Overcoming the Herd Instinct in Markets
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03 July 2019
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Ever walked into a mall and saw heaps of people gathered into lines that stretch as far as the eye could see? You have no idea what’s going on, but for some inextricable reason you feel compelled to join the back of the line too and patiently await for this mysterious artefact to reveal itself. Hopefully something or someone turns up?

If you did, you just succumbed to the lure of the herd and fallen into perhaps one of the most common investor behavioural biases. Most daily examples of herding behaviour can be completely innocuous whether you’re strolling through your neighbourhood mall or adopting the latest trends. But as seen throughout history, extreme instances of herding in markets can significantly distort prices, lead to asset bubbles and even cause recessions.

From Tulipmania that gripped 17th century Netherlands, the dotcom bubble in the early 2000s as well as the subprime mortgage crisis during the 2008-GFC, history has shown that investors are willing to suspend disbelief when market euphoria swells to reach delirious highs. This is prevalent especially during bullish market conditions and when there is abundant liquidity in the system.

Go with the Flow? Not Really…
As social creatures, people have a sense of safety in numbers. There is just a collective reassurance that comes with conforming to the wisdom of the crowd especially when navigating the treacherous peaks and slopes of markets.

But if you take a closer at just who is behind the trading desk, you may realise that that there’s isn’t anyone after all. The underlying reality of investing in stock markets today is that most trading are done by machine and algo traders who profit from short-term fluctuation in prices and ignore fundamental analysis. According to reports, 80% of daily moves in the US stock market are machine-led. In 2017, the global algorithmic trading market was valued at US$ 9,297.24 million and is projected to exhibit compound annual growth rate (CAGR) of 10.1% over the forecast period (2018 – 2026).1

Behind each market plunge is a digital herd of trading bots programmed to buy and sell based on pre-determined formulas and models. This ignites a ‘flash crash’ like that seen in 2010 when the Dow Jones Index lost close to 1,000 points in mere minutes. The S&P 500, Dow Jones industrial average and Nasdaq collectively lost $1 trillion. But in 36 minutes, the rout was all over and markets rapidly recouped back its losses.

Investors who reacted too quickly and sold into this correction would see their portfolios impacted and dragged down by this invisible digital herd. Most daily price fluctuations are just too fast and short-term in nature for any ‘human’ investor to discern any meaningful price trend/movement and make gains.

It’s also primarily a volume game for algo traders that rely on high frequency trading to make razor-thin margins. Indirectly, the proliferation of machine trading has exacerbated intraday volatility and lead to sudden spikes in markets.

Recognising Bad Behavior
Detecting herd-like behaviour in markets can be tricky for investors. By its nature, the market is dominated by emotions of greed and fear which tend to take over logical reasoning and critical judgement. Thus, investors who follow the herd tend to buy high and sell low historically.

Chart 1 below shows the performance of the S&P 500 index against equity fund flows through the years. When the S&P 500 index soared during the dotcom boom in 1999, there was also an influx of equity fund flows leading investors to a market that is already frothy and potentially overvalued. Conversely, when the markets fell after the housing bubble burst in 2009, there was a surge of outflows when investors cashed out from the market, but selling low.
Chart 1: Herd Behaviour Leads to Bad Judgement
Source: FactSet, Investment Company Institute, Standard & Poor’s, J.P. Morgan Asset Management. Mutual fund and exchange-traded funds (ETF) flows are through 28/02/19
So what is one supposed to do when there is a stampede of investors rushing in and out from the market? It’s unnerving for sure to stand against the tide, but being bold and firm with your investment conviction is what makes one stand out against the rest and outstrip peer performance. 

The answer may be as simple as doing nothing in fact.

Chart 2 shows the performance of two different portfolios with one actively traded and the other adopting a buy-and-hold strategy. The performance is starkly different with the buy-and-hold portfolio posting annualised returns of 18.6% p.a. compared to the actively traded portfolio that returned 12.3% p.a.

Timing the market is a precarious errand and your chances of missing the best days in markets can sting more than avoiding the worst days. Some of the biggest upswings often occur during a market swoon when investors have already fled.
Chart 2: Better To Do Nothing
Initial Balance
Financial Balance
Return (p.a.)
Volatility (p.a.)
Max Drowdown
Active Trading Portfolio$1,000$2,34612.3%9.3%-6.7%
Buy & Hold Portfolio$1,000$3,49818.6%10.6%-9.3%
Active trading portfolio results from 2012 to 2019 for Horizons S&P 500 Index ETP (HXS. TO) are based on 42 trading day simple moving average. The active trading portfolio is invested in the asset when the adjusted close price is greater than or equal to the moving average, otherwise the portfolio is invested in cash. Active trading portfolio model trades are executed using the end of week close price.
Source: Portfolio Visualizer, calculated from February 2012 to April 2019

A Case of FOMO
Just like real life, investors have the tendency to join the bandwagon due to just a case of FOMO (i.e. Fear of Missing Out) and burying their own consternations. A recent example would be the height of the bitcoin currency craze that sent prices to dizzying highs above its intrinsic value, if there ever was.

Astute investor Warren Buffet said that one should be, “Fearful when others are greedy and be greedy when others are fearful.” Take a step away from the herd and put on your contrarian cap to understand what is driving the euphoria in markets.

Have a long-term investment horizon in mind and understand your own risk-tolerance and liquidity needs. If you can’t stomach the volatility in your portfolio, chances are you may be taking too much risk than your capacity allows. As long you have properly done your asset allocation and are adequately diversified in your portfolio, you can confidently sit through market cycles and ride through the turbulence.

Sources 1:
  • Coherent Market Insights, Business Wire, 2019
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TENG CHEE WAI

Managing Director
Teng Chee Wai is the founder of Affin Hwang Asset Management Berhad (Affin Hwang AM). Over the past decade, he has built the Company to be the fastest growing and only independent investment management house in Malaysia’s top three, with an excess of RM47 billion in assets under management as at 31 December 2018.​

​In his capacity as Managing Director / Executive Director, Teng manages the overall business and strategic direction as well as the management of the investment team. His hands-on approach sees him actively involved in investments, product development and marketing. Teng’s critical leadership and regular participation in reviewing and assessing strategies and performance has been pivotal in allowing the Company to successfully navigate the economically turbulent decade.

Teng’s investment management experience spans more than 20 years, and his key area of expertise is in managing absolute return mandates for insurance assets and investment-linked funds in both Singapore and Malaysia. Prior to his current appointments, he was the Assistant General Manager (Investment) of Overseas Assurance Corporation (OAC) and was responsible for the investment function of the Group Overseas Assurance Corporation Ltd.​

​Teng began his career in the financial industry as an Investment Manager with NTUC Income, Singapore. He is a Bachelor of Science graduate from the National University of Singapore and has a Post-Graduate Diploma in Actuarial Studies from City University in London.
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