風險和報酬彼此之間的關係常常都是資產持有者所關心的，人們願意承受高風險以換取高報酬的情形，似乎相當地合乎直覺，然而學者使用不同模型來估計風險趨避係數，卻發現結果大不相同，而本文採2000年到2010年的台灣加權股價指數報酬率為樣本，延續前人研究利用了不對稱每日報酬平方(Asymmetric MIDAS) 、三個不對稱GARCH in Mean模型: Asymmetric GARCH(1,1)-M，Exponential GARCH(1,1)-M還有考慮金融資產報酬率通常非為常態分配的設定下採取的Exponential GARCH(1,1)-M(GED分配)所計算的條件變異數來替代風險，置入跨期資本資產定價模型(Intertemporal CAPM, ICAPM)來估計風險趨避係數。結果發現Asymmetric MIDAS估計者為正值且顯著，而不對稱GARCH模型下僅有EGARCH(1,1)-M(GED分配)所估計者於金融風暴兩年子樣本期間為正值但不顯著外，其餘皆為負值且不顯著。

[pt] Diversos estudos têm procurado uma variável de risco que empiricamente tenha uma relação positiva e significativa com os retornos condicionais de mercado. Na maior parte dos casos a escolha recai sobre novas abordagens envolvendo a variância condicional dos retornos. Neste trabalho substituímos a variância pelo Value at Risk (VaR) para analisar se no mercado brasileiro existe o trade-off entre risco e retorno. O VaR é estimado paramétrica e não parametricamente com base em janelas de dados de um a seis meses. Os resultados mostram que em nosso mercado não há relação positiva e significativa entre o VaR e os retornos mensais. A causa mais aparente para essa divergência é que o prêmio de risco de mercado é negativo em 114 dos 217 meses que compõem a série temporal da variável dependente, impactando os coeficientes do VaR nas regressões. Quando utilizados retornos com frequência diária, os resultados mostram que em períodos mais recentes há relação positiva e significativa entre esses retornos e o VaR paramétrico. / [en] Several studies have searched a risk variable with an empirically positive and significant relation with excess market returns. At the most part of the cases the choices are new approaches of conditional variance of the returns. In this paper we substitute the variance for the Value at Risk (VaR) to analyze whether in the Brazilian market there is relation between risk and returns. The VaR is estimated in parametric and nonparametric ways, considered the precedents intervals of time from one to six months. The results show that in our market there is not a positive and significant relation between VaR and the monthly market returns. The most obvious cause that supports our results is that the market premium risk is negative on 114 of 217 total monthly observations that form the temporal series of the dependent variable, impacting the VaR coefficients in the regressions. When used daily frequency returns, the results show a positive and significant relation between these results and parametric VaR in recent periods.

The food processing industry is dominated by large corporations. These firms play a critical role in forming the derived demand faced by agricultural producers, but little is understood about how these companies make strategic choices. Organizational economics provides a framework for exploring the firm's decision process. However, several theories exist in this discipline, operating in fundamentally different ways. This paper examines the two prevalent organizational theories, Transaction Cost Economics and Agency Theory, through a study of the food processing industry. This sector is thoroughly analyzed in order to make predictions from each theory regarding the aspects of capital structure and firm expansion. With accounting data for a sample of food processing firms, these predictions are then tested empirically using an ICAPM model in a cross-section of expected stock returns. Our results indicate that Agency Theory is the relevant organizational model for food manufacturers, making it the appropriate tool for evaluating the actions of these firms in agricultural markets.

