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Return Volatility (return + volatility)
Kinds of Return Volatility Selected AbstractsHow Persistent is Stock Return Volatility?JOURNAL OF BUSINESS FINANCE & ACCOUNTING, Issue 5-6 2007An Answer with Markov Regime Switching Stochastic Volatility Models Abstract:, We propose generalised stochastic volatility models with Markov regime changing state equations (SVMRS) to investigate the important properties of volatility in stock returns, specifically high persistence and smoothness. The model suggests that volatility is far less persistent and smooth than the conventional GARCH or stochastic volatility. Persistent short regimes are more likely to occur when volatility is low, while far less persistence is likely to be observed in high volatility regimes. Comparison with different classes of volatility supports the SVMRS as an appropriate proxy volatility measure. Our results indicate that volatility could be far more difficult to estimate and forecast than is generally believed. [source] On the Quantile Regression Based Tests for Asymmetry in Stock Return VolatilityASIAN ECONOMIC JOURNAL, Issue 2 2002Beum-Jo Park This paper attempts to examine whether the asymmetry of stock return volatility varies with the level of volatility. Thus, quantile regression based tests (,-tests) are presupposed. These tests differ from the diagnostic tests introduced by Engle and Ng (1993) insofar as they can provide a complete picture of asymmetries in volatility across quantiles of variance distribution and, in case of non-normal errors, they have improved power due to their robustness against non-normality. A small Monte Carlo evidence suggests that the Wald and likelihood ratio (LR) tests out of ,-tests are reasonable, showing that they outperform the Lagrange multiplier (LM) test based on least squares residuals when the innovations exhibit heavy tail. Using the normalized residuals obtained from AR(1)-GARCH(1, 1) estimation, the test results demonstrated that only the TOPIX out of six stock-return series had asymmetry in volatility at moderate level, while all stock return series except the FAZ and FA100 had more significant asymmetry in volatility at higher levels. Interestingly, it is clear from the empirical findings that, like hypothesis of leverage effects, volatility of the TOPIX, CAC40, and, MIB tends to respond significantly to extremely negative shock at high level, but is not correlated with any positive shock. These might be valuable findings that have not been seriously considered in past research, which has focussed only on mean level of volatility. [source] The Impact of Trade Characteristics on Stock Return Volatility: Evidence from the Australian Stock Exchange,ASIA-PACIFIC JOURNAL OF FINANCIAL STUDIES, Issue 2 2009Alex Frino Abstract This study examines the impact of trade characteristics on stock return volatility. Using a sample of transaction data from the Australian Stock Exchange, the trading frequency of medium sized trades is found to have the greatest impact on stock return volatility. The result lends support to the stealth trading hypothesis (Barclay and Warner, 1993). After controlling for trading frequency, the average trade size is found to have little explanatory power on price volatility. Stock return volatility is more sensitive to buyer-initiated trades than seller-initiated trades, especially so for buyer-initiated medium sized trades. This finding is consistent with the assertion that information effects are stronger for buys than for sells (Chan and Lakonishok, 1993). [source] Timing and the Holding Periods of Institutional Real EstateREAL ESTATE ECONOMICS, Issue 2 2003David Collett Literature on investors' holding periods for securities suggests that high transaction costs are associated with longer holding periods. Return volatility, by contrast, is associated with shorter holding periods. In real estate, high transaction costs and illiquidity imply longer holding periods. Research on depreciation and obsolescence suggests that there might be an optimal holding period. Sales rates and holding periods for U.K. institutional real estate are analyzed, using a proportional hazards model, over an 18-year period. The results show longer holding periods than those claimed by investors, with marked differences by type of property and over time. The results shed light on investor behavior. [source] Modeling and Forecasting Realized VolatilityECONOMETRICA, Issue 2 2003Torben G. Andersen We provide a framework for integration of high,frequency intraday data into the measurement, modeling, and forecasting of daily and lower frequency return volatilities and return distributions. Building on the theory of continuous,time arbitrage,free price processes and the theory of quadratic variation, we develop formal links between realized volatility and