About the author: Apurv Jain is a visiting researcher at Harvard Business School where he is working on using alternate data sources (Big Data) and artificial intelligence (AI) for investing. He is also an advisor to Kuvera senior management.
A Tragedy with a Serving of Schadenfreude
Imagine we read the following story of Mr. X’s investing adventures in the stock of a volatile company Y:
Early in the year, Mr. X dumped his shares (in Y company), pocketing a 100% profit of £7000. But just months later, as the market rocketed up (and perhaps afflicted with FOMO- the Fear of Missing Out), Mr. X jumped back in at a higher price—and lost £20,000 when the stock crashed.
We might say- Ha! the guy must not be smart or perhaps not well informed and recount our successes in contrast.
But what if I told you that Mr. X was Sir Issac Newton- widely regarded as one of the most important scientists ever. In addition to being brilliant, he was well connected as a member of Parliament and the master of the Royal Mint. A chart of Newton’s investing borrowed from Marc Faber via an article by Richard Evans from Telegraph[4] looks like this:
Schaden what?
Newton reportedly proclaimed, “I can calculate the movement of the stars, but not the madness of men.” He also forbade anybody to mention the word “South Sea” when he was around [3]. It is a funny story with a promising side of schadenfreude- (I looked it up)- it means “enjoyment obtained from the troubles of others.” We take comfort in the fact that this is a historic phenomenon and we tell ourselves that at least we are better at investing than the man who invented much of classical Physics.
It does not apply to me!
However, think again. As we talked about in the last blogpost, research shows investors do chase returns and it lowers the amount of money they get from investments. While research on how most mutual fund managers cannot beat their index fund benchmark is well known, not much attention has been given to the idea that return chasing behavior delivers negative alpha (performance) and exacerbates the problem. Now we will define two terms and provide some hard data.
Rupee (or Dollar) weighted return measures how many Rupees you actually made and is derived as the IRR (internal rate of return) to measure the performance of fund’s investors. This is the return that an average investor investing in the fund generated.
Time weighted returns measures the performance of the fund manager over time without taking into account how much money was invested. This is the NAV based return that the fund manager delivered.
Illustrative example:
To make this concrete, suppose you invested Rs. 100 and the manager makes 10%, then you invest another Rs. 100 to have a total of Rs. 200 invested and the manager loses 5%.
The rupee weighted or the investor return would be 10%*100 – 5%*200=0.
And the time weighted or the manager return would be (10% -5%)/2=+2.5%.
The difference between the two returns = 0% -2.5% = -2.5% would indicate the money lost from return chasing or investing more money after a recent high performance.
So what does the data say about “Chasing Returns”?
Authors Friesen and Sapp, (Journal of Banking and Finance, 2007) analyzed more than 7,000 equity mutual funds from the CRSP Survivor Bias Free US Mutual Fund database.
They find that while an average fund manager delivered 0.62% monthly return (time weighted), the average investor could only capture 0.49% monthly return (dollar weighted).
This difference of 0.49% – 0.62% = -0.13% per month is -1.56% when annualized for the average investor.
Friesen and Sapp thus conclude that investor timing decisions reduce returns by an average of 1.56% annually. Some key findings from their paper:
1/ Poor investor timing ability is significantly associated with the best performing funds. The best fund managers are not able to deliver the best return because of investor timing. The authors find that the top 30% of managers do have positive alpha of + 0.27% monthly. But investors poor timing results in -0.25% gap between the dollar return and the time weighted returns. In other words by entering and exiting at the wrong time the investors destroyed almost the entire value the managers had created.
2/Timing Under-performance is higher for larger and more costly funds. The top 20% of the funds by assets under management (AUM) have -2.28% difference in the dollar returns vs. the time weighted returns per year vs. the average of -1.56%. Older and more expensive funds are associated with investor clientele that times more poorly.
3/Equity fund suffer more than bond funds. Authors find that poor timing phenomenon is largely unique to mutual funds which attracts the less sophisticated and more active investors.
Buy High and Sell Low: Why might this happen?
We are still investigating this. But one mechanism may be that if most managers have a particular style or expertise – say value investing or small cap stock investing – the returns those styles generate tend to be cyclical and weakly related over long runs.
In this story investors do not pay attention to the long term cyclical factor but are overconfident in their ability to predict returns by extrapolating based on the past few months’ or years’ performance. These overconfident investors might systematically jump in when returns have been high for the past few months and jump out when returns have been low in the last few months. In combination with the flow phenomenon if simply using the last few months’ or years’ performance is not a good (or statistically significant) way to predict returns, these investors are in fact “buying” high (when past performance is high) and “selling” low (when past performance is low).
Similarly if institutions can only find support for a manager after a 3 to 5 year track record of good performance, then the next 3 to 5 years may not be as good since either the style/factor valuations are high which suggest lower future returns, or seeing that style of investing become successful, a lot more funds start offering such products, thus crowding out the opportunity.
So what to do?
1/Be proactive and understand the style of the manager and reflect how well that particular investing style works for you. Do your diligence and do not judge simply based on past returns.
2/If the style works for you, stick with it unless something fundamentally changes. For example, you have an unforeseen cash need etc.
3/Keep a safeguard on impulsive decision making say by committing to have at least one long conversation with your spouse or good friend before you can change your investment.
So do not be Newton in investing!
p.s. We are investigating how does the average Indian investors do vs. the academic studies we have cited and hope to update this blogpost in the future with some results.
References
1. Geoffrey C. Friesen and Travis Sapp. Mutual Fund Flows and Investor Returns: An Empirical Examination of fund Investor Timing Ability. Journal of Banking and Finance, Vol 31, pp. 2796-2816, 2007.
2. Jason C. Hsu, Brett W. Myers, Ryan J. Whitby. Timing Poorly: A Guide to Generating Poor Returns While Investing in Successful Strategies.
3. Kat Eschner. The Market Crash That Cost Newton A Fortune. January 6, 2017. https://www.smithsonianmag.com/smart-news/market-crash-cost-newton-fortune-180961655/:
4. Richard Evans. How (not) to Invest Like Sir Issac Newton. 23 May, 2014. https://www.telegraph.co.uk/finance/personalfinance/investing/10848995/How-not-to-invest-like-Sir-Isaac-Newton.html
5. https://www.merriam-webster.com/dictionary/schadenfreude
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