Active Portfolio Management Vs Index Tracking - A Study of Actively Managed Investment Funds' Performance in the UK

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1 Active Portfolio Management Vs Index Tracking - A Study of Actively Managed Investment Funds' Performance in the UK Bijan Hesni (Senior Lecturer, Harrow Business School, University of Westminster, London, UK) hesnib@wmin.ac.uk Dr. Mohsen Jahangirian (Assistant Professor, Graduate School of Management & Economics, Sharif University of Technology, Tehran, Iran) mohsen@sharif.edu Shaidaa Jafarbaglou (Graduate, Harrow Business School, University of Westminster, London, UK) SHAIDAAJ@aol.com Abstract Few topics have generated more engaging discussions between investment professionals than the debate over active versus passive portfolio management. The case for active portfolio management which can involve either the selection of individual securities or tactical adjustments to the asset classes in an investor s long-term strategic allocation is typically rooted in the belief that it is possible to produce superior investment performance than could otherwise be obtained by simply matching market-wide trends. Conversely, the case for passive investing which is buying and holding well diversified collections of securities with the desired risk exposure rests on the notion that active managers have not proven themselves capable of consistently outperforming the relevant benchmarks over time, particularly when transaction costs and management fees are taken into account. The increasing popularity of this view is evidenced by the rapid development of the market for index tracking investment products. Active portfolio management can basically be considered under Technical analysis and Fundamental analysis. Technical analysis provides a framework for studying investor behaviour, and generally focuses only on price and volume data. Typically, traders using this type of approach concern themselves chiefly with timing and are generally unaware of a company s financial health. Traders using this approach have short-term investment horizons. Fundamental analysis on the other hand involves a detailed study of macroeconomic and microeconomic factors including a company s key financial ratios and is often used to identify stocks which are likely to outperform the stock market over a period of time. Typically, traders using this approach have medium to long-term investment horizons. To determine whether active portfolio management can consistently yield higher returns than the appropriate benchmarks, performance data over periods of one, three and five years was collected for a large number of actively managed in London. Weighted average of each group of investment was calculated for each of the three time periods and compared against the performance of the appropriate Index over the same period. Statistical tests were then carried out on these values with a 99% confidence level to allow statistical conclusions to be drawn from these comparative analyses. It was found that statistically there is insufficient evidence to support the premise that actively managed can consistently outperform the appropriate indices as only in less than half of the scenarios studied, the appropriate Index was outperformed by managed. This is in line with the existing body of research some of which suggest actively managed can produce higher returns than the Index tracking while some point to the contrary. Key words: Stock Market, Investment, Active Fund Management, Index Tracking 1

2 1. Introduction In recent years, an increasing interest is being shown in the efficient market hypothesis (EMH). F. Fama one of the most influential advocates of the hypothesis defines an efficient market as one in which prices always fully reflect available information and competition will cause the full effects of new information on intrinsic values to be reflected instantaneously in actual prices. The EMH is associated with the idea of a 'random walk' where all subsequent stock price changes represent random departures from previous prices (Granger and Morgenstren 1963). The logic of the random walk idea is that if the flow of information is unhindered and information is immediately reflected in stock prices, then tomorrow s price changes will reflect only tomorrow s news and will be independent of the price changes today. However, news is by definition unpredictable and thus resulting price changes must be unpredictable and random (Murray, R., Block, F., Cottle, S., 1988). The random walk theory was further supported by Chappel, D. & Al- Loughani, N. (1997) who also concluded that past price information is useless in predicting future value. The debate about efficient markets has resulted in numerous empirical studies attempting to determine whether specific markets are in fact efficient and if so to what degree. The work of many researchers suggests that stock prices can be predicted with a fair degree of reliability (Dobbins, Witt, & Fielding 1994) and (Lee et al 1998). Two competing explanations are offered for such behaviour. Proponents of EMH such as Fama and French (1995) maintain that predictability of stock prices results from time varying equilibrium expected returns generated by rational pricing in an efficient market that compensates the level of risk undertaken. On the contrary critics of EMH such as La Porta, Lakonishok, Shliefer, and Vishny (1997) argue that the predictability of stock returns reflects the psychological factor, social movement, noise trading and fashions or fads of irrational investors in a speculative market (Russell, B. Torbey, M). 2. Active Portfolio Management Vs Passive Portfolio Management There are several studies including (Chen, Jegadeesh, and Wermers 2000) and (Baker, Litov, Wachter, and Wurgler 2004) which conclude that fund managers possess significant stock-picking skills that translate into higher abnormal returns. Brown and Goetzmann (1995) document that both superior and inferior fund performances tend to persist over consecutive one-year investment horizons. However, there is a significantly larger body of research which points to the contrary. Using newly developed statistical methods for calculating expected returns (e.g., reward-to-variability ratio, CAPM), both Sharpe(1966) and Jensen (1968) find little evidence to support the notion that, on average, managers could maintain superior investment performance in successive holding periods. They concluded that the capital markets were highly efficient and that good managers should concentrate on evaluating risk and providing diversification, spending little effort (and money) on the search for incorrectly priced securities (Sharpe, p. 138). However, Carlson (1970) notes that the benchmark used in estimating expected returns can make a difference. He showed that most of the in his sample outperformed the Dow Jones Industrial Average but failed to match the Standard & Poor s 500 and NYSE Composite indexes. 2

