871 resultados para Capital assets pricing model


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This thesis aims to investigate pricing of liquidity risks in London Stock Exchange. Liquidity Adjusted Capital Asset Pricing Model i.e. LCAPM developed by Acharya and Pedersen (2005) is being applied to test the influence of various liquidity risks on stock returns in London Stock Exchange. The Liquidity Adjusted Capital Asset Pricing model provides a unified framework for the testing of liquidity risks. All the common stocks listed and delisted for the period of 2000 to 2014 are included in the data sample. The study has incorporated three different measures of liquidity – Percent Quoted Spread, Amihud (2002) and Turnover. The reason behind the application of three different liquidity measures is the multi-dimensional nature of liquidity. Firm fixed effects panel regression is applied for the estimation of LCAPM. However, the results are robust according to Fama-Macbeth regressions. The results of the study indicates that liquidity risks in the form of (i) level of liquidity, (ii) commonality in liquidity (iii) flight to liquidity, (iv) depressed wealth effect and market return as well as aggregate liquidity risk are priced at London Stock Exchange. However, the results are sensitive to the choice of liquidity measures.

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This paper assesses the empirical performance of an intertemporal option pricing model with latent variables which generalizes the Hull-White stochastic volatility formula. Using this generalized formula in an ad-hoc fashion to extract two implicit parameters and forecast next day S&P 500 option prices, we obtain similar pricing errors than with implied volatility alone as in the Hull-White case. When we specialize this model to an equilibrium recursive utility model, we show through simulations that option prices are more informative than stock prices about the structural parameters of the model. We also show that a simple method of moments with a panel of option prices provides good estimates of the parameters of the model. This lays the ground for an empirical assessment of this equilibrium model with S&P 500 option prices in terms of pricing errors.

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In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR) with applications to asset pricing models. We focus on departures from the assumption of i.i.d. errors assumption, at univariate and multivariate levels, with Gaussian and non-Gaussian (including Student t) errors. The univariate tests studied extend existing exact procedures by allowing for unspecified parameters in the error distributions (e.g., the degrees of freedom in the case of the Student t distribution). The multivariate tests are based on properly standardized multivariate residuals to ensure invariance to MLR coefficients and error covariances. We consider tests for serial correlation, tests for multivariate GARCH and sign-type tests against general dependencies and asymmetries. The procedures proposed provide exact versions of those applied in Shanken (1990) which consist in combining univariate specification tests. Specifically, we combine tests across equations using the MC test procedure to avoid Bonferroni-type bounds. Since non-Gaussian based tests are not pivotal, we apply the “maximized MC” (MMC) test method [Dufour (2002)], where the MC p-value for the tested hypothesis (which depends on nuisance parameters) is maximized (with respect to these nuisance parameters) to control the test’s significance level. The tests proposed are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995. Our empirical results reveal the following. Whereas univariate exact tests indicate significant serial correlation, asymmetries and GARCH in some equations, such effects are much less prevalent once error cross-equation covariances are accounted for. In addition, significant departures from the i.i.d. hypothesis are less evident once we allow for non-Gaussian errors.

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In this paper, we propose exact inference procedures for asset pricing models that can be formulated in the framework of a multivariate linear regression (CAPM), allowing for stable error distributions. The normality assumption on the distribution of stock returns is usually rejected in empirical studies, due to excess kurtosis and asymmetry. To model such data, we propose a comprehensive statistical approach which allows for alternative - possibly asymmetric - heavy tailed distributions without the use of large-sample approximations. The methods suggested are based on Monte Carlo test techniques. Goodness-of-fit tests are formally incorporated to ensure that the error distributions considered are empirically sustainable, from which exact confidence sets for the unknown tail area and asymmetry parameters of the stable error distribution are derived. Tests for the efficiency of the market portfolio (zero intercepts) which explicitly allow for the presence of (unknown) nuisance parameter in the stable error distribution are derived. The methods proposed are applied to monthly returns on 12 portfolios of the New York Stock Exchange over the period 1926-1995 (5 year subperiods). We find that stable possibly skewed distributions provide statistically significant improvement in goodness-of-fit and lead to fewer rejections of the efficiency hypothesis.

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A study focusing on the identification of return generating factors and to the extent of their influence on share prices the outcome will be a tool for investment analysis in the hands of investors portfolio managers and mutual funds who are mostly concerned with changing share prices. Since the study takes into account the influence of macroeconomic variables on variations in share returns by using the outcome the government can frame out suitable policies on long term basis and that will help in nurturing a healthy economy and resultant stock market. As every company management tries to maximize the wealth of the share holders a clear idea about the return generating variables and their influence will help the management to frame various policies to maximize the wealth of the shareholders.

