Relative Distress and Return Distribution Characteristics of Japanese Stocks, a Fuzzy-Probabilistic Approach
In this article, we demonstrate that a direct relation exists between the context of Japanese firms indicating relative distress and conditional return distribution properties. We map cross-sectional vectors with company characteristics on vectors with return feature vectors, using a fuzzy identification technique called Competitive Exception Learning Algorithm (CELA)1. In this study we use company characteristics that follow from capital structure theory and we relate the recognized conditional return properties to this theory. Using the rules identified by this mapping procedure this approach enables us to make conditional predictions regarding the probability of a stock's or a group of stocks' return series for different return distribution classes (actually return indices). Using these findings, one may construct conditional indices that may serve as benchmarks. These would be particularly useful for tracking and portfolio management.
|Keywords||asset pricing, capital structure, conditional return distribution, fuzzy systems, heuristic learning|
|Publisher||Erasmus Research Institute of Management (ERIM)|
van den Bergh, W.M., Steenbeek, O.W., & van den Berg, J.. (2002). Relative Distress and Return Distribution Characteristics of Japanese Stocks, a Fuzzy-Probabilistic Approach (No. ERS-2002-29-F&A). Erasmus Research Institute of Management (ERIM). Retrieved from http://hdl.handle.net/1765/186