the conditional covariance matrix. Next, using continuously recorded observations for the Deutschemark/Dollar and Yen/Dollar spot exchange rates, we find that forecasts from a simple long,memory Gaussian vector autoregression for the logarithmic daily realized volatilities perform admirably. Moreover, the vector autoregressive volatility forecast, coupled with a parametric lognormal,normal mixture distribution produces well,calibrated density forecasts of future returns, and correspondingly accurate quantile predictions. Our results hold promise for practical modeling and forecasting of the large covariance matrices relevant in asset pricing, asset allocation, and financial risk management applications. [source] Fractional integration in agricultural futures price volatilities revisitedAGRICULTURAL ECONOMICS, Issue 1 2009Peter S. Sephton Conditional volatility; Fractional integration; Long-memory Abstract Jin and Frechette (2004) examined the degree to which agricultural price volatilities exhibited evidence of fractional integration and concluded it was important to consider both long-run and short-run memory when modeling conditional variances. The purpose of this note is to revisit the issue using new methods and techniques which generally reaffirm the view that return volatilities are fractionally integrated and conditionally heteroskedastic, with many exhibiting significant leverage effects, a result not previously reported. [source] Implied volatility forecasts in the grains complexTHE JOURNAL OF FUTURES MARKETS, Issue 10 2002David P. Simon This article finds that the implied volatilities of corn, soybean, and wheat futures options 4 weeks before option expiration have significant predictive power for the underlying futures contract return volatilities through option expiration from January 1988 through September 1999. These implied volatilities also encompass the information in out-of-sample seasonal Glosten, Jagannathan, and Runkle (GJR;1993) volatility forecasts. Evidence also demonstrates that when corn-implied volatility rises relative to out-of-sample seasonal GJR volatility forecasts, implied volatility substantially overpredicts realized volatility. However, simulations of trading rules that involve selling corn option straddles when corn-implied volatility is high relative to out-of-sample GJR volatility forecasts indicate that none of the trading rules would have been significantly profitable. This finding suggests that these options are not necessarily overpriced. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:959,981, 2002 [source] FINANCIAL CRISES AND INTERNATIONAL STOCK MARKET VOLATILITY TRANSMISSIONAUSTRALIAN ECONOMIC PAPERS, Issue 3 2010INDIKA KARUNANAYAKE This paper examines the interplay between stock market returns and their volatility, focusing on the Asian and global financial crises of 1997,98 and 2008,09 for Australia, Singapore, the UK, and the US. We use a multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model and weekly data (January 1992,June 2009). Based on the results obtained from the mean return equations, we could not find any significant impact on returns arising from the Asian crisis and more recent global financial crises across these four markets. However, both crises significantly increased the stock return volatilities across all of the four markets. Not surprisingly, it is also found that the US stock market is the most crucial market impacting on the volatilities of smaller economies such as Australia. Our results provide evidence of own and cross ARCH and GARCH effects among all four markets, suggesting the existence of significant volatility and cross volatility spillovers across all four markets. A high degree of time-varying co-volatility among these markets indicates that investors will be highly unlikely to benefit from diversifying their financial portfolio by acquiring stocks within these four countries only. [source] The relation between implied and realised volatility in the Danish option and equity marketsACCOUNTING & FINANCE, Issue 3 2001Charlotte Strunk Hansen We show that the conclusions to be drawn concerning the informational efficiency of illiquid options markets depend critically on whether one carefully recognises and appropriately deals with the econometrics of the errors-in-variables problem. This paper examines the information content of options on the Danish KFX share index. We consider the relation between the volatility implied in an option's price and the subsequently realised index return volatility. Since these options are traded infrequently and in low volumes, the errors-in-variables problem is potentially large. We address the problem directly using instrumental variables techniques. We find that when measurement errors are controlled for, call option prices even in this very illiquid market contain information about