Accountability of independent directors: Evidence from firms subject to securities litigation

We examine which independent directors are held accountable when investors sue firms for financial and disclosure-related fraud. Investors can name independent directors as defendants in lawsuits, and they can vote against their reelection to express displeasure over the directors’ ineffectiveness at monitoring managers. In a sample of securities class action lawsuits from 1996 to 2010, about 11% of independent directors are named as defendants. The likelihood of being named is greater for audit committee members and directors who sell stock during the class period. Named directors receive more negative recommendations from Institutional Shareholder Services, a proxy advisory firm, and significantly more negative votes from shareholders than directors in a benchmark sample. They are also more likely than other independent directors to leave sued firms. Overall, shareholders use litigation along with director elections and director retention to hold some independent directors more accountable than others when firms experience financial fraud.     

Using Rule Induction for Expert System Development: The Case of Asset Writedowns

There was a significant increase in the frequency and magnitude of asset writedowns by US firms during the 1980s. Auditors, financial analysts and regulators have shown considerable interest in evaluating the writedown phenomenon. This paper reports on the use of inductive learning to discover knowledge in financial data structures and describes the development and testing of a prototype expert system, WDXPERT, which evaluates asset writedowns. Real-world data relating to writedown and non-writedown firms are used for rule induction. A set of training examples comprising 42 writedown and 25 non-writedown firms are used to generate the rules using IXL, a machine-learning program. A separate holdout sample containing 43 writedown and 25 non-writedown firms are used to validate the expert system that incorporates these rules. A second validation procedure is performed by comparing the performance of the expert system with a conventional discriminant analysis model and a logit model using the same data sets. The results indicate that the expert system, WDXPERT, is a useful classification tool to group firms into writedown and non-writedown classes.     

The value of combining the information content of analyst recommendations and target prices

In assessing the usefulness of the analysts’ stock picking advice, the extant literature has largely focused on the profitability of either their stock recommendations or target prices in isolation. In this paper, we examine the profitability of investment strategies that exploit the information analysts convey through revisions in both their stock recommendations and target prices. We find that these strategies significantly outperform the comparable strategies that make use of only one analyst output.     

Three differential variables and their relation to retail strategy and profitability

The primary objective of this study is to evaluate three variables utilized frequently within the retail grocery industry to gain a differential advantage within a target market. These variables are Trading Stamps, Credit, and Delivery. Essentially, the study seeks to determine whether these differential variables are related to retail strategy and retail store profitability for a selected group of retail grocery stores belonging to a retailer cooperative. The study also seeks to determine if the utilization of the differential variables creates any profitability changes within the basic retailing strategy variables of the researched respondents.     

The different faces of coupon elasticity

Coupons account for over two-thirds of all consumer promotional efforts initiated by the manufacturers of consumer goods. In this study, the impact of coupons on brand sales is investigated and how that impact decays over the life of the coupon is demonstrated. Specifically, we present an econometric model that can capture coupon effects in terms of equivalent price reduction, account for coupon effects over time, allow inference of coupon effects when retailers decide to double or triple the coupon value, and provide both self-coupon and cross-coupon elasticities at different levels of aggregation. A widely used sales response model is adapted, and an analytical model is proposed to estimate both the self-coupon and cross-coupon (face value) elasticities of sales at the store level. From the store-level elasticity estimates for a given week, the authors analytically derive the coupon elasticities for the chain level by aggregating across stores, and over the life of the coupon by aggregating over time. The proposed sales response model is estimated with the data obtained from three markets for various product categories, and the coupon elasticities are computed. The proposed framework allows one to demonstrate the hypothetical equivalence of a shelf-price reduction for a given coupon face value in each week. Also, the effect of doubling the face value of a coupon results in more than a proportionate increase in elasticity. The authors find that both self and cross-coupon elasticities are much smaller in magnitude than the average self and cross-price elasticity measures reported in the literature.