967 resultados para International asset pricing


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The benefits of diversification from international real estate securities are generally well established. However, the drivers of international real estate securities returns are insufficiently understood. We jointly examine the empirical implications of three major international asset pricing models that account for broad macroeconomic risk factors. In addition, we develop the hypothesis that an indicator of mispriced credit is significant in explaining the time series variation in international real estate securities returns. We employ the returns generated by a large sample of firms from 20 countries over the period 1999 to 2011 to test our hypothesis. We find support for the predictions of the major international asset pricing models. We also find evidence in favour of our hypothesised link between local credit conditions and the performance of international real estate securities.

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A plethora of recent literature on asset pricing provides plenty of empirical evidence on the importance of liquidity, governance and adverse selection of equity on pricing of assets together with more traditional factors such as market beta and the Fama-French factors. However, literature has usually stressed that these factors are priced individually. In this dissertation we argue that these factors may be related to each other, hence not only individual but also joint tests of their significance is called for. In the three related essays, we examine the liquidity premium in the context of the finer three-digit SIC industry classification, joint importance of liquidity and governance factors as well as governance and adverse selection. Recent studies by Core, Guay and Rusticus (2006) and Ben-Rephael, Kadan and Wohl (2010) find that governance and liquidity premiums are dwindling in the last few years. One reason could be that liquidity is very unevenly distributed across industries. This could affect the interpretation of prior liquidity studies. Thus, in the first chapter we analyze the relation of industry clustering and liquidity risk following a finer industry classification suggested by Johnson, Moorman and Sorescu (2009). In the second chapter, we examine the dwindling influence of the governance factor if taken simultaneously with liquidity. We argue that this happens since governance characteristics are potentially a proxy for information asymmetry that may be better captured by market liquidity of a company’s shares. Hence, we jointly examine both the factors, namely, governance and liquidity – in a series of standard asset pricing tests. Our results reconfirm the importance of governance and liquidity in explaining stock returns thus independently corroborating the findings of Amihud (2002) and Gompers, Ishii and Metrick (2003). Moreover, governance is not subsumed by liquidity. Lastly, we analyze the relation of governance and adverse selection, and again corroborate previous findings of a priced governance factor. Furthermore, we ascertain the importance of microstructure measures in asset pricing by employing Huang and Stoll’s (1997) method to extract an adverse selection variable and finding evidence for its explanatory power in four-factor regressions.

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The first chapter provides evidence that aggregate Research and Development (R&D) investment drives a persistent component in productivity growth and that this embodies a risk priced in financial markets. In a semi-endogenous growth model, this component is identified by the R&D in excess of equilibrium levels and can be approximated by the Error Correction Term in the cointegration between R&D and Total Factor Productivity. Empirically, the component results being well defined and it satisfies all key theoretical predictions: it exhibits appropriate persistency, it forecasts productivity growth, and it is associated with a cross-sectional risk premium. CAPM is the most foundational model in financial economics, but is known to empirically underestimate expected returns of low-risk assets and overestimate those with high risk. The second chapter studies how risks omission and funding tightness jointly contribute to explaining this anomaly, with the former affecting the definition of assets’ riskiness and the latter affecting how risk is remunerated. Theoretically, the two effects are shown to counteract each other. Empirically, the spread related to binding leverage constraints is found to be significant at 2% yearly. Nonetheless, average returns of portfolios that exploit this anomaly are found to mostly reflect omitted risks, in contrast to their employment in previous literature. The third chapter studies how ‘sustainability’ of assets affect discount rates, which is intrinsically mediated by the risk profile of the assets themselves. This has implications for the assessment of the sustainability-related spread and for hedging changes in the sustainability concern. This mechanism is tested on the ESG-score dimension for US data, with inconclusive evidence regarding the existence of an ESG-related premium in the first place. Also, the risk profile of the long-short ESG portfolio is not likely to impact the sign of its average returns with respect to the sustainability-spread, for the time being.