3 2.1 Technical analysis Technical analysis is essentially the making and interpretation of stock charts (Malkiel, B.2003). This is in direct contrast with weak form EMH as the basic assumption of chartists is that history tends to repeat itself. Chartists technique attempts to use knowledge of the past behaviour of a price series to predict the probable future behaviour of the series (Fama, E 1995). Critics of technical analysis point at such studies as Malkiel s (A random walk down wall street) and say that the whole attempt made by chartists is a waste of time and that there is no cause and effect relationship between a stock's past price performance and its future performance (Investor Guide). In addition Fama argues that the techniques of chartists have always been surrounded by a certain degree of mysticism (Fama, E, 1995). There are three essential assumptions on which technical analysis is based. Their acceptance is essential for the validity of technical analysis as a method for stock price forecasting. According to Murphy (1999) these are: Market action discounts everything; Prices move in trends; history repeats itself. i) Market action discounts everything This has been referred to as the foundation of technical analysis (Murphy, 1999). It claims that all the factors that affect prices, whether they are economic rationale factors or other derived from human psychology, are fully reflected in the market price. Consequently, it follows from this statement that studying market action is all that is required. ii) Prices move in trends This concept is also essential for the technical approach. The existence of trends allows technical analysis to predict the direction in which prices are likely to move. If the premise that trends exist in prices is rejected, technical analysis is useless, as prices would fluctuate randomly and therefore, successful prediction would be impossible. According to Murphy (1999), The whole purpose of charting the price action of a market is to identify trends in early stages of their development for the purpose of trading in the direction of those trends. An important consequence to this assumption is that trends tend to persist in the time until a relevant fact causes their reversal (Murphy, 1999). This is an adaptation of the physical law of movement, which states that an object in motion tends to continue in motion until some external force causes it to change direction. iii) History repeats itself This final premise assumes that future is a repetition of the past and therefore, there are numerous chart patterns that have been identified over the past century that are constantly repeated in the prices charts. This assumption rests on the idea that the charts are based on the bullish or bearish psychology of investors and that this human psychology does not change over the time (Murphy, 1999). 2.2 Fundamental Analysis Fundamental analysis of stock, on the other hand, determines the fundamental value of stock by analysing available information with a special emphasis on accounting information (Abad, C. Thore, S, & Laffarga, J). It focuses upon attempting to find those companies with sustainable growth in sales and earnings, highly defensible competitive advantages, fast growing markets, and superior, valuemaximizing management, company s gearing, margin improvement, cash generation, balance sheet 3

