A Critical Review of Housing Markets

This PhD dissertation, composed of three studies, provides a critical review of the determinants of price changes in the housing market. In the first paper, I address the counterintuitive negative risk-return relationship in the housing market, previously found in the literature. I show that the negative relationship in the US can be resolved by considering the modelling differences between aggregate and cross-sectional conditions in standard asset pricing theory. The result has implications for the application of standard finance theory towards housing markets. In the second paper, I revisit the commonly-held beliefs that the nature of housing markets is mainly local and that local time-invariant amenities are crucial for understanding housing price dynamics. Based on the empirical evidence of the US housing markets, I show that the documented evidence in support of these arguments can be an artefact of sample size in the time series dimension of a panel data analysis. The result provides implications for empirical and theoretical research regarding the assumptions of housing market dynamics. The third paper presents a historical review of the long-run relationship between macroeconomic factors and housing markets from 1871 to 2012. I find that century-long evidence across 10 countries has consistently favoured the role of inflation hedging in residential real estate, yet its significance has decreased in the recent regime of inflation targeting from 1990 to 2012. During the latter period, much of the variation in housing markets is linked not to inflation risk, but rather to changes in real income. The result adds a new dimension to understanding how inflation hedging benefits can change under different momentary environments

Interest rate sensitivity of property stock in Hong Kong

Includes bibliographical references (p. 64-74).Thesis (B.Sc)--University of Hong Kong, 2010.published_or_final_versio

Asset Pricing and the Intertemporal Risk-Return Tradeoff

The intertemporal risk-return tradeoff is the cornerstone of modern empirical finance and has been the focus of much debate over the years. The reason for this is because extant literature cannot agree as to the very nature of this important relation. This is troublesome in terms of academic theory given that it challenges the notion that investors are risk-averse agents and is furthermore troublesome in practice given that market participants expect to be rewarded with higher expected returns in order to take on higher risks. The motivation for this thesis stems from the conflicting and inconclusive empirical evidence regarding the risk-return tradeoff. Through each of the chapters, it sheds new light on possible reasons as to why extant studies offer conflicting evidence and, given the enhancements and innovative approaches proposed here, it provides empirical evidence in support of a positive intertemporal risk-return tradeoff when examining several international stock markets. The research questions this thesis addresses are as follow. Firstly, is it possible that extant conflicting evidence is manifested in the use of historical realized returns to proxy for investors’ forward-looking expected returns? Secondly, can accounting for shifts in investment opportunities (i.e. intertemporal risk) better explain investors’ risk aversion and changes in the dynamic risk premium? Thirdly, is it possible that conflicting findings are the result of neglecting to account for the possibility that there exist heterogeneous investors in the stock market with divergent expectations? The empirical findings can be summarized as follows; firstly, there is a strong possibility that many existing studies cannot find a positive risk-return relation because they are relying on ex post historical realized returns as a proxy for investors’ forward-looking expected returns. Secondly, there is evidence in favor of the Merton (1973) notion that there exists intertemporal risk which impacts investors and that this type of risk should be considered. This has been also another reason why extant literature cannot agree on the nature of the intertemporal risk-return tradeoff. Finally, even after accounting for investor heterogeneity, the findings provide support for the Merton (1973) theoretical Intertemporal Capital Asset Pricing Model. Namely, in contrast to existing studies on the matter, there is evidence of fundamental traders over longer horizons and no evidence of feedback traders at such horizons. Although this sheds new light on some of the driving forces behind stock prices, the nature of investors’ degree of risk aversion seems to be best supported by the Merton (1973) theoretical Intertemporal Capital Asset Pricing Model

Continuous-time Mean-Variance Portfolio Selection with Stochastic Parameters

This paper studies a continuous-time market {under stochastic environment} where an agent, having specified an investment horizon and a target terminal mean return, seeks to minimize the variance of the return with multiple stocks and a bond. In the considered model firstly proposed by [3], the mean returns of individual assets are explicitly affected by underlying Gaussian economic factors. Using past and present information of the asset prices, a partial-information stochastic optimal control problem with random coefficients is formulated. Here, the partial information is due to the fact that the economic factors can not be directly observed. Via dynamic programming theory, the optimal portfolio strategy can be constructed by solving a deterministic forward Riccati-type ordinary differential equation and two linear deterministic backward ordinary differential equations

