The Patton Flex Strategy is managed by Patton Fund Management, Inc. to invest, both long and short, in U.S. traded equity securities of public companies. It is offered via both a separately managed account (SMA) and a limited partnership (hedge fund). The goal of the Strategy is to reduce the risk of a total portfolio while at the same time improving long-term returns.
The Strategy invests both long and short in U.S. traded equity securities of public companies. Only S&P 500 stock components are considered for the long positions in the Strategy. Short positions are select from a list of approximately 500 stocks that generally rank among the larger market cap, higher priced, and most liquid in the market. Approximately 100 positions exist at all times in the Strategy. The investment strategy of the Strategy is built entirely on principles of behavioral finance and is designed to exploit pricing inefficiencies in individual stocks.
The investment objective of the Strategy is to generate positive absolute returns that exhibit low correlations with both equity and fixed-income returns resulting in reduced risk in an investor's total portfolio while at the same time improving long-term returns. Both actual performance as well as extensive research on the strategy suggests these objectives can be met. The strategy's risk is controlled through diversification, an unwavering adherence to the investment disciplines, and a consistent allocation to both long and short positions. The strategy is ideally suited as a diversifying component within a total portfolio. The Strategy is expected to be a better diversifier than bonds due to both its higher expected return and low correlation.
Behavioral Finance is the study of human psychology and its impact on the investment decision making process. Some basic premises of Behavioral Finance are:
While the Strategy was designed and developed entirely by Mr. Patton, the underlying principles are reflected in the emerging academic field of Behavioral Finance, or what practitioners often call investor psychology. Behavioral Finance research has shown that investors tend to repeat particular cognitive errors when making decisions about stock transactions. In other words, investors' decisions are often more a product of emotion than reason. These cognitive errors result in sources of inefficiencies that, by their very nature, tend to persist over time, although never in the same stocks indefinitely. Research by Mr. Patton shows that behavioral-based inefficiencies in the pricing of individual stocks are exploitable during windows of opportunity, while the pricing of the affected stocks generally becomes more
efficient in the long term. Mr. Patton's research also shows that these inefficiencies can be exploited, for profit, with the strategy's rules-based model that excludes human emotions.
Although Behavioral Finance has become widely accepted as an important school of thought on the stock market, it offers no obvious recipe for trading profits. Instead, Behavioral Finance can be thought of as a general framework for understanding sources of stock market inefficiency. Mr. Patton utilized his experience in managing publicly traded equities, together with his study of Behavioral Finance and his knowledge of statistical modeling to create the Strategy's rules-based strategy. To accomplish this, Mr. Patton spent four years testing behavioral indicators to determine precisely what has worked as well as what is likely to continue to work. Historical back-testing is especially relevant for evaluating this strategy because the sources of the behavioral-based pricing inefficiencies are likely to persist into the future. His research utilized the most comprehensive and reliable data available, including both the University of Chicago's CRSP U.S. Stock Database and Standard and Poor's Compustat database. These two sources were merged into one proprietary database covering mid-1962 through today.
In summary, Patton believes:
The Strategy is built on these beliefs.
The Strategy has the following key elements:
The Strategy is based on the premise that behavioral-based market inefficiencies are exploitable at the firm level during windows of opportunity, while the pricing of the affected stocks generally becomes more efficient in the long term, subsequent to the initial mispricing. Since the magnitude of these inefficiencies is believed to vary through time, the strategy attempts to enter and exit positions when the pricing is most advantageous. Note that the strategy does not attempt to exploit inefficiencies at the level of the aggregate market.
Another premise of the Strategy is to invest only in highly liquid U.S. traded stocks. Under normal conditions, the portfolio consists of 50-80 long positions and 30-50 short positions. There are no sector controls.
Both long and short positions in the investment strategy are selected based on a rules-based model designed to detect when a stock is over or underpriced due to the systematic cognitive errors of investors. These particular cognitive errors result from the tendency of investors to trade based on simple heuristics, or "rules of thumb," which are susceptible to human emotion. Unwavering adherence to the model, regardless of market conditions, is critical because avoiding the temptation of human emotion is the key to profiting from, rather than falling victim to, these cognitive errors.