future realised volatility over and above the information contained in historical volatility. [source] Forecasting financial volatility of the Athens stock exchange daily returns: an application of the asymmetric normal mixture GARCH modelINTERNATIONAL JOURNAL OF FINANCE & ECONOMICS, Issue 4 2010Anastassios A. Drakos Abstract In this paper we model the return volatility of stocks traded in the Athens Stock Exchange using alternative GARCH models. We employ daily data for the period January 1998 to November 2008 allowing us to capture possible positive and negative effects that may be due to either contagion or idiosyncratic sources. The econometric analysis is based on the estimation of a class of five GARCH models under alternative assumptions with respect to the error distribution. The main findings of our analysis are: first, based on a battery of diagnostic tests it is shown that the normal mixture asymmetric GARCH (NM-AGARCH) models perform better in modeling the volatility of stock returns. Second, it is shown that with the use of the Kupiec's tests for in-sample and out-of-sample forecasting performance the evidence is mixed as the choice of the appropriate volatility model depends on the trading position under consideration. Third, at the 99% confidence interval the NM-AGARCH model with skewed Student-distribution outperforms all other competing models both for in-sample and out-of-sample forecasting performance. This increase in predictive performance for higher confidence intervals of the NM-AGARCH model with skewed Student-distribution makes this specification consistent with the requirements of the Basel II agreement. Copyright © 2010 John Wiley & Sons, Ltd. [source] What determines transaction costs in foreign exchange markets?INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS, Issue 1 2008Tarun Ramadorai Abstract Using detailed data on the currency transactions of institutional fund managers, this paper shows that funds that experience high returns on their currency holdings also incur lower transaction costs on their currency trades. This finding holds both in the cross section, i.e. funds that perform better on average incur lower average transaction costs, as well as in time series, i.e. funds that do better over the past two months incur lower transaction costs on subsequent transactions. The results are consistent with foreign exchange dealers bidding for information from successful traders. They are also consistent with foreign exchange dealers exploiting price inelastic demand for foreign currency trades, or funds acting as secondary liquidity providers in foreign exchange markets. The paper also investigates the role of fund size, transaction frequency and return volatility on transactions costs. Copyright © 2007 John Wiley & Sons, Ltd. [source] CREATING VALUE IN PENSION PLANS (OR, GENTLEMEN PREFER BONDS)JOURNAL OF APPLIED CORPORATE FINANCE, Issue 4 2003Jeremy Gold Pension funds are typically one-half to two-thirds invested in equities because equities are expected to outperform other financial assets over the long term, and the long-term nature of pension fund liabilities seems well suited to absorbing any short-term return volatility. What's more, U.S. GAAP currently makes it possible to take credit in advance for the higher anticipated earnings on equity investments without acknowledging their inherent risk. But by allowing the higher expected returns from stocks to reduce a company's current pension expenses, the accounting treatment conflicts with some very basic principles of finance (in particular, the idea that investors must earn higher returns on riskier investments just to "break even"), conceals systematic biases in the actuarial analysis, and gives managers considerable latitude to manipulate the bottom line. The authors suggest a startlingly different approach. They argue that pension assets should be invested entirely in duration-matched debt instruments for two reasons: (1) to capture the full tax benefits of pre-funding their pension obligations and (2) to improve overall corporate risk profiles by converting general stock market risk into firm-specific operating risk, where corporate managers should have a comparative advantage and can generate real value. Investing exclusively in bonds would take better advantage of the tax-exempt status of pension plans and greatly reduce fund management costs, while at the same time helping o shore up fund quality and sharpening corporate executives' focus on their real operating assets. [source] Realising the future: forecasting with high-frequency-based volatility (HEAVY) modelsJOURNAL OF APPLIED ECONOMETRICS, Issue 2 2010Professor Neil Shephard This paper studies in some detail a class of high-frequency-based volatility (HEAVY) models. These models are direct models of daily asset return volatility based on realised