What really matters when engaging in capital markets
Despite thousands of academic studies encouraging investments into capital markets, potential investors show little engagement as financial illiteracy has been exploited by banks and financial institutions for years. As a result, investors are increasingly uncertain about what information is trustworthy. Even those who already engage in capital markets usually follow inefficient and outdated investment strategies. The reason is that the average investor lacks both financial background and knowledge about the underlying mechanics driving financial markets. This article aims to refresh aspects of fundamental financial theory that investors should pay attention to when engaging in capital markets and may well serve as broad guideline to investing.
Since the disruptive work by Fama (1965) on market efficiency, there has been an ongoing debate on the performance of actively managed investments. The efficient market hypothesis categorizes market efficiency as weak, semi-strong and strong. All three states derive from the general idea that market prices are determined conditional on the information about stocks that is available to investors. Different levels of efficiency assume different sets of information are already reflected in prices. Weak form efficiency states that future stock prices cannot be predicted solely from past stock prices. In presence of semi-strong efficiency, additional to past performance data, investors cannot gain from trading on information publicly available. Finally, strong form of efficiency states that not even insider trading achieves abnormal returns. For example, a market is at least weakly efficient if participants cannot perform better than the average investor by studying past prices. However, it might not be strong form efficient, if investors in possession of insider information can consistently outperform.
Malkiel (1973) introduced the canonical random walk model to the financial world, setting a new standard. Building on the efficient market hypothesis, it has since been used extensively in financial modelling. It states that except for long-run trends (drifts), stock price movements approximately follow a so-called random walk. Since all information currently available is reflected in present prices, long-run outperformance of market returns is deemed impossible.
These findings imply that investors with informational advantage can act on this information and exploit profit opportunities before other, less informed market participants. Since trading on new information is highly profitable, investors rally to seek out all information about stocks. Following trading activity pushes prices to reflect news and restores market efficiency. The faster market prices change in response to new information, the stronger the market efficiency. This makes reliable stock price predictions impossible.
Since its introduction to the financial world, thereis a fierce debate to which extent market efficiency holds. Given perfectly efficient markets, active management should be futile. If efficiency holds, this would favor one of the best known pieces of financial theory, namely the capital asset pricing model (CAPM) by Sharpe (1964). This model prices securities using only data of past prices. It is based on the assumptions of costless information, absence of market frictions and homogeneity of investor expectations. However, in reality information is indeed costly, markets do exhibit frictions such as costs related to execution and search, and investor expectations are hardly homogeneous. Within imperfect markets, active portfolio management has earned its place as some managers may very well be able to successfully and consistently exploit market frictions and inefficiencies.
Despite the volume of articles in this vein, evidence on the systematic ability of market agents to generate abnormal profits yields at best mixed results. Among many others, French (2008) and Carhartt (1997) find evidence that active investing diminishes value compared to investment in the respective benchmarks, after accounting for fees.
Still, there is a vast amount of articles insisting a stock’s future price can be predicted based on past prices, technical indicators such as trends. For example, evidence has emerged of statistically significant differences in stock market returns during certain months and days of the week. The “January Effect” is a highly researched topic, proving a certain increase in stock prices during this month, while other research projects provide evidence on lower market returns between the months of May and October. However, one thing that all these trading strategies have in common is that once found, they tend to vanish quickly. Reason is that informed traders attempt to cease the opportunity and thereby eliminate any profitable mispricing (arbitrage pricing theory).
This is the main reason why Fama (1965) and Malkiel (2003) among many others reason that in the long-run, no profitability can be found in technical or theoretical trading strategies. Even if initially successful, it is unlikely that their success persists in the long-run. Therefore, it is reasonable to advise investment in low cost, diversified index funds to earn the average market return at comparably low risk, as shown e.g. in French (2008).
Nobel laureate and former Stanford professor William F. Sharpe (1991) summarized in his article “The Arithmetic of Active Management”:
1. Before costs, the return on the average actively managed dollar (trying to beat the market return) will equal the return on the average passively managed dollar (passively invest in the broad market) and
2. After costs, the return on the average actively managed dollar will be less than the return on the average passively managed dollar.
However, passive investors can be confident to obtain the market return, before costs, as it is generated by indices tracking a specific market benchmark. From this we can deduce that the return on the average actively managed dollar must equal the market return as well, because for each active manager outperforming the market, there must be a counterpart underperforming. Since traders are not able to actively outperform the market over a prolonged period, with the large share underperforming benchmark indices, it should be obvious for investors that passive investments yield superior returns in the long run. Furthermore, as active managers exhibit higher costs than passive managers and active and passive management must on average equal the market return before costs, the logical conclusion can only be that the after-cost return from active management must be lower than that from passive management (simply due to the difference in fees).
Based on the fact that outperforming the market in the long-run is not sustainable, evidence clearly underlines that the most important selection criteria for investment products and services are the associated costs (according to Fama (1965), Sharpe (1991) and French (2008) among many others).
The practical implication is very simple: check the costs of all financial products you have in your accounts. We will keep you posted with further articles in the next weeks how to decrease investment related cost and optimally obtain the market return with factor and tail risk optimized passive investing.
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Carhart, M. M. (1997). On Persistence in Mutual Fund Performance. The Journal of Finance, Vol. 52 No. 1.
Fama, E. F. (1965). The Behavior of Stock-Market Prices. The Journal of Business, Vol. 38 No. 1.
Fama, E. F., & French, K. R. (2008). Dissecting Anomalies. The Journal of Finance, Vol. 13 No. 4.
Malkiel, B.G. (1973). A Random Walk Down Wall Street. W. W. Norton & Company, Inc.
Malkiel, B. G. (2003). The Efficient Market Hypothesis and its Critics. Journal of Economic Perspectives, Vol. 17 No. 1.
Sharpe, W. F. (1964). Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk. The Journal of Finance, Vol. 14 No. 3.
Sharpe, W. F. (1991). The Arithmetic of Active Management. The Financial Analysts Journal. Vol. 47 No. 1.