- Email: [email protected]
Behavioral finance in Asia
Available online at www.sciencedirect.com
Pacific-Basin Finance Journal 16 (2008) 1 – 7 www.elsevier.com/locate/pacfin
Editorial
Behavioral finance in Asia Kenneth A. Kim a,⁎,1 , John R. Nofsinger b,2 a
School of Management, State University of New York at Buffalo, Buffalo, NY 14260, USA b College of Business, Washington State University, Pullman, WA 99164, USA Available online 25 April 2007
Abstract This paper introduces the Pacific-Basin Finance Journal's special issue on behavioral finance in Asia. We first briefly discuss behavioral finance in general, and then we explain why behavioral finance in Asia is an important topic worth studying. We describe the papers published in this special issue, and in doing so, we place the papers within the appropriate context of the growing literature on behavioral finance. We close by acknowledging the referees of this special issue and by offering brief concluding thoughts. © 2007 Elsevier B.V. All rights reserved. JEL classification: G11; G15; G30 Keywords: Asia; Behavioral finance; Corporate finance; Investing
1. Introduction Why might the topic of behavioral finance in Asia be important and interesting? First, the study of behavioral finance is still a young field. The academic finance community has only recently accepted it as a feasible paradigm to explain how financial market participants make decisions and, in turn, how these decisions affect financial markets. Second, Asian financial markets are among the largest in the world, and there is some evidence – anecdotal, theoretical, and empirical – that Asians suffer from cognitive biases on a different level than people of other cultures. By studying behavioral finance in Asia, we can, therefore, add to our understanding of these two important topics. ⁎ Corresponding author. Tel.: +1 716 645 3293. E-mail addresses: [email protected] (K.A. Kim), [email protected] (J.R. Nofsinger). 1 Kim and Nofsinger served as co-editors of the Pacific-Basin Finance Journal's special issue on behavioral finance in Asia. Correspondences can be addressed to either author. Author acknowledgements are contained within the paper's text. The usual disclaimer applies. 2 Tel.: +1 509 335 7200. 0927-538X/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.pacfin.2007.04.001
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K.A. Kim, J.R. Nofsinger / Pacific-Basin Finance Journal 16 (2008) 1–7
The study of behavioral finance allows cognitive psychology to play a potentially important role in finance. People are not always rational, and, thus, their financial decision making may be wholly or partially driven by behavioral biases. If people have beliefs or preferences that do not meet the traditional axioms of rational decision makers, then it is important that we identify the effects of these behavioral biases—especially if their cognitive errors impact prices and cannot be easily arbitraged away. Many finance scholars view the mid-1980s as the beginning of this area of research. DeBondt and Thaler (1985) showed that stock markets overreact to information, and Shefrin and Statman (1985) contended that investors are more likely to sell their winner stocks rather than their losers, even though selling losers (to realize tax losses) is optimal. If one believes these works to be the genesis of behavioral finance research, then the field is barely over two decades old. The pervasiveness of behavioral finance research is even younger. The behavioral finance paradigm was not widely accepted at first. In fact, DeBondt and Thaler's (1985) paper was met with considerable skepticism (Thaler, 1999). More recently, many good theoretical models have explored the ramifications of less-than-rational agents. Initially, studies focused on asset pricing, but in recent years, models have incorporated the effect that less-than-rational managers may have on corporate finance decision making. Barberis and Thaler (2003) provide an excellent literature review of the many different types of behavioral biases that financial decision makers might hold and how these biases might affect decision making and, in turn, the financial markets. Empirical papers on behavioral finance also had a slow start—primarily because arguments based on stock-level data suffer from the joint-test problem (market efficiency and asset pricing model) and were, thus, less convincing to an initially skeptical audience. Terrence Odean overcame this limitation by obtaining individual brokerage account data. In a series of papers (many with Brad Barber), he showed that individual investors suffered from several behavioral biases. Many other researchers and data sets have since empirically tested behavioral finance theories. Hirshleifer (2001) provides an excellent literature review of the empirical evidence in behavioral finance with regard to asset pricing. Somewhat surprisingly, however, few researchers have yet to use experiments to test behavioral finance theories, even though well-designed experiments allow researchers to control the environment. Asia is an interesting place to study behavioral finance because of the different levels of capitalism and financial market experience of its participants. Countries such as China have been slowly changing over the last couple of decades to a capitalistic economy from a socialistic one. On the other hand, countries such as Japan have had large economic and financial markets for a much longer time. Thus, because variations in knowledge and experience likely play a role in explaining variations in economic decision making, Asia is fertile ground for the study of behavioral finance. Also, there is a reason to believe that Asians in general suffer from cognitive biases more than do people of Western cultures. Anecdotally, individual investors in Asia are often viewed as mere gamblers. Theoretically, social scientists and psychologists have contended that culture can nurture tendencies toward behavioral biases at varying levels (e.g., Yates et al., 1989). According to Hofstede (1980), differences among cultures can be expressed on an individualism– collectivism continuum. Asian cultures tend to be based on a socially collective paradigm. It has been argued that collective-oriented societies can cause individuals to be overconfident, which is a behavioral bias. Because behavioral inclinations can be learned (Wolosin et al., 1973), cultural differences in life experiences and education may cause differences in behavior. Life experiences and education are certainly different among different cultures. To this end, some evidence exists that suggests that people raised in Asian cultures exhibit more behavioral biases than people from the United States (e.g., Yates et al., 1997).