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The increased frequency in reporting UK property performance figures, coupled with the acceptance of the IPD database as the market standard, has enabled property to be analysed on a comparable level with other more frequently traded assets. The most widely utilised theory for pricing financial assets, the Capital Asset Pricing Model (CAPM), gives market (systematic) risk, beta, centre stage. This paper seeks to measure the level of systematic risk (beta) across various property types, market conditions and investment holding periods. This paper extends the authors’ previous work on investment holding periods and how excess returns (alpha) relate to those holding periods. We draw on the uniquely constructed IPD/Gerald Eve transactions database, containing over 20,000 properties over the period 1983-2005. This research allows us to confirm our initial findings that properties held over longer periods perform in line with overall market performance. One implication of this is that over the long-term performance may be no different from an index tracking approach.

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We develop a general model to price VIX futures contracts. The model is adapted to test both the constant elasticity of variance (CEV) and the Cox–Ingersoll–Ross formulations, with and without jumps. Empirical tests on VIX futures prices provide out-of-sample estimates within 2% of the actual futures price for almost all futures maturities. We show that although jumps are present in the data, the models with jumps do not typically outperform the others; in particular, we demonstrate the important benefits of the CEV feature in pricing futures contracts. We conclude by examining errors in the model relative to the VIX characteristics

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trata da determinação das taxas de desconto ajustadas ao risco para avaliação, pelo método do fluxo de caixa descontado, do valor econômico de estatais brasileiras privatizadas no período 1991-1992. Utiliza conceitos financeiros como valor presente líquido, eficiência de mercado, capital asset pricing model e risco sistemático, que são aplicados a dados do mercado de capitais e demonstrativos financeiros das empresas. Com as metodologias de regressão linear simples múltipla, desenvolve uma equação que relaciona índices fundamentais com os coeficientes de risco sistemático (betas) das empresas de uma amostra, que por sua vez serve para estimar os coeficientes de risco das estatais.

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It is well documented venture capital‟s positive impact on creation and development of highly successful innovative companies worldwide. Venture capital not only provides funding to startups and SMEs (small and medium enterprises) that usually have financing gap, especially in emerging markets, but also brings a whole package of valuable resources that reduces companies‟ mortality rates. Using quantitative data obtained from an empirical survey as background, this paper discusses the role of venture capital in the success of innovative startups and SMEs, and it examines if, and to what extent, venture capitalists are supporting the entrepreneurial activity in Brazil. I focused on the portfolio companies analyzes and confirmed the hypothesis that the venture capital industry has been supporting entrepreneurship in Brazil. Second, I identified an important evidence of a venture capital‟s positive impact on economic activity, especially the capital market. Third, it became clear that venture capital-back entrepreneurship is highly concentrated in the Southeast region. And fourth, I identified that private equity expansion is also playing a key role on that dynamics. As consequence, I conclude that the venture capital (and private equity) industry has been very important to build an enormously dynamic and strong local entrepreneurial economy. Its committed capital grew 50% per year between 2005 and 2008 to achieve US$27 billion, which invested US$ 11 billion, which employs 1,400 professionals (75% with post-graduate degrees) and maintains 482 portfolio companies, mostly SMEs. In addition, venture capital-backed companies represented one third of the IPOs that occurred in Brazil between 2004 and 2008 (approximately US$15 billion).

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No contexto do Capital Asset Pricing Model (CAPM), este trabalho investiga a significância da alavancagem financeira na construção do risco sistemático. Testamos com dados brasileiros o procedimento de desalavancagem e realavancagem do beta comumente realizado por analistas financeiros para a construção do custo de capital próprio de empresas não negociadas em bolsa de valores. Os resultados apontam que a inclusão do tax shield na fórmula de desalavancagem/realavancagem e a utilização de valores de mercado produzem resultados mais robustos, ao passo que as divisões por setores possuem pouca capacidade como segmentadores de classe de risco sistemático.

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This article suggests a pricing model for commodities used to produce biofuel. The model is based on the concept that the deterministic component of the Wiener process is not constant and depends on time and exogenous variables. The model, which incorporates theory of storage, the convenience yield and the seasonality of harvests, was applied in the Brazilian sugar market. After predictions were made with the Kalman filter, the model produced results that were statistically more accurate than those returned by the two-factor model available in the literature.

