Professional vs. Non-Professional Investors: A Comparative study into the usage of Investment Tools

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Professional vs. Non-Professional Investors: A Comparative study into the usage of Investment Tools Gil Cohen 1 Investors use varies tools in the investment process. Some use technical or fundamental analysis, or both in that process. The difference between those investments tools have been well documented in the financial literature. However, little have been written about the difference investment behaviour between professional and non-professional investors. The aim of the following survey research is to examine differences between professional portfolio managers to nonprofessional investors in their approach towards technical and fundamental analysis. We used online survey in one of the leading business portals in addition to asking professional investors in a leading investment house in Israel. The results show no significant difference between professional and non-professional investors in terms of how frequently they use fundamental and technical investment tools. Both groups of investors use more frequently fundamental tools than technical when they make buy/sell decisions. Non- professional investors use more fundamental tools such as "analysts' recommendations" when they buy stocks and more technical tools such as "support and resistance lines" when they sell stocks. Moreover, while older investors prefer fundamental tools when they buy and sell stocks, younger investors prefer to use technical tools over fundamentals. This important result might indicate that younger investor less believe in a long time consuming fundamentals analysis than their older colleagues and they rather use a more quick method that does not demand an extensive effort and knowledge. I. Introduction Professional investors manage our money and are suppose to be well informed and well trained investors. Different researches have examined the ability of those investors to outperform the market. Malkiel (2003) for example, found that managed funds are regularly outperformed by broad index funds with equivalent risk. Moreover, he found that those funds that produced excess return in one period are not likely to do so the next. My intention in the following research is to concentrate on the process of investment decisions and not on the result of that process. In that perspective, I want to know whether professional investors use different set of tools when they make investment decisions than non-professional. I also want to know if the extent of use of investment is correlated to years of experience and age for both the professional investors group and the non-professional. Professional investors are expected to use more extensively well known investment tools by relatively to non-professional investors. They are also expected to use more sophisticated tools in the investment process over non-professional investors. I examined two sets of tools: fundamental and technical. The first uses firm's financial information while the later uses the stocks past price movement to predict future performance. II. Literature Review For many years investors used various tools to support their buying and selling stocks decisions. Two sets of tools are commonly used by investors: fundamental and technical analysis. The first uses the firm's economics data such as profits, dividends and growth projection, and the second method is based on the Dow Theory (Murphy (1999)) and uses historic price movements, and mathematical formulas to predict future returns. While fundamental analysis has been extensively researched in the finance literature, not many academics have investigated whether common practice use of technical tools can outperform the "buy and hold strategy". Example for the work that has been done in the field of technical analysis is the work of Kwon and Moon (2007) which tried to predict future price changes using technical indicators. Their prediction was based on regression with neural networks tested with 36 stocks 3. 1 Gil Cohen is the head of the finance and banking track at Carmel academic center: gilc@carmel.ac.il. DOI: 10.5176/2010-4804_2.2.176 7