近年來由於市場型式為開放主體，在財務整合，商品區隔的環境下，投資人在進行投資時，應考量全方面的訊息，亦即國家內外部所有會影響股票市場的風險因子。而風險與報酬之間是否存在抵換關係，一直以來皆為備受討論的議題，從過去的文獻當中，研究者多以變異數作為衡量風險的代理，再透過各種不同的研究方法來估計風險報酬係數，但實證上並未獲得一致的結果。本文以1981年1月至2008年7月為研究期間，台灣與韓國之股價指數月資料為樣本，所使用之模型參考Turan G. Bali & Liuren Wu(2010)的研究論文，利用簡化過後的雙變量BEKK-GARCH(1，1)模型進行估計，探討台灣與韓國股票市場跨期收益與風險之關係。本文主要分為三大部分，首先先將台灣及韓國的股價指數以美元計價，針對全球市場觀察其風險以及持續性，並且利用共變異數來判別兩國股市分別為高風險或是低風險，再者，將台灣及韓國的股價指數分別以自己國家之幣別計算，將計算出之殘差估計個別國家股市風險，看是否兩國家內部的非經濟因素，例如:政治及軍事等，會影響股市的表現。最後一部份為前兩部分的整合，比較個別國家風險與全球市場風險對台灣及韓國股市的影響以及超額報酬與風險之間的抵換關係。實證結果顯示，不論就台灣或者是韓國而言，全球市場風險的風險與報酬係數皆為正向顯著，其中又以台灣之係數較為高，透露出若在承擔相同的全球市場風險時，台灣的投資人會較韓國的投資人要求較高的報酬。在匯率風險方面，本文採Turan G. Bali & Liuren Wu(2010)所使用的研究方法，將風險與報酬的抵換關係建立在不同國家的幣別之下進行估計，由結果發現，若以美元為單位來衡量風險報酬係數，則不論是台灣或韓國，在全球市場風險下，係數皆較小；若以個別貨幣來衡量，其台灣的風險與報酬抵換係數較大，韓國之係數則是由正值轉變為負值，代表匯率的確會對市場風險值有所影響，匯率風險是可以被定價的。 / In recent years, due to the opening of the markets, there are more and more choices in the investments. Investors should consider all aspects of information in this world with financial market integration but goods market segmentation. The intertemporal relation between risk and return in the stock market has been one of the most extensively studied topics in financial economics. The risk-return coefficients across different currency denomination change when considering different specification for the conditional covariance process. We used the bivariate BEKK-GARCH (1,1) model as the basic used in the reference by Turan G. Bali & Liuren Wu (2010) estimating the risk-return coefficients and measuring how this risk aversion estimate varies with different currency denominations. We started our analysis using monthly data from January 1981 to July 2008 on the Standard & Poor's 500 index, Taiwan stock exchange corporation and Korea composite stock price index. This article was divided into three parts. First, we computed monthly returns on the indices based on U.S. dollar denomination and calculated the excess returns as the index return minus the short-term interest rate. Second, we estimated the conditional covariances between the excess returns on the world market portfolio and the excess returns on two country indices using a bivariate GARCH specification. Third, we estimated the common relation of the equations implied by the international version of the intertemporal capital asset pricing model between the expected excess returns on those two country indices and the corresponding conditional covariances. After repeating the above procedure and estimating the intertemporal risk-return relation under different currency denomination, the empirical results showed that the risk-return coefficients in the world market portfolio was significantly positive in Taiwan and Korea. We also found that the coefficient was different based on different currency denominations on behalf of the exchange rate risk can be priced.