measures constructed from high-frequency data. Our analysis identifies that the models have momentum and mean reversion effects, and that they adjust quickly to structural breaks in the level of the volatility process. We study how to estimate the models and how they perform through the credit crunch, comparing their fit to more traditional GARCH models. We analyse a model-based bootstrap which allows us to estimate the entire predictive distribution of returns. We also provide an analysis of missing data in the context of these models. Copyright © 2010 John Wiley & Sons, Ltd. [source] CEO Stock Options and Equity Risk IncentivesJOURNAL OF BUSINESS FINANCE & ACCOUNTING, Issue 1-2 2006Melissa A. Williams Abstract: We test the hypothesis that the risk incentive effects of CEO stock option grants motivate managers to take on more risk than they would otherwise. Using a sample of mergers we document that the ratio of post- to pre-merger stock return variance is positively related to the risk incentive effect of CEO stock option compensation but this relationship is conditioned on firm size, with firm size having a moderating effect on the risk incentive effect of stock options. Using a broader time-series cross-sectional sample of firms we find a strong positive relationship between CEO risk incentive embedded in the stock options and subsequent equity return volatility. As in the case of the merger sample, this relationship is stronger for smaller firms. [source] The predictive value of temporally disaggregated volatility: evidence from index futures marketsJOURNAL OF FORECASTING, Issue 8 2008Nicholas Taylor Abstract This paper examines the benefits to forecasters of decomposing close-to-close return volatility into close-to-open (nighttime) and open-to-close (daytime) return volatility. Specifically, we consider whether close-to-close volatility forecasts based on the former type of (temporally aggregated) data are less accurate than corresponding forecasts based on the latter (temporally disaggregated) data. Results obtained from seven different US index futures markets reveal that significant increases in forecast accuracy are possible when using temporally disaggregated volatility data. This result is primarily driven by the fact that forecasts based on such data can be updated as more information becomes available (e.g., information flow from the preceding close-to-open/nighttime trading session). Finally, we demonstrate that the main findings of this paper are robust to the index futures market considered, the way in which return volatility is constructed, and the method used to assess forecast accuracy. Copyright © 2008 John Wiley & Sons, Ltd. [source] Bias in the estimation of non-linear transformations of the integrated variance of returnsJOURNAL OF FORECASTING, Issue 7 2006Richard D. F. Harris Abstract Volatility models such as GARCH, although misspecified with respect to the data-generating process, may well generate volatility forecasts that are unconditionally unbiased. In other words, they generate variance forecasts that, on average, are equal to the integrated variance. However, many applications in finance require a measure of return volatility that is a non-linear function of the variance of returns, rather than of the variance itself. Even if a volatility model generates forecasts of the integrated variance that are unbiased, non-linear transformations of these forecasts will be biased estimators of the same non-linear transformations of the integrated variance because of Jensen's inequality. In this paper, we derive an analytical approximation for the unconditional bias of estimators of non-linear transformations of the integrated variance. This bias is a function of the volatility of the forecast variance and the volatility of the integrated variance, and depends on the concavity of the non-linear transformation. In order to estimate the volatility of the unobserved integrated variance, we employ recent results from the realized volatility literature. As an illustration, we estimate the unconditional bias for both in-sample and out-of-sample forecasts of three non-linear transformations of the integrated standard deviation of returns for three exchange rate return series, where a GARCH(1, 1) model is used to forecast the integrated variance. Our estimation results suggest that, in practice, the bias can be substantial.,,Copyright © 2006 John Wiley & Sons, Ltd. [source] Market Efficiency and Return Statistics: Evidence from Real Estate and Stock Markets Using a Present-Value ApproachREAL ESTATE ECONOMICS, Issue 2 2001Yuming Fu This paper develops a methodology to identify asset price response to news in the framework of the Campbell,Shiller log-linear present-value equation. We further show that a slow price adjustment in real estate markets not only induces a high serial autocorrelation in