Buying An Umbrella When It's Sunny Out

Just as it's best to buy an umbrella before it starts to rain, hedging can make sense when the market's going up. Here's a simple way you can hedge your portfolio against market risk.

Hedging when the market is up is like buying an umbrella when it's sunny out: you'll be protected when it rains (Photo by Vivienne Gucwa).

Protecting A $500k Stock Portfolio With SPY

With the market up about 22% since December's nadir, some investors may have become complacent. For those who haven't, now may be a good time to hedge against the possibility that the climb since December has been a bear market rally.

Here's a simple way of protecting a stock portfolio against further market risk using optimal, or least expensive, puts on SPY. For the purposes of this example, I'll assume your portfolio is worth $500,000, that it's closely correlated with SPY, that you have enough diversification within it to protect against stock-specific risk, and that you can tolerate a decline of up to 20% over the next several months (if you have a smaller risk tolerance, you can use the same approach entering a smaller decline threshold).

Step 1

Divide $500,000 by the current price of SPY, which was $285.83 as of Monday's close, to get 1,749 (rounded).

Step 2

Scan for the optimal, or least expensive, puts to protect against a >20% decline in 1,749 shares of SPY over the next several months (screen captures below via the Portfolio Armor iPhone app).

Note the cost here: $3,400, or 0.68% of portfolio value, which was calculated conservatively, using the asking price of the puts.

Step 3

Round up the number of SPY shares to the nearest 100 and repeat step 2.

Note that, in this case, it's cheaper to hedge rounding up to the nearest round lot: The cost was $2,808, calculated conservatively, at the ask. That's about 0.56% of a $500,000 portfolio.

Continuing This Approach

If you hedge your portfolio this way and repeat the process before the hedge expires in September, you'll be protected against >20% declines during each time period, and your annual hedging cost will be about 1.16% (assuming, for the sake of simplicity here, that hedging costs are similar in September). So, if we don't slide into a bear market, you should generate a somewhat competitive return: Roughly, the market's return minus 1.16%.

A Potentially Market-Beating Approach

The approach above might beat the market over a time period that includes a severe decline, but it's not going to beat SPY in a bull market, because of the drag of hedging cost. To beat SPY while hedging in a bull market, you need to beat the market by enough with your underlying securities that your performance, net of your hedging cost, is still higher than the market. You're not going to do that with a diversified portfolio that's highly correlated to SPY. You need a different approach to have a shot at that.

One such different approach is the concentrated, hedged portfolios generated by Portfolio Armor. Since 2017, I've been creating these portfolios and tracking their performance in real time. Here's how the ones hedged against >20% declines have done so far (performance represents six-month periods starting on the starting date; click on a starting date to go to an interactive chart for that portfolio which shows its holdings.).

PORTFOLIOS HEDGED AGAINST > 20.0% DECLINES

Starting Date Expected Return Actual Return SPY Return
June 22, 2017 8.43% 20.08% 11.27%
August 31, 2017 8.03% 9.10% 10.87%
October 12, 2017 9.00% 2.12% 5.38%
October 19, 2017 10.07% 13.05% 6.08%
October 26, 2017 8.57% 9.39% 5.13%
November 2, 2017 9.77% 10.67% 3.11%
November 9, 2017 9.59% 4.45% 5.34%
November 16, 2017 8.95% 5.18% 6.22%
November 22, 2017 9.39% 7.31% 5.90%
November 30, 2017 8.55% -4.74% 3.80%
December 8, 2017 8.34% 4.50% 5.73%
December 14, 2017 7.75% 17.49% 5.87%
December 21, 2017 9.33% 12.33% 3.36%
December 28, 2017 9.92% 9.45% 1.99%
January 4, 2018 9.65% 12.92% 0.59%
January 11, 2018 8.93% 9.14% 1.12%
January 18, 2018 9.40% 7.89% 1.55%
January 25, 2018 9.82% 6.19% 1.10%
January 29, 2018 9.29% 10.48% -0.30%
February 1, 2018 9.00% 0.84% 0.59%
February 8, 2018 7.35% 12.49% 11.75%
February 15, 2018 8.19% -6.14% 4.08%
February 22, 2018 8.54% 6.90% 6.73%
March 1, 2018 7.98% 6.66% 9.37%
March 8, 2018 8.32% -3.20% 5.82%
March 15, 2018 7.90% 2.50% 6.68%
March 22, 2018 7.62% 9.58% 11.74%
March 22, 2018 7.65% 8.82% 11.74%
March 29, 2018 8.26% 7.72% 11.48%
April 5, 2018 10.59% 0.20% 9.33%
April 12, 2018 9.36% 4.63% 4.71%
April 19, 2018 11.04% 17.36% 3.67%
April 26, 2018 10.32% 17.44% 0.53%
May 3, 2018 10.08% 7.54% 4.47%
May 10, 2018 8.64% 2.61% 3.03%
May 17, 2018 11.53% -4.37% 1.54%
May 24, 2018 11.74% -6.80% -2.63%
May 31, 2018 7.76% -4.70% 2.66%
June 7, 2018 8.62% -11.51% -4.12%
June 14, 2018 13.05% -9.78% -5.71%
June 21, 2018 12.44% -17.22% -11.31%
June 28, 2018 11.80% -7.95% -7.58%
July 5, 2018 9.11% -13.03% -6.61%
July 12, 2018 9.97% -8.37% -6.32%
July 19, 2018 10.82% -10.54% -3.83%
July 26, 2018 9.87% -6.70% -5.21%
August 2, 2018 9.76% -3.91% -3.36%
August 9, 2018 12.78% -1.44% -4.12%
August 16, 2018 14.60% 0.79% -1.33%
August 23, 2018 15.20% 0.71% -1.30%
August 30, 2018 13.16% -7.98% -2.99%
September 6, 2018 13.66% -4.72% -2.75%
September 13, 2018 17.32% -5.23% -2.25%
September 20, 2018 13.73% -0.28% -2.66%
September 27, 2018 14.71% -7.29% -2.80%
Average 10.10% 2.41% 2.13%

One note about the table above: the current, wide gap between expected returns and actual returns is largely a function of a recent run of negative returns (since expected returns for portfolios are always positive). We expect that gap to close going forward. 

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