Convertibility risk: the precautionary demand for foreign currency in a crisis

This paper presents theoretical work linking money demand to the perceptions of households about the risk that domestic currency may become inconvertible or that it may be devalued. An empirical investigation of the size of this effect is carried out using monthly data for Korea to estimate an augmented demand-for-money equation. It is found that the fear of inconvertibility arising from the 1997 Korean currency crisis may have caused broad money demand to fall by 4–5% points,equivalent to the loss of reserves of $6–7.5 billion (or about 30% of reserves as measured at end-November 1997). This is a revised version of IMF Working paper WP/2001/210; it was written while Professor Black was Senior Policy Advisor at the IMF Institute and Christofides and Mourmouras were staff members in the IMF’s Policy Development and Review Department. The views expressed are those of the authors and should not be attributed to the IMF, its Executive Board, or its management. For useful comments and suggestions we thank an anonymous referee, Tim Lane, Ydahlia Metzgen, Roberto Perelli, Tony Richards, Christian Mulder, Steve Russell, as well as seminar participants at the IMF Institute, the IMF’s Asia and Pacific Department, Federal Reserve Board, and Bank of Indonesia. We would also like to note similar (unpublished) empirical results using our approach by Dr. Rino Effendi for Indonesia and Angana Banerji for Russia     

Factors influencing the profitability of pharmaceutical research

The output from a pharmaceutical research project is a stream of candidate drugs which may be submitted to clinical trials. The value of this output depends on the characteristics of the stochastic process generating this stream, and on the extent to which the candidate drugs are chemically similar to each other. This paper explores the impact of these factors on profitability, and on the policy which should be followed for selecting candidate drugs.     

Generalized parameter functions for option pricing

We extend the benchmark nonlinear deterministic volatility regression functions of Dumas et al. (1998) to provide a semi-parametric method where an enhancement of the implied parameter values is used in the parametric option pricing models. Besides volatility, skewness and kurtosis of the asset return distribution can also be enhanced. Empirical results, using closing prices of the S&P 500 index call options (in one day ahead out-of-sample pricing tests), strongly support our method that compares favorably with a model that admits stochastic volatility and random jumps. Moreover, it is found to be superior in various robustness tests. Our semi-parametric approach is an effective remedy to the curse of dimensionality presented in nonparametric estimation and its main advantage is that it delivers theoretically consistent option prices and hedging parameters. The economic significance of the approach is tested in terms of hedging, where the evaluation and estimation loss functions are aligned.     

Factors influencing foreign direct investment of South African financial services firms in Sub-Saharan Africa

This research investigates the key elements that South African financial services firms consider before making foreign direct investments in Sub-Saharan African (SSA) markets. The results show that South African financial services firms are most strongly influenced by the political and economic stability of the country in question as well as the profitability and long-term sustainability of its specific markets. The degree of available infrastructure in terms of Information and Communication Technology as well as the existence of credible financial systems was also viewed as highly important considerations before investing in SSA. Given the uncertainty and ambiguity of most SSA markets many South African financial services firms prefer to enter existing markets via a majority stakeholder joint venture with a local partner or via a new investment if the market does not currently exist. The nature of the financial services firm also seems to influence the entry method and once in a new country most firms seem to prefer a full service presence. Additionally, the key motives cited for expansion northward were to broaden revenue bases and improve profit margins as well as to stay close to local customers.     

Human resource management and firm performance in Europe through the lens of business systems: best fit,best practice or both?

This study uses the lens of Business Systems theory to explore the importance of geographic context on the link between human resource management and organizational performance. Basing the analysis on ‘HRM bundles of competitive advantage’, drawing evidence from a large-scale survey of European private sector businesses, and using multiple methodologies, we find three distinct geographic regions and 21 ‘HRM bundles of competitive advantage’. Of those bundles 10 were significantly related to performance in one or more regions. The results raise issues about the universal applicability of HRM-performance research and have implications for the standardization of HRM policies and practices within internationally operating organizations.     

Embedded and exposed: exploring the lived experiences of African American tourists

ABSTRACT

The United States is experiencing a shift in racial demographics. Recent projections suggest that minority groups will make up over 40% of the country’s population by 2050. Such increases have made the topics of race, ethnicity, and culture an important area of study for researchers and tourism professionals alike. Existing explanations of differences in African American travel suggest that decisions are made due to marginality or ethnicity. Because travel preferences may be a byproduct of learned behaviors passed down through generations, it is imperative to understand both current and historical aspects of leisure behavior. In this qualitative study, the narratives of 12 African American tourists provided information which suggests that marginality, ethnicity, and issues related to discrimination impact their tourism-related attitudes and behaviors. Capturing the voices of African American travelers offers a more inclusive understanding of their travel experiences and insights into the relationship between race and tourism.     

Assessing the performance of symmetric and asymmetric implied volatility functions

This study examines several alternative symmetric and asymmetric model specifications of regression-based deterministic volatility models to identify the one that best characterizes the implied volatility functions of S&P 500 Index options in the period 1996–2009. We find that estimating the models with nonlinear least squares, instead of ordinary least squares, always results in lower pricing errors in both in- and out-of-sample comparisons. In-sample, asymmetric models of the moneyness ratio estimated separately on calls and puts provide the overall best performance. However, separating calls from puts violates the put-call-parity and leads to severe model mis-specification problems. Out-of-sample, symmetric models that use the logarithmic transformation of the strike price are the overall best ones. The lowest out-of-sample pricing errors are observed when implied volatility models are estimated consistently to the put-call-parity using the joint data set of out-of-the-money options. The out-of-sample pricing performance of the overall best model is shown to be resilient to extreme market conditions and compares quite favorably with continuous-time option pricing models that admit stochastic volatility and random jump risk factors.     

The Prediction of Earnings Using Financial Statement Information: Empirical Evidence With Logit Models and Artificial Neural Networks

In the past three decades, earnings have been one of the most researched variables in accounting. Empirical research provided substantial evidence on its usefulness in the capital markets but evidence in predicting earnings has been limited, yielding inconclusive results. The purpose of this study is to validate and extend prior research in predicting earnings by examining aggregate and industry-specific data. A sample of 10,509 firm-year observations included in the Compustat database for the period 1982–91 is used in the study. The stepwise logistic regression results of the present study indicated that nine earnings and non-earnings variables can be used to predict earnings. These predictor variables are not identical to those reported in prior studies. These results are also extended to the manufacturing industry. Two new variables are identified to be significant in this industry. Moreover, an Artificial Neural Network (ANN) approach is employed to complement the logistic regression results. The ANN model's performance is at least as high as the logistic regression model's predictive ability.     

Estimating corporate bankruptcy forecasting models by maximizing discriminatory power

Review of Quantitative Finance and Accounting - In this paper, we estimate coefficients of bankruptcy forecasting models, such as logistic and neural network models, by maximizing their...