Is it possible to detect a financial bubble and predict when it will burst? Dr. Didier Sornette, a former physicist who is the director of the Financial Crisis Observatory in Switzerland, developed a statistical model designed to do just that. Sornette and his colleague Anders Johansen determined in 2004 that in two thirds of the cases where financial assets suffered extremely large drawdowns, market prices followed a "super-exponential" behavior prior to their occurrences. According to mutual fund manager and former finance professor Dr. John Hussman, the Sornette model is now predicting a stock market crash as early as next year.
On Twitter last week, Hussman wrote:
"In order to push out finite-time singularity on a Sornette bubble, it has to become more vertical. There's a limit, and we're close to it."
Hussman elaborated on his prediction with the graphic below.
The Problem With Crash Predictions
One problem with crash predictions is that if you sold all of your stocks or stock ETFs every time you read one, you would have missed out on the entire cyclical bull market since the March 2009 bottom. Still, it wouldn't be prudent to ignore the risks. By hedging, you can continue to participate in the current bull market, while protecting yourself if the crash comes to pass. Below, we'll show a step-by-step way to hedge a $1,000,000 equity portfolio.
How To Hedge a $1,000,000 Portfolio
Step One: Choose a Proxy Exchange-Traded Fund (ETF)
Although some stocks can't be hedged directly, you can still hedge a diverse portfolio of mutual funds and non-hedgeable stocks against market risk by buying optimal puts* on a suitable exchange-traded fund, or ETF. The first consideration is that the ETF will need to have options traded on it, but most of the most widely-traded ETFs already do.
The second consideration is that the ETF be invested in same asset class as your portfolio. Let's assume your portfolio consists mainly of large cap U.S. stocks (IWB - News). An ETF you could use as a proxy would be the SPDR S&P 500 ETF (SPY - News), which, as its name suggests, tracks the S&P 500 Index. You could then enter its ticker symbol, SPY, in "Ticker Symbol" field in the Portfolio Armor iOS app, as in the screen capture below.
Step 2: Pick A Number Of Shares
In order to hedge a $1,000,000 equity portfolio against market risk, you would want to hedge an equivalent dollar amount of your proxy ETF. Since SPY closed at $177.29 on Friday, you would simply divide your portfolio dollar amount, $1,000,000, by $177.29, and enter the rounded quotient, 5460, in the "Shares Owned" field, as in the screen capture below.
Step 3: Pick a Threshold
Threshold, in this context, means the maximum decline in the value of your position that you are willing to risk. If you weren't sure of that, you could click on the question mark to the right of the Threshold field above, and you'd see this explanation in the screen capture below.
What is the maximum decline you are willing to risk? Generally, the larger the decline, the less expensive the hedge, and vice-versa. In some cases, a threshold that's too small can be so expensive to hedge that the cost of doing so is greater than the loss you are trying to hedge. I generally use 20% decline thresholds when hedging equities, an idea borrowed from a comment by John Hussman:
"An intolerable loss, in my view, is one that requires a heroic recovery simply to break even ... a short-term loss of 20%, particularly after the market has become severely depressed, should not be at all intolerable to long-term investors because such losses are generally reversed in the first few months of an advance (or even a powerful bear market rally)."
Essentially, 20% is a large enough threshold that it reduces the cost of hedging but not so large that it precludes a recovery. So we'll enter 20, in the Threshold field below, and tap "done", as in the screen capture below.
Step 4: Find the Optimal Puts
A few moments after tapping "Done", we'd be presented with the optimal puts. The screen capture below shows the optimal puts, as of Friday's close to hedge against a greater-than-20% drop in SPY over the next several months.
As you can see at the bottom of the screen capture shown above, the cost of this protection was 0.93% of your position (portfolio) value.
How This Hedge Would Protect Your Mutual Fund Portfolio
Remember, the reason we picked SPY in this case is because our hypothetical investor's assets were invested in large cap US stocks. If those equity assets drop in value due to a market decline, most likely, the S&P 500 Average will have dropped as well. And if the S&P 500 has dropped, the ETF tracking it, SPY, will have dropped as well. If the S&P 500 drops more than 20% -- if it drops 20.5%, 30%, 40%, or even more -- the put options above will rise in price by at least enough so that the total value of a $1,000,000 position in SPY + the puts will have only dropped by 20%, in a worst-case scenario.
Put options move in a nonlinear fashion, which enables a small dollar amount of them to hedge a much larger dollar value position in an underlying security. For an example of this nonlinearity in action, see this recent post about a hedge on Tesla Motors (TSLA).
Hedging a Portfolio Of Stocks And Bonds
The example above is simplified in that we've assumed our hypothetical investor's portfolio is entirely invested in equity assets. But what if he had some bonds or bond funds? In that case, we could use a similar process to hedge his portfolio against market risk, except instead of using just one proxy ETF, we'd use one per each asset class. So, for example, if 60% of the investor's assets were in blue chip US stocks, and 40% in US Treasury bonds, he might scan for optimal puts for a $600k position in SPY and then scan for optimal puts for a $400k position in the iShares 20+ Treasury Bond ETF (TLT - News).
*Optimal puts are the ones that will give you the level of protection you want at the lowest possible cost. Portfolio Armor uses an algorithm developed by a finance PhD to sort through and analyze all of the available puts for your stocks and ETFs, scanning for the optimal ones.
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