K.A. Kim, J.R. Nofsinger / Pacific-Basin Finance Journal 16 (2008) 1–7
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Although the psychology literature suggests that people of Asian cultures may suffer more from behavioral biases than people of Western cultures, the literature is still sparse. Weber and Hsee (2000) noted: “The bottom line is that the topic of culture and decision making has not received a lot of attention from either decision researchers or cross-cultural psychologists” (p. 34). Chen et al. (in press) provide a useful literature review from the psychology and finance literatures on the behavior of Asian people and how these behaviors might affect their investment decision making. In support of the notion that Asians suffer from behavioral biases more than people from Western cultures, they find that individual investors in China suffer more from both an overconfidence bias and the disposition effect than U.S. individual investors. Overall, behavioral finance may still be characterized as a controversial topic, but it is much less so than it once was. We now have a better understanding of how humans behave, and many researchers now accept that these behavioral inclinations can affect financial decision making. And, it is now widely accepted that there are limits to arbitrage (Shleifer and Vishny, 1997), so these behaviors may impact prices. While recent research on behavioral finance has significantly advanced our understanding of financial markets, the future looks even more promising. At finance conferences, sessions on behavioral finance are very well attended, and the audience members are often the younger scholars of the academic profession. Thaler (1999) had a wish list for the future of behavioral finance research: he wanted to see theory papers bring institutions into their models; he wanted to see more behavioral finance research on corporate finance; and he wished for more data on individual investors, particularly for online investors. We add one more: we wish for more behavioral finance research on Asian financial markets. This special issue grants most of these wishes. 2. Overview of the special issue The special issue contains eight papers. Five papers study the behavior or performance of investor decision making. The first paper by Frino et al. (2008-this issue) studies futures traders in the Sydney Futures Exchange. Might those traders who make big profits in the morning be risk seeking in the afternoon? If so, then this finding is consistent with what is known as the house– money effect. We are more likely to take risks if we feel like we are betting with our winnings rather than with our initial capital. This effect is known among gamblers, but few papers have confirmed the effect using investors. Frino et al. take extreme care with their empirical approach and confirm the existence of the house–money effect. They also find that morning winners who seek excessive risks in the afternoon end up being the biggest afternoon losers. Oh et al. (2008-this issue) compare the performance of investors in Korea who trade stocks online and those who do not. Despite the extensive availability of online investing, very little research has been conducted on this topic (one notable exception is Barber and Odean, 2002). Oh et al. identify investor types (domestic institutional investors, foreign investors, and individual investors) and their method of trade (online vs. non-online). The best and worse performers were foreign investors and individual investors, respectively, regardless of whether they were trading online. However, individuals who traded online appear to be the worse performers. Oh et al. suggest that the trading venue must be considered when comparing the relative performance of different investor types. In general, their findings are consistent with the hypothesized expectations of online trading performance. Specifically, individual investors' easy access to trading exacerbates the influence of emotions and impulsive desires, often to their detriment. Feng and Seasholes (2008-this issue) contrast male and female investors in China. Whether gender makes a difference in investing performance is, of course, a controversial issue. Using data
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on U.S. investors, Barber and Odean (2001) show that women are better investors than men. In contrast, Feng and Seasholes find that men and women in China are similar in both their inclination toward behavioral biases and their investing performance. Feng and Seasholes hint at an interesting question: If – all else being equal – we should expect men and women to be similar in their investing behaviors and performances, why do men and women investors behave and perform differently in the United States? Tan et al. (2008-this issue) study investor herding in the Chinese stock markets. Herding exists when investors' trading decisions are positively correlated to each other. In China, there exist Ashares that are mostly owned by domestic individual investors and B-shares that are mostly owned by foreign institutional investors. Many prior researchers have taken advantage of this dual-class of Chinese shares to conduct insightful studies on the effects that ownership structure might have on stock prices and their return behavior. Tan et al.'s paper examines whether herding is different between these two share types and find that, despite the ownership differences, herding exists in both share classes. However, they find that herding is higher for A-shares during periods of rising markets, high trading volume, and high market volatility; conversely, B-shares experience no herding asymmetry effects. Whether these contrasting findings are due to ownership structure differences is an open-ended question—perhaps one that will be addressed by future research. In the final investor-oriented paper that studies investment decision making, da Silva Rosa and Durand (2008-this issue) take advantage of an investing contest sponsored in