.16%      -9.18%
Best Year             30.99%       29.6%
Worst Year             1.53%      -6.24%

To test how well this strategy would have performed before 2011, I've tested it using JKD (iShares Morningstar Large Core Idx) at 25% holdings, to (sort of) match the volatility of SPLV.

Here are the results from Jan 2, 2004 through today (Oct 3, 2019):

Metric               Strategy    S&P 500
-------------------  --------   --------
Cumulative Return     818.56%    161.09%
Yearly (ann.)          15.11%      6.28%
Sharpe                   1.33       0.43
Sortino                  2.02        0.6
Max Drawdown          -20.43%    -56.78%
Longest DD Days           349      1,996
Avg. Drawdown          -1.37%     -1.93%
Avg. Drawdown Days         18         33
Volatility (ann.)      11.03%     18.13%
Best Day                4.67%     11.58%
Worst Day              -3.98%     -9.03%
Best Month             12.27%     10.77%
Worst Month            -9.29%    -16.94%
Best Year              30.99%      29.6%
Worst Year             -2.56%    -38.49%

Note that aside from a ~20% drawdown in the peak of 2008's market crash, the maximum drawdown is around -10%, which fits most people's risk tolerance.

Check out the complete tearsheet for this strategy, generated by QuantStats, of course :-)