Market crashes are an interesting area to study. Many economists and finance professors devote countless hours trying to discover the precise causes of crashes.
In 2008, it was the housing crisis. In 2000, it was Internet stocks. In 1987, it was portfolio insurance. In 1929, it was highly 
And in each case, while there were warning signs of these problems, the size of the losses caught most investors by surprise.
In the most recent crash, for example, the problems in housing existed long before the markets went into a tailspin. And the underlying problem existed for an extended period of time before every other crash as well. Yet, moving to cash at the first hint of a problem can be costly to investors because it means they will miss out on bull market gains.
What most investors want is a balance between protecting themselves from a sudden loss and participating in the upside of the market as much as possible.
A crash, by definition, is a sudden and unpredictable event. Many investors think of a crash as a one-day loss like we experienced in October 1987. Those days are actually rare, and that particular crash could have been avoided by investors who took notice that the market was already moving lower before October 1987. We find a similar pattern surrounding other one-day crashes, and getting the larger trend right would have helped investors avoid the pain.
Crashes, which we would define as single-day losses of 5% or more, are relatively rare. Only about 0.15% of trading days since 1950 (24 days) show a loss of that size. Because of their rarity, it is impossible to develop a signal that will avoid only those days. Losses of half that size, 2.5% in one day, are also too rare to develop a system. Although we see an average of three days like that a year, they account for only 1.1% of the trading days since 1950.
Instead of worrying about a crash, it might be better to worry about bear market losses of 20% or more in one year. Since 2001, using all available overlapping one-year periods, we have seen losses of 20% or more occur 12.6% of the time. And more than 6% of overlapping one-year periods since 2001 saw losses of 30% or more.
Using something as simple as a moving average would help avoid the bulk of the market losses. Selling when the S&P 500 index, or SPDR S&P 500 ETF Trust (NYSEARCA:SPY), closes below a 10-month moving average is one way to avoid large losses. A five-month moving average would trigger a move to cash even quicker and has been more profitable in the past.
The best system for moving to cash, though, might be to use daily data and sell when SPDR S&P 500 ETF Trust (NYSEARCA:SPY) falls below its 100-day moving average. Conservative investors could buy back in on a close above the 200-day moving average. This system avoided the bear market in 1987 and 2008, among its many successful trades.
This strategy assumes an all-or-nothing approach, which is impractical for most investors. If the sell signal is too early or wrong, large gains can be missed. A better approach might be to hold some insurance against a crash or a bear market by buying put options.
Put options should profit when markets decline. You could allocate 1%-2% of your portfolio to buying puts on SPDR S&P 500 ETF Trust (NYSEARCA:SPY) that expire in about 12 months. If you are wrong and the market doesn’t crash, the loss is limited to the price paid for the option. If the market does crash, this put should show a gain that helps offset losses on your other investments.
Investors should consider a combination of these two approaches to balance the risks and rewards of the stock market. When prices fall below a long-term moving average, some holdings should be sold. When prices are rising, the portfolio should be fully invested to benefit from the trend except for a small allocation to put options, which will protect your wealth in a downturn.
Buying puts on SPDR S&P 500 ETF Trust (NYSEARCA:SPY) now, and taking a more conservative approach to the markets by selling some investments if SPY falls below its 100-day moving average, seems like a sound strategy.
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