Submitted by Renato Dalla Colletta (renatodcolletta@gmail.com) on 2013-02-27T20:15:20Z No. of bitstreams: 1 Tese MPFE Renato D Colletta.pdf: 1766902 bytes, checksum: 4daf523c0cf56d0533692bcd81b813db (MD5) / Approved for entry into archive by Vera Lúcia Mourão (vera.mourao@fgv.br) on 2013-02-27T21:01:52Z (GMT) No. of bitstreams: 1 Tese MPFE Renato D Colletta.pdf: 1766902 bytes, checksum: 4daf523c0cf56d0533692bcd81b813db (MD5) / Made available in DSpace on 2013-02-27T21:05:31Z (GMT). No. of bitstreams: 1 Tese MPFE Renato D Colletta.pdf: 1766902 bytes, checksum: 4daf523c0cf56d0533692bcd81b813db (MD5) Previous issue date: 2013-01-31 / This work applies the intertemporal asset pricing model developed by Campbell (1993) and Campbell and Vuolteenaho (2004) to the Brazilian 2x3 Fama-French stock portfolios from January 2003 to April 2012 and to the US 5x5 Fama-French portfolios in dfferent time periods. The variables suggested by Campbell and Vuolteenaho (2004) to forecast US market excess returns from 1929 to 2001 were also good excess return predictors for the Brazilian market on the recent period, except the term structure yield spread. However, we found that an increase in the small stock value spread predicts a higher market excess return, which is not consistent with the intertemporal model explanation for the value premium. Moreover, using the residuals of the forecasting VAR to define the test portfolios’ cash flow and discount rate shock risk sensitivity, we found that the resulting intertemporal model explains little of the variance in the cross section of returns. For the US market, we conclude that the proposed variables’ ability to forecast market excess returns is not constant in time. Campbell and Vuolteenaho’s (2004) success in explaining the value premium for the US market in the 1963 to 2001 sub-sample is a result of the VAR specification in the full sample, since we show that none of the variables are statistically significant return predictors in this sub-sample. / Esse trabalho é uma aplicação do modelo intertemporal de apreçamento de ativos desenvolvido por Campbell (1993) e Campbell e Vuolteenaho (2004) para as carteiras de Fama-French 2x3 brasileiras no period de janeiro de 2003 a abril de 2012 e para as carteiras de Fama-French 5x5 americanas em diferentes períodos. As varíaveis sugeridas por Campbell e Vuolteenaho (2004) para prever os excessos de retorno do mercado acionário americano no period de 1929 a 2001 mostraram-se também bons preditores de excesso de retorno para o mercado brasileiro no período recente, com exceção da inclinação da estrutura a termo das taxas de juros. Entretanto, mostramos que um aumento no small stock value spread indica maior excesso de retorno no futuro, comportamento que não é coerente com a explicação para o prêmio de valor sugerida pelo modelo intertemporal. Ainda, utilizando os resíduos do VAR preditivo para definir o risco de choques de fluxo de caixa e de choques nas taxas de desconto das carteiras de teste, verificamos que o modelo intertemporal resultante não explica adequadamente os retornos observados. Para o mercado norte-americano, concluímos que a habilidade das variáveis propostas para explicar os excessos de retorno do mercado varia no tempo. O sucesso de Campbell e Vuolteenaho (2004) em explicar o prêmio de valor para o mercado norte-americano na amostra de 1963 a 2001 é resultado da especificação do VAR na amostra completa, pois mostramos que nenhuma das varíaveis é um preditor de retorno estatisticamente significante nessa sub-amostra.

This thesis consists of three empirical essays studying the capital market implications of the accounting for R&D costs. The first empirical study (Chapter 2) re-visits the debate over the positive R&D-returns relation. The second empirical study (Chapter 3) examines the risk relevance of current R&D accounting. The third empirical study (Chapter 4) explores the joint impact of R&D intensity and competition on the relative relevance of the idiosyncratic part of earnings. Prior research argues that the positive relation between current R&D activity and future returns is evidence of mispricing, a compensation for risk inherent in R&D or a transformation of the value/growth anomaly. The first empirical study contributes to this debate by taking into account the link between R&D activity, equity duration and systematic risk. This link motivates us to employ Campbell and Vuolteenaho (2004)'s intertemporal asset pricing model (ICAPM) which accommodates stochastic discount rates and investors' intertemporal preferences. The results support a risk based explanation; R&D intensive firms are exposed to higher discount rate risk. Hedge portfolio strategies show that the mispricing explanations is not economically significant. The second empirical study contributes to prior research on the value relevance of financial reporting information on R&D, by proposing an alternative approach which relies on a return variance decomposition model. We find that R&D intensity has a significant influence on market participants' revisions of expectations regarding future discount rates (or, discount rate news) and future cash flows (or, cash flow news), thereby driving returns variance. We extend this investigation to assess the risk relevance of this information by means of its influence on the sensitivity of cash flow and discount rate news to the market news. Our findings suggest R&D intensity is associated with significant variation in the sensitivity of cash flow news to the market news which implies that financial reporting information on R&D is risk relevant. Interestingly, we do not establish a similar pattern with respect to the sensitivity of discount news to the market news which may dismiss the impact of sentiment in stock returns of R&D intensive firms. The third empirical study examines the effect of financial reporting information on R&D to the value relevance of common and idiosyncratic earnings. More specifically, we investigate the value relevance of common and idiosyncratic earnings through an extension of the Vuolteenaho (2002) model which decomposes return variance into its discount rate, idiosyncratic and common cash flow news. We demonstrate that the relative importance of idiosyncratic over common cash flow news in explaining return variance increases with firm-level R&D intensity. Extending this analysis, we find that this relation varies with the level of R&D investment concentration in the industry. Those results indicate that the market perceives that more pronounced R&D activity leads to outcomes that enable the firm to differentiate itself from its rivals. However, our results also suggest that the market perceives that this relation depends upon the underlying economics of the industry where the firm operates.

