Internationally cross-listed stock prices during overlapping trading hours: price discovery and exchange rate effects

We analyze exchange rates along with equity quotes for 3 German firms from New York (NYSE) and Frankfurt (XETRA) during overlapping trading hours to see where price discovery occurs and how stock prices adjust to an exchange rate shock. Findings include: (a) the exchange rate is exogenous with respect to the stock prices; (b) exchange rate innovations are more important in understanding the evolution of NYSE prices than XETRA prices; and (c) most (but not all) of the fundamental or random walk component of firm value is determined in Frankfurt.     

Noise trading and stock market volatility

We investigate the relative effects of fundamental and noise trading on the formation of conditional volatility. We find significant positive (negative) effects of investor sentiments on stock returns (volatilities) for both individual and institutional investors. There are greater positive effects of rational sentiments on stock returns than irrational sentiments. Conversely, there are significant (insignificant) negative effects of irrational (rational) sentiments on volatility. Also, we find asymmetric (symmetric) spillover effects of irrational (rational) bullish and bearish sentiments on the stock market. Evidence in favor of irrational sentiments is consistent with the view that investor error is a significant determinant of stock volatilities.     

A common factor analysis for the US and the German stock markets during overlapping trading hours

We employ a bivariate common factor model to establish a permanent-transitory decomposition of two major stock indices (the Deutsche Aktienindex (DAX) for Germany and the Dow Jones Industrial Average (DJIA) for the United States). Using high-frequency data, we (1) identify a common trend shared by both indices, (2) find that the DJIA contributes up to 95% to the total innovation of the common factor, (3) show that both markets adjust within minutes to a system-wide shock, and (4) verify by hypothesis testing that the DJIA is the driving force in the transatlantic system of stock indices.     

Contemporaneous ADR pricing: intraday dynamics during overlapping trading hours

We contribute to the literature by identifying and accurately measuring the drivers of American depositary receipt (ADR) returns contemporaneously across various global time zones. We consider ADRs as two inherently distinct asset classes – stocks and currencies – bundled into one. Throughout, we use a relatively refined, focused, and synchronized minute-by-minute data set on ADRs and all other variables. ADRs from all countries with regular trading hours that overlap with those of the US are considered individually and in clusters. We analyze the interplay of several factors that influence ADRs pricing patterns. Further, we investigate whether such patterns vary by currency, ADR, industry, and emerging/developed market classifications. Our findings indicate that synchronized returns on underlying shares comprise 68.5–74% of the explained returns in ADRs. The remaining 31.5–26% of returns are generated by movements in currency rates. These results are robust across the several models and estimation methods employed. Our findings also show persistent small price discrepancies between ADRs and dollar-adjusted underlying shares on a minute-by-minute basis, implying possible arbitrage opportunities. However, we conclude that trading and ADR conversion costs render such opportunities unattractive.     

Information-based stock trading and managerial incentives: evidence from China's stock market

This paper uses stock price informativeness, or information-based stock trading, to help explain the pay–performance sensitivity (PPS) of chief executive officer (CEO) compensation in China's listed firms. We argue that higher stock price informativeness, which we measure by the probability of informed trading, helps and encourages shareholders to incentivize the top management team based on stock market performance. The regression results support our argument and show that a higher level of stock price informativeness is associated with higher CEO PPSs. Moreover, the impact of stock price informativeness on CEO incentives is stronger for privately controlled listed firms than it is for state-controlled listed firms. The results also hold when information asymmetry is approximated by the accuracy and dispersion of the earnings forecasts made by financial analysts.     

The ex-dividend day stock price anomaly: evidence from the Greek stock market

This paper examines the ex-dividend stock price and trading volume behavior in the Greek stock market for the period 2000–2004. We use both standard event-study methodology and cross-sectional regression analysis in assessing the ex-dividend stock price anomaly. We find that stock prices drop less than the dividend amount. By examining abnormal returns as well as abnormal trading volume around the ex-dividend day, we find strong evidence of short-term trading, which is consistent with the presence of dividend-capturing activities around the ex-dividend day. The results from the cross-sectional regression analysis confirm that the short-term trading hypothesis explains the ex-dividend day stock price anomaly in Greece.

On detection of volatility spillovers in overlapping stock markets

This paper applies a recently proposed structural vector autoregressive model identification method to an established, previously unidentified theoretical model of stock market volatility spillovers. The structural model is identified and can be estimated with the method of maximum likelihood. Volatility spillovers can then be tested with the standard likelihood ratio test. This way our test, unlike the majority of the existing volatility spillover tests, has its foundations firmly in the economic theory. Our test is developed for fully overlapping stock markets. The empirical application of the paper considers stock markets of the eurozone in the years 2010–2011. Evidence of volatility spillovers is found.     