Australia. Students, who paid $10 for every portfolio they entered into the contest, were given a fictitious $200,000 and could not invest more than $40,000 in any single stock. The contest's goal was simply to maximize the wealth of the entry portfolio after a 1-year holding period. The authors hypothesize that, even though most entrants were students majoring in business, the availability heuristic would drive portfolio formation decisions. Specifically, they suggest that the more news stories that appeared in the national press about a company during the month prior to when the entries were due, the more likely that company's stock would be included in entrants' portfolios. The results support their hypothesis. In fact, they find that the availability heuristic did a better job at explaining portfolio formation decisions than did firm size. Brown and Mitchell (2008-this issue) consider a behavioral explanation for stock price clustering on the Chinese stock markets. In China, 8 is widely considered a lucky number whereas 4 is considered unlucky. The authors find that Chinese stock prices ended with 8 twice as often as they ended with 4, and this preference was most prevalent for Chinese A-shares, which are primarily owned by domestic Chinese investors. For Chinese B-shares, which are primarily owned by foreigners, the tendency for stocks to end in 8 was much lower than it was for A-shares. Although most behavioral finance studies have focused on investment decision making, the behavioral finance literature on corporate finance decision making is growing quickly. Excellent theory papers have been published recently, but empirical studies still remain scant. The hurdle is identifying acceptable proxies of managerial behavior. Two papers in this special issue tackle the issue of incorporating behavioral biases in corporate finance decision making. First, Lin et al. (2008a-this issue) study hubris in the mergers and acquisitions market in Japan. Roll (1986) proposed hubris as an explanation for why so many nonvalue-enhancing mergers are conducted; namely, bidding managers are overconfident and optimistic in their valuation of an acquisition. Although some anecdotal evidence suggests that hubris does not play a role in Japanese takeovers, Lin et al. find results to the contrary. Using the bidding firm's past performance as a proxy measure for hubris, they find that those firms with the potential for high hubris (i.e., high past performers) experience low returns around bid dates. These results, which are consistent with a hubris explanation for mergers and acquisitions, contradict the finding of Kang et al. (2000),
K.A. Kim, J.R. Nofsinger / Pacific-Basin Finance Journal 16 (2008) 1–7
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who reported that the past performance of Japanese bidders is positively correlated to their returns around bid dates. However, the sample in the Kang et al. paper is mostly from Japan's pre-bubble period while the Lin et al. study sample is mostly from the period after the bubble burst. In the second paper on behavioral biases in corporate finance decision making, Lin et al. (2008b-this issue) use Taiwanese data to study pecking order and managerial optimism. Although the contention that firms follow a pecking order for financing deficits or capital expenditures is not highly disputed, the underlying explanation for why firms follow this pecking order is a matter of debate. Prior research has suggested managerial optimism as an explanation: optimistic managers may believe their firms are undervalued, and, as such, they prefer to access debt capital instead of equity capital. Lin et al. find evidence consistent with this hypothesis. Namely, using managements' earnings forecast as a proxy measure of managerial optimism, they find that firms with optimistic managers are more likely to finance deficits with debt rather than equity. Hopefully, we will see more research on behavioral corporate finance in the future. 3. Conclusion The behavioral finance paradigm for explaining how agents behave and how their behavior might affect financial markets looks like it is here to stay. Although conducting research on behavioral finance poses many challenges and hurdles, the authors in this special issue have (to a high degree) successfully addressed those challenges. We suspect that even more of those challenges and hurdles will be overcome in future research. Our overall goal with this special issue was to help bring behavioral finance theories to Asian financial markets. The Asian financial markets represent a fruitful testing ground for behavioral finance researchers: the papers in this special issue represent solid proof of this assertion. We hope that readers will enjoy and benefit from the contents of these studies as much as we enjoyed and benefited from putting this issue together. And, of course, we hope these papers help spur the next generation of behavioral finance research. Acknowledgements In total, we received 41 initial submissions to the special issue, although not all papers were sent out for review (most commonly because they did not fit with the theme of this special issue). The editorial review process was rigorous, and, unfortunately, we had to make the difficult decision of rejecting some very interesting and provocative papers. Among the eight papers that were finally accepted, most were revised at least twice. Thus, the papers in this issue are certainly polished. When we initially undertook the task of putting together a special issue on behavioral finance in Asia, we had very little idea of how difficult that task would be. As co-editors, we took turns serving as point person on each paper; however, for every paper, we consulted with one another before any decisions were made, which required that we both read every paper that was submitted. However, our task of evaluating papers was made tremendously easier as we took advantage of the expertise and the time of the papers' referees, whose reports were thoughtful, constructive, and extremely helpful to the authors. More often than not, we also engaged in active communication with referees. The following scholars, who were outstanding in their willingness to contribute their time to make this a great special issue, served as referees: Kee-Hong Bae, Queen's University, Canada Kent Baker, American University Glenn Boyle, University of Otago, New Zealand Greg Brown, University of North Carolina at Chapel Hill
