993 resultados para EQUITY PRICES


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Bouman and Jacobsen (American Economic Review 92(5), 1618–1635, 2002) examine monthly stock returns for major world stock markets and conclude that returns are significantly lower during the May–October periods versus the November–April periods in 36 of 37 markets examined. They argue that, in general, the Halloween strategy outperforms the buy and hold strategy thereby casting doubt on the validity of the efficient market paradigm. More recently, Maberly and Pierce (Econ Journal Watch 1(1), 29–46, 2004) re-examine the evidence for U.S. equity prices and conclude that Bouman and Jacobsen’s results are not robust to alternative model specifications. Extending prior research, this paper examines the robustness of the Halloween strategy to alternative model specifications for Japanese equity prices. The Halloween effect is concentrated in the period prior to the introduction of Nikkei 225 index futures in September 1986. After the internationalization of Japanese financial markets in the mid-1980s, the Halloween effect disappears.

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While the literature shows that perks can affect firm values positively or negatively, we argue that firms with higher perks are more likely to be associated with a lower quality of financial reporting, which, in turn, can affect the informativeness of stock prices. Based on hand-collected data on perks from Chinese listed firms, we find that firms with lower perks are associated with higher informativeness of stock prices (or lower R-square). Moreover, the positive association between perks and R-square is shown to be weaker for firms with higher financial reporting quality through audit and earnings quality measures.

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We show that stock prices of firms with gender-diverse boards reflect more firm-specific information after controlling for corporate governance, earnings quality, institutional ownership and acquisition activity. Further, we show that the relationship is stronger for firms with weak corporate governance suggesting that gender-diverse boards could act as a substitute mechanism for corporate governance that would be otherwise weak. The results are robust to alternative specifications of informativeness and gender diversity and to sensitivity tests controlling for time-invariant firm characteristics and alternative measures of stock price informativeness. We also find that gender diversity improves stock price informativeness through the mechanism of increased public disclosure in large firms and by encouraging private information collection in small firms. © 2011 Elsevier B.V.

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This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.

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In recent years, a sharp divergence of London Stock Exchange equity prices from dividends has been noted. In this paper, we examine whether this divergence can be explained by reference to the existence of a speculative bubble. Three different empirical methodologies are used: variance bounds tests, bubble specification tests, and cointegration tests based on both ex post and ex ante data. We find that, stock prices diverged significantly from their fundamental values during the late 1990's, and that this divergence has all the characteristics of a bubble.

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One reason for the recent asset price bubbles in many developed countries could be regulatory capital arbitrage. Regulatory and legal changes can help traditional banks to move their assets off their balance sheets into the lightly regulated shadows and thus enable regulatory arbitrage through the securitized sector. This paper adopts a global vector autoregression (GVAR) methodology to assess the effects of regulatory capital arbitrage on equity prices, house prices and economic activity across 11 OECD countries/ regions. A counterfactual experiment disentangles the effects of regulatory arbitrage following a change in the net capital rule for investment banks in April 2004 and the adoption of the Basel II Accord in June 2004. The results provide evidence for the existence of an international finance multiplier, with about half of the countries overshooting U.S. impulse responses. The counterfactual shows that regulatory arbitrage via the U.S. securitized sector may enhance the cross-country reallocation of capital from housing markets towards equity markets.

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Examinamos as diferenças de preço entre diferentes classes de ações em companhias abertas no Brasil com particular ênfase a empresas privatizadas, e discutimos o papel do controlador, liquidez, e problemas de governanças que influenciam esta diferença ao longo do tempo. Nos incluímos uma breve discussão sobre o sistema societário brasileiro, e seus efeitos sobre os acionistas, e as características do processo de privatização, antes de passar a análise econométrica. Encontramos evidência empírica que suporta a hipótese de que a razão ação sem direito a voto sobre a participação acionária total, liquidez, e tipo de controle majoritário, e mudanças na regulamentação são significativas na determinação das diferenças de preço entre ações.

