قدرت خلق و خوی بازار - شواهدی از بازارهای در حال ظهور

This article focuses on investor behavior and, consequently, the mood in the market. By using a self-organizing network we develop a model which tries to capture the market mood and serves as an indicator of the reasonableness of selling or purchasing securities. In this sense, the final result of this model is the same as in the model-type prediction of future stock prices, with the only exception being that one is not required to know the concrete future values of the selected security. This will indirectly support the hypothesis that psychological factors are an important (if not key) market driving force.

The current global financial crisis began with reduced confidence among investors, which directly affected the price movement of securities listed on financial markets. The developments on international markets have confirmed the phenomenon of a “social infection,” in which real estate owners, issuers and owners of mortgage securities, regulators, and credit-rating agencies contributed to the formation of a bubble and its “ex-post” burst. Although the crisis began with the collapse of the US mortgage market, this is not considered the main reason for the crisis, but merely a trigger. The main culprits for the great vulnerability of the financial system can be found elsewhere. However, it has been clearly demonstrated that an appropriate understanding of the risks and investor confidence are exceptionally important for today's financial markets. This article presents the significance of understanding the market situation by using a model solution. Various approaches are used for modeling financial markets. The ones more commonly used include the agent and systemic approaches. The agent approach is used to model small individual units and simulate their interaction (Arthur et al., 1997 and LeBaron, 2002). In contrast, the systemic approach is used to model the representative behavior of agents and simulate the behavior of a system (Andresen, 1997 and Raczynski, 2000). This article uses the systemic approach and proceeds from the premise that the market mood provides key information about developments happening on the market, and that the market is thus not subject to factors arising from fundamental variables. By using a self-organizing network (Kohonen variants)–a neural network model, which is used primarily in data mining–it will show a situation in a financial market in which the primary interest is placed on information that may refer to comprehending the market situation from a mood — that is, from a psychological perspective. This kind of approach will enable the development of a selected market model that may serve as an indicator of the reasonableness of selling or purchasing securities. In this sense, the final result of this model is the same as in the model-type prediction of future stock prices, with the only exception being that one is not required to know the concrete future values of the selected security. This will indirectly support the hypothesis that psychological factors are an important market driving force. We believe that a model capable of describing the market situation can thus identify important changes in the market — that is, those having a direct impact on future stock price movements. This is especially important in emerging markets; therefore, the proposed model was tested on data from the Ljubljana Stock Exchange, a rapidly growing, small, open-economy market. This type of market is not only subject to influences from its own national economy, but also to developments on global financial markets. This article has been divided into six sections. The introduction is followed by a section on the methodology. Section 3 presents the characteristics of the data used for testing the hypothesis. The development of the model is presented in Section 4, and the results of the simulations performed in Section 5. The conclusion presents the article's key findings.

