Jump risk and cross section of stock returns: evidence from China’s stock market

Various studies have confirmed the existence of jumps in different financial markets. However, there is sparse theoretical or empirical effort to examine the dynamic relation between jump risk and cross-sectional expected stock returns. We follow a stylized SDF-based diffusion-jump model to examine its testable implications about the relation between cross-section expected excess returns and variations in jump intensities across stocks. The zero-cost portfolio, exploiting the return spreads between the top and bottom decile portfolios formed on jump intensity, could earn an annualized return as high as 24% with an annualized Sharpe ratio of 1.67. A Fama-MacBeth test shows that stock excess returns monotonically decrease in jump intensity even after controlling for other common risk factors.     

Accounting variables and stock returns： Evidence from Istanbul stock exchange

The fundamental relationship between accounting variables and stock returns is a recurring theme in financial research. One of the major purposes of accounting is to help investors provide reliable, comparable and accurate information. If accounting data are informative about fundamental values and changes in values, they should be correlated with stock price changes. This study provides theory and evidence showing how accounting variables explain stock returns and examines the relationship between the stock returns and accounting variables of listed non financial companies in ISE-100 Indice for 2006-2008 period by using panel data methodology. Empirical analysis consists of 192 observations of 64 companies in years 2006-2008 to examine the effects of inventory, accounts receivable, gross margin, operating expense, return on assets, cash flow, leverage, liquidity, price/earnings, return on equity on stock returns. The results of the study confirm that the predicted roles of fundamental factors and stock returns are significantly related to gross margin, cash flow, leverage and equity variables. The model explains about 13.35 % of the variation of annual stock returns with the leverage variable with most of the significant power.     

Determinants of market price of stock： A study on bank leasing and insurance companies of Bangladesh

Financial firms make up a substantial fraction of the domestic equity market. A number of studies subsequently used different conceptual and methodological approaches to model equity return of financial services firms. Movement of the stock price as the consequence of the movement of the micro and macroeconomic factors is strongly supported by the literature review. Dhaka Stock Exchange in Bangladesh is inefficient in weak form. Multiple regression analysis is conducted to find out the relationship microeconomic factors with the stock price. In this study found a significant linear relationship among market return and some microeconomic factors such as net asset value per share, dividend percentage, earning per share of bank leasing and insurance companies. Also found non-linear relationship among the variables is insignificant at 95 percent level of significance.     

When do high‐level managers believe they can influence the stock price? Antecedents of stock price expectancy cognitions

Stock based rewards are often used to motivate high‐level managers to take actions to increase the stock price of the firm. However, numerous constraints may weaken the perceived link between individual effort and stock price appreciation for many recipients. This study introduces a new construct, stock price expectancy, which we define as individuals' perceptions of influence over their firm's stock price. We examined its antecedents in a sample of 349 high‐level U.S. managers and found that employment at corporate headquarters, firm size, hierarchical level, and contact with investment analysts predicted stock price expectancy perceptions. © 2010 Wiley Periodicals, Inc.     

The role of the seller’s stock performance in the market reaction to divestiture announcements

Divestitures have the potential to create shareholder value. However, the extent of the market reaction should depend on the likelihood of finding more valuable uses for the divested assets or the ability on the part of the seller to eliminate negative synergies. We hypothesize that strong performers have less scope to achieve substantial improvements compared to poorly performing firms. Using the seller’s stock return in excess of the market return in the 1-year and 2-year periods preceding the divestiture announcement to expose the divesting firm’s inefficient use of its assets, we show that the market reaction to divestiture announcements is significantly higher for underperforming firms. The difference in abnormal returns can be as high as 4 %. In contrast, none of the accounting-based variables that have been used in previous studies are found to be significantly related to the announcement returns. These results suggest that the firm’s stock performance is a more useful indicator of the wealth effect associated with divestitures.     

The institution efficiency of stock price limits： An experimental analysis on the two stocks market with continuous bid

Price limits in product market have been discarded in classic microeconomics. However, price limits affect the trade behavior of the same agent, since agents in the stock market change their trade status frequently. Due to the controversy on the institution effectiveness of the price limits in stock market, this paper design an experimental market with two stocks with continuous bid, in which we investigate the impact of the price limits on the stock market. The results show that the price limits moderate the price volatility within and between the trades periods, thus can stabilize stock price. In addition, price limits, when measured by traditional approach, restrain the fluidity of the market, reduce the volatility of transaction shares and maintain durative of fluidity. While volatility-based fluidity measurements show that the fluidity is enhanced significantly in stock market with price limits.     

