951 resultados para Asset Pricing, Expectations, Beta
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Realiza uma revisão bibliográfica dos testes empíricos do modelo CAPM - Capital Asset Pricing Model, e mostra os resultados de testes de modelos multi-fatores para ações brasileiras.
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Managers know more about the performance of the organization than investors, which makes the disclosure of information a possible strategy for competitive differentiation, minimizing adverse selection. This paper's main goal is to analyze whether or not an entity's level of diclosure may affect the risk perception of individuals and the process of evaluating their shares. The survey was carried out in an experimental study with 456 subjects. In a stock market simulation, we investigated the pricing of the stocks of two companies with different levels of information disclosure at four separate stages. The results showed that, when other variables are constant, the level of disclosure of an entity can affect the expectations of individuals and the process of evaluating their shares. A higher level of disclosure by an entity affected the value of its share and the other company's.
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The study examines the Capital Asset Pricing Model (CAPM) for the mining sector using weekly stock returns from 27 companies traded on the New York Stock Exchange (NYSE) or on the London Stock Exchange (LSE) for the period of December 2008 to December 2010. The results support the use of the CAPM for the allocation of risk to companies. Most companies involved in precious metals (particularly gold), which have a beta value less than unity (Table 1), have been actuated as shelter values during the financial crisis. Values of R2 do not shown very explanatory power of fitted models (R2 < 70 %). Estimated coefficients beta are not sufficient to determine the expected returns on securities but the results of the tests conducted on sample data for the period analysed do not appear to clearly reject the CAPM
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This thesis studies the field of asset price bubbles. It is comprised of three independent chapters. Each of these chapters either directly or indirectly analyse the existence or implications of asset price bubbles. The type of bubbles assumed in each of these chapters is consistent with rational expectations. Thus, the kind of price bubbles investigated here are known as rational bubbles in the literature. The following describes the three chapters. Chapter 1: This chapter attempts to explain the recent US housing price bubble by developing a heterogeneous agent endowment economy asset pricing model with risky housing, endogenous collateral and defaults. Investment in housing is subject to an idiosyncratic risk and some mortgages are defaulted in equilibrium. We analytically derive the leverage or the endogenous loan to value ratio. This variable comes from a limited participation constraint in a one period mortgage contract with monitoring costs. Our results show that low values of housing investment risk produces a credit easing effect encouraging excess leverage and generates credit driven rational price bubbles in the housing good. Conversely, high values of housing investment risk produces a credit crunch characterized by tight borrowing constraints, low leverage and low house prices. Furthermore, the leverage ratio was found to be procyclical and the rate of defaults countercyclical consistent with empirical evidence. Chapter 2: It is widely believed that financial assets have considerable persistence and are susceptible to bubbles. However, identification of this persistence and potential bubbles is not straightforward. This chapter tests for price bubbles in the United States housing market accounting for long memory and structural breaks. The intuition is that the presence of long memory negates price bubbles while the presence of breaks could artificially induce bubble behaviour. Hence, we use procedures namely semi-parametric Whittle and parametric ARFIMA procedures that are consistent for a variety of residual biases to estimate the value of the long memory parameter, d, of the log rent-price ratio. We find that the semi-parametric estimation procedures robust to non-normality and heteroskedasticity errors found far more bubble regions than parametric ones. A structural break was identified in the mean and trend of all the series which when accounted for removed bubble behaviour in a number of regions. Importantly, the United States housing market showed evidence for rational bubbles at both the aggregate and regional levels. In the third and final chapter, we attempt to answer the following question: To what extend should individuals participate in the stock market and hold risky assets over their lifecycle? We answer this question by employing a lifecycle consumption-portfolio choice model with housing, labour income and time varying predictable returns where the agents are constrained in the level of their borrowing. We first analytically characterize and then numerically solve for the optimal asset allocation on the risky asset comparing the return predictability case with that of IID returns. We successfully resolve the puzzles and find equity holding and participation rates close to the data. We also find that return predictability substantially alter both the level of risky portfolio allocation and the rate of stock market participation. High factor (dividend-price ratio) realization and high persistence of factor process indicative of stock market bubbles raise the amount of wealth invested in risky assets and the level of stock market participation, respectively. Conversely, rare disasters were found to bring down these rates, the change being severe for investors in the later years of the life-cycle. Furthermore, investors following time varying returns (return predictability) hedged background risks significantly better than the IID ones.