The rules-based discipline for closing long positions also operates on the underlying premise that the pricing of the affected stocks tends to move toward greater efficiency in the long term. That is, a stock will not remain mispriced indefinitely. A key characteristic of the exit discipline is its focus on positions that negatively impact the performance of the Strategy. This discipline exploits the behavior-based disposition effect, the human tendency to be overly reluctant to accept losses, and it also avoids the human temptation to "double down" on losers that might otherwise appear to be underpriced. The result is that winning positions are allowed to run while losers are culled out generally before they damage overall portfolio performance materially. Again, the key is a disciplined adherence to the rules-based model.
History clearly demonstrates that the long-term trend of the equity market has been upward. Furthermore, the Manager's research on market behavior within each calendar year since July 1963 suggests that, on average, most stock market gains occurred during the months of November through May. It follows that the months of June through October tend to be the months when the market periodically experienced its larger losses. As further confirmation, research by Bouman and Jacobsen found this seasonal pattern in U.S. equity markets to be robust, statistically significant, and persistent since 1802. Thus, this seasonal pattern is incorporated into the Strategy to enhance long-term return and reduce downside risk.
The Strategy maintains approximately $2 - $5 of positions for each $1 of capital invested. Generally during periods of low to normal volatility, the Strategy will target $5 of positions for each $1 of capital invested. Generally during periods of higher volatility, the position sizes are systematically reduced to as low as a target of $2 of positions for each $1 of capital invested. This is done to reduce risk during periods of heightened volatility and is supported by the Manager's research. See the following section heading "Portfolio Construction: Reducing Target Exposure".
Furthermore, the targeted amount of capital invested in long and short positions will also vary based upon the relative volatility of the long and short positions. This again is done to reduce risk and is supported by the Manager's research. See the following section heading "Portfolio Construction: Balancing Long/Short Volatility".
Based upon the research just described above, the allocation of dollars committed to longs and shorts changes seasonally as illustrated below.
During the months of June through October the Strategy is dollar neutral with approximately equal amounts of capital in both longs and shorts. This is intended to significantly reduce downside risk during the time period when the larger losses in the market tend to occur. Assuming low to normal volatility, during the months of November through May the Strategy's positions are allocated to create a long bias with approximately $3 in long positions and $2 in short positions for each $1 of capital. This creates the opportunity to capture more of the gains the market tends to produce during these months. This construction is consistent with the Manager's research on market seasonality. During periods of higher volatility, exposure to both long and short positions is reduced proportionately.
The Strategy maintains approximately $2 - $5 of positions for each $1 of capital invested. When exposure, employing the use of leverage, is greater than capital it expected to increase the volatility and risk of the Strategy.
Generally during periods of low to normal volatility, the Strategy will target $5 of positions for each $1 of capital invested. The Manager's research suggests this results in an acceptable level of risk. As volatility increases, the investment strategy is designed to systematically reduce the Strategy's exposure, resulting in a systematic reduction of the Strategy's risk during periods of heightened volatility.
As volatility falls from higher levels and sustains lower volatility levels, the investment strategy of the Strategy will systematically increase exposure.
This risk control is employed daily to systematically maintain the targeted Strategy exposure based upon the current volatility.
The Strategy maintains both long and short positions at all times. To maintain an acceptable level of risk, the level of exposure to longs and shorts is adjusted based upon their respective volatility.
Consider the following example of how this risk control impacts the Strategy. If the goal is to have an equal amount of risk in both the long positions and short positions, the Strategy would have equal amounts of dollars invested in both long positions and short positions assuming the volatility of the longs and shorts are equal. This is represented by the following formula:
[Longs $ Value] x [Longs Volatility] = [Shorts $ Value] x [Shorts Volatility]
On the other hand, if the volatility is not equal for longs and shorts but instead the shorts had volatility that was twice the level of the longs, only half as many dollars need to be invested in short positions relative to longs to maintain equal risk.
This risk control is employed daily to systematically maintain the target risk exposure between long and short positions.