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Colin Camerer, California Institute of Technology Joon Chae, Seoul National University, Korea Charles Chang, Cornell University Wen-I Chuang, National Taiwan University of Science and Technology Richard Deaves, McMaster University, Canada Michael Dowling, University of Dublin, Ireland Laura Frieder, Purdue University Geoffrey Friesen, University of Nebraska-Lincoln Dave Haushalter, Pennsylvania State University Soosung Hwang, City University, United Kingdom Jung-wook Kim, University of Alberta, Canada Lisa Kramer, University of Toronto, Canada Alexander Kurov, West Virginia University Sonya Lim, DePaul University Peter Locke, George Washington University Brian Lucey, University of Dublin, Ireland David McLean, Boston College David Michayluk, University of Technology at Sydney, Australia Jason Mitchell, University of Western Australia Henry Oppenheimer, University of Rhode Island Gioia Pescetto, University of Durham, United Kingdom Mark Peterson, Southern Illinois University at Carbondale Yiming Qian, University of Iowa Oliver Rui, Chinese University of Hong Kong Mark Seasholes, University of California, Berkeley Itzhak Venezia, Hebrew University of Jerusalem Qinghai Wang, University of Wisconsin-Milwaukee Marc Weidenmeir, Claremont McKenna College Fei Wu, Massey University, New Zealand Shanhong Wu, State University of New York at Buffalo Yexiao Xu, University of Texas, Dallas Ning Zhu, University of California, Davis Finally, we would be remiss if we did not extend our gratitude to the administrations at the business schools of the State University of New York at Buffalo and Washington State University for supporting us in this effort. Last but not least, we are especially grateful to Ghon Rhee for giving us this opportunity to put together this special issue. References Barber, B., Odean, T., 2001. Boys will be boys: gender, overconfidence, and common stock investments. Quarterly Journal of Economics 116, 261–292. Barber, B., Odean, T., 2002. Online investors: do the slow die first? Review of Financial Studies 15, 455–487. Barberis, N., Thaler, R., 2003. A survey of behavioral finance. In: Constantinides, G., Harris, M., Stulz, R. (Eds.), Handbook of the Economics of Finance. North-Holland, Amsterdam. Brown, P., Mitchell, J., 2008. Culture and stock price clustering: evidence from the Peoples' Republic of China. PacificBasin Finance Journal 16, 95–120 (this issue). Chen, G., Kim, K.A. Nofsinger, J.R. Rui, O.M., in press. Trading performance, disposition effect, overconfidence, representativeness bias, and experience of emerging market investors. Journal of Behavioral Decision Making.
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da Silva Rosa, R., Durand, R.B., 2008. The role of salience in portfolio formation. Pacific-Basin Finance Journal 16, 78–94 (this issue). DeBondt, W.F.M., Thaler, R.H., 1985. Does the stock market overreact? Journal of Finance 40, 793–808. Feng, L., Seasholes, M.S., 2008. Individual investors and gender similarities in an emerging stock market. Pacific-Basin Finance Journal 16, 44–60 (this issue). Frino, A., Grant, J., Johnstone, D., 2008. The house money effect and local traders on the Sydney Futures Exchange. Pacific-Basin Finance Journal 16, 8–25 (this issue). Hirshleifer, D., 2001. Investor psychology and asset pricing. Journal of Finance 56, 1533–1597. Hofstede, G., 1980. Culture's Consequences. Sage Publishers, Beverly Hills, CA. Kang, J.-K., Shivdasani, A., Yamada, T., 2000. The effect of bank relations on investment decisions: An investigation of Japanese takeover bids. Journal of Finance 55, 2197–2218. Lin, B.-X., Michayluk, D., Oppenheimer, H.R., Reid, S.F., 2008a. Hubris amongst Japanese bidders. Pacific-Basin Finance Journal 16, 121–159 (this issue). Lin, Y.-H., Hu, S.-Y., Chen, M.-S, 2008b. Testing pecking order prediction from the viewpoint of managerial optimism: some empirical evidence from Taiwan. Pacific-Basin Finance Journal 16, 160–181 (this issue). Oh, N.Y., Parwada, J.T., Walter, T.S., 2008. Investors' trading behavior and performance: online versus non-online equity trading in Korea, Pacific-Basin Finance Journal, this issue. Pacific-Basin Finance Journal 16, 26–43 (this issue). Roll, R., 1986. The hubris hypothesis of corporate takeovers. Journal of Business 59, 197–216. Shefrin, H., Statman, M., 1985. The disposition to sell winners too early and ride losers too long: theory and evidence. Journal of Finance 40, 777–790. Shleifer, A., Vishny, R., 1997. The limits of arbitrage. Journal of Finance 52, 35–55. Tan, L., Chiang, T.C, Mason, J.R, Nelling, E., 2008. Herding behavior in Chinese stock markets: an examination of A and B shares. Pacific-Basin Finance Journal 16, 61–77 (this issue). Thaler, R.H., 1999. The end of behavioral finance. Financial Analysts Journal 55, 12–17. Weber, E.U., Hsee, C.K., 2000. Culture and individual judgment and decision making. Applied Psychology: An International Review 49, 32–61. Wolosin, R.J., Sherman, S.J., Till, A., 1973. Effects of cooperation and competition on responsibility attribution after success and failure. Journal of Experimental Social Psychology 9, 220–235. Yates, J.F., Lee, J., Bush, J.G., 1997. General knowledge overconfidence: cross-national variations, response style, and “reality”. Organizational Behavior and Human Decision Processes 70, 87–94. Yates, J.F., Zhu, Y., Ronis, D.L., Wang, D.F., Shinotsuka, H., Toda, W., 1989. Probability judgment accuracy: China, Japan, and the United States. Organizational Behavior and Human Decision Processes 43, 147–171.