Investor sentiment and stock volatility: New evidence

This study investigates the predictability of sentiment measure on stock realized volatility. We propose a new investor sentiment index (NISI) based on the partial least squares method. This sentiment index outperforms many existing sentiment indicators in three aspects. First, in-sample result shows that the NISI has greater predictive power relative to the others. Most sentiment indicators show predictability in the non-crisis period only while the NISI is also effective in the crisis period. Furthermore, the NISI exhibits more prominent superiority in longer horizons forecasting. Second, further analysis indicates that the NISI has robust predictability before and after the Chinese stock market turbulence periods while the others not. Importantly, the NISI is still effective significantly after considering leverage effect while most of the others not. Finally, out-of-sample analysis demonstrates that the NISI is more powerful than other sentiment measures. This result is reproducible in different robustness checks.     

The macroeconomic determinants of technology stock price volatility

Stock prices reflect the value of anticipated future profits of companies. Since business cycle conditions impact the future profitability of firms, expectations about the business cycle will affect the current value of firms. This paper uses daily and monthly data from July 1986 to December 2000 to investigate the macroeconomic determinants of US technology stock price conditional volatility. Technology share prices are measured using the Pacific Stock Exchange Technology 100 Index. One of the novel features of this paper is to incorporate a link between technology stock price movements and oil price movements. The empirical results indicate that the conditional volatilities of oil prices, the term premium, and the consumer price index each have a significant impact on the conditional volatility of technology stock prices. Conditional volatilities calculated using daily stock return data display more persistence than conditional volatilities calculated using monthly data. These results further our understanding of the interaction between oil prices and technology share prices and should be of use to investors, hedgers, managers, and policymakers.     

Forecasting stock market volatility: Further international evidence

Abstract

This paper evaluates the out-of-sample forecasting accuracy of eleven models for monthly volatility in fifteen stock markets. Volatility is defined as within-month standard deviation of continuously compounded daily returns on the stock market index of each country for the ten-year period 1988 to 1997. The first half of the sample is retained for the estimation of parameters while the second half is for the forecast period. The following models are employed: a random walk model, a historical mean model, moving average models, weighted moving average models, exponentially weighted moving average models, an exponential smoothing model, a regression model, an ARCH model, a GARCH model, a GJR-GARCH model, and an EGARCH model. First, standard (symmetric) loss functions are used to evaluate the performance of the competing models: mean absolute error, root mean squared error, and mean absolute percentage error. According to all of these standard loss functions, the exponential smoothing model provides superior forecasts of volatility. On the other hand, ARCH-based models generally prove to be the worst forecasting models. Asymmetric loss functions are employed to penalize under-/over-prediction. When under-predictions are penalized more heavily, ARCH-type models provide the best forecasts while the random walk is worst. However, when over-predictions of volatility are penalized more heavily, the exponential smoothing model performs best while the ARCH-type models are now universally found to be inferior forecasters.     

Technical trading rules for nonlinear dynamics of stock returns: evidence from the G-7 stock markets

This paper explores a possible link between an asymmetric dynamic process of stock returns and profitable technical trading rules. Using the G-7 stock market indexes, we show that the dynamic process of daily index returns is better characterized by nonlinearity arising from an asymmetric reverting property. The asymmetric reverting property of stock returns is exploitable in generating profitable buy and sells signals for technical trading strategies. The bootstrap analysis shows that not all nonlinearities generate profitable buy and sell signals, but rather only the nonlinearities generating a consistent asymmetrical pattern of return dynamics can be exploitable for the profitability of the trading rules. The significant positive (negative) returns from buy (sell) signals are a consequence of trading rules that exploit the asymmetric nonlinear dynamics of the stock returns that revolve around positive (negative) unconditional mean returns under prior positive (negative) return patterns. Our results corroborate the arguments for the usefulness of technical trading strategies in stock market investments.     

Impact of stock market trading on currency market volatility spillovers

This research aims to detect the volatility linkages among various currencies during operating and non-operating hours of three major stock markets (Tokyo, London and New York) by employing bivariate VAR-BEKK-GARCH model in selected currency pairs. In particular, the aim is to analyze whether the major stock markets have a differential impact on volatility linkages in currency markets. The results indicate that volatility linkages in intraday are far stronger then in daily results. One remarkable result is that rather than major currencies, some minor and exotic currencies play a leading role in volatility transmission during trading hours of major stock markets.     

Index futures and positive feedback trading: evidence from major stock exchanges

This paper tests the hypothesis that the introduction of index futures has increased positive feedback trading in the spot markets of six industrialized nations. The analysis is based on a model that assumes two different groups of investors, i.e., risk averse expected utility maximizing investors and positive feedback traders. There is evidence consistent with positive feedback trading before the introduction of index futures across all markets under investigation. In the period following the introduction of index futures, there is no evidence supporting the hypothesis that positive feedback trading drives short-term dynamics of stock returns. The possibility that this is due to possible migration of feedback traders from the spot to the futures markets is also tested. The results show no evidence of positive feedback trading in the futures markets. Overall, the findings support the view that futures markets help stabilize the underlying spot markets by reducing the impact of feedback traders and thus attracting more rational investors who make the markets more informationally efficient and thus providing investors with superior ways of managing risk.     