Does weather impact the stock market? Empirical evidence in Taiwan

Psychological evidence suggests close relationships between weather and mood. Individuals feel in a more positive frame of mind on sunny than cloudy days. This study applies GJR–GARCH to examine the relationship among weather, stock returns and risk in Taiwan from 2001 to 2007. The empirical results indicate that precipitation does not significantly influence stock return and risk; likewise, sunshine hours and temperature insignificantly influence stock return, but do significant impact stock risk. These findings demonstrate that weather effect really exist in stock market, and can help investors in making innovative investment and management decisions.     

Time-varying lead–lag structure between investor sentiment and stock market

This paper uses the thermal path method to study the lead–lag structure of sentiment and the stock market. First, based on principal component analysis, four indicators are selected to construct the sentiment index. Furthermore, the effectiveness of the thermal path method is verified by numerical simulation. Finally, the lead-lag characteristics of the Shanghai Stock Index and the sentiment index are studied via the symmetric thermal optimal path method. The analysis results show that in the short term, investor sentiment has a leading position in the stock market, which may be related to the herd effect and buying the winners behavior. However, over a longer period of time, investor sentiment is affected mainly by fluctuation in the market, which may be related to the existence of cyclical fluctuations in the market and futures arbitrage. In addition, the stock market's leading effect appears mainly from January 2006 to January 2012, with an average lead time of one month.     

Are day traders bias free?—evidence from internet stock message boards

This study addresses the issue whether day traders’ recommendations on stocks are biasfree. We test whether on average day traders’ “Hold” sentiment is skewed and different from a neutral opinion. Posted messages and mature text classifier technology provide a novel approach to analyze the content of these “Hold” sentiment postings among day traders. Findings indicate that the self-disclosed “Hold” sentiment conveys an optimistic opinion and significantly differs from neutral. These results help both investors and researchers to better understand day traders’ psychology and behaviors when they recommend stocks. The paper also provides insight into the construction of future online sentiment indexes based on stock message boards.     

Is the liberalization policy effective on improving bivariate cointegration of current accounts, foreign exchange, stock prices? Further evidence from Asian markets

This paper fist examines three set of bivariate cointegrations between any two of current accounts, stock markets, and currency exchange markets in 10 Asian countries. Furthermore, this work examined the effect of country characters on this bivariate cointegration. Our findings suggest that for three sets of cointegration test, each sample country at least exists one cointegration. India consistently exhibited a bi-directional causal relationship between any two of three indicators. Unlike Pan et al. (Int Rev Econ Financ 16:503–520, 2007 and Phylaktis and Ravazzolo (J Int Money Financ 24:1031–1053, 2005), this study found that such cointegration is influenced by three characteristics: capital control; flexibility in foreign exchange rates; and the ratio of trade to GDP. These characteristics are the result of liberalization in each Asian country. This implies that liberalization policies are effective on improving the cointegration between any two of financial markets and current account for 10 Asian countries.     

The 1986–88 stock market: Investor sentiment or fundamentals?

This paper tests the widely held proposition that investor sentiment contributed to the stock market crash of 1987. Using weekly data during the 1986–8 period and conventional measures of stock fundamentals, changes in fundamentals are found to have a statistically significant influence on the movement of stock prices. In addition, a much-discussed measure of investor sentiment is used to test the proposition that investor sentiment contributed to the stock market crash of 1987. However, insignificant results regarding the investor sentiment index suggest that either the recently proposed sentiment index is faulty or investor sentiment did not significantly influence stock prices in the period surrounding the 1987 crash.     

Sovereign rating changes—Do they provide new information for stock markets?

The purpose of this paper is to examine the impact of sovereign rating changes on international financial markets using a comprehensive database of 42 countries, covering the major regions in the world over the period 1995–2003. In general, we find that rating agencies provide stock and foreign exchange markets with new tradable information. Specifically, rating upgrades (downgrades) significantly increased (decreased) USD denominated stock market returns and decreased (increased) volatility. Whereas the mean response is contributed evenly by the local currency stock returns and exchange rate changes that make up the USD returns, only the foreign exchange volatility was behind the USD denominated return volatility. In addition, we find significant asymmetric effects of rating announcements. The market responses – both return and volatility – are more pronounced in the cases of downgrades, foreign currency debt, emerging market debt, and during crisis periods. This study has important policy implications for international investors’ asset allocation plans and for regulatory bodies such as the Basel Committee who increasingly rely upon Moody's, Standard and Poor's and Fitch's ratings for their regulatory regimes.     

