767 resultados para Stock return predictability


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We examine the short-term price behavior of ten Asian stock market indexes following large price changes or “shocks”. Under the standard OLS regression, there is stronger support for return continuations particularly following positive and negative price shocks of less than 10% in absolute size. The results under the GJR-GARCH method provide stronger support for market efficiency, especially for large price shocks. For example, for the Hong Kong stock index, negative shocks of less than -5% but more than -10% generate a significant one day cumulative abnormal return (CAR) of-0.754% under the OLS method, but an insignificant CAR of 0.022% under the GJR-GARCH. We find no support for the uncertainty information hypothesis. Furthermore, the CARs following the period after the Asian financial crisis adjust more quickly to price shocks.

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This study seeks to explain the leverage in UK stock returns by reference to the return volatility, leverage and size characteristics of UK companies. A leverage effect is found that is stronger for smaller companies and has greater explanatory power over the returns of smaller companies. The properties of a theoretical model that predicts that companies with higher leverage ratios will experience greater leverage effects are explored. On examining leverage ratio data, it is found that there is a propensity for smaller companies to have higher leverage ratios. The transmission of volatility shocks between the companies is also examined and it is found that the volatility of larger firm returns is important in determining both the volatility and returns of smaller firms, but not the reverse. Moreover, it is found that where volatility spillovers are important, they improve out-of-sample volatility forecasts. © 2005 Taylor & Francis Group Ltd.

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The aim in this paper is to replicate and extend the analysis of visual technical patterns by Lo et al. (2000) using data on the UK market. A non-parametric smoother is used to model a nonlinear trend in stock price series. Technical patterns, such as the 'head-and-shoulders' pattern, that are characterised by a sequence of turning points are identified in the smoothed data. Statistical tests are used to determine whether returns conditioned on the technical patterns are different from random returns and, in an extension to the analysis of Lo et al. (2000), whether they can outperform a market benchmark return. For the stocks in the FTSE 100 and FTSE 250 indices over the period 1986 to 2001, we find that technical patterns occur with different frequencies to each other and in different relativities to the frequencies found in the US market. Our extended statistical testing indicates that UK stock returns are less influenced by technical patterns than was the case for US stock returns.

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For some time there has been a puzzle surrounding the seasonal behaviour of stock returns. This paper demonstrates that there is an asymmetric relationship between systematic risk and return across the different months of the year for both large and small firms. In the case of both large and small firms systematic risk appears to be priced in only two months of the year, January and April. During the other months no persistent relationship between systematic risk and return appears to exist. The paper also shows that when systematic risk is priced, the size of the systematic risk premium is higher for large firms than for small firms and varies significantly across the months of the year.

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This thesis examines the effect of rights issue announcements on stock prices by companies listed on the Kuala Lumpur Stock Exchange (KLSE) between 1987 to 1996. The emphasis is to report whether the KLSE is semi strongly efficient with respect to the announcement of rights issues and to check whether the implications of corporate finance theories on the effect of an event can be supported in the context of an emerging market. Once the effect is established, potential determinants of abnormal returns identified by previous empirical work and corporate financial theory are analysed. By examining 70 companies making clean rights issue announcements, this thesis will hopefully shed light on some important issues in long term corporate financing. Event study analysis is used to check on the efficiency of the Malaysian stock market; while cross-sectional regression analysis is executed to identify possible explanators of the rights issue announcements' effect. To ensure the results presented are not contaminated, econometric and statistical issues raised in both analyses have been taken into account. Given the small amount of empirical research conducted in this part of the world, the results of this study will hopefully be of use to investors, security analysts, corporate financial managements, regulators and policy makers as well as those who are interested in capital market based research of an emerging market. It is found that the Malaysian stock market is not semi strongly efficient since there exists a persistent non-zero abnormal return. This finding is not consistent with the hypothesis that security returns adjust rapidly to reflect new information. It may be possible that the result is influenced by the sample, consisting mainly of below average size companies which tend to be thinly traded. Nevertheless, these issues have been addressed. Another important issue which has emerged from the study is that there is some evidence to suggest that insider trading activity existed in this market. In addition to these findings, when the rights issue announcements' effect is compared to the implications of corporate finance theories in predicting the sign of abnormal returns, the signalling model, asymmetric information model, perfect substitution hypothesis and Scholes' information hypothesis cannot be supported.

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Can companies reduce the volatility and increase the liquidity of their stocks by trading them? In the context of the Italian stock market, where companies have far more leeway to sell as well as buy their own stocks than in the U.S., the answer is yes. We examine the effects of trading (open-market share repurchases and treasury shares sales) on liquidity (bid–ask spread) and volatility (return variance). Further, we examine the impact of shareholder approvals of repurchase programs on liquidity and volatility. We find clear evidence that trading increases liquidity and reduces volatility. These results are consistent with our analysis of the motives Italian companies give for making share repurchases.