Pacific-Basin Finance Journal 16 (2008) 1 – 7 www.elsevier.com/locate/pacfin
Editorial
Behavioral finance in Asia Kenneth A. Kim a,⁎,1 , John R. Nofsinger b,2 a
School of Management, State University of New York at Buffalo, Buffalo, NY 14260, USA b College of Business, Washington State University, Pullman, WA 99164, USA Available online 25 April 2007
Abstract This paper introduces the Pacific-Basin Finance Journal's special issue on behavioral finance in Asia. We first briefly discuss behavioral finance in general, and then we explain why behavioral finance in Asia is an important topic worth studying. We describe the papers published in this special issue, and in doing so, we place the papers within the appropriate context of the growing literature on behavioral finance. We close by acknowledging the referees of this special issue and by offering brief concluding thoughts. © 2007 Elsevier B.V. All rights reserved. JEL classification: G11; G15; G30 Keywords: Asia; Behavioral finance; Corporate finance; Investing
1. Introduction Why might the topic of behavioral finance in Asia be important and interesting? First, the study of behavioral finance is still a young field. The academic finance community has only recently accepted it as a feasible paradigm to explain how financial market participants make decisions and, in turn, how these decisions affect financial markets. Second, Asian financial markets are among the largest in the world, and there is some evidence – anecdotal, theoretical, and empirical – that Asians suffer from cognitive biases on a different level than people of other cultures. By studying behavioral finance in Asia, we can, therefore, add to our understanding of these two important topics. ⁎ Corresponding author. Tel.: +1 716 645 3293. E-mail addresses: [email protected] (K.A. Kim), [email protected] (J.R. Nofsinger). 1 Kim and Nofsinger served as co-editors of the Pacific-Basin Finance Journal's special issue on behavioral finance in Asia. Correspondences can be addressed to either author. Author acknowledgements are contained within the paper's text. The usual disclaimer applies. 2 Tel.: +1 509 335 7200. 0927-538X/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.pacfin.2007.04.001
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K.A. Kim, J.R. Nofsinger / Pacific-Basin Finance Journal 16 (2008) 1–7
The study of behavioral finance allows cognitive psychology to play a potentially important role in finance. People are not always rational, and, thus, their financial decision making may be wholly or partially driven by behavioral biases. If people have beliefs or preferences that do not meet the traditional axioms of rational decision makers, then it is important that we identify the effects of these behavioral biases—especially if their cognitive errors impact prices and cannot be easily arbitraged away. Many finance scholars view the mid-1980s as the beginning of this area of research. DeBondt and Thaler (1985) showed that stock markets overreact to information, and Shefrin and Statman (1985) contended that investors are more likely to sell their winner stocks rather than their losers, even though selling losers (to realize tax losses) is optimal. If one believes these works to be the genesis of behavioral finance research, then the field is barely over two decades old. The pervasiveness of behavioral finance research is even younger. The behavioral finance paradigm was not widely accepted at first. In fact, DeBondt and Thaler's (1985) paper was met with considerable skepticism (Thaler, 1999). More recently, many good theoretical models have explored the ramifications of less-than-rational agents. Initially, studies focused on asset pricing, but in recent years, models have incorporated the effect that less-than-rational managers may have on corporate finance decision making. Barberis and Thaler (2003) provide an excellent literature review of the many different types of behavioral biases that financial decision makers might hold and how these biases might affect decision making and, in turn, the financial markets. Empirical papers on behavioral finance also had a slow start—primarily because arguments based on stock-level data suffer from the joint-test problem (market efficiency and asset pricing model) and were, thus, less convincing to an initially skeptical audience. Terrence Odean overcame this limitation by obtaining individual brokerage account data. In a series of papers (many with Brad Barber), he showed that individual investors suffered from several behavioral biases. Many other researchers and data sets have since empirically tested behavioral finance theories. Hirshleifer (2001) provides an excellent literature review of the empirical evidence in behavioral finance with regard to asset pricing. Somewhat surprisingly, however, few researchers have yet to use experiments to test behavioral finance theories, even though well-designed experiments allow researchers to control the environment. Asia is an interesting place to study behavioral finance because of the different levels of capitalism and financial market experience of its participants. Countries such as China have been slowly changing over the last couple of decades to a capitalistic economy from a socialistic one. On the other hand, countries such as Japan have had large economic and financial markets for a much longer time. Thus, because variations in knowledge and experience likely play a role in explaining variations in economic decision making, Asia is fertile ground for the study of behavioral finance. Also, there is a reason to believe that Asians in general suffer from cognitive biases more than do people of Western cultures. Anecdotally, individual investors in Asia are often viewed as mere gamblers. Theoretically, social scientists and psychologists have contended that culture can nurture tendencies toward behavioral biases at varying levels (e.g., Yates et al., 1989). According to Hofstede (1980), differences among cultures can be expressed on an individualism– collectivism continuum. Asian cultures tend to be based on a socially collective paradigm. It has been argued that collective-oriented societies can cause individuals to be overconfident, which is a behavioral bias. Because behavioral inclinations can be learned (Wolosin et al., 1973), cultural differences in life experiences and education may cause differences in behavior. Life experiences and education are certainly different among different cultures. To this end, some evidence exists that suggests that people raised in Asian cultures exhibit more behavioral biases than people from the United States (e.g., Yates et al., 1997).
