Evaluating Expert Systems in a Financial Domain: A Study Demonstrating Issues in Case Selection,Validation Standards and Evaluator Bias

This article describes and generalizes a validation study of four commercially available personal financial planning expert systems and the rationale for the research methodology used. Our evaluation of these systems adds to the understanding of verification and validation issues related to case selection, validation standards and evaluator bias. The article describes the systems, their domain and the empirical method—field tests using hypothetical cases—and relates that method to the literature. Comparing same-task systems combines multiple system perspectives and multiple models. Our methodology did efficiently and effectively identify conflicting terminology, omissions and system weaknesses but was inadequate for comparing the complex plan recommendations. The results re-emphasize the importance of continual knowledge base updating, formal system testing and the need for external evaluation. The results also show the value of comparing multiple, same-task systems.     

Regime‐dependent smile‐adjusted delta hedging

We introduce several regime‐dependent smile‐adjusted deltas and compare their efficiency with the smile‐adjusted deltas that are popular with option traders. Using years of daily option prices, out‐of‐sample hedging performance tests for options of all moneyness and maturities and daily, weekly, or fortnightly rebalancing show that even the simplest regime‐dependent smile‐adjustment consistently outperforms implied BSM delta hedging and local volatility and minimum variance smile‐adjustments. Markov‐switching deltas offer the best performance, with delta‐hedging errors often half the size of implied BSM hedging errors. During volatile markets risk reduction from regime‐dependent delta hedging is much greater than during tranquil periods.     

Characteristics and Information Value of Credit Watches

We analyze credit watch and rating actions to better understand the role of credit watches in the credit rating process. We find that watch actions are more frequently prompted by specific, publicly known events than are rating actions. The likelihood that a watch action precedes a rating action varies systematically with proxies for investor demand for credit quality information and the adverse consequences of issuing a rating change prematurely. Credit watches occur more often in response to deterioration in credit quality, and issuers make concerted efforts to address the concerns that prompted down watches. Down watches are less likely than up watches to indicate the direction of the subsequent rating change. Watch announcements are associated with abnormal stock returns, indicating that credit watch actions are significant information events. Our results suggest that credit watches are informative and facilitate the stability of ratings by allowing firms to correct deficiencies and prevent downgrades.     

Country Market Sequential Order-of-Entry: A Learning Effects Approach

ABSTRACT

In this article, we identify and describe the sequential order-of-entry problem. The sequential order-of-entry problem arises when, after having identified a desirable set of country markets to enter, firms are unable (because of budgetary constraints), or unwilling (because of possible learning or strategic issues), to enter all at once. The question then arises whether some sequences to entering the desirable set of country markets are better than others? Answering this question is shown to be nontrivial. The article outlines a number of arguments for the existence of superior sequences to entering a set of desirable country markets, and develops normative and dynamic frameworks to aid in the identification and evaluation of sequences.     

HRD involvement in merger and acquisition decisions and strategy development: four organizational portraits

Although the financial and strategic aspects of mergers and acquisitions are well researched, little work has been done on the human resource development implications of this popular topic. The purpose of this case study research project was to explore the timing and scope of HRD involvement in four organizations recently involved in a merger or acquisition, by using three theoretical models as lenses. The results demonstrated that HRD normally was not involved in the initial decision‐making to merge or acquire, even though post‐deal HRD initiatives, particularly related to change management, were perceived as critical indicators of success.     

Artificial neural networks in accounting and finance: modeling issues

This article reviews the literature on artificial neural networks (ANNs) applied to accounting and finance problems and summarizes the ‘suggestions’ from this literature. The first section reviews the basic foundation of ANNs to provide a common basis for further elaboration and suggests criteria that should be used to determine whether the use of an ANN is appropriate. The second section of the paper discusses development of ANN models including: selection of the learning algorithm, choice of the error and transfer functions, specification of the architecture, preparation of the data to match the architecture, and training of the network The final section presents some general guidelines and a brief summary of research progress and open research questions. Copyright © 2000 John Wiley & Sons, Ltd.