Examining macroeconomic models through the lens of asset pricing

We develop new methods for representing the asset-pricing implications of stochastic general equilibrium models. We provide asset-pricing counterparts to impulse response functions and the resulting dynamic value decompositions (DVDs). These methods quantify the exposures of macroeconomic cash flows to shocks over alternative investment horizons and the corresponding prices or investors’ compensations. We extend the continuous-time methods developed in Hansen and Scheinkman (2012) and Borovi?ka et al. (2011) by constructing discrete-time, state-dependent, shock-exposure and shock-price elasticities as functions of the investment horizon. Our methods are applicable to economic models that are nonlinear, including models with stochastic volatility.     

PRICING OF HIGH‐DIMENSIONAL AMERICAN OPTIONS BY NEURAL NETWORKS

Pricing of American options in discrete time is considered, where the option is allowed to be based on several underlyings. It is assumed that the price processes of the underlyings are given Markov processes. We use the Monte Carlo approach to generate artificial sample paths of these price processes, and then we use the least squares neural networks regression estimates to estimate from this data the so‐called continuation values, which are defined as mean values of the American options for given values of the underlyings at time t subject to the constraint that the options are not exercised at time t. Results concerning consistency and rate of convergence of the estimates are presented, and the pricing of American options is illustrated by simulated data.     

Prediction of bank financial strength ratings: The case of Turkey

Bank financial strength ratings have gained widespread popularity especially after the recent financial turmoil. Rating agencies were criticized because of their ratings and failure to predict the bankruptcy of the banks. Based on this observation, we investigate whether the forecast of the rating of bank's financial strength using publicly available data is consistent with those of the credit rating agency. We use the data of Turkish banks for this investigation. We take a country-specific approach because previous studies found that proxies used for environmental factors (political, economic, and financial risk of the country) did not have any explanatory power and it is hard to find international data for other important factors such as franchise value, concentration, and efficiency. We use two popular multivariate statistical techniques (multiple discriminant analysis and ordered logistic regression) to estimate a suitable model and we compare their performances with those of two mostly used data mining techniques (Support Vector Machine and Artificial Neural Network). Our results suggest that our predictions are consistent with those of Moody's financial strength rating in general.. The important factors in rating are found to be profitability (measured by return on equity), efficient use of resources, and funding the businesses and the households instead of the government that shows efficient placement of the funds.     

The view from above: the relevance of shared aerial drone videos for destination marketing

ABSTRACT

The use of drones to produce videos has generated a large amount of visually appealing footage of various destinations. They attract much attention, but there are issues that affect their production, and their relevance to destination marketing. This research examines YouTube meta-data and spatial overlay analysis of shared aerial drone videos from the United Kingdom (UK). The results suggest that shared aerial drone videos have some unique user-generated content (UGC) characteristics and their spatial distribution tends to favor more populated areas. Theoretical and practical implications for destination marketing are further discussed.     

Saliency of outside options in the lost wallet game

This paper reports an experiment designed to shed light on an empirical puzzle observed by Dufwenberg and Gneezy (Games and Economic Behavior 30:163–182, 2000) that the size of the foregone outside option by the first mover does not affect the behavior of the second mover in a lost wallet game. Our conjecture was that the original protocol may not have made the size of the forgone outside option salient to second movers. Therefore, we change two features of the Dufwenberg and Gneezy protocol: (i) instead of the strategy method we implement a direct response method (sequential play) for the decision of the second mover; and (ii) we use paper money certificates that are passed between the subjects rather than having subjects write down numbers representing their decisions. We observe that our procedure yields qualitatively the same result as the Dufwenberg and Gneezy experiment, i.e., the second movers do not respond to the change in the outside option of the first movers.     

Foreign News and Spillovers in Emerging European Stock Markets

We analyze foreign news and spillovers in the emerging EU stock markets (the Czech Republic, Hungary, and Poland). We employ high‐frequency five‐minute intraday data on stock market index returns and four classes of EU and US macroeconomic announcements during 2004–07. We account for the difference of each announcement from its market expectation and we jointly model the volatility of the returns accounting for intraday movements and day‐of‐the‐week effects. Our findings show that intraday interactions on the new EU markets are strongly determined by mature stock markets as well as the macroeconomic news originating thereby. We show that strong contemporaneous links across markets are present even after controlling for macroeconomic announcements. Finally, in terms of specific announcements, we are able to show the exact sources of macro news spillovers from the developed foreign markets to the three new EU markets under research.