K.A. Kim, J.R. Nofsinger / Pacific-Basin Finance Journal 16 (2008) 1–7
3
Although the psychology literature suggests that people of Asian cultures may suffer more from behavioral biases than people of Western cultures, the literature is still sparse. Weber and Hsee (2000) noted: “The bottom line is that the topic of culture and decision making has not received a lot of attention from either decision researchers or cross-cultural psychologists” (p. 34). Chen et al. (in press) provide a useful literature review from the psychology and finance literatures on the behavior of Asian people and how these behaviors might affect their investment decision making. In support of the notion that Asians suffer from behavioral biases more than people from Western cultures, they find that individual investors in China suffer more from both an overconfidence bias and the disposition effect than U.S. individual investors. Overall, behavioral finance may still be characterized as a controversial topic, but it is much less so than it once was. We now have a better understanding of how humans behave, and many researchers now accept that these behavioral inclinations can affect financial decision making. And, it is now widely accepted that there are limits to arbitrage (Shleifer and Vishny, 1997), so these behaviors may impact prices. While recent research on behavioral finance has significantly advanced our understanding of financial markets, the future looks even more promising. At finance conferences, sessions on behavioral finance are very well attended, and the audience members are often the younger scholars of the academic profession. Thaler (1999) had a wish list for the future of behavioral finance research: he wanted to see theory papers bring institutions into their models; he wanted to see more behavioral finance research on corporate finance; and he wished for more data on individual investors, particularly for online investors. We add one more: we wish for more behavioral finance research on Asian financial markets. This special issue grants most of these wishes. 2. Overview of the special issue The special issue contains eight papers. Five papers study the behavior or performance of investor decision making. The first paper by Frino et al. (2008-this issue) studies futures traders in the Sydney Futures Exchange. Might those traders who make big profits in the morning be risk seeking in the afternoon? If so, then this finding is consistent with what is known as the house– money effect. We are more likely to take risks if we feel like we are betting with our winnings rather than with our initial capital. This effect is known among gamblers, but few papers have confirmed the effect using investors. Frino et al. take extreme care with their empirical approach and confirm the existence of the house–money effect. They also find that morning winners who seek excessive risks in the afternoon end up being the biggest afternoon losers. Oh et al. (2008-this issue) compare the performance of investors in Korea who trade stocks online and those who do not. Despite the extensive availability of online investing, very little research has been conducted on this topic (one notable exception is Barber and Odean, 2002). Oh et al. identify investor types (domestic institutional investors, foreign investors, and individual investors) and their method of trade (online vs. non-online). The best and worse performers were foreign investors and individual investors, respectively, regardless of whether they were trading online. However, individuals who traded online appear to be the worse performers. Oh et al. suggest that the trading venue must be considered when comparing the relative performance of different investor types. In general, their findings are consistent with the hypothesized expectations of online trading performance. Specifically, individual investors' easy access to trading exacerbates the influence of emotions and impulsive desires, often to their detriment. Feng and Seasholes (2008-this issue) contrast male and female investors in China. Whether gender makes a difference in investing performance is, of course, a controversial issue. Using data
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on U.S. investors, Barber and Odean (2001) show that women are better investors than men. In contrast, Feng and Seasholes find that men and women in China are similar in both their inclination toward behavioral biases and their investing performance. Feng and Seasholes hint at an interesting question: If – all else being equal – we should expect men and women to be similar in their investing behaviors and performances, why do men and women investors behave and perform differently in the United States? Tan et al. (2008-this issue) study investor herding in the Chinese stock markets. Herding exists when investors' trading decisions are positively correlated to each other. In China, there exist Ashares that are mostly owned by domestic individual investors and B-shares that are mostly owned by foreign institutional investors. Many prior researchers have taken advantage of this dual-class of Chinese shares to conduct insightful studies on the effects that ownership structure might have on stock prices and their return behavior. Tan et al.'s paper examines whether herding is different between these two share types and find that, despite the ownership differences, herding exists in both share classes. However, they find that herding is higher for A-shares during periods of rising markets, high trading volume, and high market volatility; conversely, B-shares experience no herding asymmetry effects. Whether these contrasting findings are due to ownership structure differences is an open-ended question—perhaps one that will be addressed by future research. In the final investor-oriented paper that studies investment decision making, da Silva Rosa and Durand (2008-this issue) take advantage of an investing contest sponsored in Australia. Students, who