III. Database and Survey design IV. Results The survey 2 used in this research was consisted of two stages: 2 The First, a group of professional portfolio managers (41 managers) at one of the major Israeli investment houses were asked to fill in a short questionnaire. Second, an online survey via one of the leading financial portals in Israel was addressed to the users of the portal. The portal we used is widely recognized for being regularly visited by market investors, not necessarily professional. 305 users responded to the survey3. All the respondents were asked to indicate their gender, age, and number of years of active experience in the capital market. Table 1 (in Appendix 1) reports the basic descriptive statistics of our sample. The majority of our participants were males (78.05% and 74.10% in the professionals and non-professionals groups, respectively), 30 to 40 years old (53.66% and 55.08%, respectively), and had more than 10 years of experience in stock market investments (39.02% and 40.98%, respectively). The survey questionnaire consisted of 14 questions, 4 questions involve fundamental investment tools and 10 questions technical tools (the questions appear in Appendix 2). In each question, participants were asked to rate appropriateness of a statement on a Likert scale between 1 (strongly disagree) and 5 (strongly agree). 1 The survey was conducted by Gil Cohen, Andrey Kudriavzev and S. Hon -Snir 1 The first stage of the survey took place in January 2011, and the second one in March-April 2011. The "Bizportal" (http://www.bizportal.co.il/) web-site was involved. Table 1 summarizes the differences and the similarities between professional and nonprofessional investors when they make investment decisions. The Table shows in general that investors make more extensive use of fundamental tools than of technical ones when they make buy/sell decisions. This result might imply that both professional and non-professional investors adapt a long run investment point of view rather than a shorter one that is represented better by technical tools. No statistically significant behavior differences have been found between the two groups examined. That is, professionals and nonprofessionals make approximately the same use of the examined investment tools. One may argue, that we examined only the most common fundamental and technical tools available to investors and that professional investors may be using a more advanced set of tools along with the examined traditional tools. The most popular buying and selling tool is a fundamental one analyzing the firm's financial statements for both professional and nonprofessional investors. The second most usable tool which is technical in type is "support and resistance lines", third, again a fundamental tool "analysts' recommendations", forth, "Moving averages" followed by the other technical tools. The described results show that investors, both professional and non-professional, use both fundamental and technical tools as a mix for achieving the best possible decisions. Table 1: Professional versus Non- professional use of known investment tools. Investment Tool Non-professional Professional Analysts' recommendation 3.16 3.13 0.20 Financial Statements 3.59 3.65 0.40 Mean fundamental Support and Resistance lines 3.32 3.07 3.36 3.22 0.37 0.52 Moving Averages 2.72 2.78 0.11 Stochastic Oscillator 1.95 1.93 0.51 8

2.31 2.34 0.08 MACD Oscillator 2.3 2.2 0.2 Mean technical 2.47 2.78 2.49 2.75 0.23 Next, I address the buying versus selling issue for each of the two discussed groups of investors: professional and non-professional. Table 2A summarizes the results for the former group, and Table 2B for the latter. Table 2A shows that non-professional investors use more extensively investment tools when they buy stocks than when they sell stocks. This result agrees with our expectation that because of the "endowment effect", investors are more rational when they buy the stock and more emotional when they sell it. Moreover, they use more fundamental than technical tools when they buy stocks, while the opposite occurs when they sell it. Table 2A: versus use of Investment tools by non-professional investors. Analysts 3.25 recommendation Financial Statements 3.63 Mean fundamental 3.43 Support and Resistance 3.04 lines Moving Averages 2.72 Stochastic Oscillator 1.93 2.32 MACD Oscillator Mean Technical 2.46 2.74 Notes: ** significance<0.05, *** significance<0.10 3.08 3.65 3.32 3.10 2.71 1.98 2.29 2.47 2.71 3.66** 1.45 3.15** 1.6*** 0.40 2.86** 0.55 0.36 0.78 1.75*** With respect to specific tools, non-professional investors make relatively frequent use of analysts' recommendations when they buy a stock and of two technical tools ("stochastic oscillator" and "support and resistance lines") when they sell it. Table 2B: versus use of Investment tools by professional investors. Analysts recommendation Financial Statements Mean fundamental Support and Resistance lines Moving Averages Stochastic Oscillator MACD Oscillator Mean Technical 3.20 3.68 3.43 3.24 2.78 1.95 2.34 2.21 2.51 2.77 3.07 3.63 3.34 3.20 2.78 1.90 2.34 2.19 2.49 2.73 1.09 0.35 1.02 0.62 0.00 0.57 0.00 0.57 0.66 1.17 9