Essays on Empirical Asset Pricing Models

This thesis examines co-movement across industry return and value and momentum asset price anomalies through a new perspective and uses machine learning and spatial econometrics approaches. The first chapter examines the main approaches developed in the cross-section asset pricing literature for finding risk variables. The second chapter focuses on spatial co-movement across US industry returns. We show that spatial co-movement explains the variance in US industry returns after accounting for exposure to common variables, serial dynamics, and industry sector-specific characteristics using a dynamic spatial panel data model. The results show that an investment strategy that buys industry portfolios with high own-return and high spatially connected (neighboring) portfolio return and sells industry portfolios with low own-return and low spatially connected (neighboring) portfolio return generates an annual non-market return of approximately 8%. In the third chapter of the dissertation, we propose a multi-factor model in which the extra variables (apart from the standard market factor) are the innovation in each sparse principal component. Our findings demonstrate that our suggested hedging factors, which include Production (PR), Housing (H), Yield (Y), and Yield Spread (YS), explain a significant portion of the spread in average equity premia of the momentum portfolio deciles and value portfolio returns. In addition, the paper examines whether the multi-factor model is consistent with Merton\u27s (1973) ICAPM framework

ORGANIZATIONAL ECONOMICS AND THE FOOD PROCESSING INDUSTRY

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\u27s 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

Non-United States Firms\u27 Exchange Rate Exposure and the Pricing of Exchange Rate Risk in Foreign Stock Markets

This two part dissertation is an in depth study of the measurement of foreign currency economic exposure faced by foreign firms and whether or not this exposure is associated with significant risk premia within these firms\u27 national equity markets. Firms from four foreign countries; Germany, the United Kingdom, Japan and Canada are classified as purely domestic firms, exporters with low (20%-39%) percentages of foreign sales to total sales, exporters with high (over 40%) percentages of foreign sales to total sales, or multinational corporations. Essay I focuses on the economic exposure of these non-US firms. Foreign exchange rate volatility can impact a firm\u27s cash flows and discount rate. Economic exposure can therefore effect the firm\u27s long run profitability, consequentially producing changes in shareholder\u27s wealth. We find that while purely domestic and low exporting firms are not typically exposed to exchange rate changes, high exporting and multinational firms are. Although the level of this exposure varies across exchange rates, it is consistently positive. The percent foreign sales to total sales is a significant determinant of this exposure. We also find that country specific domestic market indexes explain more of the various sample variances than does a world market index. Essay II extends the Chen, Roll, and Ross (1986) multi-factor pricing model to the four national equity markets represented by the firms in Essay I. Multi-factor pricing tests are run on sub-samples designated by the primary trading activities previously describes, as well as on well diversified samples for each country. The results indicate that exchange rate change is not a diversifiable risk in the equity markets of Germany and Japan. We also find that the significant pricing of exchange rate risk is not consistently based upon underlying levels of economic exposure

Three essays on pricing kernel in asset pricing

Pricing Kernel extends concepts from economics and finance to include adjustments for risk. When pricing kernel is given, by non-arbitrage theory, all securities can be priced. Searching for a proper pricing kernel is one of the most important tasks for researchers in asset pricing. In this thesis, we attempt to search a proper pricing kernel in three different scenarios. In chapter 1, we attempt to find a robust pricing kernel for a stochastic volatility model with parameter uncertainty in an incomplete commodity market. Based on a class of stochastic volatility models in Trolle and Schwartz (2009), we investigate how the parameter uncertainty affects the risk premium and commodity contingent claim pricing. To answer this question, we follow a two-step procedure. Firstly, we propose a benchmark approach to find an optimal pricing kernel for the model without parameter uncertainty. Secondly, we uncover a robust pricing kernel via a robust approach for the model with parameter uncertainty. Thirdly, we apply the two pricing kernels into the commodity contingent claim pricing and quantify effect of parameter uncertainty on contingent claim securities. We find that the parameter uncertainty attributes a negative uncertainty risk premium. Moreover, the negative uncertainty risk premium yields a positive uncertainty volatility component in the implied volatilities in the option market. In chapter 2, we propose a multi-factor model with a quadratic pricing kernel, in which the underlying asset return is a linear function of multi-factors and the pricing kernel is a quadratic function of multi-factors. The model provides a potential unified framework to link cross sectional literatures, time-series literatures, option pricing literatures and term structure literatures. By examining option data from 2005 to 2008, this model dramatically improves the cross-sectional fitting of option data both in sample and out of sample than many standard GARCH volatility models such as Christoffersen, Heston and Nandi (2011). This model also offers explanations for several puzzles such as the U shape relationship between the pricing kernel and market index return, the implied volatility puzzle and fat tails of risk neutral return density function relative to the physical distribution. In chapter 3, we investigate whether idiosyncratic volatility risk premium is cross-sectional variant. We use stock historical moving average price as a proxy for retail ownership and examine whether idiosyncratic volatility is correlated with stock price level. Evidence from cross-sectional regressions and portfolio analysis both suggests that low-priced stocks (high retail ownership) have a significantly higher idiosyncratic volatility risk premium than high-priced stocks (low retail ownership). Especially, evidence in subsample tests suggests that lowest-priced stocks (highest retail ownership) have a significantly positive idiosyncratic risk premium while highest-priced stocks (lowest retail ownership) have an insignificant one, which is consistent with theoretical predictions of Merton (1986) and classical portfolio theory