Market vulnerability results from investor behavior, and traditional finance theory is not capable of explaining this phenomenon. Many answers to this are provided by behavioral finance, which studies the influence of mood and other psychological factors on an individual's decision (Barberis et al., 1998, Hong et al., 2000 and Hong and Stein, 1999). The basic principles of behavioral finance are reflected in all aspects of the current financial crisis: from an overly optimistic credit policy that led to the crisis, to the current fluctuations on the stock markets. This article sought to empirically support the hypothesis that the developments on the financial markets reflect the collective mood of the market players. A model for predicting market psychology was thus developed; it was based on the application of a self-organizing network algorithm. The estimated model was then applied to a mechanical trading system, which independently adopts investment decisions, based on the current daily data. This ensures an objective assessment of the model and thus also indicates that the suggested hypothesis is valid. The model was developed using data from the Ljubljana Stock Exchange. Data reflecting the mood of the market as a whole were used in addition to data directly connected with estimated trading in shares of Gorenje d.d. The model's robustness was confirmed with its effective performance on data outside the development sample, covering a period of five years. The solid performance of the model is not merely an indication supporting the suggested hypothesis, but also carries important implications for understanding the financial crisis on the Slovenian financial market. It can thus be established that similar principles apply to the Slovenian financial market as well as for developed markets. It is obvious that psychological factors are extremely important in determining market dynamics, which means that they are largely the key to solving the current financial crisis. First question which can be raised based on the results is, whether similar results may occur elsewhere. We believe that the success of a model depends on the nature of the observed market. If such market is weak efficient, there is little chance for successful model predictions. Additionally, factors which may influence the behavior of investors can raise the rate of success for prediction models. Many researchers have tried to test the efficient market hypothesis for markets around the world. The results suggest that developed markets are generally weak form efficient; that means that the successive returns are independent and follow random walk (Fama, 1970). On the other hand, the research evidence on emerging markets is controversial: some of the researchers find evidence of weak form efficiency (Urrutia, 1995 and Ojah and Karemera, 1999), whereas the others find the evidence of non-randomness stock price behavior (Harvey, 1995). The Slovenian stock market still inhibits features of an emerging market where the case for less efficiency is due to several factors: (1) it is not unlikely that the market participants are not well informed and behave irrational compare to mature markets, (2) emerging markets generally suffer a certain market imperfections such as transaction costs, lack of timely information, cost of acquiring new information, greater uncertainty about the future, (3) due to the problem of thin trading, in smaller emerging markets it is easier for large traders to manipulate the market, ergo, as a less organized market without market makers and timely available information, there always remain a possibility to make profit by large investors and insiders (Mobarek and Keasey, 2000). The building blocks of the traditional finance rely mainly on investors' rationality (the concept homo economicus) and strength of the self correcting mechanism of arbitrage. These features are not always confirmed in developed markets, let alone in emerging markets. The sources of irrationality are mainly psychological biases. In emerging economies, probably due to short history of capital markets, we may find very distinct characteristic, that people have problem with representativeness, sample size and understanding the law of return to the mean. This lead to difficulties in drawing correct conclusions based on available information. Conservatism, belief perseverance and anchoring slow down the reaction of the market to new information. Kahneman and Tversky (1979) propose the prospect theory, which discovers unstable preferences that may vary depending on context in which the alternatives are presented (a second important source of irrationality). The prospect theory explains so called disposition effect — eagerness of people to sell an asset that has just brought profit and strong reluctance to close a position that has been bringing losses. This effect may be responsible for market unpredictable reactions to new information, a pattern typical for emerging markets. The third source of irrationality discovered in emerging markets comes from arbitrage mechanism. These markets are characterized by implementation barriers for arbitrage, usually related to taking a short position. Small capitalization of stocks and their illiquidity, accompanied by legal constraints–short selling is often simply not allowed for institutional investors–produce circumstances where mispricing remain unchallenged for a relatively long time. The absence of arbitrage increases the risk that irrationality on the market may become stronger and may drive the mispricing to even a greater extent (Shleifer, 2000). In explaining the nature of stock markets foreign investors play an important role. The empirical analysis about the behavior and the effects of foreign investors on equity markets is two sided: one focuses on concurrent movements between stock's returns and foreign flows, the other focuses on anomalies that may cause destabilizing effects such as herding, positive feedback trading, volatility jumps and price pressure. A number of empirical studies examine the behavior of foreign investors vis a vis domestic investors in emerging markets. Choe et al. (1999) find that individual investors in Korea exhibit short-run contrarian behavior whereas foreign investors exhibit momentum behavior. Grinblatt (2001) reports that Finnish domestic investors generally tend to be contrarian investors while foreign investors tend to be momentum investors. Given the short history of emerging markets, the domestic investors' trading experience and hence level of sophistication is unlikely to be comparable to that of investors from mature markets. Given that margin trading and short sales are usually not permitted in emerging equity markets, Ng and Wu (2005) report, that in Chinese equity market institutions act as momentum traders when they buy and sell stocks, but the group of less sophisticated individual investors behave as contrarian investors when they buy stocks and have the tendency to hold on to stock with past poor performance; interestingly the most sophisticated and wealthier individuals are likely to pursue momentum-buy investing, and at the same time they also exhibit strong disposition effect. Herding behavior is blamed to be irrational since it can lead to mispricing, especially bubbles. The motivation for this kind of individual behavior may be the group pressure. Persaud (2002) argues that Value at Risk (VaR) models led banks to herd, causing a lack of liquidity on markets, As investors in emerging markets are increasingly using the same VaR models, the tendency is convergence of the market participants' behavior. Regulators should therefore incentive diversity of behavior among the market participants through the use of different risk management systems. Macroeconomic information rather than firm-specific information tends to have a more significant impact on investor behavior in markets which exhibit herding. Chang et al., 1999 and McQueen et al., 1996 found directional symmetry, the rate of increase in security return dispersion as a function of the market return is higher in up market, relative to down market days. Information asymmetries between foreign and local investors lead to information advantages of local investors that impact prices and finally lead to positive feedback trading by foreign investors. This informational advantage can derive from a variety of sources, including the ability to access relevant locally available information, lower costs of accessing such information, or the timeliness of access to relevant information. A number of empirical researches find evidence of positive feedback trading on emerging markets. Alemanni and Ornelas (2008) survey on literature that analyze this issue and find evidence of feedback trading on 9 of the 11 studies, while evidence of contemporaneous relationship between flows and returns is presented in all researches that have tested it. We can conclude that the majority of studies of the behavior of foreign investors in emerging markets could find little evidence that these investors have brought problems to local markets. Their flows bring benefits such as greater risk sharing and high market liquidity. Restrictive regulations are therefore not recommended. This finding is valid also for Slovenian stock market.