paid $10 for every portfolio they entered into the contest, were given a fictitious $200,000 and could not invest more than $40,000 in any single stock. The contest's goal was simply to maximize the wealth of the entry portfolio after a 1-year holding period. The authors hypothesize that, even though most entrants were students majoring in business, the availability heuristic would drive portfolio formation decisions. Specifically, they suggest that the more news stories that appeared in the national press about a company during the month prior to when the entries were due, the more likely that company's stock would be included in entrants' portfolios. The results support their hypothesis. In fact, they find that the availability heuristic did a better job at explaining portfolio formation decisions than did firm size. Brown and Mitchell (2008-this issue) consider a behavioral explanation for stock price clustering on the Chinese stock markets. In China, 8 is widely considered a lucky number whereas 4 is considered unlucky. The authors find that Chinese stock prices ended with 8 twice as often as they ended with 4, and this preference was most prevalent for Chinese A-shares, which are primarily owned by domestic Chinese investors. For Chinese B-shares, which are primarily owned by foreigners, the tendency for stocks to end in 8 was much lower than it was for A-shares. Although most behavioral finance studies have focused on investment decision making, the behavioral finance literature on corporate finance decision making is growing quickly. Excellent theory papers have been published recently, but empirical studies still remain scant. The hurdle is identifying acceptable proxies of managerial behavior. Two papers in this special issue tackle the issue of incorporating behavioral biases in corporate finance decision making. First, Lin et al. (2008a-this issue) study hubris in the mergers and acquisitions market in Japan. Roll (1986) proposed hubris as an explanation for why so many nonvalue-enhancing mergers are conducted; namely, bidding managers are overconfident and optimistic in their valuation of an acquisition. Although some anecdotal evidence suggests that hubris does not play a role in Japanese takeovers, Lin et al. find results to the contrary. Using the bidding firm's past performance as a proxy measure for hubris, they find that those firms with the potential for high hubris (i.e., high past performers) experience low returns around bid dates. These results, which are consistent with a hubris explanation for mergers and acquisitions, contradict the finding of Kang et al. (2000),
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who reported that the past performance of Japanese bidders is positively correlated to their returns around bid dates. However, the sample in the Kang et al. paper is mostly from Japan's pre-bubble period while the Lin et al. study sample is mostly from the period after the bubble burst. In the second paper on behavioral biases in corporate finance decision making, Lin et al. (2008b-this issue) use Taiwanese data to study pecking order and managerial optimism. Although the contention that firms follow a pecking order for financing deficits or capital expenditures is not highly disputed, the underlying explanation for why firms follow this pecking order is a matter of debate. Prior research has suggested managerial optimism as an explanation: optimistic managers may believe their firms are undervalued, and, as such, they prefer to access debt capital instead of equity capital. Lin et al. find evidence consistent with this hypothesis. Namely, using managements' earnings forecast as a proxy measure of managerial optimism, they find that firms with optimistic managers are more likely to finance deficits with debt rather than equity. Hopefully, we will see more research on behavioral corporate finance in the future. 3. Conclusion The behavioral finance paradigm for explaining how agents behave and how their behavior might affect financial markets looks like it is here to stay. Although conducting research on behavioral finance poses many challenges and hurdles, the authors in this special issue have (to a high degree) successfully addressed those challenges. We suspect that even more of those challenges and hurdles will be overcome in future research. Our overall goal with this special issue was to help bring behavioral finance theories to Asian financial markets. The Asian financial markets represent a fruitful testing ground for behavioral finance researchers: the papers in this special issue represent solid proof of this assertion. We hope that readers will enjoy and benefit from the contents of these studies as much as we enjoyed and benefited from putting this issue together. And, of course, we hope these papers help spur the next generation of behavioral finance research. Acknowledgements In total, we received 41 initial submissions to the special issue, although not all papers were sent out for review (most commonly because they did not fit with the theme of this special issue). The editorial review process was rigorous, and, unfortunately, we had to make the difficult decision of rejecting some very interesting and provocative papers. Among the eight papers that were finally accepted, most were revised at least twice. Thus, the papers in this issue are certainly polished. When we initially undertook the task of putting together a special issue on behavioral finance in Asia, we had very little idea of how difficult that task would be. As co-editors, we took turns serving as point person on each paper; however, for every paper, we consulted with one another before any decisions were made, which required that we both read every paper that was submitted. However, our task of evaluating papers was made tremendously easier as we took advantage of the expertise and the time of the papers' referees, whose reports were thoughtful, constructive, and extremely helpful to the authors. More often than not, we also engaged in active communication with referees. The following scholars, who were outstanding in their willingness to contribute their time to make this a great special issue, served as referees: Kee-Hong Bae, Queen's University, Canada Kent Baker, American University Glenn Boyle, University of Otago, New Zealand Greg Brown, University of North Carolina at Chapel Hill