Cette thèse tente d'évaluer l'intégration des marchés émergents dans une perspective régionale et intra-régionale. Elle contribue à la littérature existante en développant un modèle dynamique d’évaluation des actifs financiers à l’international (ICAPM) avec changement de régime. Spécifiquement, les rentabilités attendues peuvent passer du régime de segmentation parfaite au régime d’intégration parfaite ou inversement en fonction d’un certain nombre de facteurs nationaux, régionaux et internationaux qui sont susceptibles d’influencer le processus d’intégration financière. Le champ d’étude s’étend aux pays de l’Asie de Sud-est, d’Europe Sud-est, de l’Amérique Latine et du Moyen Orient sur la période 1996-2008. Nous développons le modèle de Bekaert et Harvey (1995) où la PPA n’est pas vérifiée, et les variances et covariances conditionnelles sont modélisées grâce à un processus GARCH multivarié. Cette approche permet de déterminer simultanément le niveau d’intégration au cours du temps de toutes les zones dans le marché mondial et le niveau d’intégration intra-régionale dans chaque région. Il permet aussi d’analyser la formation de la prime de risque totale. Nos résultats empiriques montrent que les marchés émergents restent encore très segmentés du marché mondial et des marchés régionaux. Ces résultats suggèrent que l’inclusion des actifs des marchés émergents continue à générer des gains de diversification substantiels, et que les règles d’évaluation devraient être conformes à un état d’intégration partielle. / The purpose of this thesis is to study the dynamics of the global integration process of four emerging market regions into the world and the regional market, while taking into account the importance of exchange rate and local market risk. An international capital asset pricing model suitable for partially integrated markets and departure from purchasing power parity was developed in the spirit of Bekaert and Harvey (1995)’s regime-switching model in order to explain the time-variations in expected returns on regional emerging market indices. In its fully functional form, the model allows the market integration measure as well as the global and local risk premiums to vary through time. We mainly find that the integration degree in emerging market regions (Latin America, Asia, Southeastern Europe, and the Middle East) varied widely through time over the period 1996-2008 and is satisfactorily explained by global, regional and national factors. Even though it reaches fairly high values during several periods, and exhibit an upward trend towards the end of the estimation period, the emerging market regions under consideration still remain segmented from the world and regional market. These results thus suggest that diversification into emerging market assets continue to produce substantial profits and that the asset pricing rules should reflect a state of partial integration. Our investigation, which addresses the evolution and formation of total risk premiums, confirm this empirically.

My dissertation investigates the financial linkages and transmission of economic shocks between the US and the smallest emerging markets (frontier markets). The first chapter sets up an empirical model that examines the impact of US market returns and conditional volatility on the returns and conditional volatilities of twenty-one frontier markets. The model is estimated via maximum likelihood; utilizes the GARCH model of errors, and is applied to daily country data from the MSCI Barra. We find limited, but statistically significant exposure of Frontier markets to shocks from the US. Our results suggest that it is not the lagged US market returns that have impact; rather it is the expected US market returns that influence frontier market returns The second chapter sets up an empirical time-varying parameter (TVP) model to explore the time-variation in the impact of mean US returns on mean Frontier market returns. The model utilizes the Kalman filter algorithm as well as the GARCH model of errors and is applied to daily country data from the MSCI Barra. The TVP model detects statistically significant time-variation in the impact of US returns and low, but statistically and quantitatively important impact of US market conditional volatility. The third chapter studies the risk-return relationship in twenty Frontier country stock markets by setting up an international version of the intertemporal capital asset pricing model. The systematic risk in this model comes from covariance of Frontier market stock index returns with world returns. Both the systematic risk and risk premium are time-varying in our model. We also incorporate own country variances as additional determinants of Frontier country returns. Our results suggest statistically significant impact of both world and own country risk in explaining Frontier country returns. Time-variation in the world risk premium is also found to be statistically significant for most Frontier market returns. However, own country risk is found to be quantitatively more important.

