The work presented in this dissertation can be grouped around two major themes. The first theme relates to the asset allocation and the second theme relates to risk management. In Chapter Three, we investigate the dynamics of foreign exchange and stock returns based on an extended version of Sentana and Wadhwani (1992) model. This study is mainly driven by the wish to explain two major stylized facts that puzzled the older models. We find evidence to support that only intertemporal variation in the foreign exchange risk premium can be explained by time¡Vvarying covariance priced risk factors. Furthermore, we also find that the first order autocorrelation of both foreign exchange and stock market returns in Taiwan is negatively related to the level of conditional volatility and covariance. This time-varying nature of the serial correlation pattern is consistent with our model where some traders follow feedback strategies. The three nested asset pricing models with four models of conditional second moments are strongly rejected. We conclude that our extended Sentana and Wadhwani model is more adequate in explaining the dynamics of foreign exchange and stock markets. In Chapter Four, we investigate the risk management of futures market and spot market returns. There is widespread evidence that the volatility of stock returns display an asymmetric response to good and bad news. This paper attempted and found the asymmetric behavior co-existence in spot as well as future markets. By using the Asymmetric Dynamic Model (ADC) proposed by Kroner and Ng (1998), we estimated the conditional covariance matrix asymmetric and calculated dynamic optimal hedge ratios. With the help of that asymmetric model, our ¡§out of sample¡¨ dynamic hedging strategy out-performed that of normally dynamic hedging strategies. However, while taking the transaction costs into consideration, the performance was even worse than that of the static strategy.

A large literature has related the failure of interest rate parity in the foreign exchange market to the existence of a time-varying risk premium. Nevertheless, most modern open economy DSGE models imply a (near) perfect interest rate parity condition. This paper presents a stylized two-country incomplete-markets model in which countries have strong precautionary motives because they face international liquidity constraints, the presence of which successfully generates a time-varying risk premium: the country that has accumulated debt after experiencing relative worse times has stronger precautionary motives and its asset carries a risk premium. (author's abstract) / Series: Department of Economics Working Paper Series

This thesis consists of three papers that make independendet contributions to the field of financial economics. As such, the papers, Chapter 2, Chapter 3, and Chapter 4, can be read independently of each other. In Chapter 2, we construct a simple measure of the aggregate illiquidity of hedge fund portfolios, and show that it has strong in- and out-of-sample forecasting power for 72 portfolios of international equities, U.S. corporate bonds, and currencies, over the 1994 to 2011 period. The forecasting ability of hedge fund illiquidity for asset returns is, in most cases, greater than, and provides independent information relative to, well-known predictive variables for each of these asset classes. We construct a simple equilibrium model to rationalise our findings and empirically verify auxiliary predictions of the model. In Chapter 3, I analyse the risk-shifting of hedge funds. Since the information on hedge fund holdings is very restricted, researchers have used the variance of returns as a proxy for risk. I propose a new method for measuring the time-varying variance. I use this method to investigate whether equity long-short hedge funds engage in risk-shifting driven by their past performance relative to their peers. I find that hedge funds which have strongly underperformed or outperformed their peers in recent months increase their exposure to the core strategy, i.e. the equity long-short strategy, and to non-core strategies. The risk shifting is mitigated for hedge funds with long redemption periods. Chapter 4 contributes to the equity premium prediction literature. I improve the forecast performance of typical single variable predictive regressions used in the equity premium prediction literature through Bayesian priors derived from consumption-based asset pricing models. To implement these model-based priors, I develop a Bayesian procedure which is rooted in the macroeconometrics literature. I find that the model-based priors can increase the explanatory power, measured by the out-of-sample R², of the single variable predictive regressions by several percentage points.

I find evidence of predictability in out-of-sample data for four risk premia using simple econometric models. Two factor return models are used, an APT model and the Wilshire Atlas. I demonstrate that investors can exploit conditioning information to manage their exposures to risk factors. The results suggest that the investment opportunities set changes in a large and an economically significant way. I show that the growth rate in money supply and trend in stock market valuations are the main drivers respectfully of the risk premia associated with the Book-to-Market and Size factors from the Wilshire model. The predictability results are mixed with respect to Business Cycle Theory. At times investors price business cycle risk while at other times they exhibit herding tendencies.

This thesis investigates systematic liquidity risk and short-term stock price reaction to large one-day price changes. We study 642 constituents of the FTSALL share index over the period from 1st July 1992 to 29th June 2007. We show that the US evidence of a priced systematic liquidity risk of Pastor and Stambaugh (2003) and Liu (2006) is not country-specific. Particularly, systematic liquidity risk is priced in the London Stock Exchange when Amihud's (2002) illiquidity ratio is used as a liquidity proxy. Given the importance of systematic liquidity risk in the asset pricing literature, we are interested in testing whether the different levels of systematic liquidity risk across stocks can explain the anomaly following large one-day price changes. Specifically, we expect that the stocks with high sensitivity to the fluctuations in aggregate market liquidity to be more affected by price shocks. We find that most liquid stocks react efficiently to price shocks, while the reactions of the least liquid stocks support the uncertain information hypothesis. However, we show that time-varying risk is more important than systematic liquidity risk in explaining the price reaction of stocks in different liquidity portfolios. Indeed, the time varying risk explains nearly all of the documented overreaction and underreaction following large one-day price changes. Our evidence suggests that the observed anomalies following large one-day price shocks are caused by the pricing errors arising from the use of static asset pricing models. In particular, the conditional asset pricing model of Harris et al. (2007), which allow both risk and return to vary systematically over time, explain most of the observed anomalies. This evidence supports the Brown et al. (1988) findings that both risk and return increase in a systematic fashion following price shocks.

