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The field of behavioural finance has shown that human brains have evolved over thousands of years to be more suited to survival than investing. Survival usually involves doing what others are doing without question (running to escape the sabre-toothed tiger or more recently filling your shopping trolley with toilet rolls and bottled water because everyone else is), whereas successful investing typically involves doing the opposite of the crowd. In addition to this tendency to follow the crowd, our brains also hamper our ability to invest as a result of many other behavioural biases such as overconfidence, loss aversion, recency bias, confirmation bias and hindsight bias (so brilliantly being displayed by the UK media now).
Furthermore, during times of stress, our emotions take over to a greater extent and these biases become worse.
“One of the most important features of behaviour under stress for investors is how our time horizons contract. In the midst of panic our concern becomes singularly focused on what is happening right now; we are gripped by the fears of today and abandon any thought of the future. Whilst in certain situations in life this can be considered an effective adaptation for meeting our long-term investment objectives such myopia can be staggeringly damaging”
Joe Wiggins, Behavioural Investment 26 March 2020
If you accept that these biases are likely to lead to sub-optimal decisions, it is important to consider what steps you might take to keep your emotions in check.
1. Accept what you (and others) can forecast and what you cannot.
Right now, we are being bombarded with forecasts about the likely number of deaths from coronavirus, as well as the economic impact of the decision to shut down major economies. Faced with this barrage of bad news, investors become ‘gripped by the fears of today and abandon any thought of the future’ and their survival instinct tells them to sell cyclicals no matter how lowly valued they are and buy defensives no matter how highly valued they are. They would, however, do well to remind themselves of the historic failure of forecasting especially within the field of economics. Whilst we do not have the space here to list all the historic failures of forecasting, it is worth considering a couple of topical examples: forecasting models used by epidemiologists and the oil price.
Whilst the UK government seems to be placing a large amount of faith in Professor Neil Ferguson’s forecasting ability, it should be noted that he does not have an unblemished track record in this area as the text below demonstrates.
In the late nineties, experts had forecast that avian flu strain A/H5N1, “even in the best-case scenarios” was to “cause 2 (million) to 7 million deaths” worldwide. A British professor named Neil Ferguson scaled that up to 200 million. It killed 440. This same Ferguson in 2002 had projected 50-50,000 deaths from so-called “Mad Cow Disease”. On its face, what possible good is a spread that large? But the final toll was slightly over 200.’
The oil price has collapsed this year in response to the huge decline in demand as industry has been shut down and transport has ground to a halt. Predictably, ‘experts’ are now anchoring off today’s price and forecasting that it might never trade above $10 again. This is not the first time that this has happened. In what is now one of the magazine’s most infamous articles, The Economist published a report in March 1999 highlighting how the price of oil had fallen to just over $10 per barrel, its lowest level in real terms since 1973. The article postulated whether given the trend in prices since the late 1900s that prices could, and should, fall even further:
‘Yet here is a thought: $10 might actually be too optimistic. We may be heading for $5… Thanks to new technology and productivity gains, you might expect the price of oil, like that of most other commodities, to fall slowly over the years. Judging by the oil market in the pre-OPEC era, a “normal” market price might now be in the $5-10 range. Factor in the current slow growth of the world economy and the normal price drops to the bottom of that range.’ 
By mid-2000, the price had recovered to $30 (a 200% rise) and by mid-2008 it was trading at $140 at which point some ‘experts’ were forecasting that the oil price could now exceed $200. By the end of the year, it was back down at $44.
Try to accept that forecasting is incredibly difficult and therefore do not base an investment strategy around forecasts. You might think that we are in secular stagnation which will lead to permanently low inflation and interest rates but be honest and ask what degree of confidence you have in that forecast. Have you historically been a very accurate forecaster of the inflation rate and if so, was that based on a solid repeatable process or luck? Could you be demonstrating overconfidence in your skills as a forecaster? Furthermore, if you build an entire strategy around that view and get it wrong (which is a reasonably likely outcome), the entire strategy will be wrongly positioned, and returns will suffer accordingly.
2. Use base rates rather than forecasts to try to increase your probabilities of a successful outcome.
In statistics, the base rate generally refers to the (base) class probabilities. For instance, in the US, the base rate of being a Christian is one in three whilst the base rate of owning a mobile phone is nine out of every ten. Given that successful investing involves playing the probabilities, you would think that investors would always choose options that increase their probabilities of success but that is not the case due to what is known as ‘the base rate fallacy’.
This describes people’s tendency to use mental short cuts or heuristics rather than base rates. In a famous experiment carried out by Amos Tversky and Daniel Kahneman they gave subjects a short character sketch of a woman called Linda, describing her as, “31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations”.
People reading this description then ranked the likelihood of different statements about Linda. Amongst others, these included “Linda is a bank teller”, and, “Linda is a bank teller and is active in the feminist movement”. People showed a strong tendency to rate the latter, more specific statement as more likely, even though a conjunction of the form “Linda is both X and Y” can never be more probable than the more general statement “Linda is X” i.e the base rate for bank tellers is higher than bank tellers who are also active in the feminist movement.
The explanation in terms of heuristics is that the judgment was distorted because, for the readers, the character sketch was representative of the sort of person who might be an active feminist but not of someone who works in a bank. When people rely on representativeness, they can fall into an error which breaks a fundamental law of probability.
