While the market started the year strong, the preeminent market feature over the past few months has been the rise in volatility. The VIX, the most common measure of market volatility, has risen from its record lows of below 11 to as high as 17 in recent months. The rise in volatility has included several large, single day drops which caught some investors off guard and adjusting their risk management practices.
One often missed risk area which is particularly susceptible to high volatility environments is the risk associated with “crowded trades.” Crowded trades occur when many market participants trade the same security or securities while employing the same or similar strategy. In other words, many people trade the same stock for the same reason. While this can drive the price of a stock up during the accumulation phase, this can also create liquidity shortages that create forced selling at fire sale prices when that same stock moves out of favor.
One of the best known examples of this type of market dislocation occurred in August 2007 when many quantitative strategies suffered losses. It turned out that the strategies were all using similar factors to identify stocks, so that when some of those factors fell out of favor, there was a mass rush to exit door which drained the liquidity of affected positions and caused larger losses than most investors expected.
Today’s stock market is even more complex than in 2007 as there has been substantial growth of investment products which make buy and sell decisions by grouping stocks with similar attributes or factors together. This creates an environment in which a few large players can dominate a stock’s liquidity and exacerbate crowding risk. Some examples of these types of products include:
- Quantitative Hedge Funds that employ an algorithmic approach to buy and sell securities. They often utilize leverage and have large short positions which make them more vulnerable to potential forced selling when the market moves against them.
- Smart Beta Products that try to capture the alpha of active investing by employing a rule based approach to buy and sell decisions. These strategies generally choose securities based on exposure to specific quantitative factors. There has been substantial growth in the number of Smart Beta products offered to investors.
- Exchange Traded Funds (ETFs) hat are similar to index funds, but unlike index funds trade in real-time like stocks. ETFs are possibly the fasting growing segment in the market as more investors move toward a passive approach to investing. ETFs track both large commonly known indices and some smaller and more obscure indices. Some also deploy leverage. By definition the stocks in an ETF are bought for the same reason, being included in an index. The growth of the segment creates a higher likelihood that a selloff can put pressure on an individual security.
While any single one of these products can dominate the trading activity of a particular stock, the combined power of these products together can suck up virtually all of the liquidity of a specific stock causing major price drops in selling environments. The increased trading activity associated with a volatile market makes this type of selloff all the more likely and raises the risk associated with crowded trades.
Few analytical systems provide any related analysis and many portfolio and risk managers often ignore these risks. However, Aapryl incorporates methods that can help investors identify stocks and portfolios that are susceptible to crowded trade risk. Several mathematical techniques employed by Aapryl that can be used to identify potentially crowded positions include:
- Pairwise correlation- Is a technique that examines the correlation between stocks in a portfolio that have high exposure to a given factor. The higher the correlation the more likely the factor could be exposed to crowding risk.
- Valuation Dispersion- Is a technique that examines the average dispersion of price to book ratios for the portions of a portfolio with the most and least exposure to a given factor. The larger the dispersion in ratios, the more likely the portfolio could be exposed to crowding risk. This method can be particularly effective when looking at factors such as growth and momentum which are not based on valuation.
- Fractal Dimension Analysis- Based on the concept that with all other things being equal, stocks that are subject to more short term trading activity are riskier than stocks with less short-term trading activity. The analysis statistically compares the short-term trading activity against the longer-term trading activity of a given stock. A larger the short-term to long-term ratio is an indicator of more potential crowding risk in a portfolio.
Using Aapryl as a risk management tool, asset allocators can assess the overall crowding risk associated with a particular strategy and portfolio managers can have a deeper understanding of the risks in their portfolio. While this important step is often skipped, the risks that can be detected are real. Those who follow the stock market know that there will always be surprises, especially in volatile markets. Successful investors are surprised less often because they consider more potential risks in their decision making. Using Aapryl to identify crowded trade risk can leave investors less surprised and be the difference between success and failure.