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Roles of leadership in coping with uncertainty are explored in this paper. Through an in‐depth, empirically (CEOs of top, ASEAN publicly listed corporations) grounded discussion, the authors argued for the presence of a deep cultural divide between Eastern and Western leaders on coping with uncertainty. In the process, the authors devise a two dimensional, organic versus forecastability model of strategy behavior for polarizing East‐West leadership styles. Aspects of the Sun Tzu’s Art of War and 5,000 years old, I Ching are discussed with respect to foreknowledge and foresight respectively.

The objective of this paper is to investigate the validity of stock valuation theories and their forecasting ability by conducting an empirical study. It employs four most commonly used theories which are then tested using 19-year banking-firm market data. The usefulness of these models demonstrates with promising results.

This paper conducts a multi-country study using the multi-model testing approach to evaluate validity of theories and forecast accuracy of banking firms. It employs four methodology models used in finance literature; (1) P/E multiples model, (2) accounting-information-based clean surplus model, (3) theoretical model based on Gordon and Shapiro (1956) method and (4) the Damodaran-Kottler Free Cash Flow or FCF theory based on discounting model.

The tests show that the four theories under tests have a significant fit with actual price formation. The explained variation ranges from 72 to 92%, so the explanatory power of the theories accounting for variations in bank prices over 19-year period is substantial. The models fit suggest that the P/E model has superior predictive power followed by the RIM, DDM and FCFE. These findings shed new lights on the relative performance of valuation models.

The study is limited in terms of the sample period size for 1999–2019. The availability of essential financial data prior to 2000 is very limited, so one can understand interpretation of statistical results under certain assumptions.

The paper suggests that one-factor model is better than the two-factor model.

The work done in this paper is unpublished and original contribution to banking and finance literature and also not under consideration for publication in any other journal.

The economic doctrine of market efficiency plays an essential role in securities fraud litigation. In lawsuits alleging violations of SEC Rule 10b-5, the plaintiffs typically must argue that the market for the relevant security is efficient, and therefore that the “fraud on the market” doctrine applies. However, the term “market efficiency” is often applied imprecisely. In this chapter, we discuss properties of efficient markets that have been proposed in academic research, legal scholarship, and case law. We explore what must be assumed about capital markets for each of these properties to hold. We then ask how, in practice, each property could be rebutted.

This chapter is designed to outline how current methods in formal policy analysis have evolved to better respect limits to an analyst's knowledge. These limits are referred to as model uncertainty both in order to capture the idea that formal policy analysis is predicated on mathematically precise formulations that embody assumptions on the part of an analyst and because model uncertainty, which represents a recognition of the potential for these assumptions to produce unsound analyses, has been an active area of research in economics and statistics for the last 15 or so years. The argumentation in this chapter is not original and is admittedly selective. For Austrian economists, the paper will hopefully be of interest in indicating how empirical work is evolving in a way that better respects limits to a social scientist's knowledge. I certainly do not mean to suggest that these arguments should eliminate the objections that have been raised by some Austrian economists to formal empirical work. Rather, the intent of this chapter is to indicate the possibility of dialog and debate between Austrian and non-Austrian economists on the role of formal empirical work. In several contexts, I have introduced arguments concerning the limits of formal econometric analysis by Hayek and von Mises to both illustrate how the perspectives in this chapter relate to their views in order to suggest why, in my judgment, some of their skepticism is unwarranted.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

This article examines predictability of returns and volatily in three major stock markets, the U.S., U.K., and Japan, using the Vector Autoregrassive and the Autoregressive Conditional Heteroskedastic (ARCH) approaches. We find that in all three markets dividendprice ratios and/or dividend growth rates predict returns. Moreover, there is persistence in the variance of stock returns attribute to the innovations related to the same variables.

Accounting and decision making rely heavily on forecasts. For several reasons, we should expect ongoing increases in forecasting accuracy. The purpose of this paper is to test the hypothesis of improved forecasts over time.

The paper analyzes original monthly sales plans and current data for three different car models in six different countries over 15 years and over several product life cycles (PLCs). Forecasting accuracy is calculated as one minus forecasting error. Forecasting error is measured with MAD/MEAN for periods of years or relative deviations per month. The hypothesis of decreasing forecasting errors is tested with the non‐parametric Mann/Kendall trend test. Additional interviews with managers were conducted to elicit details of internal forecasting organization and instruments.

The paper finds no evidence of increased forecasting accuracy in general over 15 years or over subsequent PLCs. This seems surprising, given improved statistical methods and software in general, and experience and learning effects of the organization itself. However, there is evidence from the case, that the reason lies in environmental uncertainty and volatility and not in internal factors within the control of the company.

Evidence from one case study is limited in its external validity. Future studies should analyze the forecasts of more companies, more industries and different forecasting objects, the latter including consumer, industrial goods and services. In the absence of further research, the results seem to negate the common assumption, that companies are generally able to make accurate forecasts, including those for accounting purposes. This hypothesis is clearly confuted.

The paper describes a methodology for companies to analyze their own forecasting accuracy and to identify possible reasons for a lack of accuracy, or basic approaches to increasing it.

Most studies on forecasting accuracy rely on interviews and questionnaires, entailing bias that is difficult to control. Few studies analyze archival data in order to measure forecasting accuracy; so that our study avoids much of the bias mentioned above. Despite the inevitable limitations of case studies, a study such as the present one at least allows us to dispute a common hypothesis about forecasting accuracy in practice.

This study examines predicability and volatility in three major stock markets, (the US, UK, and Japan) using the Vector Autoregressive Approach and the Multivariate Autoregressive Conditional Heteroskedastic‐in‐mean (ARCH‐M) approach. We find that in the three markets: a) stock returns are predictable, and b) there is persistence in the variance of stock returns, and c) predictability and persistence are attributed to common sources of information.

The purpose of this paper is to test the export‐led growth hypothesis for South Asia, a diverse region consisting of one large country, India, surrounded by a number of medium and small countries such as Pakistan, Bangladesh, Sri Lanka, Nepal, Bhutan and Maldives.

To test this, the study employs cointegration and error‐correction modelling, using data from the International Financial Statistics of the IMF.

The study produces fairly mixed results, and does not find any conclusive evidence in favour of export‐led growth. While India, Maldives and Nepal exhibit export‐led growth, Bangladesh and Bhutan show the opposite result of growth‐led exports. In Pakistan and Sri Lanka no causality in either direction was found. The mixed nature of the results is further confirmed by taking a common time period since 1980.

South Asia is one of the poorest regions of the world; so success or otherwise of export‐led growth is of great interest for policy purposes. For example, the finding of export‐led growth for the largest economy of the region, India, is particularly heartening as, by opening up its markets further to the other countries of the region, it can fuel growth in the entire region.

This study tries to fill an important gap in the literature as it is the first comprehensive study of the region as a whole.