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During the last few decades there have been far going financial market deregulation, technical development, advances in information technology, and standardization of legislation between countries. As a result, one can expect that financial markets have grown more interlinked. The proper understanding of the cross-market linkages has implications for investment and risk management, diversification, asset pricing, and regulation. The purpose of this research is to assess the degree of price, return, and volatility linkages between both geographic markets and asset categories within one country, Finland. Another purpose is to analyze risk asymmetries, i.e., the tendency of equity risk to be higher after negative events than after positive events of equal magnitude. The analysis is conducted both with respect to total risk (volatility), and systematic risk (beta). The thesis consists of an introductory part and four essays. The first essay studies to which extent international stock prices comove. The degree of comovements is low, indicating benefits from international diversification. The second essay examines the degree to which the Finnish market is linked to the “world market”. The total risk is divided into two parts, one relating to world factors, and one relating to domestic factors. The impact of world factors has increased over time. After 1993, when foreign investors were allowed to freely invest in Finnish assets, the risk level has been higher than previously. This was also the case during the economic recession in the beginning of the 1990’s. The third essay focuses on the stock, bond, and money markets in Finland. According to a trading model, the degree of volatility linkages should be strong. However, the results contradict this. The linkages are surprisingly weak, even negative. The stock market is the most independent, while the money market is affected by events on the two other markets. The fourth essay concentrates on volatility and beta asymmetries. Contrary to many international studies there are only few cases of risk asymmetries. When they occur, they tend to be driven by the market-wide component rather than the portfolio specific element.
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Using a new dataset which contains monthly data on 1015 stocks traded on the London Stock Exchange between 1825 and 1870, we investigate the cross section of stock returns in this early capital market. Unique features of this market allow us to evaluate the veracity of several popular explanations of asset pricing behavior. Using portfolio analysis and Fama–MacBeth regressions, we find that stock characteristics such as beta, illiquidity, dividend yield, and past-year return performance are all positively correlated with stock returns. However, market capitalization and past-three-year return performance have no significant correlation with stock returns.
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We generalize the concept of .systematic risk to a broad class of risk measures potentially accounting for high distribution moments, downside risk, rare disasters, as well as other risk attributes. We offer two different approaches. First is an equilibrium framework generalizing the Capital Asset Pricing Model, two-fund separation, and the security market line. Second is an axiomatic approach resulting in a systematic risk measure as the unique solution to a risk allocation problem. Both approaches lead to similar results extending the traditional beta to capture multiple dimensions of risk. The results lend themselves naturally to empirical investigation.
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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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Latent variable models in finance originate both from asset pricing theory and time series analysis. These two strands of literature appeal to two different concepts of latent structures, which are both useful to reduce the dimension of a statistical model specified for a multivariate time series of asset prices. In the CAPM or APT beta pricing models, the dimension reduction is cross-sectional in nature, while in time-series state-space models, dimension is reduced longitudinally by assuming conditional independence between consecutive returns, given a small number of state variables. In this paper, we use the concept of Stochastic Discount Factor (SDF) or pricing kernel as a unifying principle to integrate these two concepts of latent variables. Beta pricing relations amount to characterize the factors as a basis of a vectorial space for the SDF. The coefficients of the SDF with respect to the factors are specified as deterministic functions of some state variables which summarize their dynamics. In beta pricing models, it is often said that only the factorial risk is compensated since the remaining idiosyncratic risk is diversifiable. Implicitly, this argument can be interpreted as a conditional cross-sectional factor structure, that is, a conditional independence between contemporaneous returns of a large number of assets, given a small number of factors, like in standard Factor Analysis. We provide this unifying analysis in the context of conditional equilibrium beta pricing as well as asset pricing with stochastic volatility, stochastic interest rates and other state variables. We address the general issue of econometric specifications of dynamic asset pricing models, which cover the modern literature on conditionally heteroskedastic factor models as well as equilibrium-based asset pricing models with an intertemporal specification of preferences and market fundamentals. We interpret various instantaneous causality relationships between state variables and market fundamentals as leverage effects and discuss their central role relative to the validity of standard CAPM-like stock pricing and preference-free option pricing.
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This paper develops a general stochastic framework and an equilibrium asset pricing model that make clear how attitudes towards intertemporal substitution and risk matter for option pricing. In particular, we show under which statistical conditions option pricing formulas are not preference-free, in other words, when preferences are not hidden in the stock and bond prices as they are in the standard Black and Scholes (BS) or Hull and White (HW) pricing formulas. The dependence of option prices on preference parameters comes from several instantaneous causality effects such as the so-called leverage effect. We also emphasize that the most standard asset pricing models (CAPM for the stock and BS or HW preference-free option pricing) are valid under the same stochastic setting (typically the absence of leverage effect), regardless of preference parameter values. Even though we propose a general non-preference-free option pricing formula, we always keep in mind that the BS formula is dominant both as a theoretical reference model and as a tool for practitioners. Another contribution of the paper is to characterize why the BS formula is such a benchmark. We show that, as soon as we are ready to accept a basic property of option prices, namely their homogeneity of degree one with respect to the pair formed by the underlying stock price and the strike price, the necessary statistical hypotheses for homogeneity provide BS-shaped option prices in equilibrium. This BS-shaped option-pricing formula allows us to derive interesting characterizations of the volatility smile, that is, the pattern of BS implicit volatilities as a function of the option moneyness. First, the asymmetry of the smile is shown to be equivalent to a particular form of asymmetry of the equivalent martingale measure. Second, this asymmetry appears precisely when there is either a premium on an instantaneous interest rate risk or on a generalized leverage effect or both, in other words, whenever the option pricing formula is not preference-free. Therefore, the main conclusion of our analysis for practitioners should be that an asymmetric smile is indicative of the relevance of preference parameters to price options.
