What explains the investment anomaly in the Chinese stock market?

2017 ◽  
Vol 8 (4) ◽  
pp. 495-520 ◽  
Author(s):  
Jieting Chen
Keyword(s):  
Risk Factor ◽  
Stock Market ◽  
Risk Premium ◽  
Regime Switching ◽  
Expected Returns ◽  
Chinese Stock Market ◽  
Content Type ◽  
Switching Model ◽  
Market Regimes ◽  
Markov Regime Switching Model

Purpose This paper aims to examine the Chinese investment anomaly and dissect it from a perspective of rational expectation framework. Design/methodology/approach Characteristic-based sorting and Fama–MacBeth two-stage cross-sectional regression are adopted to test the relationship between corporate investment and expected returns in both portfolio and individual stock levels. Under the framework of pricing kernels, an investment-based common risk factor is constructed to test the role of risk played in the negative investment-return relationship. Moreover, a Markov regime switching model is adopted to investigate the time-varying risk premium across market regimes. Findings Empirical results provide ample evidence showing that there is a negative relationship between investment and expected returns in the Chinese stock market. The new investment-based risk factor is found to capture the return differences across characteristic-based portfolios. In addition, risk premium of the new risk factor is not only statistically positive throughout the sample period, but also has an asymmetry that is higher during market downturn but lower under bull market. Research limitations/implications This paper merely tests the hypotheses derived from rational school. Practical implications Investment strategies based on characteristic-sorted portfolios should be adjusted to different market regimes. Originality/value First, this paper provides comprehensive empirical results by adopting different methodologies for investigating the investment anomaly in China. Second, an investment-based factor is constructed specifically for the Chinese stock market for the first time. Finally, this is the first paper to investigate the asymmetric risk premium across the Chinese bear and bull regimes by using a multivariate Markov regime switching model.

Hybrid Balanced Justified Treynor ratio

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saeid Tajdini ◽  
Mohsen Mehrara ◽  
Reza Tehrani
Keyword(s):  
Regime Switching ◽  
Weighted Average ◽  
First Grade ◽  
Weighted Averaging ◽  
Markov Switching Model ◽  
Final Model ◽  
Content Type ◽  
Switching Model ◽  
The Third ◽  
Markov Regime Switching Model

PurposeRisk and return are the most important components in the financial and investment world and the existence of a better balance between them with the goal of the best solution for investing in different assets has always been studied and discussed by researchers. For this purpose in this study introduced the Hybrid Balanced Justified Treynor ratio (HBJTR) criterion.Design/methodology/approachThis study introduced the HBJTR criterion, which has three major attributes, including combination of both the frequency and severity of the risk using Markov regime switching model which was modeled on the Justified Beta (Jßi). The second is the merger of data of both the cycles of boom and recession, which was modeled on the Hybrid Justified Treynor Ratio (HJTR). The third was the balancing act in two periods of boom and recession, which was introduced on the HBJTR model.FindingsBased on a weighted averaging of the Justified Treynor ratio of both the cycles of boom and recession, which was introduced by the HJTR term in this study, the superiority in the first grade related to the two indexes were sugar index (0.0096) and insurance index (0.0053). Finally, using the final model in this study, namely HBJTR, the overall advantage was the defensive index, i.e. the insurance index of 1.23.Originality/valueIn other words, the HBJTRi criterion consists of three steps: first, the Justified Beta (Jßi) and Justified Treynor ratio of each index using two regimes of Markov switching model were calculated for each of the cycles of boom and recession separately according to formulas 8 and 9. In the second step, the weighted average was taken from both Justified Treynor ratios of boom and recession cycles, which was called the HJTR. In the third step, to calculate the HBJTR criterion

Do global sentiment shocks spillover towards emerging and frontier markets?