excess returns, but also dampens the return volatility and the correlation with excess returns in other asset markets. Using Hong Kong real estate and stock market data, we find that the quarterly real estate price assimilates only about half the effect of market news, whereas the quarterly stock price incorporates the news fully. Our analysis identifies a cumulative price adjustment that recovers lost information in real estate returns due to market inefficiency and thereby restores the real estate return volatility and the correlation between real estate and stock markets. [source] Stock Valuation and Learning about ProfitabilityTHE JOURNAL OF FINANCE, Issue 5 2003PÁstor We develop a simple approach to valuing stocks in the presence of learning about average profitability. The market-to-book ratio (M/B) increases with uncertainty about average profitability, especially for firms that pay no dividends. M/B is predicted to decline over a firm's lifetime due to learning, with steeper decline when the firm is young. These predictions are confirmed empirically. Data also support the predictions that younger stocks and stocks that pay no dividends have more volatile returns. Firm profitability has become more volatile recently, helping explain the puzzling increase in average idiosyncratic return volatility observed over the past few decades. [source] How potent are news reversals?: Evidence from the futures marketsTHE JOURNAL OF FUTURES MARKETS, Issue 1 2009Arjun Chatrath A theoretical model is presented, which predicts a heightening in return volatility following a news reversal. A reversal occurs when a value of an economic indicator that is larger than the forecasted value is followed in the following month by a value smaller than the forecasted value, or vice versa. The model also suggests that the effects of a news reversal will be more pronounced early in the monthly macroeconomic news cycle. The predictions of the model for trading activity are less clear. The main predictions of the model were tested employing intraday data for the nearby Treasury bond futures contract. Consistent with the model, the data show significantly greater responses in volatility per standard-deviation surprise when there is a news reversal, than otherwise. Further, the increased sensitivity in volatility is especially perceptible early in the announcement cycle. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 29:42,73, 2009 [source] The stock closing calland futures price behavior: Evidence from the Taiwan futures marketTHE JOURNAL OF FUTURES MARKETS, Issue 10 2007Hsiu-Chuan Lee This study examines the behavior of futures prices around stock market close before and after changes to the batching period of the stock closing call. On July 1, 2002, the Taiwan Stock Exchange expanded the length of the batching period roughly 10-fold, from an average of 30 seconds to 5 minutes. This change presents an opportunity to analyze how a stock closing method affects the behavior of index futures prices. Empirical results indicate that an increase in the length of the batching period affects the return volatility and trading volume of index futures contracts around stock market close. Furthermore, preclose stock returns have a great impact on extended futures returns when the batching period of the stock closing call is long. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:1003,1019, 2007 [source] Intradaily periodicity and volatility spillovers between international stock index futures marketsTHE JOURNAL OF FUTURES MARKETS, Issue 6 2005Chunchi Wu This paper examines short-run information transmission between the U.S. and U.K. markets using the S&P 500 and FTSE 100 index futures. Ultrahighfrequency futures data are employed,which have a number of advantages over the low-frequency spot data commonly used in previous studies,in establishing that volatility spillovers are in fact bidirectional. The generalized autoregressive conditionally heteroskedastic model (GARCH) is employed to estimate the mean and volatility spillovers of intraday returns. A Fourier flexible function is utilized to filter the intradaily periodic patterns that induce serial correlation in return volatility. It was found that estimates of volatility persistence and speed of information transmission are seriously affected by intradaily periodicity. The bias in parameter estimation is removed by filtering out the intradaily periodic component of the transaction data. Contrary to previous findings, there is evidence of spillovers in volatility between the U.S. and U.K. markets. Results indicate that the volatility of the U.S. market is affected by the most recent volatility surprise in the U.K. market. