An overwhelmingly large number of research studies in corporate Finance span the basis formed by chiefly three corporate policies - Financial policy (leverage), dividend policy, and investment policy. The two most oft-cited frictions, agency issues and asymmetric information, add complexities to the nexus formed by the policies. My empirical dissertation, "Three essays in real estate and entrepreneurial Finance" is an attempt to capture some of the interplay of the nexus formed by three policies and/or the two frictions in the realm of real estate Finance and entrepreneurial Finance. The dissertation is a collection of two single-authored essays in real estate Finance and an essay (joint work) in entrepreneurial Finance.
This thesis considers two main subjects divided in four problems in the broad field of mathematical finance. The first chapter treats option pricing followed by three chapters on the application of the machine learning algorithm of Random Forests to finance, specifically to risk capital aggregation, portfolio optimization and macro stress testing. In all four chapters new methodologies to treat the respective subjects are developed. All proposed models are benchmarked against commonly applied methods in the respective fields and found to outperform their peers.
The risk of financial positions is measured by the minimum amount of capital to raise and invest in eligible portfolios of traded assets in order to meet a prescribed acceptability constraint. We investigate nondegeneracy, finiteness and continuity properties of these risk measures with respect to multiple eligible assets. Our finiteness and continuity results highlight the interplay between the acceptance set and the class of eligible portfolios. We present a simple, alternative approach to the dual representation of convex risk measures by directly applying to the acceptance set the external characterization of closed, convex sets. We prove that risk measures are nondegenerate if and only if the pricing functional admits a positive extension which is a supporting functional for the underlying acceptance set, and provide a characterization of when such extensions exist. Finally, we discuss applications to set-valued risk measures, superhedging with shortfall risk, and optimal risk sharing.
We present results from a large-scale international survey on risk preferences conducted in 53 countries. In all countries, we find, on average, an attitude of risk aversion in gains and of risk seeking in losses. The degree of risk aversion shows significant cross-country differences. Moreover, risk attitudes in our sample depend not only on economic conditions but also on cultural factors, as measured by the Hofstede dimensions individualism and uncertainty avoidance. The data may also serve as an interesting starting point for further research on cultural differences in behavioral economics.
Inflation expectations are a key variable in conducting monetary policy. However, these expectations are generally unobservable and only certain proxy variables exist, such as surveys on inflation expectations. This article offers guidance on the appropriate quantification of household inflation expectations in the Swiss Consumer Survey, where answers are qualitative in nature. We apply and evaluate different variants of the probability approach and the regression approach; we demonstrate that models that include answers on perceived inflation and allow for time-varying response thresholds yield the best results; and we show why the originally proposed approach of Fluri and Spörndli (1987) has resulted in heavily biased inflation expectations since the mid-1990s. Furthermore, we discuss some of the key features of Swiss household inflation expectations, i.e. the fact that there has been a shift in expectation formation since 2000 (expectations are better anchored and less adaptive, and there is lower disagreement of expectations). We suggest that this may be linked to the Swiss National Bank’s adjustment of its monetary policy framework around this time. In addition, we outline how expectation formation in Switzerland is in line with the sticky information model, where information disseminates slowly from professional forecasters to households.
A new multivariate time series model with various attractive properties is motivated and studied. By extending the CCC model in several ways, it allows for all the primary stylized facts of financial asset returns, including volatility clustering, non-normality (excess kurtosis and asymmetry), and also dynamics in the dependency between assets over time. A fast EM-algorithm is developed for estimation. Each element of the vector return at time tt is endowed with a common univariate shock, interpretable as a common market factor. This leads to the new model being a hybrid of GARCH and stochastic volatility, but without the estimation problems associated with the latter, and being applicable in the multivariate setting for potentially large numbers of assets. A feasible technique which allows for multivariate option pricing is presented, along with an empirical illustration.
This paper develops a method to measure and compare social performance of microfinance investments at the level of microfinance investment vehicles. Drawing from measurement theory, it develops formal quality criteria that individual social performance indicators, the selection, and the aggregation of such indicators into a single metric need to satisfy. Social performance indicators are selected for both microfinance investment vehicles, and their underlying portfolio. The method presented here uses data of the microfinance investment universe to determine a rating framework for the underlying of microfinance institutions, in addition to a unique set of variables captured at MIV level. The paper demonstrates the approach in a sample calculation and serves as a guideline for a future empirical application among microfinance investment vehicles.