This thesis investigates systematic liquidity risk and short-term stock price reaction to large one-day price changes. We study 642 constituents of the FTSALL share index over the period from 1st July 1992 to 29th June 2007. We show that the US evidence of a priced systematic liquidity risk of Pastor and Stambaugh (2003) and Liu (2006) is not country-specific. Particularly, systematic liquidity risk is priced in the London Stock Exchange when Amihud's (2002) illiquidity ratio is used as a liquidity proxy. Given the importance of systematic liquidity risk in the asset pricing literature, we are interested in testing whether the different levels of systematic liquidity risk across stocks can explain the anomaly following large one-day price changes. Specifically, we expect that the stocks with high sensitivity to the fluctuations in aggregate market liquidity to be more affected by price shocks. We find that most liquid stocks react efficiently to price shocks, while the reactions of the least liquid stocks support the uncertain information hypothesis. However, we show that time-varying risk is more important than systematic liquidity risk in explaining the price reaction of stocks in different liquidity portfolios. Indeed, the time varying risk explains nearly all of the documented overreaction and underreaction following large one-day price changes. Our evidence suggests that the observed anomalies following large one-day price shocks are caused by the pricing errors arising from the use of static asset pricing models. In particular, the conditional asset pricing model of Harris et al. (2007), which allow both risk and return to vary systematically over time, explain most of the observed anomalies. This evidence supports the Brown et al. (1988) findings that both risk and return increase in a systematic fashion following price shocks. / Yarmouk University, Jordan.

<p>The cross-sectional variation of stock returns used to be described by the Capital Asset Pricing Model until the early 90‟s. Anomalies, such as, book-to-market effect and small firm effect undermined CAPM‟s ability to explain stock returns and Fama & French (1992) have shown that simple firm attributes, like, firm size and book-to-market value can explain the returns far better than Beta. Following Fama & French many other researchers examine the explanatory powers of CAPM and other asset pricing models. However, most of those studies use US data. There are some researches done in different countries than US, however more out-of-sample studies need to be conducted.</p><p>To our knowledge there are very few studies using the Swedish data and this thesis contributes to that small pool of studies. Moreover, the studies testing the CAPM use the unconditional version of the model. There are some papers suggesting the use of a conditional CAPM that would exhibit better explanatory powers than the unconditional CAPM. Different ways of conditioning the CAPM have been proposed, but one that we think is the least complex and possible to make use of in the business world is the dual-beta model. This conditional CAPM assumes a different relationship between beta and stock returns during the up markets and down markets. Furthermore, the model has not thoroughly been tested outside the US. Our study is the first to use the dual-beta model in Sweden. In addition, the momentum effect has lately been given some attention and Fama & French‟s (1993) three factor model has not been able to explain the abnormal returns related to that anomaly. We test the Fama & French three factor model, CAPM and Carhart‟s four factor model‟s explanatory abilities of the momentum effect using Swedish stock returns. Ultimately, our aim is to find the best model that describes stock return cross-section on the Stockholm Stock Exchange.</p><p>We use returns of all the non-financial firms listed on Stockholm Stock Exchange between September, 1997 and April, 2010. The number of companies included in our time sample is 366. The results of our tests indicate that the small firm effect, book-to-market effect and the momentum effect are not present on the Stockholm Stock Exchange. Consequently, the CAPM emerges as the one model that explains stock return cross-section better than the other models suggesting that Beta is still a proper measure of risk. Furthermore, the conditional version of CAPM describes the stock return variation far better than the unconditional CAPM. This implies using different Betas to estimate risk during up market conditions and down market conditions.</p>

The cross-sectional variation of stock returns used to be described by the Capital Asset Pricing Model until the early 90‟s. Anomalies, such as, book-to-market effect and small firm effect undermined CAPM‟s ability to explain stock returns and Fama &amp; French (1992) have shown that simple firm attributes, like, firm size and book-to-market value can explain the returns far better than Beta. Following Fama &amp; French many other researchers examine the explanatory powers of CAPM and other asset pricing models. However, most of those studies use US data. There are some researches done in different countries than US, however more out-of-sample studies need to be conducted. To our knowledge there are very few studies using the Swedish data and this thesis contributes to that small pool of studies. Moreover, the studies testing the CAPM use the unconditional version of the model. There are some papers suggesting the use of a conditional CAPM that would exhibit better explanatory powers than the unconditional CAPM. Different ways of conditioning the CAPM have been proposed, but one that we think is the least complex and possible to make use of in the business world is the dual-beta model. This conditional CAPM assumes a different relationship between beta and stock returns during the up markets and down markets. Furthermore, the model has not thoroughly been tested outside the US. Our study is the first to use the dual-beta model in Sweden. In addition, the momentum effect has lately been given some attention and Fama &amp; French‟s (1993) three factor model has not been able to explain the abnormal returns related to that anomaly. We test the Fama &amp; French three factor model, CAPM and Carhart‟s four factor model‟s explanatory abilities of the momentum effect using Swedish stock returns. Ultimately, our aim is to find the best model that describes stock return cross-section on the Stockholm Stock Exchange. We use returns of all the non-financial firms listed on Stockholm Stock Exchange between September, 1997 and April, 2010. The number of companies included in our time sample is 366. The results of our tests indicate that the small firm effect, book-to-market effect and the momentum effect are not present on the Stockholm Stock Exchange. Consequently, the CAPM emerges as the one model that explains stock return cross-section better than the other models suggesting that Beta is still a proper measure of risk. Furthermore, the conditional version of CAPM describes the stock return variation far better than the unconditional CAPM. This implies using different Betas to estimate risk during up market conditions and down market conditions.