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Tests for random walk behaviour in the Italian stock market are presented, based on an investigation of the fractal properties of the log return series for the Mibtel index. The random walk hypothesis is evaluated against alternatives accommodating either unifractality or multifractality. Critical values for the test statistics are generated using Monte Carlo simulations of random Gaussian innovations. Evidence is reported of multifractality, and the departure from random walk behaviour is statistically significant on standard criteria. The observed pattern is attributed primarily to fat tails in the return probability distribution, associated with volatility clustering in returns measured over various time scales. © 2009 Elsevier Inc. All rights reserved.

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Extreme stock price movements are of great concern to both investors and the entire economy. For investors, a single negative return, or a combination of several smaller returns, can possible wipe out so much capital that the firm or portfolio becomes illiquid or insolvent. If enough investors experience this loss, it could shock the entire economy. An example of such a case is the stock market crash of 1987. Furthermore, there has been a lot of recent interest regarding the increasing volatility of stock prices. ^ This study presents an analysis of extreme stock price movements. The data utilized was the daily returns for the Standard and Poor's 500 index from January 3, 1978 to May 31, 2001. Research questions were analyzed using the statistical models provided by extreme value theory. One of the difficulties in examining stock price data is that there is no consensus regarding the correct shape of the distribution function generating the data. An advantage with extreme value theory is that no detailed knowledge of this distribution function is required to apply the asymptotic theory. We focus on the tail of the distribution. ^ Extreme value theory allows us to estimate a tail index, which we use to derive bounds on the returns for very low probabilities on an excess. Such information is useful in evaluating the volatility of stock prices. There are three possible limit laws for the maximum: Gumbel (thick-tailed), Fréchet (thin-tailed) or Weibull (no tail). Results indicated that extreme returns during the time period studied follow a Fréchet distribution. Thus, this study finds that extreme value analysis is a valuable tool for examining stock price movements and can be more efficient than the usual variance in measuring risk. ^

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The increase in the number of financial restatements in recent years has resulted in a significant decrease in the amount of market capitalization for restated companies. Prior literature did not differentiate between single and multiple restatements announcements. This research investigated the inter-relationships among multiple financial restatements, corporate governance, market microstructure and the firm’s rate of return in the form of three essays by differentiating between single and multiple restatement announcement companies. First essay examined the stock performance of companies announcing the financial restatement multiple times. The postulation is that prior research overestimates the abnormal return by not separating single restatement companies from multiple restatement companies. This study investigated how market penalizes the companies that announce restatement more than once. Differentiating the restatement announcement data based on number of restatement announcements, the results supported the non persistence hypothesis that the market has no memory and negative abnormal returns obtained after each of the restatement announcements are completely random. Second essay examined the multiple restatement announcements and its perceived resultant information asymmetry around the announcement day. This study examined the pattern of information asymmetry for these announcements in terms of whether the bid-ask spread widens around the announcement day. The empirical analysis supported the hypotheses that the spread does widen not only around the first restatement announcement day but around every subsequent announcement days as well. The third essay empirically examined the financial and corporate governance characteristics of single and multiple restatement announcements companies. The analysis showed that corporate governance variables influence the occurrence of multiple restatement announcements and can distinguish multiple restatements announcement companies from single restatement announcement companies.

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My dissertation investigates the financial linkages and transmission of economic shocks between the US and the smallest emerging markets (frontier markets). The first chapter sets up an empirical model that examines the impact of US market returns and conditional volatility on the returns and conditional volatilities of twenty-one frontier markets. The model is estimated via maximum likelihood; utilizes the GARCH model of errors, and is applied to daily country data from the MSCI Barra. We find limited, but statistically significant exposure of Frontier markets to shocks from the US. Our results suggest that it is not the lagged US market returns that have impact; rather it is the expected US market returns that influence frontier market returns The second chapter sets up an empirical time-varying parameter (TVP) model to explore the time-variation in the impact of mean US returns on mean Frontier market returns. The model utilizes the Kalman filter algorithm as well as the GARCH model of errors and is applied to daily country data from the MSCI Barra. The TVP model detects statistically significant time-variation in the impact of US returns and low, but statistically and quantitatively important impact of US market conditional volatility. The third chapter studies the risk-return relationship in twenty Frontier country stock markets by setting up an international version of the intertemporal capital asset pricing model. The systematic risk in this model comes from covariance of Frontier market stock index returns with world returns. Both the systematic risk and risk premium are time-varying in our model. We also incorporate own country variances as additional determinants of Frontier country returns. Our results suggest statistically significant impact of both world and own country risk in explaining Frontier country returns. Time-variation in the world risk premium is also found to be statistically significant for most Frontier market returns. However, own country risk is found to be quantitatively more important.

