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Proceedings ArticleDOI

A Nonlinear Dynamic System in Behavioral Finance: Evidence from Chinese Stock Market

01 Oct 2017-
About: This article is published in International Conference on Management Science and Engineering.The article was published on 2017-10-01 and is currently open access. It has received None citations till now. The article focuses on the topics: Stock market bubble & Stock market.
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Journal ArticleDOI
TL;DR: In this article, the cross spectrum between two variables can be decomposed into two parts, each relating to a single causal arm of a feedback situation, and measures of causal lag and causal strength can then be constructed.
Abstract: There occurs on some occasions a difficulty in deciding the direction of causality between two related variables and also whether or not feedback is occurring. Testable definitions of causality and feedback are proposed and illustrated by use of simple two-variable models. The important problem of apparent instantaneous causality is discussed and it is suggested that the problem often arises due to slowness in recording information or because a sufficiently wide class of possible causal variables has not been used. It can be shown that the cross spectrum between two variables can be decomposed into two parts, each relating to a single causal arm of a feedback situation. Measures of causal lag and causal strength can then be constructed. A generalisation of this result with the partial cross spectrum is suggested.

16,349 citations

Journal ArticleDOI
TL;DR: In this paper, the authors study whether the behavior of stock prices, in relation to size and book-tomarket-equity (BE/ME), reflects the behaviour of earnings and find no link between BE/ME factors in earnings and returns.
Abstract: We study whether the behavior of stock prices, in relation to size and book-tomarket-equity (BE/ME), reflects the behavior of earnings. Consistent with rational pricing, high BE/ME signals persistent poor earnings and low BE/ME signals strong earnings. Moreover, stock prices forecast the reversion of earnings growth observed after firms are ranked on size and BE/ME. Finally, there are market, size, and BE/ME factors in earnings like those in returns. The market and size factors in earnings help explain those in returns, but we find no link between BE/ME factors in earnings and returns. FAMA AND FRENCH (1992) FIND that two variables, market equity (ME) and the ratio of book equity to market equity (BE/ME) capture much of the crosssection of average stock returns. If stocks are priced rationally, systematic differences in average returns are due to differences in risk. Thus, with rational pricing, size (ME, stock price times shares outstanding) and BE/ME must proxy for sensitivity to common risk factors in returns. Fama and French (1993) confirm that portfolios constructed to mimic risk factors related to size and BE/ME add substantially to the variation in stock returns explained by a market portfolio. Moreover, a three-factor asset-pricing model that includes a market factor and risk factors related to size and BE/ME seems to capture the cross-section of average returns on U.S. stocks. The evidence that size and book-to-market-equity proxy for sensitivity to risk factors in returns is consistent with a rational-pricing story for the role of size and BE/ME in average returns. But return tests cannot tell a complete economic story. Size and BE/ME remain arbitrary indicator variables that, for unexplained economic reasons, are related to risk factors in returns. The goal here is to begin to fill this economic void. Specifically, we study whether the behavior of stock prices, in relation to size and book-tomarket-equity, is consistent with the behavior of earnings. We first ask whether stock prices properly reflect differences in the evolution of profitability when stocks are grouped on size and BE/ME. We confirm that, as predicted by simple rational-pricing models, BE/ME is related to

3,590 citations

Journal ArticleDOI
TL;DR: In this article, the authors develop a top-down approach to measure investor sentiment and quantify its effects, and show that it is quite possible to measure sentiment and that waves of sentiment have clearly discernible, important, and regular effects on individual firms and on the stock market as a whole.
Abstract: Investor sentiment, defined broadly, is a belief about future cash flows and investment risks that is not justified by the facts at hand. The question is no longer whether investor sentiment affects stock prices, but how to measure investor sentiment and quantify its effects. One approach is "bottom up," using biases in individual investor psychology, such as overconfidence, representativeness, and conservatism, to explain how individual investors underreact or overreact to past returns or fundamentals. The investor sentiment approach that we develop in this paper is, by contrast, distinctly "top down" and macroeconomic: we take the origin of investor sentiment as exogenous and focus on its empirical effects. We show that it is quite possible to measure investor sentiment and that waves of sentiment have clearly discernible, important, and regular effects on individual firms and on the stock market as a whole. The top-down approach builds on the two broader and more irrefutable assumptions of behavioral finance -- sentiment and the limits to arbitrage -- to explain which stocks are likely to be most affected by sentiment. In particular, stocks that are difficult to arbitrage or to value are most affected by sentiment.

2,147 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigate investor sentiment and its relation to near-term stock market returns and find that many commonly cited indirect measures of sentiment are related to direct measures (surveys) of investor sentiment.

896 citations

Journal ArticleDOI
TL;DR: In this paper, a nonparametric test for Granger non-causality was proposed to avoid the over-rejection observed in the frequently used test proposed by Hiemstra and Jones [1994].

794 citations