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Cette thèse de doctorat consiste en trois chapitres qui traitent des sujets de choix de portefeuilles de grande taille, et de mesure de risque. Le premier chapitre traite du problème d’erreur d’estimation dans les portefeuilles de grande taille, et utilise le cadre d'analyse moyenne-variance. Le second chapitre explore l'importance du risque de devise pour les portefeuilles d'actifs domestiques, et étudie les liens entre la stabilité des poids de portefeuille de grande taille et le risque de devise. Pour finir, sous l'hypothèse que le preneur de décision est pessimiste, le troisième chapitre dérive la prime de risque, une mesure du pessimisme, et propose une méthodologie pour estimer les mesures dérivées. Le premier chapitre améliore le choix optimal de portefeuille dans le cadre du principe moyenne-variance de Markowitz (1952). Ceci est motivé par les résultats très décevants obtenus, lorsque la moyenne et la variance sont remplacées par leurs estimations empiriques. Ce problème est amplifié lorsque le nombre d’actifs est grand et que la matrice de covariance empirique est singulière ou presque singulière. Dans ce chapitre, nous examinons quatre techniques de régularisation pour stabiliser l’inverse de la matrice de covariance: le ridge, spectral cut-off, Landweber-Fridman et LARS Lasso. Ces méthodes font chacune intervenir un paramètre d’ajustement, qui doit être sélectionné. La contribution principale de cette partie, est de dériver une méthode basée uniquement sur les données pour sélectionner le paramètre de régularisation de manière optimale, i.e. pour minimiser la perte espérée d’utilité. Précisément, un critère de validation croisée qui prend une même forme pour les quatre méthodes de régularisation est dérivé. Les règles régularisées obtenues sont alors comparées à la règle utilisant directement les données et à la stratégie naïve 1/N, selon leur perte espérée d’utilité et leur ratio de Sharpe. Ces performances sont mesurée dans l’échantillon (in-sample) et hors-échantillon (out-of-sample) en considérant différentes tailles d’échantillon et nombre d’actifs. Des simulations et de l’illustration empirique menées, il ressort principalement que la régularisation de la matrice de covariance améliore de manière significative la règle de Markowitz basée sur les données, et donne de meilleurs résultats que le portefeuille naïf, surtout dans les cas le problème d’erreur d’estimation est très sévère. Dans le second chapitre, nous investiguons dans quelle mesure, les portefeuilles optimaux et stables d'actifs domestiques, peuvent réduire ou éliminer le risque de devise. Pour cela nous utilisons des rendements mensuelles de 48 industries américaines, au cours de la période 1976-2008. Pour résoudre les problèmes d'instabilité inhérents aux portefeuilles de grandes tailles, nous adoptons la méthode de régularisation spectral cut-off. Ceci aboutit à une famille de portefeuilles optimaux et stables, en permettant aux investisseurs de choisir différents pourcentages des composantes principales (ou dégrées de stabilité). Nos tests empiriques sont basés sur un modèle International d'évaluation d'actifs financiers (IAPM). Dans ce modèle, le risque de devise est décomposé en deux facteurs représentant les devises des pays industrialisés d'une part, et celles des pays émergents d'autres part. Nos résultats indiquent que le risque de devise est primé et varie à travers le temps pour les portefeuilles stables de risque minimum. De plus ces stratégies conduisent à une réduction significative de l'exposition au risque de change, tandis que la contribution de la prime risque de change reste en moyenne inchangée. Les poids de portefeuille optimaux sont une alternative aux poids de capitalisation boursière. Par conséquent ce chapitre complète la littérature selon laquelle la prime de risque est importante au niveau de l'industrie et au niveau national dans la plupart des pays. Dans le dernier chapitre, nous dérivons une mesure de la prime de risque pour des préférences dépendent du rang et proposons une mesure du degré de pessimisme, étant donné une fonction de distorsion. Les mesures introduites généralisent la mesure de prime de risque dérivée dans le cadre de la théorie de l'utilité espérée, qui est fréquemment violée aussi bien dans des situations expérimentales que dans des situations réelles. Dans la grande famille des préférences considérées, une attention particulière est accordée à la CVaR (valeur à risque conditionnelle). Cette dernière mesure de risque est de plus en plus utilisée pour la construction de portefeuilles et est préconisée pour compléter la VaR (valeur à risque) utilisée depuis 1996 par le comité de Bâle. De plus, nous fournissons le cadre statistique nécessaire pour faire de l’inférence sur les mesures proposées. Pour finir, les propriétés des estimateurs proposés sont évaluées à travers une étude Monte-Carlo, et une illustration empirique en utilisant les rendements journaliers du marché boursier américain sur de la période 2000-2011.

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The goal of this paper is to estimate time-varying covariance matrices.Since the covariance matrix of financial returns is known to changethrough time and is an essential ingredient in risk measurement, portfolioselection, and tests of asset pricing models, this is a very importantproblem in practice. Our model of choice is the Diagonal-Vech version ofthe Multivariate GARCH(1,1) model. The problem is that the estimation ofthe general Diagonal-Vech model model is numerically infeasible indimensions higher than 5. The common approach is to estimate more restrictive models which are tractable but may not conform to the data. Our contributionis to propose an alternative estimation method that is numerically feasible,produces positive semi-definite conditional covariance matrices, and doesnot impose unrealistic a priori restrictions. We provide an empiricalapplication in the context of international stock markets, comparing thenew estimator to a number of existing ones.