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Colin Camerer, California Institute of Technology Joon Chae, Seoul National University, Korea Charles Chang, Cornell University Wen-I Chuang, National Taiwan University of Science and Technology Richard Deaves, McMaster University, Canada Michael Dowling, University of Dublin, Ireland Laura Frieder, Purdue University Geoffrey Friesen, University of Nebraska-Lincoln Dave Haushalter, Pennsylvania State University Soosung Hwang, City University, United Kingdom Jung-wook Kim, University of Alberta, Canada Lisa Kramer, University of Toronto, Canada Alexander Kurov, West Virginia University Sonya Lim, DePaul University Peter Locke, George Washington University Brian Lucey, University of Dublin, Ireland David McLean, Boston College David Michayluk, University of Technology at Sydney, Australia Jason Mitchell, University of Western Australia Henry Oppenheimer, University of Rhode Island Gioia Pescetto, University of Durham, United Kingdom Mark Peterson, Southern Illinois University at Carbondale Yiming Qian, University of Iowa Oliver Rui, Chinese University of Hong Kong Mark Seasholes, University of California, Berkeley Itzhak Venezia, Hebrew University of Jerusalem Qinghai Wang, University of Wisconsin-Milwaukee Marc Weidenmeir, Claremont McKenna College Fei Wu, Massey University, New Zealand Shanhong Wu, State University of New York at Buffalo Yexiao Xu, University of Texas, Dallas Ning Zhu, University of California, Davis Finally, we would be remiss if we did not extend our gratitude to the administrations at the business schools of the State University of New York at Buffalo and Washington State University for supporting us in this effort. Last but not least, we are especially grateful to Ghon Rhee for giving us this opportunity to put together this special issue. References Barber, B., Odean, T., 2001. Boys will be boys: gender, overconfidence, and common stock investments. Quarterly Journal of Economics 116, 261–292. Barber, B., Odean, T., 2002. Online investors: do the slow die first? Review of Financial Studies 15, 455–487. Barberis, N., Thaler, R., 2003. A survey of behavioral finance. In: Constantinides, G., Harris, M., Stulz, R. (Eds.), Handbook of the Economics of Finance. North-Holland, Amsterdam. Brown, P., Mitchell, J., 2008. Culture and stock price clustering: evidence from the Peoples' Republic of China. PacificBasin Finance Journal 16, 95–120 (this issue). Chen, G., Kim, K.A. Nofsinger, J.R. Rui, O.M., in press. Trading performance, disposition effect, overconfidence, representativeness bias, and experience of emerging market investors. Journal of Behavioral Decision Making.
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da Silva Rosa, R., Durand, R.B., 2008. The role of salience in portfolio formation. Pacific-Basin Finance Journal 16, 78–94 (this issue). DeBondt, W.F.M., Thaler, R.H., 1985. Does the stock market overreact? Journal of Finance 40, 793–808. Feng, L., Seasholes, M.S., 2008. Individual investors and gender similarities in an emerging stock market. Pacific-Basin Finance Journal 16, 44–60 (this issue). Frino, A., Grant, J., Johnstone, D., 2008. The house money effect and local traders on the Sydney Futures Exchange. Pacific-Basin Finance Journal 16, 8–25 (this issue). Hirshleifer, D., 2001. Investor psychology and asset pricing. Journal of Finance 56, 1533–1597. Hofstede, G., 1980. Culture's Consequences. Sage Publishers, Beverly Hills, CA. Kang, J.-K., Shivdasani, A., Yamada, T., 2000. The effect of bank relations on investment decisions: An investigation of Japanese takeover bids. Journal of Finance 55, 2197–2218. Lin, B.-X., Michayluk, D., Oppenheimer, H.R., Reid, S.F., 2008a. Hubris amongst Japanese bidders. Pacific-Basin Finance Journal 16, 121–159 (this issue). Lin, Y.-H., Hu, S.-Y., Chen, M.-S, 2008b. Testing pecking order prediction from the viewpoint of managerial optimism: some empirical evidence from Taiwan. Pacific-Basin Finance Journal 16, 160–181 (this issue). Oh, N.Y., Parwada, J.T., Walter, T.S., 2008. Investors' trading behavior and performance: online versus non-online equity trading in Korea, Pacific-Basin Finance Journal, this issue. Pacific-Basin Finance Journal 16, 26–43 (this issue). Roll, R., 1986. The hubris hypothesis of corporate takeovers. Journal of Business 59, 197–216. Shefrin, H., Statman, M., 1985. The disposition to sell winners too early and ride losers too long: theory and evidence. Journal of Finance 40, 777–790. Shleifer, A., Vishny, R., 1997. The limits of arbitrage. Journal of Finance 52, 35–55. Tan, L., Chiang, T.C, Mason, J.R, Nelling, E., 2008. Herding behavior in Chinese stock markets: an examination of A and B shares. Pacific-Basin Finance Journal 16, 61–77 (this issue). Thaler, R.H., 1999. The end of behavioral finance. Financial Analysts Journal 55, 12–17. Weber, E.U., Hsee, C.K., 2000. Culture and individual judgment and decision making. Applied Psychology: An International Review 49, 32–61. Wolosin, R.J., Sherman, S.J., Till, A., 1973. Effects of cooperation and competition on responsibility attribution after success and failure. Journal of Experimental Social Psychology 9, 220–235. Yates, J.F., Lee, J., Bush, J.G., 1997. General knowledge overconfidence: cross-national variations, response style, and “reality”. Organizational Behavior and Human Decision Processes 70, 87–94. Yates, J.F., Zhu, Y., Ronis, D.L., Wang, D.F., Shinotsuka, H., Toda, W., 1989. Probability judgment accuracy: China, Japan, and the United States. Organizational Behavior and Human Decision Processes 43, 147–171.