The Strengths & Weaknesses Of Index Investing

The Dow jones have not dropped more than 20 basis point in the last 10 years, many analysts have brand this as the longest bull market. Raymond James (2018) found that ability of a peer group to add value relative to an index is highly dependent on the market environment. Generally, the study finds that active management underperforms the index in bull markets, but outperforms the index in bear and neutral market at a statistically significant level than zero at 95% confidence except small cap. Across all three studied asset classes, the peer group performs worse than the index in bull markets in regard to excess returns.

Index investing, its purpose and the types of securities used by retail and institutional clients to index invest

Index investing is a strategy that involves the process of using index funds to build a passive investment strategy. Index investors decide which markets they want to invest in, how much money to put, and utilize index funds to put that plan in place. They are simply mutual funds where the managers construct the index in a way that will replicate the market’s return, by constructing the fund with the same weight of the securities that make that benchmark index. Generally, both retail and institutional investors invest in securities such as bonds, options, and futures contracts as well as in stocks. However, because institutional investors handle high volume of trades at once they tend to avoid securities of small value like stocks that are selling for less than $10 a share, which the retail investors fill the void where they predominantly make the market.

Under the assumption that markets are inefficient fund managers actively pick ‘winners and losers’ stocks to try and beat the market and receive alpha. Index Investing falls in the opposite spectrum where markets are assumed efficient, therefore participants in the aggregate are better at determining prices than a single individual. Index investing aims to utilize index funds to replicate a benchmark and mimic said market to then achieve as close of a return of said market as possible.

The strengths and weaknesses of index investing its increase in popularity and its implications on Market efficiency

Passive in nature since index investing requires less resources than that of its more active counterpart. Ferri (2010) wrote in a Forbes article, “the fees for active investing are too high, the opportunities are too few, and the talent is too rare”. Even though market anomalies exist the benefits are generally too small to outweigh the transaction costs required (Malkiel, 2003). The ‘Efficient Market Hypothesis’ suggest that the benefits are absorbed by the market and reflected in price (Schwert, 2001). A study conducted by Malkiel (2003) found that of the 355 U.S equity mutual funds beginning in 1970, over 50% of those closes over the 32-year period. He also found over a 10-year period, 71% of these funds in the U.S gets outperformed by Vanguard index fund, proving that for a long term-investors passive investment is ‘safer’.

However, Arnott believes in his WSJ article that traditional indexing is not optimal. Touted as the ‘Noisy Market Hypothesis’ he outlines that indexes based on market capitalization, during reconstruction to mimic the benchmark could lead to the fund eventually consisting of more overvalued securities (lower expected return) and less undervalued securities (higher expected return) (Jakab,2018). Fundamentalist address this problem by building custom indexes on fundamentals such as book value, sales, earnings etc. to break that traditional relationship.

As Raymond James (2018) found out that active investing has its place in bear and neutral markets, where active investors winning 68%, 61% and 80% of the time on large-cap, small cap and international large-cap core respectively but not the case in the bullish market. Where those investors only beat the index investors 15% ,44%, and only 9% of the time respectively. Considering that the Dow Jones is in its longest bullish market index investing with its low cost, relative safeness and consistent outperformance have found increase in popularity. As increase in technology coupled with reforms in market operations returns on anomalies seem to attenuate over time building a case for index investing.

Evidence in shift from active management to much more passive index investing is evident, big asset management such as BlackRock aims to direct most of their funds to take a more passive strategies (Patten, 2017). Warren Buffet, further established that for both retail and institutional investors should opt for the more low-cost index funds, claiming further that over this 10 year $100 billion have been wasted by manager (Buhayar, 2017). This shift reflects the industry to more align with the EMH. However, reconstituting of the fund is often done by managers to match the benchmark’s composition. Index managers can potentially buy securities at a premium and sell securities at a discount. This allows opportunity to “front-run” on reconstitution dates, diminishing the EHM (Dyakov, 2012). Market efficiency, the momentum anomaly and detail and a investment strategy to exploit it.

Market efficiency dictates that prices will change to immediately reflect new information in an instantaneous and unbiased manner. Since prices reflect incoming information that is unpredictable in nature, so then must price move unpredictably. Market inefficiency occurs when signals arises that investors can use to predict the market and generate excess returns (Fama, 1970). Existence of exploitable signals does not necessarily mean markets are inefficient, active investors that seek alpha and those that look for these anomalies inadvertently acting as a correction tool, as these investors trade and price change to absorb the new information making the market more inefficient. Market inefficiency therefore is predicated on a persistent and consistent signal that active investors use to constantly generate excess return and beat the market.

Momentum explains why stocks that wins continue to win and vice versa, it is a market anomaly because it violates the EHM assumption of instantaneous information absorption. Koening (1999) describes a behavioural reason called the herding effect where the impact of loss on utility is reduced when incurred with investors s/he considers its peer group as follows investors follow the crowd and invest on securities that have performed well instead on those with good future prospect. Conservatism, can contribute to short term momentum as individuals fail to reconstruct their view of the future therefore underreacting resulting in lagged price movement not consistent with the EHM. Jagadeesh (1993) found that excess return from longing past winners and shorting losers can reach 1% monthly return on a 6-12-month time horizon. Debondt et al (1985) finds a price reversal in a longer horizon where ‘losers’ in the past 3-5 years tend to outperform the winners.

Many attribute momentums to be caused also by cognitive biases, Daniel et al (1998) attributes two psychological biases to the momentum anomaly; overconfidence which is overreacting to private information, and self-attribution bias when information becomes public. If information aligns with expectation the investor will be more confident, but if not, they would under react. The over and under reaction caused by this cognitive bias comes to explain the short term and the long-term price reversals momentum anomalies.