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Neste trabalho, discute-se a fixação de taxas de retorno de concessões no Brasil, com aplicação específica ao caso da metodologia da Agência Nacional de Transportes Terrestres (ANTT). Mostra-se a inadequação da regulamentação vigente, baseada no conceito de taxa interna de retorno (TIR), e não de custo de oportunidade do capital. A partir de um exemplo com dados referentes ao auge da crise financeira internacional (dezembro de 2008), evidencia-se também a falta de lógica decorrente da utilização de retornos e preços passados na estimação de taxas de retorno, um procedimento comum a toda a área de concessões de serviços públicos no Brasil. Propõe-se uma metodologia alternativa cujos resultados são sensíveis às condições correntes de mercado de capitais, que produz resultados coerentes com a situação então vigente.

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The consumption capital asset pricing model is the standard economic model used to capture stock market behavior. However, empirical tests have pointed out to its inability to account quantitatively for the high average rate of return and volatility of stocks over time for plausible parameter values. Recent research has suggested that the consumption of stockholders is more strongly correlated with the performance of the stock market than the consumption of non-stockholders. We model two types of agents, non-stockholders with standard preferences and stock holders with preferences that incorporate elements of the prospect theory developed by Kahneman and Tversky (1979). In addition to consumption, stockholders consider fluctuations in their financial wealth explicitly when making decisions. Data from the Panel Study of Income Dynamics are used to calibrate the labor income processes of the two types of agents. Each agent faces idiosyncratic shocks to his labor income as well as aggregate shocks to the per-share dividend but markets are incomplete and agents cannot hedge consumption risks completely. In addition, consumers face both borrowing and short-sale constraints. Our results show that in equilibrium, agents hold different portfolios. Our model is able to generate a time-varying risk premium of about 5.5% while maintaining a low risk free rate, thus suggesting a plausible explanation for the equity premium puzzle reported by Mehra and Prescott (1985).

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El capital financiero es muy volátil y si el inversor no obtiene una remuneración adecuada al riesgo que asume puede plantearse el retirar su capital del patrimonio de la empresa y, en consecuencia, producir un cambio estructural en cualquier sector de la economía. El objetivo principal es el estudio de los coeficientes de regresión (coeficiente beta) de los modelos de valoración de activos empleados en Economía Financiera, esto es, el estudio de la variación de la rentabilidad de los activos en función de los cambios que suceden en los mercados. La elección de los modelos utilizados se justifica por la amplia utilización teórica y empírica de los mismos a lo largo de la historia de la Economía Financiera. Se han aplicado el modelo de valoración de activos de mercado (capital asset pricing model, CAPM), el modelo basado en la teoría de precios de arbitraje (arbitrage pricing theory, APT) y el modelo de tres factores de Fama y French (FF). Estos modelos se han aplicado a los rendimientos mensuales de 27 empresas del sector minero que cotizan en la bolsa de Nueva York (New York Stock Exchange, NYSE) o en la de Londres (London Stock Exchange, LSE), con datos del período que comprende desde Enero de 2006 a Diciembre de 2010. Los resultados de series de tiempo y sección cruzada tanto para CAPM, como para APT y FF producen varios errores, lo que sugiere que muchas empresas del sector no han podido obtener el coste de capital. También los resultados muestran que las empresas de mayor riesgo tienden a tener una menor rentabilidad. Estas conclusiones hacen poco probable que se mantenga en el largo plazo el equilibrio actual y puede que sea uno de los principales factores que impulsen un cambio estructural en el sector minero en forma de concentraciones de empresas. ABSTRACT Financial capital is highly volatile and if the investor does not get adequate compensation for the risk faced he may consider withdrawing his capital assets from the company and consequently produce a structural change in any sector of the economy. The main purpose is the study of the regression coefficients (beta) of asset pricing models used in financial economics, that is, the study of variation in profitability of assets in terms of the changes that occur in the markets. The choice of models used is justified by the extensive theoretical and empirical use of them throughout the history of financial economics. Have been used the capital asset pricing model, CAPM, the model XII based on the arbitrage pricing theory (APT) and the three-factor model of Fama and French (FF). These models have been applied to the monthly returns of 27 mining companies listed on the NYSE (New York Stock Exchange) or LSE(London Stock Exchange), using data from the period covered from January 2006 to December 2010. The results of time series and cross sectional regressions for CAPM, APT and FF produce some errors, suggesting that many companies have failed to obtain the cost of capital. Also the results show that higher risk firms tend to have lower profitability. These findings make it unlikely to be mainteined over the long term the current status and could drive structural change in the mining sector in the form of mergers.