809 resultados para Stock Returns


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We use the consumption-based asset pricing model with habit formation to study the predictability and cross-section of returns from the international equity markets. We find that the predictability of returns from many developed countries' equity markets is explained in part by changing prices of risks associated with consumption relative to habit at the world as well as local levels. We also provide an exploratory investigation of the cross-sectional implications of the model under the complete world market integration hypothesis and find that the model performs mildly better than the traditional consumption-based model. the unconditional and conditional world CAPMs and a three-factor international asset pricing model. (C) 2004 Elsevier B.V. All rights reserved.

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This paper examines the economic significance of return predictability in Australian equities. In light of considerable model uncertainty, formal model-selection criteria are used to choose a specification for the predictive model. A portfolio-switching strategy is implemented according to model predictions. Relative to a buy-and-hold market investment, the returns to the portfolio-switching strategy are impressive under several model-selection criteria, even after accounting for transaction costs. However, as these findings are not robust across other model-selection criteria examined, it is difficult to conclude that the degree of return predictability is economically significant.

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Are the learning procedures of genetic algorithms (GAs) able to generate optimal architectures for artificial neural networks (ANNs) in high frequency data? In this experimental study,GAs are used to identify the best architecture for ANNs. Additional learning is undertaken by the ANNs to forecast daily excess stock returns. No ANN architectures were able to outperform a random walk,despite the finding of non-linearity in the excess returns. This failure is attributed to the absence of suitable ANN structures and further implies that researchers need to be cautious when making inferences from ANN results that use high frequency data.

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Purpose – The purpose of this paper is to investigate the impact of foreign exchange and interest rate changes on US banks’ stock returns. Design/methodology/approach – The approach employs an EGARCH model to account for the ARCH effects in daily returns. Most prior studies have used standard OLS estimation methods with the result that the presence of ARCH effects would have affected estimation efficiency. For comparative purposes, the standard OLS estimation method is also used to measure sensitivity. Findings – The findings are as follows: under the conditional t-distributional assumption, the EGARCH model generated a much better fit to the data although the goodness-of-fit of the model is not entirely satisfactory; the market index return accounts for most of the variation in stock returns at both the individual bank and portfolio levels; and the degree of sensitivity of the stock returns to interest rate and FX rate changes is not very pronounced despite the use of high frequency data. Earlier results had indicated that daily data provided greater evidence of exposure sensitivity. Practical implications – Assuming that banks do not hedge perfectly, these findings have important financial implications as they suggest that the hedging policies of the banks are not reflected in their stock prices. Alternatively, it is possible that different GARCH-type models might be more appropriate when modelling high frequency returns. Originality/value – The paper contributes to existing knowledge in the area by showing that ARCH effects do impact on measures of sensitivity.

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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 paper investigates whether the non-normality typically observed in daily stock-market returns could arise because of the joint existence of breaks and GARCH effects. It proposes a data-driven procedure to credibly identify the number and timing of breaks and applies it on the benchmark stock-market indices of 27 OECD countries. The findings suggest that a substantial element of the observed deviations from normality might indeed be due to the co-existence of breaks and GARCH effects. However, the presence of structural changes is found to be the primary reason for the non-normality and not the GARCH effects. Also, there is still some remaining excess kurtosis that is unlikely to be linked to the specification of the conditional volatility or the presence of breaks. Finally, an interesting sideline result implies that GARCH models have limited capacity in forecasting stock-market volatility.

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The properties of an iterative procedure for the estimation of the parameters of an ARFIMA process are investigated in a Monte Carlo study. The estimation procedure is applied to stock returns data for 15 countries. © 2012.

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We provide theory and evidence to complement Choi's [RFS, 2013] important new insights on the returns to equity in `value' firms. We show that higher future earnings growth ameliorates the value-reducing effect of leverage and, because the market for earnings is incomplete, reduces the earnings-risk sensitivity of the default option. Ceteris paribus, a levered firm with low (high) earnings growth is more sensitive to the first (second) of these effects thus generating higher (lower) expected returns. We demonstrate this by modeling equity as an Asian-style call option on net earnings and find significant empirical support for our hypotheses.

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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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Mestrado em Finanças

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Do “The Best Companies to Work” have Higher Stock Returns? The main purpose of this work is to prove the link between job satisfaction and the firm’s value. The «Best Companies to Work» list give us our measure for job satisfaction. The sample of this work is composed by firms listed in STOXX Europe 600 Index. We compared the monthly returns of a portfolio composed by firms present in the «Best Companies to Work» list with two other benchmark portfolios, using the four-factor model proposed by Carhart (1997), from January 2010 to December 2014. Our results show that the BCWE600 portfolio outperforms both benchmark portfolios. In other words, companies classified as Best Companies to Work generated 0.40%/month and 4.94%/year higher stock returns than their peers over the 2010-2014 period. Also, the market risk in portfolio BCWE600 is inferior compared to other portfolios. This work shows that firms with the most satisfied workers get better results, resulting in higher returns for it’s shareholders.

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In this paper, we follow Jegadeesh and Titman's (1993, Journal of Finance) approach to examine 25 momentum/contrarian trading strategies using monthly stock returns in China for the period from 1994 to 2007. Our results suggest that there is no momentum profitability in any of the 25 strategies. In contrast, there is some evidence of reversal effects where the past winners become losers and past losers become winners afterward. The contrarian profit is statistically significant for the strategies using short formation and holding periods, especially for the formation periods of 1 to 3 months and the holding periods of 1 to 3 months. The contrarian strategies can generate about 12% per annum on average. Moreover, we follow Heston and Sadka (2008, Journal of Financial Economics) to investigate where there is any seasonal pattern in the cross-sectional variation of average stock returns in our momentum/contrarian strategies. There is no evidence of any seasonal pattern, and the results are robust to different formation and holding periods.