4 strength, and overall quality of earnings and assets. Its position in its markets, its reputation, the quality and acceptance of its products or services, the growth and risks of the market and the nature of the company's competition are all important fundamental factors (Insight Capital Research and Management). This information may be gathered by meeting or interviewing company management, analyzing company reports, contacting customers, suppliers, or industry analysts. As recognized by Graham and Dodd (1962) fundamental analysis is a long-term oriented exercise where the management plays an essential role: Over the long term, forecasting increasingly depends on a correct appraisal of competence and integrity of management. The company s record demonstrates what ongoing management has accomplished and is the primary source of judgment about the quality of management (Graham, B. Dodd, DL 1962). Well-managed companies are more likely to keep generating a steady stream of revenues in the future as well. Hence there is a link between the past and current record of a company and its future earning prospect (Abad, C. Thore, S, & Laffarga, J). In order to assess the extent to which stock prices reflect information about future earnings contained in the current financial statement data, a test developed by Mishkin (1983) was later applied by a series of researchers (such as Sloan (1996), Collins and Hribar (2000), Thomas (2000) and Xie (2001)). Results from these studies seem to indicate that stock prices do not fully reflect information about future earnings contained in the financial information. (Abad, C. Thore, S, & Laffarga, J) As claimed by several researchers (such as Ou and Penman (1989), Stober (1992), Holtasen & lacker (1992) and Xie (2001)) market prices do not instantly incorporate all the relevant information contained in the financial statements, and that abnormal returns can be generated (Abad, C. Thore, S, & Laffarga, J). The proponents of the EMH often charge that fundamental analysis is worthless, as a stock s price will always already take into account the company s financial data. (Investor Guide) furthermore critics argue that fundamental analysis is too unscientific a process. Most investment professionals however believe that fundamental analysis is useful either alone or combined with other techniques (Investor Guide). Aby (2001) focused on combining fundamental variables to screen stocks for value by developing four portfolios based on four fundamental conditions namely single digit P/E, Market price < Book value, established track records on return on equity (ROE > 12%), and dividends of less than 25% of earnings. The conclusion was that when the four criteria are used to screen stocks, quality investment seemed to perform well. Lakonishok et al found that a wide range of value strategies, based on sales growth, book-to-market, cash flow, earnings, have produced higher returns and refute Fama and French s claims that these value strategies are fundamentally riskier. Using data from end April to end April 1990, for NYSE Lakonishok et al found evidence that the market appears to have consistently overestimated future growth rate for glamour stocks relative to value stocks, and that the reward for fundamental risk does not explain the 10% -11% does not explain the higher average returns on value stocks. Fama and French (1995) responded to the above by focusing on size and book-to- value, and form portfolios of stocks partitioned by these variables, from NYSE, AMEX and NASDAQ from 1963 to Their results demonstrated that both size and book-to- market equity, are related to profitability, but find no evidence that returns respond to the book-to-market factor in earnings. They conclude that 4

5 size and book-to- market equity are proxies for sensitivity to risk factors in returns. Their results also suggest that there is a size factor in fundamentals that might lead to a size related factor in returns. Abarbanell and Bushee (1998) examined whether the application of fundamental analysis can yield significant abnormal returns. They reported that signals reflect traditional rules of fundamental analysis, such as change in inventories, accounts receivable and capital expenditure, and these can be used to form portfolios that earn abnormal returns (Becker, Y., Ochman, R., 2003). Piotroski (2000) investigated whether fundamental analysis can be used to provide abnormal returns, and right shift the returns spectrum earned by a value investor. In anomaly terms, Piotroski focused on high book-to-market securities, and showed that the mean return earned by a high book-to-market investor can be shifted to the right by at least 7.5% annually, and a simple investment strategy based on high book-to-market securities generates a 23% annual return between 1976 and The research is stimulated by the observation that portfolios of high book-to-market firms normally contain several strong performing firms (achieving strong returns), and many deteriorating ones (achieving poor returns). Piotroski defines three different classes of financial performance signals, namely profitability, gearing liquidity and source of, and operating efficiency. From these three classes of signals, he then defined nine simple signals, and used an aggregate score of the nine signals is to rank the constituents. The nine signals involved seven fundamental variables, namely net income before extraordinary items, cash flow from operations, leverage, liquidity, whether external financing has been raised recently, current gross margin scaled by total sales, and current year asset turnover ratio. Within the portfolios constructed from the higher aggregates, Piotroski noted that the returns are concentrated in small and medium sized companies, companies with low share turnover, and firms with low analyst following. (It was also noted that superior performance is not dependant on initial low share prices). 2.3 Index Tracking A debate has played out recently in the journal of portfolio management between the advocates of index tracking, such as Vanguard s John Bogle, and the Wall Street journal s Jonathan Clements and Princeton s Burton Malkiel who believes investors are better off purchasing an index fund rather than managed and those who argue that managed can give a better return than index such as Wachovia s Dylan Minor (Rienker, K and Tower, E 2004). Malkiel looked at return of managed from 1971 thorough to1991 and compared them to two benchmarks, the Wilshire 5000 index and the S&P 500 index, his conclusions were most investors are considerably better off by purchasing a low expense index fund than by trying to select an active fund manager who appears to posses a hot hand (Malkiel, B, 1995). 2.4 Stock Market Anomalies Researchers have uncovered numerous stock market anomalies that seem to contradict the efficient market hypothesis. These anomalies are effectively systems or patterns that can be used to outperform passive and/or buy-and-hold strategies (Investor Home). The main anomalies that have been recorded in the literature include: 5