The inability to effectively hedge against unfavourable exchange rate movements, using the current forward exchange rate as the only guideline, is a key inhibiting factor of international trade. Market participants use the current forward exchange rate quoted in the market to make decisions regarding future exchange rate changes. However, the current forward exchange rate is not solely determined by the interaction of demand and supply, but is also a mechanistic estimation, which is based on the current spot exchange rate and the carry cost of the transaction. Results of various studies, including this study, demonstrated that the current forward exchange rate differs substantially from the realized future spot exchange rate. This phenomenon is known as the exchange rate puzzle. This study contributes to the dynamics of modelling exchange rate theories by developing an exchange rate model that has the ability to explain the realized future spot exchange rate and the exchange rate puzzle. The exchange rate model is based only on current (time t) economic fundamentals and includes an alternative approach of incorporating the impact of the interaction of two international financial markets into the model. This study derived a unique exchange rate model, which proves that the exchange rate puzzle is a pseudo problem. The pseudo problem is based on the generally excepted fallacy that current non–stationary, level time series data cannot be used to model exchange rate theories, because of the incorrect assumption that all the available econometric methods yield statistically insignificant results due to spurious regressions. Empirical evidence conclusively shows that using non–stationary, level time series data of current economic fundamentals can statistically significantly explain the realized future spot exchange rate and, therefore, that the exchange rate puzzle can be solved. This model will give market participants in the foreign exchange market a better indication of expected future exchange rates, which will considerably reduce the dependence on the mechanistically derived forward points. The newly derived exchange rate model will also have an influence on the demand and supply of forward exchange, resulting in forward points that are a more accurate prediction of the realized future exchange rate. / Thesis (Ph.D. (Risk management))--North-West University, Potchefstroom Campus, 2011.

The inability to effectively hedge against unfavourable exchange rate movements, using the current forward exchange rate as the only guideline, is a key inhibiting factor of international trade. Market participants use the current forward exchange rate quoted in the market to make decisions regarding future exchange rate changes. However, the current forward exchange rate is not solely determined by the interaction of demand and supply, but is also a mechanistic estimation, which is based on the current spot exchange rate and the carry cost of the transaction. Results of various studies, including this study, demonstrated that the current forward exchange rate differs substantially from the realized future spot exchange rate. This phenomenon is known as the exchange rate puzzle. This study contributes to the dynamics of modelling exchange rate theories by developing an exchange rate model that has the ability to explain the realized future spot exchange rate and the exchange rate puzzle. The exchange rate model is based only on current (time t) economic fundamentals and includes an alternative approach of incorporating the impact of the interaction of two international financial markets into the model. This study derived a unique exchange rate model, which proves that the exchange rate puzzle is a pseudo problem. The pseudo problem is based on the generally excepted fallacy that current non–stationary, level time series data cannot be used to model exchange rate theories, because of the incorrect assumption that all the available econometric methods yield statistically insignificant results due to spurious regressions. Empirical evidence conclusively shows that using non–stationary, level time series data of current economic fundamentals can statistically significantly explain the realized future spot exchange rate and, therefore, that the exchange rate puzzle can be solved. This model will give market participants in the foreign exchange market a better indication of expected future exchange rates, which will considerably reduce the dependence on the mechanistically derived forward points. The newly derived exchange rate model will also have an influence on the demand and supply of forward exchange, resulting in forward points that are a more accurate prediction of the realized future exchange rate. / Thesis (Ph.D. (Risk management))--North-West University, Potchefstroom Campus, 2011.