Behavioral Economics is the relatively new field of combining insights from psychology, judgement and decision making with economics to generate a more accurate understanding of human behaviour. Much of traditional economic and financial theory assumes individuals act rationally and consider all available information. Behavioral economics seeks to explain why people make decisions that are not rational. There have already been 2 Nobel prizes (in Economics) awarded to this area We want to discuss what implications this has for the financial markets.
When people are faced with an uncertain situation that demands time and thinking effort (yes thinking saps energy!) researchers have found that people face difficulty making rational choices. Personal biases can influence decision-making processes and have been found to drive individuals to make sub-optimal decisions.
At times, markets are not rational because human participants are not rational. Behavioural economics acknowledges this. Investors should be aware of these When it comes to money so that they will avoid making the same mistakes
Research has identified over 50 different types of bias but we can focus 3 common ones that we think impede portfolio performance.
Anchoring Bias
Here is the stock chart of of a company from 2010 to 2015
If you purchased a stock at 100 and the price doubled to 200 in 6 months and the valuation has also gone up significantly. Would you buy, sell or hold?
In 1 yrs time the stock has moved up to 300, if you had sold at 200 would you have bought it back again? Unlikely? Why? Our initial cost of 100 and the price we sold at 200 are our anchors. Is there a way we can ease the memory of what price we paid / sold it before? This the problem we are attempting to solve when we allocate a stock in the portfolio.
When we make decisions, we often use an anchor or focal point as a reference. Humans tend to put a heavy reliance on this initial information. This affects our other areas of our lives. What age should your kids start dating? If your kid tells you their classmates are dating at 13 years old, you would probably allow them to date at 15years. You were anchored to the initial number that you took reference from.
The bias is even more insidious than that since our brain could be anchored even on totally irrelevant numbers. In “Predictably Irrational”, the psychologist, Dan Ariely, demonstrated that a bunch of smart, highly numerate MIT students were easily tricked by an irrelevant number. The researchers showed certain high value items like wine or a textbook to the students. Next, the students had to write down the last two digits of their ID as if that’s the price of the item. After that, the students were invited to bid for the item. People with IDs ending in 80 to 99 ended up paying close to 3 times more than people with IDs ending in 00 to 19. Surely our ID numbers should not drive how much we think something is worth?
The punchline is the same stock in 2020 is at 1700
One of our aims with using an algorithm is to ask if we can stay invested longer and resist the temptation to sell out too early.
Loss aversion – Its so Painful to Sell?
The next bias is loss aversion. This is the pain of losing (money, item etc.) is psychologically twice as painful as the pleasure of gaining the same amount.
You bought a stock at $9 per share now it has dropped to $8. You justify that the stock is cheap and it is trading at 0.5x Price to Book value. Book value is a measure of all the assets (property, equipment, cash) minus all liabilities (bank loans, debt, payables). By buying it at a price to book of 0.5x you can double your money if the price goes back to 1x book. After a few more quarters / years of bad earnings the stock is now trading at $4. Again you justify that the bad news has already been reflected in the price and refuse to crystalize the loss. This goes on and repeats itself for a couple of years. If you sell now you will crystalize a loss and maybe look bad in front of your boss?
Loss aversion also interacts with status quo bias, which is an emotional bias that makes people prefer the current (known) state versus change. In investing we argue that the stock has moved sideways and we should maintain status quo. In reality, the opportunity cost of holding on instead of investing in other better investments could be very costly.
Herding Bias – I love to be in the crowd!!
Herding also occurs in animals like schools of fish. In humans we see this in riots and strikes. There is embarrassment if you are the only one owning the stock and you are wrong. Whereas it feels safe in the crowd if all your peers also own the stock and the stock went down significantly. You are less likely to be fired.
“Nobody gets fired for buying IBM” . A common phase used for people in various firms say when they have to look for a piece of software or consultancy service. By choosing a big brand name, employees believe they are protected if the project did not go according to plan. This behaviour is similar when fund managers look at an index or at other competing funds before deciding what stocks to buy. It often feels safer in a herd but this may not be in the best interest of clients when the stock goes down. It reflects a lack of ownership and employees who are not willing to be innovative and learn from mistakes.
We decided to design our algorithm to sidestep most of the issues highlighted here. As a fund manager, we want to make our decisions in an environment without time pressure, which is the best way of avoiding sub-optimal decisions. But that is not realistic when the human portfolio manager has to continuously monitor and trade around the portfolio. We have therefore deliberately designed our algorithm to remove most of the uncertainty in the decision making. By deliberately deciding to trade infrequently, (3 to 5 times a year), we want to deliver the most optimal outcome for our clients.