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:553,585, 2005 [source] Testing the mixture-of-distributions hypothesis using "realized" volatilityTHE JOURNAL OF FUTURES MARKETS, Issue 7 2003James C. Luu The mixture-of-distributions hypothesis (MDH) posits that price volatility and trading volume are both subordinated to the same information arrival rate or "news" process. Existing studies that test MDH have the problem that both the information arrival rate and volatility are unobservable. Recent work (e.g., Andersen et al., 2001) suggests that intraday returns can be used to construct estimates of daily return volatility that are more precise than those constructed using daily returns. In a way, realized volatility becomes observable. Conducting a number of tests of MDH we find that every conclusion based on the daily squared return is reversed when using realized volatility based on intraday returns. Hence, the mixed evidence on MDH in the existing literature can in part be attributed to the use of poor realized volatility measures. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:661,679, 2003 [source] Expiration day effects: The case of Hong KongTHE JOURNAL OF FUTURES MARKETS, Issue 1 2003Ying-Foon Chow Regulators around the world often express concerns about the high volatility of stock markets due to index derivative expirations. Earlier studies of expiration day effects have found large volume effects, abnormal return volatility, and price effects during the last hour of trading on expiration days when the settlement is based on the closing price. This article examines the impact of the expiration of Hang Seng Index (HSI) derivatives on the underlying cash market in Hong Kong for the period from 1990 to 1999. The HSI derivative market is different from most other markets in the sense that the settlement price is computed by taking the average of 5-minute quotations of the HSI on the last trading day, thus providing an alternative setting for testing expiration day effects. Our empirical findings indicate that expiration days in Hong Kong may be associated with a negative price effect and some return volatility on the underlying stock market, but there is no evidence of abnormal trading volume on the expiration day, or price reversal after expiration. Thus, the existence of expiration day effects cannot be confirmed in the Hong Kong market. [JEL classification: G13; G14; G15]. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:67,86, 2003 [source] Index futures leadership, basis behavior, and trader selectivityTHE JOURNAL OF FUTURES MARKETS, Issue 7 2002Arjun Chatrath Employing intraday data for futures and cash values for the S&P 500 over the 1993,1996 period, we attempt to characterize the lead,lag relationship between these two markets and their basis behavior. Our findings show evidence of pronounced futures leadership when markets are rising, with no feedback from the cash market. However, when markets are falling, futures leadership is less evident and significant feedback from the cash market is noted. We also provide evidence of a positive relationship between the basis and return volatility. We offer an explanation, based on trader selectivity, for the leadership-asymmetry and the basis,volatility relationship. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:649,677, 2002 [source] What moves German Bund futures contracts on the Eurex?THE JOURNAL OF FUTURES MARKETS, Issue 7 2002Hee-Joon Ahn The German 10-year Bund futures contract traded on the Eurex futures and options exchange in Frankfurt became the world's most actively traded derivative product by the end of 1999. In this article, we provide a detailed exploration of the interday and intraday return volatility in the Bund futures contract using a sample of five-min returns from 1997 to 1998. The evolution of interday volatility is described best by a MA(1)-fractionally integrated process that allows for the long-memory features. At the intraday level, we find that macroeconomic announcements from both Germany and the U.S. are an important source of volatility. Among the various German announcements, we identify the IFO industry survey of business climate, industrial production (preliminary), and Bundesbank policy meeting as being by far the most important. The three most significant U.S. announcements include the employment report, the National Association of Purchasing Managers (NAPM) survey, and employment costs. Overall, U.S. macroeconomic announcements have a far greater impact on the Bund futures market than their German counterparts. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:679,696, 2002 [source] Bayesian modeling of financial returns: A relationship between volatility and trading volumeAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 2 2010Carlos A. Abanto-Valle Abstract The modified mixture model with Markov switching volatility specification is introduced to analyze the relationship between stock return volatility and trading volume. We propose to construct an algorithm based on Markov chain Monte Carlo simulation methods to estimate all the parameters in the model using a Bayesian approach. The series of returns and trading volume of the British Petroleum stock will be analyzed. Copyright © 2009 John Wiley & Sons, Ltd. [source] On the Quantile Regression Based Tests for Asymmetry in Stock Return VolatilityASIAN ECONOMIC JOURNAL, Issue 2 2002Beum-Jo Park This paper attempts to examine whether the asymmetry of stock return volatility varies with the level of volatility. Thus, quantile regression based tests (,-tests) are presupposed. These tests differ from the diagnostic tests introduced by Engle and Ng (1993) insofar as they can provide a complete picture of asymmetries in volatility across quantiles of variance distribution and, in case of non-normal errors, they have improved power due to their robustness against non-normality. A small Monte Carlo evidence suggests that the Wald and likelihood ratio (LR) tests out of ,-tests are reasonable, showing that they outperform the Lagrange multiplier (LM) test based on least squares residuals when the innovations exhibit heavy tail. Using the normalized residuals obtained from AR(1)-GARCH(1, 1) estimation, the test results demonstrated that only the TOPIX out of six stock-return series had asymmetry in volatility at moderate level, while all stock return series except the FAZ and FA100 had more significant asymmetry in volatility at higher levels. Interestingly, it is clear from the empirical findings that, like hypothesis of leverage effects, volatility of the TOPIX, CAC40, and, MIB tends to respond significantly to extremely negative shock at high level, but is not correlated with any positive shock. These might be valuable findings that have not been seriously considered in past research, which has focussed only on mean level of volatility. [source] The Impact of Trade Characteristics on Stock Return Volatility: Evidence from the Australian Stock Exchange,ASIA-PACIFIC JOURNAL OF FINANCIAL STUDIES, Issue 2 2009Alex Frino Abstract This study examines the impact of trade characteristics on stock return volatility. Using a sample of transaction data from the Australian Stock Exchange, the trading frequency of medium sized trades is found to have the greatest impact on stock return volatility. The result lends support to the stealth trading hypothesis (Barclay and Warner, 1993). After controlling for trading frequency, the average trade size is found to have little explanatory power on price volatility. Stock return volatility is more sensitive to buyer-initiated trades than seller-initiated trades, especially so for buyer-initiated medium sized trades. This finding is consistent with the assertion that information effects are stronger for buys than for sells (Chan and Lakonishok, 1993). [source] The Impact of Day-Trading on Volatility and Liquidity,ASIA-PACIFIC JOURNAL OF FINANCIAL STUDIES, Issue 2 2009Jay M. Chung Abstract We examine day-trading activities for 540 stocks traded on the Korea Stock Exchange using transactions data for the period from 1999 to 2000. Our cross-sectional analysis reveals that day-traders prefer lower-priced, more liquid, and more volatile stocks. By estimating various bivariate VAR models using minute-by-minute data, we find that greater day-trading activity leads to greater return volatility and that the impact of a day-trading shock dissipates gradually within an hour. Past return volatility also positively affects future day-trading activity. We also find that past day-trading activity negatively affects bid-ask spreads, and past bid-ask spreads negatively affect future day-trading activity. Finally, we find that day-traders use short-term contrarian strategies and their order imbalance affects future returns positively. This result is consistent with a cyclical behavior of day-traders who concentrate their buy or sell trades at the bottom or peak of the short-term price cycles, respectively. [source] Volatility, Market Structure, and the Bid-Ask Spread,ASIA-PACIFIC JOURNAL OF FINANCIAL STUDIES, Issue 1 2009Kee H. Chung Abstract We test the conjecture that the specialist system on the New York Stock Exchange (NYSE) provides better liquidity services than the NASDAQ dealer market in times of high return volatility when adverse selection and inventory risks are high. We motivate our conjecture from the observation that there is a designated specialist for each stock on the NYSE who is directly responsible for maintaining a reasonable level of liquidity (i.e., the bid-ask spread) as the ,liquidity provider of last resort' whereas there is no such designated dealer on NASDAQ. Empirical evidence is consistent with our conjecture. In a similar vein, we show that the specialist system provides better liquidity than the dealer market in thin markets. [source] | |||||||||||||||||||||||||