All investors make errors that can often be traced back to a behavioral bias or emotional mistake.
If under certain circumstances these mistakes are systematic, then it is not a stretch to believe we can develop systematic strategies to profit from them. After all, this is the essence of active portfolio management, finding mispriced assets and benefiting from them.
And we believe a good source of mis-pricing is found in investors’ emotional or behavioral mistakes.
One potential benefit of this approach is its longevity. Investors have been making emotional / behavioral mistakes in the market for over a century. In a very broad example, Warren Buffett’s quote “Be fearful when others are greedy and greedy when others are fearful” is evidence that some have been profiting from other investors’ behavioral mistakes for a long time.
This is a very vague example, so we endeavored over the past year to find specific instances where it appeared an asset (stock, commodity, bond) was mispriced due to certain behavioral biases, and created investing strategies to target the behavioral bias / mispriced asset.
In the following, we share our strategy development framework and a strategy on which we have been working. This is for demonstration purposes only, and of course we would welcome any feedback from readers.
BEHAVIORAL STRATEGY DEVELOPMENT FRAMEWORK
1) Find instances of behavioral bias
There are instances in the marketplace that certainly elicit more biased behavior than others. Often these are emotionally charged times caused by a set of new information or changing sentiment.
When sentiment shifts, it can often trigger behavioral biases. Investors, in aggregate, tend to be susceptible to herd like behavior. If it seems like everyone is doing something, there is a strong behavioral desire to join them. There are numerous biases behind this including confirmation, cognitive dissonance and fear of missing out. These are some of the behavioral biases that feed bubbles and bear markets. This can work in both directions, such as investors neglecting companies that have fewer buy ratings or are not in the media very often.
2) Evidence of market impact
This is the hard part – is the behavioral bias causing an asset to be mispriced and under what conditions? We researched a great number of types of scenarios or situations over the past decades where we had a strong belief investor biases were impacting behavior. During this quantitative stage of our strategy development, we were looking for patterns of consistent mispricing of an asset and how the mispricing corrected over time.
It has to make sense intuitively. The quantitative research is important but the mispricing must be logical and potentially attributable to a behavioral bias.
Once a reliable pricing anomaly was found, our quantitative approach dug deeper analyzing how the anomaly acted in different market environments, across different sectors and for companies with different characteristics.
3) Develop trading strategy
Once a reliable mispricing anomaly was discovered, we then developed trading strategies designed to profit from it. The strategy optimization process is rather quant heavy and helped refine the strategy as to what kind of market is best or what kind of companies does the strategy have the most success.
The trading strategy was further refined to include stop- loss levels, trade duration and profit taking parameters. This helped further remove our emotions from the strategy implementation.
This was a very high summary look at how we develop and research new strategies. The markets are always changing and evolving which requires continuous adaptation.
FRAMEWORK IN ACTION – EARNINGS OVERREACTION
1) Instance of behavioral bias
When a company reports earnings, there can often be an overload of new information for the market to absorb. If the earnings are a big surprise, in either direction, this could cause emotions to become elevated, triggering increased biased behavior.
We have found under certain condition there is a tendency for share prices to overreact to earnings. If a company is truly worth its future discounted cash flow for the next 10- 20 years, why would one quarter carry such a big impact if they miss or beat expectation. This is the availability or recency bias in action, placing too much weight on information that is readily or newly available.
2) Evidence of Earnings Overreaction
We analyzed companies that experienced a big price reaction, either up or down, to an earnings report with the question: are investors overreacting to the newly available information? In some cases the answer was yes and in some no. The one which we will cover today is the overreaction to negative earnings surprises. We found that less volatile companies, which we bucketed as higher quality, seemed to recover well from the initial price decline. This was more notable compared to lower quality (more volatile) companies.
Intuitively this does make sense. A higher quality company misses earnings and its share price drops. There is more likely to be investors viewing the suddenly lower price as a buying opportunity in a quality company, thus helping bid the share price back up.
3) Trading Strategy
Potential buy ideas can be triggered by a higher quality company missing earnings and suffering a price drop. Further analysis was focused on the timing of the trade, shortly after the price reaction or waiting till end of day, plus whether the price reaction was counter or in line with the prevailing direction of the share price.
Finally, trade parameters were added including stop-loss levels and profit taking. Stop-loss is important as sometimes an earnings miss is just the start of something worse for a company.
Twitter: @ConnectedWealth
Any opinions expressed herein are solely those of the authors, and do not in any way represent the views or opinions of any other person or entity.