6 a) Size effect: Banz (1981) showed that firms that were small as provided by market capitalization had provided with much larger returns than large firms. Banz s sample includes all common stocks which had been traded on the New York Stock Exchange (NYSE) for at least five years between 1926 and He calculated average excess returns from holding very small firms long and very large firms short over the period of was 19.8 on an annualized basis, a rate well above the average return for the market. This strategy, which suggests large profits, leaves the investor with a poorly diversified portfolio. Banz found out the size effect was most pronounced for the smallest firms in his sample and also that it was not uniform throughout the period. He offered no conclusion as to why smaller firms should have given much larger returns than larger firms Banz (1981). Other researchers such as Reinganum (1981, 1982) and Blume & Stambaugh (1983) have also confirmed the size effect. They have confirmed the following explanations for the size effect: Market liquidity - the really large gains from the size effect seem to apply to shares of the smallest companies. Information - small firms do not represent information as frequently or as high quality as large firms. Misstatement of beta - in a study covering the period of April 1961 to March 1985, Levis (1989) found a size effect on the London Stock Exchange (LSE). Levis reported that the size effect was related closely to the dividend yield effect and a PE effect (Levis, M., 1989). b) Price earnings ratio: Basu (1977) carried out the first academic study which allowed for risk and avoided any survivorship bias. From his sample of over 1400 firms which trade in NYSE between September 1986 and August 1971, he found out companies with lower PE ratios tend to produce higher returns than predicted. c) Price to Book value Roenberg, Reid and Lanstein (1985) examine a sample of 1400 companies over the period of and found that excess returns could be earned by investing in companies which had a low share price to book vale ratio. 3. Methodology 3.1 Research Approach & Philosophy This research is primarily based on quantitative data and is analytical and explanatory. A deductive approach has been undertaken. This research follows the positivist research philosophy, as there will be an emphasis on a highly structured methodology to facilitate replication and on quantifiable observations that lend themselves to statistical analysis (Gill and Johnson 1997, cited by Saunders et al 2003, p 83). There is also a phenomenological element to it as quantitative data, in form of related literature is being used to support the quantitative findings. According to Saunders, Phillip and Thornhill (2003) a deductive approach has two important implications. Firstly concepts need to be structured and operationalized in such a way that will allow facts to be measured quantitatively. This facilitates replication, which is an important issue to ensure reliability. Secondly it allows the researcher to select samples of sufficient size in order to generalize the results. 6