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The increase in the number of financial restatements in recent years has resulted in a significant decrease in the amount of market capitalization for restated companies. Prior literature does not differentiate between single and multiple restatements announcements. This research investigates the inter-relationships among multiple financial restatements, corporate governance, market microstructure and the firm's rate of return in the form of three essays by differentiating between single and multiple restatement announcement companies. First essay examines the stock performance of companies announcing the financial restatement multiple times. The postulation is that prior research overestimates the abnormal return by not separating single restatement companies from multiple restatement companies. This study investigates how market penalizes the companies that announce restatement more than once. Differentiating the restatement announcement data based on number of restatement announcements, the results support for non persistence hypothesis that the market has no memory and negative abnormal returns obtained after each of the restatement announcements are completely random. Second essay examines the multiple restatement announcements and its perceived resultant information asymmetry around the announcement day. This study examines the pattern of information asymmetry for these announcements in terms of whether the bid-ask spread widens around the announcement day. The empirical analysis supports the hypotheses that the spread does widen not only around the first restatement announcement day but around every subsequent announcement days as well. The third essay empirically examines the financial and corporate governance characteristics of single and multiple restatement announcements companies. The analysis shows that corporate governance variables influence the occurrence of multiple restatement announcements and can distinguish multiple restatements announcement companies from single restatement announcement companies.

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We study the impact of S&P index membership on REIT stock returns. Given the hybrid nature of REITs, their returns may become more like those of other indexed stocks and less like those of their underlying properties. The existing literature does not offer clear predictions on these potential outcomes. Taking advantage of the inclusion of REITs in major S&P indexes starting in 2001, we find that shared index membership significantly increases the correlation between REIT returns after controlling for the stock characteristics that determine index membership. We also document that index membership enhances the link between REIT stock returns and the performance of the underlying real estate, consistent with improved pricing efficiency. REIT investors appear to be able to enjoy the benefits of improved visibility and liquidity associated with index membership as well as the exposure to underlying real estate markets and the related benefits of diversification.

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[Excerpt] This study examines the relation between the level of institutional investor ownership and the magnitude of security price variability at quarterly earnings announcement dates. Prior research consistently documents a negative association between firm size and announcement-date return variability. One explanation for this finding is that as more timely, alternative information becomes available on large firms prior to an announcement date, their security prices become informative, thereby reducing the information content of the earnings announcement. Large firms are closely followed by institutional investors. These investors dedicate substantial resources to information search. Therefore, the link between size and information production may be attributable to the influence of institutional investors on the information production process. Because institutional trades can also affect security prices, however, the precise impact of institutional following on the variability of prices at quarterly earnings dates is not evident.

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International research shows that low-volatility stocks have beaten high-volatility stocks in terms of returns for decades on multiple markets. This abbreviation from traditional risk-return framework is known as low-volatility anomaly. This study focuses on explaining the anomaly and finding how strongly it appears in NASDAQ OMX Helsinki stock exchange. Data consists of all listed companies starting from 2001 and ending close to 2015. Methodology follows closely Baker and Haugen (2012) by sorting companies into deciles according to 3-month volatility and then calculating monthly returns for these different volatility groups. Annualized return for the lowest volatility decile is 8.85 %, while highest volatility decile destroys wealth at rate of -19.96 % per annum. Results are parallel also in quintiles that represent larger amount of companies and thus dilute outliers. Observation period captures financial crisis of 2007-2008 and European debt crisis, which embodies as low main index annual return of 1 %, but at the same time proves the success of low-volatility strategy. Low-volatility anomaly is driven by multiple reasons such as leverage constrained trading and managerial incentives which both prompt to invest in risky assets, but behavioral matters also have major weight in maintaining the anomaly.

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Throughout the last years technologic improvements have enabled internet users to analyze and retrieve data regarding Internet searches. In several fields of study this data has been used. Some authors have been using search engine query data to forecast economic variables, to detect influenza areas or to demonstrate that it is possible to capture some patterns in stock markets indexes. In this paper one investment strategy is presented using Google Trends’ weekly query data from major global stock market indexes’ constituents. The results suggest that it is indeed possible to achieve higher Info Sharpe ratios, especially for the major European stock market indexes in comparison to those provided by a buy-and-hold strategy for the period considered.