FACTORS & BEHAVIOURAL BIASES

Humans Make Factors

May 2017. Reading Time: 10 Minutes. Author: Nicolas Rabener.

SUMMARY

  • Investors are humans and not the homo economicus
  • Investing is influenced by a wide variety of behavioural biases
  • Factors can be explained by a single or multiple biases

INTRODUCTION

When reading research on factors there are typically several explanation for the existence of factors. Some of the reasons are mathematical or statistical while others are more directly related to human characteristics. Some of these behavioural biases, which are often considered irrational for the homo economicus, have been described as early as 1759 by the economist Adam Smith. In this short paper we’re going to outline some of the biases that meaningfully influence investing behaviour and then describe which factors can be explained or influenced by them.

BEHAVIORIAL BIASES

We have listed 12 (the Dirty Dozen) that have a significant influence on investing behaviour. Empirical evidence shows that retail as well as institutional investors are affected by these biases.

  1. Survivorship Bias
  • Description: Focusing on the surviving entities of a data set
  • Example: Value investing works, just look at Warren Buffett
  1. Hindsight Bias
  • Description: An investor believes that an event was predictable while in reality it wouldn’t have been very likely to derive that conclusion before the event
  • Example: It was clear in 2000 that Apple was going to be a winner
  1. Loss aversion
  • Description: People tend to suffer more from losses than from equivalent gains
  • Example: Investors prefer not to lose $5 than to gain $5
  1. Anchoring
  • Description: Focusing on historic information and not adapting to a changing market
  • Example: US GDP growth is normal at 3%
  1. Mental Accounting
  • Description: Separating money into different mental accounts based on subjective criteria
  • Example: Going for lunch to Subway to save money, but buying Fiji water as a drink
  1. Confirmation Bias
  • Description: Looking for information that confirms an investor’s theory vs contradicting it
  • Example: My price target for one stock in my portfolio is achieved, therefore my system works
  1. Herding
  • Description: Following everyone else
  • Example: Buying tech stocks in 1999
  1. Disposition Effect
  • Description: Tendency of investors to sell shares whose price increased and keep shares whose price decreased
  • Example: Sold Amazon and kept Valiant in 2016
  1. Overconfidence
  • Description: Investors tend overestimate their own abilities
  • Example: More than 75% of the fund managers believe they can beat the market
  1. Narrow Framing
  • Description: Select investments individually and not in context of the portfolio
  • Example: Adding Apple to a US equities portfolio
  1. Local Bias (Familiarity)
  • Description: Investors tend to prefer stocks close to their home
  • Example: Having no allocation to international stocks
  1. Lottery Stock Preference
  • Description: Investors prefer stocks with high idiosyncratic volatility and skewness
  • Example: Tesla

FACTOR EXPLANATIONS

There are different schools of thinking regarding what drives factor performance; broadly speaking we can differentiate between two drivers: risk sentiment and behavioural biases. Some factors tend to perform when risk sentiment is positive or negative and investors receive a risk premia for holding factor portfolios. Other factors are not directly impacted by risk sentiment and can be better explained by behavioural biases.

Value & Size:

  • Cheap and small stocks are more risky securities, they promise higher returns
  • Effectively greed is driving the factor performance

Momentum

  • Buying winners and selling losers is driven by several biases, which are partially conflicting
  • Can be explained by herding, disposition effect, and anchoring

Low Volatility

  • Buying stocks with low volatility and selling stocks with high volatility
  • Can be explained by the lottery stock preference

Quality & Growth:

  • Stocks with high quality and growth tend to be less risky securities, these provide safety
  • Effectively fear is driving the factor performance

FURTHER THOUGHTS

Behavioural biases partially explain why investing is such a difficult undertaking as investors don’t act rationally all the time. We don’t believe humans will change any of these characteristics anytime soon and instead of fighting our nature, investors should take advantage of these. Factor investing is one of the obvious choices.

ABOUT THE AUTHOR

Nicolas Rabener is the Managing Director of FactorResearch, which provides quantitative solutions for factor investing. Previously he founded Jackdaw Capital, an award-winning quantitative investment manager focused on equity market neutral strategies. Before that Nicolas worked at GIC (Government of Singapore Investment Corporation) in London focused on real estate investments across the capital structure. He started his career working in investment banking at Citigroup in London and New York. Nicolas holds a Master of Finance from HHL Leipzig Graduate School of Management, is a CAIA charter holder, and enjoys endurance sports (100km Ultramarathon, Mont Blanc, Mount Kilimanjaro).

Connect with me on LinkedIn or Twitter.

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