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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 paper assesses the importance of fund flows in the performance evaluation of Australian international equity funds. Two concepts of fund flows are considered in the context of a conditional asset pricing model. The first measure is net fund flow relative to fund size and the second is net fund flow relative to sector flows. We find that incorporating a fund flow measure relative to the sector flow results in a reduction of measured perverse market timing. The results indicate that, at the individual fund level, cash flows are relevant in assessing management outcomes.

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Prepared for presentation at the Portuguese Finance Network International Conference 2014, Vilamoura, Portugal, June 18-20

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"The purpose of the XII Iberian-Italian Congress of Financial and Actuarial Mathematics is to provide a meeting point for researchers in Financial Economics from different countries and research backgrounds in universities, government or financial institutions. In fact, the Congress which is currently taking place in Lisbon has been organized to encourage communication and debate among the participants as well as to reinforce the bonds between us.The current edition of the Congress is characterized by the quality and diversity of the papers that have been submitted with special attention to the International Financial Crisis and measures of risk in different financial markets. However, as the Congress Program indicates, there are also parallel sessions about traditional topics in finance such as asset pricing, insurance, corporate finance, etc.Although this Congress has always been organized alternately between Spain and Italy, this year we have the great pleasure of celebrating it in Portugal which will be included as a permanent partner." [prefácio]

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Currently, financial economics is unable to predict changes in asset prices with respect to changes in the underlying risk factors, even when an asset's dividend is independent of a given factor. This paper takes steps towards addressing this issue by highlighting a crucial component of wealth effects on asset prices hitherto ignored by the literature. Changes in wealth do not only alter an agents risk aversion, but also her perceived 'riskiness' of a security. The latter enhances significantly the extent to which market- clearing leads to endogenously-generated correlation across asset prices, over and above that induced by correlation between payoffs, giving the appearance of 'contagion.'

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The framework presents how trading in the foreign commodity futures market and the forward exchange market can affect the optimal spot positions of domestic commodity producers and traders. It generalizes the models of Kawai and Zilcha (1986) and Kofman and Viaene (1991) to allow both intermediate and final commodities to be traded in the international and futures markets, and the exporters/importers to face production shock, domestic factor costs and a random price. Applying mean-variance expected utility, we find that a rise in the expected exchange rate can raise both supply and demand for commodities and reduce domestic prices if the exchange rate elasticity of supply is greater than that of demand. Whether higher volatilities of exchange rate and foreign futures price can reduce the optimal spot position of domestic traders depends on the correlation between the exchange rate and the foreign futures price. Even though the forward exchange market is unbiased, and there is no correlation between commodity prices and exchange rates, the exchange rate can still affect domestic trading and prices through offshore hedging and international trade if the traders are interested in their profit in domestic currency. It illustrates how the world prices and foreign futures prices of commodities and their volatility can be transmitted to the domestic market as well as the dynamic relationship between intermediate and final goods prices. The equilibrium prices depends on trader behaviour i.e. who trades or does not trade in the foreign commodity futures and domestic forward currency markets. The empirical result applying a two-stage-least-squares approach to Thai rice and rubber prices supports the theoretical result.

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An affine asset pricing model in which traders have rational but heterogeneous expectations aboutfuture asset prices is developed. We use the framework to analyze the term structure of interestrates and to perform a novel three-way decomposition of bond yields into (i) average expectationsabout short rates (ii) common risk premia and (iii) a speculative component due to heterogeneousexpectations about the resale value of a bond. The speculative term is orthogonal to public informationin real time and therefore statistically distinct from common risk premia. Empirically wefind that the speculative component is quantitatively important accounting for up to a percentagepoint of yields, even in the low yield environment of the last decade. Furthermore, allowing for aspeculative component in bond yields results in estimates of historical risk premia that are morevolatile than suggested by standard Affine Gaussian term structure models which our frameworknests.

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In models where privately informed agents interact, agents may need to formhigher order expectations, i.e. expectations of other agents' expectations. This paper develops a tractable framework for solving and analyzing linear dynamic rational expectationsmodels in which privately informed agents form higher order expectations. The frameworkis used to demonstrate that the well-known problem of the infinite regress of expectationsidentified by Townsend (1983) can be approximated to an arbitrary accuracy with a finitedimensional representation under quite general conditions. The paper is constructive andpresents a fixed point algorithm for finding an accurate solution and provides weak conditions that ensure that a fixed point exists. To help intuition, Singleton's (1987) asset pricingmodel with disparately informed traders is used as a vehicle for the paper.