2020 ◽  
Vol 47 (3) ◽  
pp. 433-465 ◽  
Author(s):  
Mobeen Ur Rehman ◽  
Nicholas Apergis
Keyword(s):  
Stock Market ◽  
Regime Switching ◽  
Linear Models ◽  
Market Returns ◽  
Markov Regime Switching ◽  
Stock Market Returns ◽  
Content Type ◽  
Regime Switching Model ◽  
Switching Model ◽  
Investor Sentiments

PurposeThis study aims to investigate the impact of sentiment shocks based on US investor sentiments, bearish and bullish market conditions. Earlier studies, though very few, only consider the effect of investor sentiments on stock returns of emerging frontier Asian (EFA) markets.Design/methodology/approachThis study uses the application of regime switching model because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in this study’s case, thereby adjusting investor sentiments shocks to stock market returns.FindingsThe results of the Markov regime switching method suggests that US sentiment, bullish and bearish market shocks act as a main contributors for inducing variation in EFA stock market returns. The study’s non-parametric robustness results highlight an asymmetric relationship across the mean series, whereas a symmetric relationship across variance series. The study also reports Thailand as the most sensitive market to global sentiment shocks.Research limitations/implicationsThe sensitivity of the EFA markets to these global sentiment shocks highlights their sensitivity and implications for investors relying merely on returns correlation and spillover. These findings also suggest that spillover from developed to emerging and frontier equity markets only in the form of returns following traditional linear models may not be appropriate.Practical implicationsThis paper supports the behavioral aspect of investors and resultant spillover from developed market sentiments to emerging and frontier market returns across international equity markets offering more rational justification for an irrational behavior.Originality/valueThe study’s motivation to use the application of regime switching models is because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in the study’s case, thereby adjusting investor sentiments shocks to stock market returns. It is also useful of the adjustment attributable to exogenous events.

Evidence on aggregate volatility risk premium for the French stock market

2019 ◽  
Vol 46 (1) ◽  
pp. 72-91
Author(s):  
Amal Zaghouani Chakroun ◽  
Dorra Mezzez Hmaied
Keyword(s):  
Risk Factor ◽  
Stock Market ◽  
Risk Premium ◽  
Factor Model ◽  
Excess Returns ◽  
Time Series Regression ◽  
Volatility Risk ◽  
Content Type ◽  
Volatility Risk Premium ◽  
Fama And French

Purpose The purpose of this paper is to examine alternative six- and seven-factor equity pricing models directed at capturing a new factor, aggregate volatility, in addition to market, size, book to market, profitability, investment premiums of the Fama and French (2015) and Fama and French’s (2018) aggregate volatility augmented model. Design/methodology/approach The models are tested using a time series regression and Fama and Macbeth’s (1973) methodology. Findings The authors show that both six- and seven-factor models best explain average excess returns on the French stock market. In fact, the authors outperform Fama and French’s (2018) model. The authors use sensitivity of aggregate volatility of a stock VCAC as a proxy to construct the aggregate volatility risk factor. The spanning tests suggest that Fama and French’s (1993, 2015, 2018) and Carhart’s (1997) models do not explain the aggregate volatility risk factor FVCAC. The results show that the FVCAC factor earns significant αs across the different multifactor models and even after controlling for the exposure to all the other in Fama and French’s (2018) model. The asset pricing tests show that it is systematically priced. In fact, the authors find a significant and negative (positive) relation between the aggregate volatility risk factor and the excess returns in the French stock market when it is rising (falling), in addition, periods with downward market movements tend to coincide with high volatility. Originality/value The authors contribute to the related literature in several ways. First, the authors test two new empirical six- and seven-factor model and the authors compare them to Fama and French’s (2018) model. Second, the authors give new evidence about the VCAC, using it for the first time to the authors’ knowledge, to construct a volatility risk premium.

Investor attention is a risk pricing factor? Evidence from Chinese investors for self-selected stocks

2019 ◽  
Vol 10 (1) ◽  
pp. 95-112 ◽  
Author(s):  
Dayong Dong ◽  
Keke Wu
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Risk Premium ◽  
Significant Risk ◽  
Chinese Stock Market ◽  
Investor Attention ◽  
Recognition Mechanism ◽  
Content Type ◽  
Exposure Factor ◽  
Risk Pricing