Table 2B demonstrates that professional investors also use investment tools more frequently when they buy stocks than when they sell them. However, this difference and all other differences in employing specific investment tools (fundamental and technical) have not proven statistical significance. Next I want to examine whether years of active experience in the market, age and gender affects investor's behavior. Table 3 summarizes the differences between experienced and nonexperienced investors using 5 years of experience as a splitter of the data. Investment Tool Table 3: The use of investment tools by Experienced and Not experienced investors. More than 5 Less than 5 Years years Analysts' recommendation 3.24 3.23 3.09 3.05 Financial Statements 3.75 3.48 3.66 3.44 Support and Resistance lines 3.15 2.94 3.18 3.00 Moving Averages 2.82 2.63 2.82 2.60 Stochastic Oscillator 1.89 2.00 1.95 2.01 2.35 2.31 MACD Oscillator 2.26 2.32 2.27 2.38 2.76 2.69 Notes: 1. Less and more than 5 years of experience in the market as an active investor. 2. ** significance<0.05, *** significance<0.10 0.08 0.41 2.35** 1.79*** 1.62*** 1.44 1.53 1.70*** 0.93 0.55 0.42 0.09 0.46 0.09 0.45 Table 3 shows that generally more experienced investors use investment tools more extensively than less experienced investors. This is true for both fundamentals and technical tools. However, the difference is a specifically strong for analyzing financial statement which as mentioned above, is considered the most important fundamentals tool. Table 4 concentrates on age difference of investment behavior. No differences have been found between professional and nonprofessional investors in terms of what is described in table 3. 10

Table 4: The use of investment tools by the age of the investor. Tool Investment More than 40 Less than 40 Years of age Years of age Analysts' recommendation 3.38 3.20 1.42 3.21 3.04 1.31 Financial Statements 3.80 3.59 1.63*** 3.84 3.49 2.67** Support and Resistance 3.22 3.02 1.20 lines 3.15 3.09 0.35 Moving Averages 2.66 2.75 0.62 2.57 2.76 1.20 Stochastic Oscillator 1.78 1.98 1.45 1.80 2.02 1.67*** 2.12 2.38 1.69*** 2.07 2.36 1.85*** MACD Oscillator 2.16 2.31 0.97 2.18 0.79 2.71 2.73 0.21 Note. ** significance<0.05, *** significance<0.10 Table 4 demonstrates very interesting phenomena. While older investors prefer fundamental tools when they buy and sell stocks, younger investors prefer to use technical tools over fundamentals. This result agrees with the former observed results concerning the preferences of the experienced investors over the less experienced. This important result might indicate that younger investor less believe in a long time consuming fundamentals analysis than their older colleagues and they rather use a more quick method that does not demand an extensive effort and knowledge. No differences have been found between professional and nonprofessional investors in terms of what is described in table 4. Finally I did not find any gender difference of behavior between man and women. V. Summary and conclusions In the current study I used an online survey published at one of the leading Israeli financial portals and a questionnaire that was distributed among professional portfolio managers. I did not find significant differences between professional and non-professional investors in terms of how frequently they use fundamental and technical investment tools. It might be the case that professional investors use a more sophisticated non conventional set of tools that are not available to non-professional investors. Both groups of investors use fundamental tools more frequently than technical ones when they make buy/sell decisions. This result may indicate a relatively long investment horizon suitable to fundamental analysis relatively to short-run investment preferences in which technical analysis is needed. I found that non-professional investors use more fundamental tools such as analysts' recommendations when they buy stocks and more technical tools such as "support and resistance lines" when they sell stocks. Such difference in buying and selling behavior between has not been found for the professional investors group. This study has also shed light on an important issue which is age differences impact on investing behavior. While older and more experienced investors use more traditional long run fundamental analysis, younger investors prefer less time consuming methods of stock buying or selling. That may result from their finance education and nature. 11