7 3.2 Appropriate Benchmark As indicated by Sharpe, Alexander and Bailey (1999) it is essential when measuring the performance of different trading strategies to compare them with an appropriate benchmark. The reason for this is that in order to determine how successful an actively managed fund has been, it has to be compared to an appropriate benchmark which in this study are the FTSE 100, FTSE All share and Small Cap Indices. 3.3 Statistical Tests To determine the significance and degree of reliability of our research findings, it was necessary to carry out some statistical tests. In doing so, the following factors were considered: I. The fund manager s performance was set to be a random variable. II. Samples were drawn from all the investment currently available in the London Stock Exchange. III. Funds were grouped according to their underlying investment criteria. IV. Taking into account the varying size of each investment fund within a group, their weighted average return was compared against the return from the appropriate market index (e.g. FTSE100, FTSE Small-cap, FTSE All-share, etc) over a specific period. V. Performances were statistically tested over a one-year, a three-year and a five-year period. VI. Although the population variances are unknown, large sample data (with a size of 81 or more) allows us to apply the normal distribution in the statistical analysis VII. For each period, the mean performance of n is compared against a single performance figure associated with the market index concerned. This means there is only one random variable involved in the test analysis. Therefore, H 0 & H 1 were defined as follows: a. H 0 : U fund IP (Index Performance) b. H 1 : U fund > IP VIII. It should be pointed out that active portfolio management inherently carries a higher management charge than managing an index tracking fund. Consequently, these lower charges act as an incentive for investors to prefer the latter type of unless there is compelling evidence in the form of superior performance by actively managed. IX. There are three populations (groups of ) from which samples were drawn for analysis. These are: a. Funds which can invest in all shares listed in the London Stock Exchange b. Funds which can invest in top 100 shares listed in the London Stock Exchange c. Funds which can invest in all small company shares listed in the London Stock Exchange Therefore, there are nine comparative situations in total made up of three sample groups over three distinct time periods of one, three and five years. 7

8 4. Statistical Results and Analysis a) All Companies Investment Funds Based on our sample data, the following results were obtained: Performance comparison table over 1-year, 3-year & 5 year period 1 Year 3 Year 5 Year Performance of the FT All-Share Index 21.70% 32.00% (1.60%) Average performance of all 16.25% 23.20% 1.03% Average performance of best % 59.06% 77.19% Average performance of worst % (6.10%) (26.24%) Sample size (n) Standard Deviation 4.32% 13.13% 23.12% Over the five-year period, out of 198, 130 (nearly 2/3 of all managed) produced negative return. The following charts depict the performance of against the Index over the three time periods: Performance Comparison over 1 Year 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% all Best 10 Worst 10 FTSE All Share Index Performance Comparison over 3 Years 80.00% 60.00% 40.00% 20.00% 0.00% % all Best 10 Worst 10 FTSE All Share Index 8

9 Performance Comparison over 5 Years % 80.00% 60.00% 40.00% 20.00% 0.00% % % all Best 10 Worst 10 FTSE All Share Index The test measure (U) is calculated for each of the three periods and they are checked against the confidence intervals, assuming a 99% significance level. The following table shows the results. 1 year 3 years 5 years U Confidence Interval [-, 2.33] [-, 2.33] [-, 2.33] H 0 : U fund IP Accepted Accepted Accepted As the above table shows, the FT All-Share Index statistically outperformed the average performance of the All Companies Investment Funds over the periods of one, three and five years with a significance level of 99%. In other words, the performance of FT All-Share Index has been superior to the average performance of the All-Companies Investment Funds in long, medium as well as the short terms. This could imply that investors interested in investing in which invest in all shares listed in the London Stock Exchange would be statistically better off with the FT All-Share Index. b) UK Top 100 Equities Investment Funds Based on our sample data, the following results were obtained: Performance comparison table over 1-year, 3-year & 5 year period 1 Year 3 Year 5 Year Performance of the FT 100 Index 21.70% 28.70% (5.60%) Average performance of all 18.82% 30.68% 34.98% Average performance of best % 61.26% 67.25% Average performance of worst % 13.93% (2.34%) Sample size (n) Standard Deviation 4.16% 10.92% 20.89% Over the five-year period, out of 94, only 10 produced negative return which is quite impressive given that the FTSE100 Index fell by 5.6% over the same period. In fact as the above table shows, even the worst performing on average performed better than the Index over the five year period! One possible reason for this superior performance could be that following the market crash of late 1990s and the year 2000, any investment fund switching from defensive stocks such as the utilities into oil and technology stocks benefited disproportionately from the recovery in these sectors in relation to the Index. The following charts depict the performance of against the Index over the three time periods. 9