Let’s consider how heuristics such as loss aversion and representativeness might lead to sub-optimal decisions in investing and how that decision might be improved using base rates. If you are thinking about selling a stock that’s halved or firing a fund manager that has underperformed, it might help to consider the base rates for that decision.
Research conducted by the Brandes Institute in its 2004 paper ‘Falling Knives Around the World’, sought to consider the subsequent performance of stocks whose share prices had fallen considerably. In their research, they defined a falling knife as a stock whose price had declined 60% or more over a 12-month period. The stocks’ absolute performance was tracked, as well as the performance of their country’s benchmark over the three years following its fall.
The results were telling. In the US, even counting those companies that went bankrupt, the knives returned an average annual performance of 11.2% in the following three years, versus the 4.6% average of the S&P 500 Index. For non-US knives, the average return was 10.8% per year, while their MSCI country index advanced at an average annual rate of only 5.3%. This would suggest that dumping a stock where the share price has already fallen considerably does not have a good probability of success.
How about the decision to disinvest from an underperforming fund manager? Again a well-known study by Amit Goyal and Sunil Wahal in 2008 of the hiring and firing of managers by large institutional investors in the US showed two things:
If institutional investors and the expensive consultants they use are bad at hiring and firing, it shouldn’t come as a surprise that ordinary investors fare no better. Indeed, new research by Morningstar shows that to be true.
3. Have a clear process and stick with it.
A good start point is to have an investment process that has been empirically shown to work over a long period of time. As the chart below shows, in the long run, value tends to work, momentum also does whereas quality does not, and growth does not.
Source: Research Associates, LLC, based on data from CRSP and Compustat, 2016.
The next part is to accept that your process will not work all the time and will not work in all market environments. It is critically important to focus on process over outcome as the latter is almost irrelevant in the short term whilst the former means nearly everything in the long term. Because your process in not working right now, however, it does not mean it will never work again. This merely demonstrates recency bias which is the tendency to focus on the most recent available data.
The most fatal thing that investors can do is to abandon a successful long-term investment strategy during a period that it is not working. This is simple to say but incredibly difficult to follow even for some of the most brilliant investors of our generation as the two stories below hopefully prove.
‘In March 2000, Julian Robertson made the decision to return all Tiger Management’s investors’ money. He shut down the hedge fund. Robertson and Tiger had been one of the early stars of the hedge fund world. He took $8 million in capital in 1980 and turned it into over $20 billion by the fund’s 1998 peak. But Robertson was too early to the party of shorting internet stocks. His dogmatic value-based philosophy on investing led him to be long old-economy companies in the late 1990s, in the face of a rampant growth-focused bull market.’
It meant that when he reached his peak in AUM, that was just when he started losing money. And because of that timing, many have said he actually lost more money for investors than he ever made them in the prior 18 years. Ironically, in March 2000, when Tiger threw in the towel, the market peaked, and Robertson ended up being proven right. He made plenty of money after 2000, as he remained short the internet bubble with his own money, but his investors never got to participate.’
Even worse, Stanley Druckenmiller who was George Soros’ partner at Quantum Fund, capitulated and bought technology stocks in March 2000. Here is how Druckenmiller summarised his experience of 2000 in an interview in November 2013:
“I bought the top of the tech market in March of 2000 [after quickly making money in the same space in mid-late 1999] in an emotional fit I had because I couldn’t stand the fact that it was going up so much and it violated every rule I learned in 25 years.
I bought the tech market very well in mid-1999 and sold everything out in January and was sitting pretty; and I had two internal managers who were making about 5% a day and I just couldn’t stand it. And I put billions of dollars in within hours of the top. And, boy, did I get killed the next couple monthsc”
4. Try to extend your time frames, and think long term
Having stated on the first page that during periods of stress investors time horizons tend to contract, it would be useful to have some ideas to combat that. In this regard, I can only describe what has worked for me.
Market volatility mixed with a constant stream of dire warnings about the future can be extremely stressful for investors. At times such as this, it is important to focus on what you can control (your philosophy and process) and to try to not get anxious about what you cannot control (daily share price movements and short-term fund performance).
I will finish with two of my favourite quotes on this subject.
“The investor with a portfolio of sound stocks should expect their prices to fluctuate and should neither be concerned by sizeable declines nor become excited by sizeable advances. He should always remember that market quotations are there for his convenience, either to be taken advantage of or to be ignored.”
“It is largely the fluctuations which throw up the bargains and the uncertainty due to the fluctuations which prevents other people from taking advantage of them.”
 ‘After Repeated Failures, Its Time to Permanently Dump Epidemic Models’ by Michael Fumento 18 April 2020
 Drowning in Oil, The Economist, March 1999
 The Selection and Termination of Investment Management Firms by Plan Sponsors
AMIT GOYAL and SUNIL WAHAL∗ THE JOURNAL OF FINANCE•VOL. LXIII, NO. 4• AUGUST 2008
 Thing Twice Before You Ditch That Laggard Fund in Your Portfolio by Jeffrey Ptak
 One of the Greatest Hedge Fund Managers Ever Lost His Investors More Than He Ever Made Them
By Valens Research October 30, 2019
 The Risks of Speculating During Rising Markets by Safal Niveshak 9 May 2019
The statements and opinions expressed in this article are those of the author as of the date of publication, and do not necessarily represent the view of RWC Partners Limited.. This article does not constitute investment advice and the information shown above is for illustrative purposes only and should not be construed as a recommendation or advice to buy or sell any security. No investment strategy or risk management technique can guarantee returns or eliminate risks in any market environment.
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