REFERENCES: De Bondt and Thaler, 1990 W.F.M. De Bondt and R.H. Thaler, Do security analysts overreact? American Economic Review, 80 (1990), pp. 52 57. De La Fuente, D., A Garrido, J. Laviada and A. Gomez, 2006, Generic algorithms to optimize the time to make stock market investment, Proceeding of the 8th annual conference of generic and evolutionary computations, ACM Press, NY. Easton, G. Taylor, P. Shroff and T. Sougiannis, 2002, Using forecast of earnings to simultaneously estimate growth and the rate of return on equity investment. Journal of Accounting Research, 40, pp. 657 676. Fernandez-Rodriguez, F., C. Gonzalez-Martel and S. Sosvilla- Rivero, 2001, Optimisation of technical Rules by Genetic Algorithms: Evidence from the Madrid Stock Market, Fundacíon de Estudíos de Economía Aplicada (2001). Frankel, R., S.P. Kothari and J. Weber, 2006, Determinants of the in formativeness of analyst research. Journal of Accounting and Economics, 41 (2006), pp. 29 54. Kahneman, Daniel, Jack Knetsch and Richard H. Thaler, 1990, Experimental Tests of the Endowment Effect and the Coase Theorem, American Economic Review 80(2). : Keane and Runkle, M.P. Keane and D.E. Runkle, 1998, Are financial analysts forecasts of corporate profit rational?. Journal of Political Economy, 106 (1998), pp. 768 805. Kothari, S.P, 2001, Capital markets research in accounting. Journal of Accounting and Economics, 31, pp. 105 231 Kwon Y and B. Moon, 2007, A hybrid neurogenetic approach for stock forecasting. IEEE Transactions on Neural Networks, 18 3 (2007), pp. 851 864. Lin, L., L. Cao, J. Wang and C. Zhang, 2004, The applications of genetic algorithms in stock market data mining optimisation, A. Zanasi, N. Ebecken, C. Brebbia, Editors Data Mining V: Data Mining, Text Mining and their Business Applications (DATA MINING 2004), WIT Press, Southampton, Boston, p. 448. Malkiel, B.G, 2003. The efficient market hypothesis and its critics. Journal of economics perspective. Vol 17,1 59-82. Murphy, J. J. 1999. Technical analysis of the financial markets. New York Institute of Finance.. Skabar A., and I. Cloete, 2002, Neural networks, financial trading and the efficient markets hypothesis, Australian Computer Society, Inc., Darlinghurst, Australia. Subramanian,h., S. Ramamoorthy, P. Stone and B.J. Kuipers, 2006, Designing safe, profitable automated stock trading agents using evolutionary algorithms: Proceedings of the 8th annual conference on Genetic and evolutionary computation, ACM Press, 12

Appendix 1 Sample descriptive statistics Panel A: Portfolio managers (41 respondents) Category Number Percent of total 1. Gender: Men Women 32 9 78.05 21.95 2. Age: 18-30 30-40 40-50 50-60 60+ 9 22 9 1 0 21.95 53.66 21.95 2.44 0.00 3. Capital market investor for: Less than 3 years 3 to 5 years 5 to 10 years More than 10 years 5 10 10 16 12.20 24.39 24.39 39.02 Panel B: Market investors (305 respondents) Category Number Percent of total 1. Gender: Men Women 226 79 74.10 25.90 2. Age: 18-30 30-40 40-50 50-60 60+ 76 168 49 11 1 24.92 55.08 16.07 3.61 0.33 3. Capital market investor for: Less than 3 years 3 to 5 years 5 to 10 years More than 10 years 107 29 44 125 35.08 9.51 14.43 40.98 13

Appendix 2 Questionnaire 1. I use Analysts recommendations when I buy stocks. 2. I use Analysts recommendations when I sell stocks. 3. I use financial statements when I buy stocks. 4. I use financial statements when I sell stocks. 5. I use support and resistance lines when I buy stocks. 6. I use support and resistance lines when I sell stocks. 7. I use moving averages when I buy stocks. 8. I use moving averages when I sell stocks. 9. I use the stochastic oscillator when I buy stocks. 10. I use the stochastic oscillator when I sell stocks. 11. I use the RSI oscillator when I buy stocks. 12. I use the RSI oscillator when I sell stocks. 13. I use the MACD oscillator when I buy stocks. 14. I use the MACD oscillator when I sell stocks. 14