The momentum strategy and the contrarian strategy introduced by Jagadeesh et al (1993) and Debondt et al (1985) respectively are the basic strategy that exploits this momentum by longing past winners and shorting past loser while the latter longs past losers and so on, resulting in 1% monthly abnormal profit. One deviation of the traditional strategy is introduced by Hong et al (2000) that consider the size and residual analyst coverage. Predicating on the assumption that information about small firms and firms with low analyst reach investors more slowly, using momentum strategies more profits are generated for these small, low analyst coverage firm. The study links momentum profit to the firm’s diffusion of information, the less the firm’s diffusion the more momentum profit can be realized.

Usefulness of the investment strategy to an institutional fund manager in the current index investing trend

The strategy introduced by Hong et al, can be readily implemented by institutional funds that have many resources to seek out firms with the characteristic. Findings from Gwilym et al (2012) however finds that although momentum strategies in general do well in a bull market it lacks favourable result for very small stocks. As Hvidkjaer (2006) stated retail investors are the ones that drive these momentums. Furthermore Baltzer (2015) found that “retail investors are strongly contrarian and are prone to the disposition effect as they under value winning stocks and over value losing ones. In a bull market institutional fund manager can exploit this momentum which can generate a persistent 9.6% average annual return. However, with the attenuative nature of return anomalies across the board, the probability that the institutional fund can outperform index investing is slim. As Raymond Jaymes (2018) suggest the fund in the bullish Dow Jones market will have far less than 50% chance of succeeding.

In conclusion, as the U.S stock market experience its longest bullish market to date there is evident in shift from active strategies to the more passive index investing strategies. The trends discussed above shows that Index Investing has become the most cost-effective strategy for investors of all kind retail or institutional to adopt especially in a bullish nature of the stock market. Regardless however, markets are not fully efficient, the fact that anomalies such as momentum still exist proves that although market are becoming more efficient, there are still inherent problems and constraints on the EHM that builds the case for a more active investing strategy. Active managers however must recognize the direction of the market and adjust accordingly. As Cain (2018) suggest a case can be made for a hybrid strategy where a huge amount of the fund is based on Index funds but still allowing the manager to exploit short term anomalies, effectively generating alpha plus the market return.

References:

1. Baltzer, M., Jank, S., & Smajlbegovic, E. (2015). Who Trades on Momentum?. SSRN Electronic Journal. doi: 10.2139/ssrn.2517462
2. Buhayar, M. (2017). Buffett Says $100 Billion Wasted Trying to Beat the Market. [online] Bloomberg.com. Available at: https://www.bloomberg.com/news/articles/2017-02-25/buffett-says-100-billion-has-been-wasted-on-investment-fees [Accessed 1 October 2018].
3. CAIN, T. (2018). Hybrid ETFs may offer the best of both worlds. Retrieved from https://www.theglobeandmail.com/globe-investor/hybrid-etfs-may-offer-the-best-of-both-worlds/article34998035/
4. Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor psychology and security market under- and overreactions. Journal of Finance, 53, 1839-1885De
5. Bondt, W. F. M., & Thaler, R. (1985). Does the stock market overreact? Journal of Finance, 40, 793-805.
6. Dyakov, T., & Verbeek, M. (2012). Front-Running of Mutual Fund Fire-Sales. SSRN Electronic Journal. doi: 10.2139/ssrn.2170660
7. Fama, E. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal Of Finance, 25(2), 383. doi: 10.2307/2325486
8. Ferri, R. (2018). A Decent Decade For Index Investors. Retrieved from https://www.forbes.com/2010/01/05/stocks-bonds-not-bad-decade-personal-finance-indexer-ferri.html#738e5f792452
9. Gwilym, O., Clare, A., Seaton, J., & Thomas, S. (2012). Tactical Equity Investing Across Bull and Bear Markets. The Journal Of Wealth Management, 14(4), 61-69. doi: 10.3905/jwm.2012.14.4.061
10. Hong, H., Lim, T., & Stein, J.C. (2000). Bad news travels slowly: Size, analyst coverage, and the profitability of momentum strategies. Journal of Finance, 55, 265-295. doi:10.1111/0022- 1082.00206
11. Hvidkjaer, S. (2006). A trade-based analysis of momentum. Review of Financial Studies, 19, 457-491. doi:10.1093/rfs/hhj016
12. Jakab, S. (2018). The Hidden Weaknesses of Index Funds. Retrieved from https://www.wsj.com/articles/the-hidden-weaknesses-of-index-funds-1476799335
13. James, R. (2018). ACTIVE AND PASSIVE INVESTING IN BULL, BEAR AND NEUTRAL MARKETS [Ebook]. Retrieved from https://www.raymondjames.com/-/media/rj/dotcom/files/corporations-and-institutions/related-services/institutional-consulting-services/ams_activepassive_white_paper_ics.pdf
14. Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock-market efficiency. Journal of Finance, 48, 65-91.
15. Koening, J. (1999). Behavioral Finance: Examining Thought Processes for Better Investing. Trust & Investments, 69, 17-23.
16. Malkiel, B. (2003). Passive Investment Strategies and Efficient Markets. European Financial Management, 9(1), pp.1-10.
17. Patten, S. (2017). Passive storm a wake-up call to investors. [online] Financial Review. Available at: http://www.afr.com/personal-finance/passive-storm-a-wakeup-call-to-investors-20170426-gvt23m [Accessed 1 October 2018].
18. Schwert, W. (2001). Anomalies and Market Efficiency. 1st ed. Rochester: Elsevier Science, p.956.