Corporate diversification and asymmetric information: evidence from stock market trading characteristics

We examine the relation between firm diversification and asymmetric information empirically using metrics drawn from the market microstructure literature. We find that the average diversified firm in our sample has somewhat less severe asymmetric information problems than a similarly constructed portfolio of stand-alone firms chosen to approximate the segments of the conglomerate. We also find that the information asymmetry of diversified firms is very similar to that of individual focused firms that approximate the conglomerates along several dimensions not including industry composition. We conclude that greater diversification is not on average associated with increased asymmetric information.     

The impact of trading halts on liquidity and price volatility: Evidence from the Australian Stock Exchange

This study examines market behaviour around trading halts associated with information releases on the Australian Stock Exchange, which operates an open electronic limit order book. Using the Lee, Ready and Seguin (1994) pseudo-halt methodology, we find trading halts increase both volume and price volatility. Trading halts also increase bid-ask spreads and reduce market depth at the best-quotes in the immediate post-halt period. The results of this study imply that trading halts impair rather than improve market quality in markets that operate open electronic limit order books.     

Price volatility,welfare, and trading hours in asset markets

This paper studies the consequences of opening asset markets more often for the properties of asset prices and social welfare. For all reasonable parameter values, increasing trading hours lowers average asset prices, increases unconditional asset price volatility at a given point in time, and decreases unconditional asset price volatility when averaged over the period of time that includes the additional hours that markets are open. Unconditional social welfare is increased by opening markets more often, although the welfare gains are small – well below 1% of lifetime consumption. In contrast, because expanding hours of trading affects agents' information sets, the welfare effect of more trading hours conditional on information available to agents can be large and the effect can be negative.     

How candlestick features affect the performance of volatility forecasts: evidence from the stock market

In this study, we used asymmetric GJR-X models to investigate how the return and volatility estimates in the stock market on any given day are affected by the features of the preceding day's candlestick. Empirical results show that, first, for symmetric volatility specification, the upper and lower shadows of yesterday can, respectively, lower and raise the return today, whereas both upper and lower shadows of yesterday can increase today's volatility. Notably, the upper and lower shadows elicited asymmetric responses in the sizes of the volatility and return increments. Conversely, for asymmetric volatility specification, leverage effect may affect the asymmetric response and prevent the upper shadow from influencing the return and volatility. Second, for symmetric volatility specification, the black and white real bodies of yesterday can, respectively, augment and abate today's return and volatility, indicating that the black real body produces a distinct type of leverage effect to influence volatility. Importantly, for asymmetric specification, the effects of the black and white real bodies appear the same as for the symmetric specification, but are less significant. Lastly, the real bodies (or, respectively, asymmetric volatility specification) influenced the accuracy of volatility forecasts more strongly than the upper and lower shadows (or, respectively, symmetric volatility specification).     

Stock price volatility in a multiple security overlapping generations model

A number of empirical studies have reached the conclusion thatstock price volatility cannot be fully explained within thestandard dividend discount model. This article proposes a resolutionbased upon a model that contains both a random supply of riskyassets and finitely lived agents who trade in a multiple securityenvironment. As the analysis shows there exist 2^K equilibriawhen K securities trade. The low volatility equilibria haveproperties analogous to those found in the infinitely livedagent models of Campbell and Kyle (1991) and Wang (1993, 1994).In contrast, the high-volatility equilibria have very differentcharacteristics. Within the high-volatility equilibria verylarge price variances can be generated with very small supplyshocks. Adding securities to the economy further reduces therequired supply shocks. Using previously established empiricalresults the model can reconcile the data with supply shocksthat are less than 10% as large as observed return shocks. Theseresults are shown to hold even when the dividend process ismean reverting.     

Institutional investors and stock returns volatility: Empirical evidence from a natural experiment

In this paper, we provide empirical evidence on the impact of institutional investors on stock market returns dynamics. The Polish pension system reform in 1999 and the associated increase in institutional ownership due to the investment activities of pension funds are used as a unique institutional characteristic. Performing a Markov-switching-GARCH analysis we find empirical evidence that the increase of institutional ownership has temporarily changed the volatility structure of aggregate stock returns. The results are interpretable in favor of a stabilizing effect on index stock returns induced by institutional investors.     

The price adjustment and lead-lag relations between stock returns: microstructure evidence from the Taiwan stock market

This paper investigates the price adjustment and lead-lag relations between returns on five size-based portfolios in the Taiwan stock market. It finds evidence that the price adjustment of small-stock portfolios is not slower than that of large-stock portfolios. Additionally, limited evidence supports a positive leading role of large-stock portfolio returns over small-stock portfolio returns. These two findings are substantially different from the results of previous research on developed markets.