Political Risk in Credit Evaluation: Empirical Studies and Survey Results

Financing trade between economic agents located in different countries is affected by many types of risks, resulting from incomplete information about the debtor, the problems of enforcing international contracts, or the prevalence of political and financial crises. Trade is important for economic development and the availability of trade finance is essential, especially for developing countries. Relatively few studies treat the topic of political risk, particularly in the context of international lending. This thesis explores new ground to identify links between political risk and international debt defaults. The core hypothesis of the study is that the default probability of debt increases with increasing political risk in the country of the borrower. The thesis consists of three essays that support the hypothesis from different angles of the credit evaluation process. The first essay takes the point of view of an international lender assessing the credit risk of a public borrower. The second investigates creditworthiness assessment of companies. The obtained results are substantiated in the third essay that deals with an extensive political risk survey among finance professionals in developing countries. The financial instruments of core interest are export credit guaranteed debt initiated between the Export Credit Agency of Finland and buyers in 145 countries between 1975 and 2006. Default events of the foreign credit counterparts are conditioned on country-specific macroeconomic variables, corporate-specific accounting information as well as political risk indicators from various international sources. Essay 1 examines debt issued to government controlled institutions and conditions public default events on traditional macroeconomic fundamentals, in addition to selected political and institutional risk factors. Confirming previous research, the study finds country indebtedness and the GDP growth rate to be significant indicators of public default. Further, it is shown that public defaults respond to various political risk factors. However, the impact of the risk varies between countries at different stages of economic development. Essay 2 proceeds by investigating political risk factors as conveivable drivers of corporate default and uses traditional accounting variables together with new political risk indicators in the credit evaluation of private debtors. The study finds links between corporate default and leverage, as well as between corporate default and the general investment climate and measeures of conflict in the debtor country. Essay 3 concludes the thesis by offering survey evidence on the impact of political risk on debt default, as perceived and experienced by 103 finance professionals in 38 developing countries. Taken together, the results of the thesis suggest that various forms of political risk are associated with international debt defaults and continue to pose great concerns for both international creditors and borrowers in developing countries. The study provides new insights on the importance of variable selection in country risk analysis, and shows how political risk is actually perceived and experienced in the riskier, often lower income countries of the global economy.

An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions

This paper uses the Value-at-Risk approach to define the risk in both long and short trading positions. The investigation is done on some major market indices(Japanese, UK, German and US). The performance of models that takes into account skewness and fat-tails are compared to symmetric models in relation to both the specific model for estimating the variance, and the distribution of the variance estimate used as input in the VaR estimation. The results indicate that more flexible models not necessarily perform better in predicting the VaR forecast; the reason for this is most probably the complexity of these models. A general result is that different methods for estimating the variance are needed for different confidence levels of the VaR, and for the different indices. Also, different models are to be used for the left respectively the right tail of the distribution.

Information, risk and trust in the food chain : Ex-ante valuation of consumer willingness to pay for beef quality information using the contingent valuation method

The safety of food has become an increasingly interesting issue to consumers and the media. It has also become a source of concern, as the amount of information on the risks related to food safety continues to expand. Today, risk and safety are permanent elements within the concept of food quality. Safety, in particular, is the attribute that consumers find very difficult to assess. The literature in this study consists of three main themes: traceability; consumer behaviour related to both quality and safety issues and perception of risk; and valuation methods. The empirical scope of the study was restricted to beef, because the beef labelling system enables reliable tracing of the origin of beef, as well as attributes related to safety, environmental friendliness and animal welfare. The purpose of this study was to examine what kind of information flows are required to ensure quality and safety in the food chain for beef, and who should produce that information. Studying the willingness to pay of consumers makes it possible to determine whether the consumers consider the quantity of information available on the safety and quality of beef sufficient. One of the main findings of this study was that the majority of Finnish consumers (73%) regard increased quality information as beneficial. These benefits were assessed using the contingent valuation method. The results showed that those who were willing to pay for increased information on the quality and safety of beef would accept an average price increase of 24% per kilogram. The results showed that certain risk factors impact consumer willingness to pay. If the respondents considered genetic modification of food or foodborne zoonotic diseases as harmful or extremely harmful risk factors in food, they were more likely to be willing to pay for quality information. The results produced by the models thus confirmed the premise that certain food-related risks affect willingness to pay for beef quality information. The results also showed that safety-related quality cues are significant to the consumers. In the first place, the consumers would like to receive information on the control of zoonotic diseases that are contagious to humans. Similarly, other process-control related information ranked high among the top responses. Information on any potential genetic modification was also considered important, even though genetic modification was not regarded as a high risk factor.

