تجزیه و تحلیل عوامل تصمیم گیری برای سرمایه گذاری در سهام با DEMATEL و فرایند تحلیل شبکه ای
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|6154||2011||9 صفحه PDF||سفارش دهید||7389 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 38, Issue 7, July 2011, Pages 8375–8383
Existing methodologies of equity investment, such as fundamental analysis, technical analysis, and institutional investor analysis, explore important factors of stock price behaviors. However, the interdependent relationships of the key factors have not yet been fully studied. This paper provides the first analysis on the interactive relationships among the factors in incorporating the methods of Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP). The empirical results show that factors from the existing analytical methodologies have significant interactive and self-feedback dynamics. Among the key factors, profitability is the most important one affecting investment decision, followed by growth and trading volume. In addition, due to the complexity of the ANP, this study proposes a new methodology to simplify the process, and empirical evidences indicate that the approach is effective and efficient.
Equity stock is the most popular financial asset in capital markets. Academic researchers, industrial practitioners, and investors have employed various techniques to analyze the dynamics of stock prices. In particular, different methods have been developed to set certain selection criteria in choosing individual stocks with promising returns, and three methodologies have been broadly applied: the fundamental analysis, technical analysis, and institutional investor analysis. These methods are used to explore key factors that yield significant impacts on stock prices and the effectiveness of the factors are often individually and independently analyzed. This study, on the other hand, employs the Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP) to focus on the analyzes of interdependent relationships among the factors. Through the understanding of the interactions between key factors, this study seeks to provide more efficient and effective investment decision making process. Fundamental analysis studies key elements of financial conditions such as earnings and dividend prospects along with overall market conditions such as interest rates to predict the movements of stock price. The method is based on the key assumption where stock performance of a firm could fully reflect its operating condition. Recent researches have adopted the method include Tang and Shum, 2003, Fama and French, 2006, Wu and Xu, 2006, Edirisinghe and Zhang, 2007, Girard and Omran, 2007, Chen and Zhang, 2007, Cole et al., 2008 and Samaras et al., 2008, and Benjamas, Riza, and Ramesh (2008) and others. Technical analysis studies for recurrent and predictable patterns in stock prices such as return momentum and herding behaviors, and consequently, seeks to forecast future trends of stock movements. Recent examples with application of the approach are Lee and Rui, 2002, Darrat et al., 2003, Wang and Chan, 2006, Avramov et al., 2007, Yamawaki and Tokuoka, 2007 and Zarandi et al., 2009, and Li and Kuo (2008). Institutional investor analysis investigates the relationships between stock price and trading activity of institutional investors such as the institutional buy/sell signals. Recent studies applying this methodology include Griffin et al., 2003, Darrat et al., 2003, Wang and Cheng, 2004, Cai and Zheng, 2004, Avramov et al., 2006, Bohl and Brzeszczyński, 2006 and Chiyachantana et al., 2006, and Hirose, Kato, and Bremer (2009) and among others. These prior researches mainly investigate the unidirectional impacts of each individual factor on the dynamics of stock price rather than explore the interdependences and feedback effects among the factors and their relative marginal strengths. Consequently, due to lack of analyzes on these quantitative interdependences between factors, above approaches do not provide direct assessments and proper comparisons on the economic significances of these factors. This research accordingly applies two quantitative methods, the DEMATEL and ANP, to evaluate the level of interdependences among those factors and to add on the understandings of dynamics of stock return. DEMATEL is one of tools on decision making of multiple criteria and is able to transform qualitative issues into quantitative tasks for analysis. ANP can be applied to analyze the interactive relations between factors with proper measurements of the weight for each factorial criterion. Consequently, each alternative in the decision making would be evaluated and prioritized to determine the length and area of improvements. By selecting the proper critical value in the process, the optimal combination of decision making can then be determined. Tzeng, Chiang, and Li (2007) applied the method of DEMATEL into multiple criteria decision making (MCDM) model, and Ou Yang, Shieh, Jun-Der Leu, and Tzeng (2008) proposed the application of both DEMATEL and ANP methods as the hybrid MCDM model. Cheng and Li (2007) used ANP to find out key selecting criteria for a strategic partner and further to identify the relative importance among the criteria. Lee, Kim, Cho, and Park (2009a) uses ANP to analyze the problem of network technology, to consider the related technology network required, and to seek out the core technology and the characteristics of network technology. Additional recent researches adopted DEMATEL or ANP are Lin et al., 2009a, Hsieh et al., 2008, Lin et al., 2008, Lin et al., 2009b, Lee et al., 2009b and Tzeng et al., 2009, and Li and Tzeng (2009) and others. This study contributes to literature in several ways. First, this paper provides the evidence in applications of ANP and DEMATEL on stock market dynamics, particularly the process of investment decision making. Second, the relations of interdependences among key factors in stock investment are quantitatively analyzed through investigations of experts’ perceptions. Third, theoretical analyzes are confirmed with empirical applications of recent data. Based on the empirical outcomes, the paper finds the methodologies are able to produce robust analyzes in generating valuable and practical investment strategy. The rest of this paper is organized as follows. In Section 2, key existing models of stock investment decision making are reviewed, and in Section 3, the application of ANP and DEMATEL is introduced. In Section 4, empirical outcomes are presented, and Section 5 concludes the research.
نتیجه گیری انگلیسی
Equity stock is a key financial asset of capital market, and researchers have adopted various techniques to analyze factors of its investment decision making. Majority of prior researches discussed the factors independently for their direct effeteness on stock performance, and the interactive impacts between factors were rarely studied. This paper adopts the methods of DEMATEL and ANP to analyze the interdependences between key factors of stock investment decision making. By integrating the dynamic influence relationship obtained by DEMATEL with ANP, levels of direct and interactive impacts for factors are quantified and ranked, and the outcomes are robust to actual performances of sample stocks. The proposed method also simplifies the existing models and raise efficiency without affecting the key outcomes. The empirical results provide evidences of significant interdependent and self-feedback relationships among factors of the three major analytical techniques. The weights of factors are numerically obtained and demonstrate that the most important factor is profitability, followed by growth, local institutional investors, risk, moving average, foreign institutional investors, RSI, trading volume, and operation and asset management. The outcome is identical to results produced by existing process, which is more complex than proposed approach. Individual stocks filtered by the ranked factors show consistent predictions of actual performances. The finding consolidated from mathematical theories and judgments of experts is essentially useful to investors where investment strategy can be specifically constructed according to the importance of factors and lead to better portfolio management.