Connectedness and risk spillovers in China’s stock market: A sectoral analysis

This paper shows how sectors in the Chinese stock market are connected and investigates risk spillovers across these sectors. Using graph theory and a recently developed time series technique, we are able to identify the systemically important sector in the market and the patterns of risk spillovers across sectors over time. Unlike standard econometric modeling, graph theory enables us to approach this question in a more reader-friendly way. The empirical results show that Industrial sector plays a central role and should thus be considered the systemically most important sector in the Chinese stock market. The spillover structure is found to be time-varying. While Industrial sector dominates the system for most of the time, other sectors such as Consumer Discretionary sector also occasionally appear as the central sector. Our empirical results also indicate that the simple correlation-based approach can produce equally useful information as more advanced econometric models.     

“Speculative Influence Network” during financial bubbles: application to Chinese stock markets

We introduce the Speculative Influence Network (SIN) to decipher the causal relationships between sectors (and/or firms) during financial bubbles. The SIN is constructed in two steps. First, we develop a Hidden Markov Model (HMM) of regime-switching between a normal market phase represented by a geometric Brownian motion and a bubble regime represented by the stochastic super-exponential Sornette and Andersen (Int J Mod Phys C 13(2):171–188, 2002) bubble model. The calibration of the HMM provides the probability at each time for a given security to be in the bubble regime. Conditional on two assets being qualified in the bubble regime, we then use the transfer entropy to quantify the influence of the returns of one asset i onto another asset j, from which we introduce the adjacency matrix of the SIN among securities. We apply our technology to the Chinese stock market during the period 2005–2008, during which a normal phase was followed by a spectacular bubble ending in a massive correction. We introduce the Net Speculative Influence Intensity variable as the difference between the transfer entropies from i to j and from j to i, which is used in a series of rank ordered regressions to predict the maximum loss (%MaxLoss) endured during the crash. The sectors that influenced other sectors the most are found to have the largest losses. There is some predictability obtained by using the transfer entropy involving industrial sectors to explain the %MaxLoss of financial institutions but not vice versa. We also show that the bubble state variable calibrated on the Chinese market data corresponds well to the regimes when the market exhibits a strong price acceleration followed by clear change of price regimes. Our results suggest that SIN may contribute significant skill to the development of general linkage-based systemic risks measures and early warning metrics.     

A bivariate causality between stock prices and exchange rates: evidence from recent Asianflu☆

This paper applies recently developed unit root and cointegration models to determine the appropriate Granger relations between stock prices and exchange rates using recent Asian flu data. Via impulse response functions, it is found that data from South Korea are in agreement with the traditional approach. That is, exchange rates lead stock prices. On the other hand, data of the Philippines suggest the result expected under the portfolio approach: stock prices lead exchange rates with negative correlation. Data from Hong Kong, Malaysia, Singapore, Thailand, and Taiwan indicate strong feedback relations, whereas that of Indonesia and Japan fail to reveal any recognizable pattern. %JEL classification: F300; G150     

Are stock prices related to the political uncertainty index in OECD countries? Evidence from the bootstrap panel causality test

This study applies the bootstrap panel causality test proposed by Kónya (2006. Econ Modell 23, 978) to investigate the causal link between political uncertainty and stock prices for seven OECD countries over the monthly period of 2001.01 to 2013.04. This modeling approach allows us to examine both cross-sectional dependency and country-specific heterogeneity. Our empirical results indicate that not all the countries are alike and that the theoretical prediction that stock prices fall at the announcement of a policy change is not always supported. Specifically, we find evidence for the stock price leading hypothesis for Italy and Spain, while the political uncertainty leading hypothesis cannot be rejected for the United Kingdom and the United States. In addition, the neutrality hypothesis was supported in the remaining three countries (Canada, France and Germany), while no evidence for the feedback hypothesis was found.     

Did Vietnam stock market avoid the “contagion risk” from China and the U.S.? The contagion effect test with dynamic correlation coefficients

This paper examines the Vietnamese stock market with an extension of the recent investigation of risk contagion effects. Daily data spanning October 9, 2006–June 19, 2009 are sourced for the empirical validation of the risk contagion between the stock markets in Vietnam, China, and the U.S. To facilitate the validation of contagion effects with market related coefficients, this paper constructs a bivariable EGARCH model of dynamic condition correlation coefficients. First, we examine whether there are contagion effects when there is a financial crisis in the Vietnamese stock market. Next, we verify whether the contagion risk triggered by the crisis can affect the Vietnamese market and examine which market influences the Vietnamese market the most. We find that compared to the U.S. stock market, the Chinese stock market brings more contagion risk to the Vietnamese market, and these effects gain more significance after the sub-prime mortgage crisis.     

General Situation of the Experiments of Enterprise Groups

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