Purpose The purpose of this paper is to empirically examine whether investor attention is a significant risk pricing factor. Design/methodology/approach Using investor attention data from Eastmoney.com, which provides for each stock the number of investors whose watch list includes that stock on a daily basis, this paper constructs a “heat” factor based on the change in investor attention and a “market exposure” factor based on the proportion of attention on a given stock over the attention to all stocks. Using the Fama−MacBeth two-step regression and a rolling analysis, this study examines the ability of the investor attention factor to explain market returns. Findings The empirical results show that there exists a risk premium for the “heat” factor and “market exposure” factor that is significantly different from zero. This finding shows that investor attention can systematically influence stock returns, making it a significant risk pricing factor. Practical implications This paper’s research on the risk pricing factors of investor attention can help investors to rationally build investment portfolios, avoid risks and form a sound investment concept, which will further reveal the information recognition mechanism of the capital market and standardize the information disclosure behavior of listed companies. Originality/value This paper provides evidence that investor attention is a risk pricing factor for the stock market. There are “heat” factors and “market exposure” factors in the Chinese stock market that significantly affect the purchasing behavior of individual investors.

Financial flexibility, managerial efficiency and firm life cycle on firm performance

2019 ◽  
Vol 16 (2) ◽  
pp. 168-180
Author(s):  
Heng-Yu Chang ◽  
Chun-Ai Ma
Keyword(s):  
Life Cycle ◽  
Firm Performance ◽  
Stock Market ◽  
Life Cycles ◽  
Mature Stage ◽  
Chinese Stock Market ◽  
Financial Flexibility ◽  
Content Type ◽  
Listed Firms ◽  
Managerial Efficiency

Purpose As the capital market in China is still developing, several constraints on a Chinese-listed firm’s financing strategy have a direct impact on its financial flexibility. The purpose of this paper is to reconstruct traditional financial flexibility index (FFI) derived from the western context, provide empirical evidence within eastern context by modified FFI and examine how the managerial efficiency of Chinese-listed firms is demonstrated with modified FFI to escort corporate life cycle hypothesis. Design/methodology/approach By tailored FFI to fit the contemporary operations of Chinese-listed firms, this study investigates how managerial efficiency varies across different life stages to demonstrate the moderating power in the firm performance of financially flexible firm. Findings It is found that financially flexible firms in the Chinese stock market generally experience good firm performance, yet the managerial efficiency could gradually be diminishing at their mature stage even firms’ financial flexibility remains consistent with the agency theory. This paper sheds light on the necessity to reexamine the components in financial flexibility based on the eastern context, and provides avenue to further understand the managerial behavior of Chinese listed firms when considering firm life cycles. Research limitations/implications Although it is difficult for this current study to offer the precise weights on each factor in calculating financial flexibility, the judgment matrix method is adopted to at least provide reliable estimates in accordance with Chinese business contexts with less than 10 percent errors in contrast to the actual weights. Practical implications This modified FFI is particularly suitable for Chinese-listed firms under certain unique financial reporting regulations by adjusting a number of weights and factors. This study may help practitioners understand the managerial conduct of publicly listed firms in China. Originality/value The paper constructs a modified FFI with Chinese stock market characteristics embedded, and provides insightful evidence to explain the new pecking order theory by considering the life cycle stage of Chinese-listed companies.

scholarly journals Asymmetric Reactions of China’s Stock Market to Short-Term Interest Rates

2016 ◽  
Vol 8 (5) ◽  
pp. 260 ◽  
Author(s):  
Fang Fang ◽  
Weijia Dong ◽  
Xin Lv
Keyword(s):  
Stock Market ◽  
Interest Rates ◽  
Stock Returns ◽  
Regime Switching ◽  
Developed Countries ◽  
Short Term ◽  
Bear Market ◽  
Bull Market ◽  
Negative Effect ◽  
Markov Regime Switching Model

This paper investigates how China’s stock market reacts to short-term interest rates, as represented by the Shanghai Interbank Offered Rate (Shibor). We adopt the Markov Regime Switching model to divide China’s stock market into Medium, Bull and Bear market; and then examine how Shibor influences market returns and risk in different market regimes. We find that short-term interest rates have a significant negative effect on stock returns in Medium and Bull market, but could not affect stock returns in Bear market. In addition, different maturities of Shibor have different effects on stock returns. Furthermore, we find that the short-term interest rates have a negative effect on market risk in Bull market, but a positive effect in Bear market. Our findings show that China’s market is quite peculiar and distinctive from the U.S. market or other developed countries’ markets in many ways.

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