Taking the Emotion out of Investing

The basics of investing are well known. Buy when prices are low; sell when they’re high. Diversify your assets. Defeat short-term market volatility by focusing on long-term goals. Don’t buy based on emotion.

These ideas sound easy, but are difficult in practice. Most do-it-yourself stock market investors consistently underperform a basic market index. In 20 years, the S&P was up 9.2%, while the average investor received less than 5%, and the average mutual fund investor only received 3.7%.

Why is this? It seems like our brains are hard-wired to be shortsighted. We most often seek immediate gratification and our brains justify our actions later.   The below graphic is a humorous illustration of what happens when investors attempt to time the market, or get caught up in emotional investing.

AO-cycles

http://cuffelinks.com.au/investing-against-the-herd-part-1-resisting-emotion/

Interestingly, a method was created to capitalize on the emotional investing of small-time investors in the mid 20th century called the “Odd Lot Theory.”  It went like this:

A standard lot represents 100 shares. Institutional investors purchase nice even numbers of lots, while individual investors purchase smaller amounts, referred to as “odd lots.” If one assumed that smaller investors trade based on emotion, then emotional trading can be discovered by these smaller “odd lots.” If one assumed that all emotional investing is bad, one would want to do the exact opposite of whatever the small investors were doing. Therefore, if a small investor purchased 7 shares of Apple stock, we would short Apple, and if they sold 7 shares, we would buy.

cool-cartoon-9139122

 

Investors have been attempting to remove emotion from investing for a long time. The solution is create an investment plan and stick to it. This is called an “algorithm,” or a procedure or formula for solving a problem.

The most common example of an investment algorithm is index fund investing. When one has funds to invest, one would simply deposit funds in a stock index, like the S&P 500. When money is needed, one would simply withdraw funds. The index fund represents the combined wisdom of everybody, and is the average return of all investors.

The trouble with algorithms is that most lack the mental fortitude to apply their system consistently. Following a plan is just plain hard, even if one lays out the rules beforehand.   A look at February gym membership cancelation shows how fickle follow through can be. It has been said that 88% of the population have failed at least one New Year’s Resolution.  Investors can likewise become emotionally invested and attached to the roller-coaster volatility of the stock market, or break their algorithm of only buying index funds by purchasing that one “really hot stock” championed on CNBC.

This has led to a rise in automated trading. Machines don’t call out sick, don’t have bad hair days, and aren’t interested in that latest “Mad Money” stock tip. This means that a machine will consistently follow through with arranged investment strategies, and hence remove emotional from the trading decision making process.

Marketplace lending is an interesting place for this application. By design, emotion is almost eliminated from the decision making process. There is little personally identifiable information in the listings, and investors are forced to make many small decisions quickly. Selling loans is also more difficult than stock, which means that it is harder to sell on emotion.

Just like in stocks, automated trading is becoming entrenched in marketplace lending. An investor can use a tool like LendingRobot to define rules once and be assured that those rules will be faithfully execute. Decision fatigue and emotion are eliminated, and over time one can analyze and improve those rules to ensure portfolio optimization.

The difficulty of managing emotion in investing is being simplified and solved with automation. Now if only we could automate our workout routine…

 

Leave a Reply

Website Protected by Spam Master