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The paper investigates the pricing of derivative securities with calendar-time maturities.
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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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Seit Etablierung der ersten Börsen als Marktplatz für fungible Güter sind Marktteilnehmer und die Wissenschaft bemüht, Erklärungen für das Zustandekommen von Marktpreisen zu finden. Im Laufe der Zeit wurden diverse Modelle entwickelt. Allen voran ist das neoklassische Capital Asset Pricing Modell (CAPM) zu nennen. Die Neoklassik sieht den Akteur an den Finanzmärkten als emotionslosen und streng rationalen Entscheider, dem sog. homo oeconomicus. Psychologische Einflussfaktoren bei der Preisbildung bleiben unbeachtet. Mit der Behavioral Finance hat sich ein neuer Zweig zur Erklärung von Börsenkursen und deren Bewegungen entwickelt. Die Behavioral Finance sprengt die enge Sichtweise der Neoklassik und geht davon aus, dass psychologische Effekte die Entscheidung der Finanzakteure beeinflussen und dabei zu teilweise irrational und emotional geprägten Kursänderungen führen. Eines der Hauptprobleme der Behavioral Finance liegt allerdings in der fehlenden formellen Ermittelbarkeit und Testbarkeit der einzelnen psychologischen Effekte. Anders als beim CAPM, wo die einzelnen Parameter klar mathematisch bestimmbar sind, besteht die Behavioral Finance im Wesentlichen aus psychologischen Definitionen von kursbeeinflussenden Effekten. Die genaue Wirkrichtung und Intensität der Effekte kann, mangels geeigneter Modelle, nicht ermittelt werden. Ziel der Arbeit ist es, eine Abwandlung des CAPM zu ermitteln, die es ermöglicht, neoklassische Annahmen durch die Erkenntnisse des Behavioral Finance zu ergänzen. Mittels der technischen Analyse von Marktpreisen wird versucht die Effekte der Behavioral Finance formell darstellbar und berechenbar zu machen. Von Praktikern wird die technische Analyse dazu verwendet, aus Kursverläufen die Stimmungen und Intentionen der Marktteilnehmer abzuleiten. Eine wissenschaftliche Fundierung ist bislang unterblieben. Ausgehend von den Erkenntnissen der Behavioral Finance und der technischen Analyse wird das klassische CAPM um psychologische Faktoren ergänzt, indem ein Multi-Beta-CAPM (Behavioral-Finance-CAPM) definiert wird, in das psychologisch fundierte Parameter der technischen Analyse einfließen. In Anlehnung an den CAPM-Test von FAMA und FRENCH (1992) werden das klassische CAPM und das Behavioral-Finance-CAPM getestet und der psychologische Erklärungsgehalt der technischen Analyse untersucht. Im Untersuchungszeitraum kann dem Behavioral-Finance-CAPM ein deutlich höherer Erklärungsgehalt gegenüber dem klassischen CAPM zugesprochen werden.
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We propose a nonparametric method for estimating derivative financial asset pricing formulae using learning networks. To demonstrate feasibility, we first simulate Black-Scholes option prices and show that learning networks can recover the Black-Scholes formula from a two-year training set of daily options prices, and that the resulting network formula can be used successfully to both price and delta-hedge options out-of-sample. For comparison, we estimate models using four popular methods: ordinary least squares, radial basis functions, multilayer perceptrons, and projection pursuit. To illustrate practical relevance, we also apply our approach to S&P 500 futures options data from 1987 to 1991.
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El WACC o Coste Medio Ponderado de Capital es la tasa a la que se deben descontar los flujos para evaluar un proyecto o empresa. Para calcular esta tasa es necesario determinar el costo de la deuda y el costo de los recursos propios de la compañía; el costo de la deuda es la tasa actual del mercado que la empresa está pagando por su deuda, sin embargo el costo de los recursos propios podría ser difícil y más complejo de estimar ya que no existe un costo explícito. En este trabajo se presenta un panorama de las teorías propuestas a lo largo de la historia para calcular el costo de los recursos propios. Como caso particular, se estimará el costo de los recursos propios sin apalancamiento financiero de seis empresas francesas que no cotizan en bolsa y pertenecientes al sector de Servicios a la Persona (SAP). Para lograr lo anterior, se utilizará el Proceso de Análisis Jerárquico (AHP) y el Modelo de Valoración del Precio de los Activos Financieros (CAPM) con base en lo presentado por Martha Pachón (2013) en “Modelo alternativo para calcular el costo de los recursos propios”.