10 Performance Comparison over 1 Year all Av for best 10 Av for worst 10 FTSE 100 Index Performance Comparison over 3 Years Average Av for best 10 Av for worst 10 FTSE 100 Index Performance Comparison over 5 Years Average Av for best 10 Av for worst 10 FTSE 100 Index The following table shows the results of statistical tests: 1 year 3 years 5 years U Confidence Interval [-, 2.33] [-, 2.33] [-, 2.33] H 0 : U fund IP Accepted Accepted Rejected As the above table shows, the FT100 Index statistically outperformed the average performance of the UK Top 100 Equities Investment only over the periods of one and three years, with a significance level of 99%. In other words, the performance of FT100 Index has been superior to the average performance of the UK Top 100 Equities Investment only in the short and medium terms. One possible reason for this could be that the London market in line with the rest of the world experienced a significant recovery from the crash of late 1990s over the past three years. 10

11 d) UK Smaller Companies (Small-Cap) Investment Funds Based on our sample data, the following results were obtained: Performance comparison table over 1-year, 3-year & 5 year period 1 Year 3 Year 5 Year Performance of the FT Small-cap Index 16.90% 41.10% (1.30%) Average performance of all 20.48% 47.14% 20.19% Average performance of best % 71.67% % Average performance of worst % 19.59% (30.44%) Sample size (n) Standard Deviation 6.40% 17.08% 36.08% Over the five-year period, out of 81, 30 produced negative returns which is not a bad performance given that the FTSE Small-cap Index fell by 1.3% over the same period. In fact as the above table shows, the actively managed outperformed the Index over all three periods. However, while the top ten performing significantly beat the Index, the bottom ten performing produce considerably lower returns than the Index in each period. This makes investing in this type of managed somewhat of a lottery despite the average return from all in this category being higher than the return from the Index. The following charts depict the performance of against the Index over the three time periods. Performance Comparison over 1 Year 40.00% 30.00% 20.00% 10.00% 0.00% all best 10 worst 10 FT Small-cap Index Performance Comparison over 3 Years 80.00% 60.00% 40.00% 20.00% 0.00% all best 10 worst 10 FT Small-cap Index 11

12 Performance Comparison over 5 Years % % 50.00% 0.00% % all best 10 worst 10 FT Small-cap Index The following table shows the results of statistical tests: 1 year 3 years 5 years U Confidence Interval [-, 2.33] [-, 2.33] [-, 2.33] H 0 : U fund IP Rejected Rejected Rejected As the above table shows, the FT Small-Cap Index statistically underperformed the average performance of the UK Small-Cap Investment over all three periods with a significance level of 99%. This implies that investors interested in which invest in shares of small companies are on average statistically better off with actively managed than investing in Index tracking. 5. Conclusions & Further Research Our conclusions are not too dissimilar to those found by previous researcher referred to in the literature review section of this paper. We have found that in 4 out of nine sets of comparative analysis, statistically with a 99% confidence level the appropriate index was outperformed by the actively managed while in 5 remaining scenarios, we cannot statistically conclude that managed outperform the indices. This neither rejects nor accepts the premise that investors are better off investing in actively managed. With the right investment manager at the helm, it is possible to earn much higher returns than the return achievable from an index tracking fund. It s also worth pointing out that over 5 year period, the Index market produced only 1 superior result out of 3. Whereas, its performance was higher than the actively managed for 2 out of 3 results associated with the one-year period. This would suggest that the Index market might have statistically been paying off better than the fund managers are doing, rather over shorter periods. Another important concluding remark is that the FT Index performs better in All-Companies market rather than specific market segments, such as the top 100 largest companies, and the small companies. In other words, the fund managers could handle specific, small market segments with a higher performance than that of the Indexes. This indicates the need for further research into the characteristics and attributes of successful fund managers. Additionally, since our research was limited to three broad types of managed in the UK, 12

13 there is a need to extend this study to cover a wider range of managed investment in the UK and in other well developed financial markets around the world. 13

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