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Includes bibliography

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Includes bibliography

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Includes bibliography

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In this article a partial-adjustment model, which shows how equity prices fail to adjust instantaneously to new information, is estimated using a Kalman filter. For the components of the Dow Jones Industrial 30 index I aim to identify whether overreaction or noise is the cause of serial correlation and high volatility associated with opening returns. I find that the tendency for overreaction in opening prices is much stronger than for closing prices; therefore, overreaction rather than noise may account for differences in the return behavior of opening and closing returns.

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A "self-exciting" market is one in which the probability of observing a crash increases in response to the occurrence of a crash. It essentially describes cases where the initial crash serves to weaken the system to some extent, making subsequent crashes more likely. This thesis investigates if equity markets possess this property. A self-exciting extension of the well-known jump-based Bates (1996) model is used as the workhorse model for this thesis, and a particle-filtering algorithm is used to facilitate estimation by means of maximum likelihood. The estimation method is developed so that option prices are easily included in the dataset, leading to higher quality estimates. Equilibrium arguments are used to price the risks associated with the time-varying crash probability, and in turn to motivate a risk-neutral system for use in option pricing. The option pricing function for the model is obtained via the application of widely-used Fourier techniques. An application to S&P500 index returns and a panel of S&P500 index option prices reveals evidence of self excitation.

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The increased availability of high frequency data sets have led to important new insights in understanding of financial markets. The use of high frequency data is interesting and persuasive, since it can reveal new information that cannot be seen in lower data aggregation. This dissertation explores some of the many important issues connected with the use, analysis and application of high frequency data. These include the effects of intraday seasonal, the behaviour of time varying volatility, the information content of various market data, and the issue of inter market linkages utilizing high frequency 5 minute observations from major European and the U.S stock indices, namely DAX30 of Germany, CAC40 of France, SMI of Switzerland, FTSE100 of the UK and SP500 of the U.S. The first essay in the dissertation shows that there are remarkable similarities in the intraday behaviour of conditional volatility across European equity markets. Moreover, the U.S macroeconomic news announcements have significant cross border effect on both, European equity returns and volatilities. The second essay reports substantial intraday return and volatility linkages across European stock indices of the UK and Germany. This relationship appears virtually unchanged by the presence or absence of the U.S stock market. However, the return correlation among the U.K and German markets rises significantly following the U.S stock market opening, which could largely be described as a contemporaneous effect. The third essay sheds light on market microstructure issues in which traders and market makers learn from watching market data, and it is this learning process that leads to price adjustments. This study concludes that trading volume plays an important role in explaining international return and volatility transmissions. The examination concerning asymmetry reveals that the impact of the positive volume changes is larger on foreign stock market volatility than the negative changes. The fourth and the final essay documents number of regularities in the pattern of intraday return volatility, trading volume and bid-ask spreads. This study also reports a contemporaneous and positive relationship between the intraday return volatility, bid ask spread and unexpected trading volume. These results verify the role of trading volume and bid ask quotes as proxies for information arrival in producing contemporaneous and subsequent intraday return volatility. Moreover, asymmetric effect of trading volume on conditional volatility is also confirmed. Overall, this dissertation explores the role of information in explaining the intraday return and volatility dynamics in international stock markets. The process through which the information is incorporated in stock prices is central to all information-based models. The intraday data facilitates the investigation that how information gets incorporated into security prices as a result of the trading behavior of informed and uninformed traders. Thus high frequency data appears critical in enhancing our understanding of intraday behavior of various stock markets’ variables as it has important implications for market participants, regulators and academic researchers.

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Recent empirical findings suggest that the long-run dependence in U.S. stock market volatility is best described by a slowly mean-reverting fractionally integrated process. The present study complements this existing time-series-based evidence by comparing the risk-neutralized option pricing distributions from various ARCH-type formulations. Utilizing a panel data set consisting of newly created exchange traded long-term equity anticipation securities, or leaps, on the Standard and Poor's 500 stock market index with maturity times ranging up to three years, we find that the degree of mean reversion in the volatility process implicit in these prices is best described by a Fractionally Integrated EGARCH (FIEGARCH) model. © 1999 Elsevier Science S.A. All rights reserved.