Studies on Binary Time Series Models with Applications to Empirical Macroeconomics and Finance

This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

Essays on Risk Modeling. Applications to Portfolio and Risk Management (summary section only)

In this thesis we deal with the concept of risk. The objective is to bring together and conclude on some normative information regarding quantitative portfolio management and risk assessment. The first essay concentrates on return dependency. We propose an algorithm for classifying markets into rising and falling. Given the algorithm, we derive a statistic: the Trend Switch Probability, for detection of long-term return dependency in the first moment. The empirical results suggest that the Trend Switch Probability is robust over various volatility specifications. The serial dependency in bear and bull markets behaves however differently. It is strongly positive in rising market whereas in bear markets it is closer to a random walk. Realized volatility, a technique for estimating volatility from high frequency data, is investigated in essays two and three. In the second essay we find, when measuring realized variance on a set of German stocks, that the second moment dependency structure is highly unstable and changes randomly. Results also suggest that volatility is non-stationary from time to time. In the third essay we examine the impact from market microstructure on the error between estimated realized volatility and the volatility of the underlying process. With simulation-based techniques we show that autocorrelation in returns leads to biased variance estimates and that lower sampling frequency and non-constant volatility increases the error variation between the estimated variance and the variance of the underlying process. From these essays we can conclude that volatility is not easily estimated, even from high frequency data. It is neither very well behaved in terms of stability nor dependency over time. Based on these observations, we would recommend the use of simple, transparent methods that are likely to be more robust over differing volatility regimes than models with a complex parameter universe. In analyzing long-term return dependency in the first moment we find that the Trend Switch Probability is a robust estimator. This is an interesting area for further research, with important implications for active asset allocation.

Essays on Stock Option Compensation and the Role of Incentives and Risk (summary section only)

Managerial pay-for-performance sensitivity has increased rapidly around the world. Early empirical research showed that pay-for-performance sensitivity resulting from stock ownership and stock options appeared to be quite low during the 1970s and early 1980s in the U.S. However, recent empirical research from the U.S. shows an enormous increase in pay-for-performance sensitivity. The global trend has also reached Finland, where stock options have become a major ingredient of executive compensation. The fact that stock options seem to be an appealing form of remuneration from a theoretical point of view combined with the observation that the use of this compensation form has increased significantly during the recent years, implies that research on the dynamics of stock option compensation is highly relevant for the academic community, as well as for practitioners and regulators. The research questions of the thesis are analyzed in four separate essays. The first essay examines whether stock option compensation practices of Finnish firms are consistent with predictions from principal-agent theory. The second essay explores one of the major puzzles in the compensation literature by studying determinants of stock option contract design. In theory, optimal contract design should vary according to firm characteristics. However, in the U.S., variation in contract design seems to be surprisingly low, a phenomenon generally attributed to tax and accounting considerations. In Finland, however, firms are not subject to stringent contracting restrictions, and the variation in contract design tends, in fact, to be quite substantial. The third essay studies the impact of price- and risk incentives arising from stock option compensation on firm investment. In addition, the essay explores one of the most debated questions in the literature, in particular, the relation between incentives and firm performance. Finally, several strands of literature in both economics and corporate finance hypothesize that economic uncertainty is related to corporate decision-making. Previous research has shown that risk tends to slow down firm investment. In the fourth essay, it is hypothesized that firm risk slows down growth from a more universal perspective. Consistent with this view, it is shown that risk not only tends to slow down firm investment, but also employment growth. Moreover, the essay explores whether the nature of firms’ compensation policies, in particular, whether firms make use of stock option compensation, affects the relation between risk and firm growth. In summary, the four essays contribute to the current understanding of stock options as a form of equity incentives, and how incentives and risk affect corporate decision-making. By this, the thesis promotes the knowledge related to the modern theory of the firm.