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One of the main developments in the global economy during the past decades has been the growth of emerging economies. Projections for their long-term growth, changes in the investment climate, corporate transparency and demography point to an increasing role for these emerging economies in the global economy. Today, emerging economies are usually considered as financial markets offering opportunities for high returns, good risk diversification and improved return-to-risk ratios. However, researchers have noted that these advantages may be in decline because of the increasing market integration. Nevertheless, it is likely that certain financial markets and specific sectors will remain partially segmented and somewhat insulated from the global economy for the year to come. This doctoral dissertation investigates several stock markets in Emerging Eastern Europe (EEE), including the ones in Russia, Poland, Hungary, the Czech Republic, Bulgaria and Slovenia. The objective is to analyze the returns and financial risks in these emerging markets from international investor’s point of view. This study also examines the segmentation/integration of these financial markets and the possibilities to diversify and hedge financial risk. The dissertation is divided into two parts. The first includes a review of the theoretical background for the articles and a review of the literature on EEE stock markets. It includes an overview of the methodology and research design applied in the analysis and a summary of articles from the second part of this dissertation and their main findings. The second part consists of four research publications. This work contributes to studies on emerging stock markets in four ways. First, it adds to the body of research on the pricing of risk, providing new empirical evidence about partial stock market segmentation in EEE. The results suggest that the aggregate emerging market risk is a relevant driver for stock market returns and that this market risk can be used to price financial instruments and forecast their performance. Second, it contributes to the empirical research on the integration of stock markets, asset prices and exchange rates by identifying the relationships between these markets through volatility and asset pricing. The results show that certain sectors of stock markets in EEE are not as integrated as others. For example, the Polish consumer goods sector, the Hungarian telecommunications sector, and the Czech financial sector are somewhat isolated from their counterparts elsewhere in Europe. Nevertheless, an analysis of the impact of EU accession in 2004 on stock markets suggests that most of the EEE markets are becoming increasingly integrated with the global markets. Third, this thesis complements the scientific literature in the field of shock and volatility spillovers by examining the mechanism of spillover distribution among the EU and EEE countries. The results illustrate that spillovers in emerging markets are mostly from a foreign exchange to the stock markets. Moreover, the results show that the effects of external shocks on stock markets have increased after the enlargement of the EU in 2004. Finally, this study is unique because it analyzes the effects of foreign macroeconomic news on geographically closely related countries. The results suggest that the effects of macroeconomic announcements on volatility are significant and have effect that varies across markets and their sectors. Moreover, the results show that the foreign macroeconomic news releases, somewhat surprisingly, have a greater effect on the EEE markets than the local macroeconomic news. This dissertation has a number of implications for the industry and for practitioners. It analyses financial risk associated with investing in Emerging Eastern Europe. Investors may use this information to construct and optimize investment portfolios. Moreover, this dissertation provides insights for investors and portfolio managers considering asset allocation to protect value or obtain higher returns. The results have also implications for asset pricing and portfolio selection in light of macroeconomic news releases.

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This thesis discusses the basic problem of the modern portfolio theory about how to optimise the perfect allocation for an investment portfolio. The theory provides a solution for an efficient portfolio, which minimises the risk of the portfolio with respect to the expected return. A central feature for all the portfolios on the efficient frontier is that the investor needs to provide the expected return for each asset. Market anomalies are persistent patterns seen in the financial markets, which cannot be explained with the current asset pricing theory. The goal of this thesis is to study whether these anomalies can be observed among different asset classes. Finally, if persistent patterns are found, it is investigated whether the anomalies hold valuable information for determining the expected returns used in the portfolio optimization Market anomalies and investment strategies based on them are studied with a rolling estimation window, where the return for the following period is always based on historical information. This is also crucial when rebalancing the portfolio. The anomalies investigated within this thesis are value, momentum, reversal, and idiosyncratic volatility. The research data includes price series of country level stock indices, government bonds, currencies, and commodities. The modern portfolio theory and the views given by the anomalies are combined by utilising the Black-Litterman model. This makes it possible to optimise the portfolio so that investor’s views are taken into account. When constructing the portfolios, the goal is to maximise the Sharpe ratio. Significance of the results is studied by assessing if the strategy yields excess returns in a relation to those explained by the threefactormodel. The most outstanding finding is that anomaly based factors include valuable information to enhance efficient portfolio diversification. When the highest Sharpe ratios for each asset class are picked from the test factors and applied to the Black−Litterman model, the final portfolio results in superior riskreturn combination. The highest Sharpe ratios are provided by momentum strategy for stocks and long-term reversal for the rest of the asset classes. Additionally, a strategy based on the value effect was highly appealing, and it basically performs as well as the previously mentioned Sharpe strategy. When studying the anomalies, it is found, that 12-month momentum is the strongest effect, especially for stock indices. In addition, a high idiosyncratic volatility seems to be positively correlated with country indices on stocks.