Changes in REIT Liquidity 1990–1994: Evidence from Intra-day Transactions

This study uses data on intra-day transactions to analyze whether real estate investment (REIT) liquidity as measured by the bid-ask spread changed from 1990 to 1994, a period during which the industry's market capitalization increased from $8.7 billion to $45 billion. REIT percentage spreads (spread as percentage of share price) narrowed significantly, primarily attributable to higher share prices rather than narrower dollar-value spreads. An empirical model is used to analyze the determinants of percentage spreads. Return variance and share price, not market capitalization are found to be the primary determinants of percentage spreads in both periods. This suggests that the liquidity of REIT securities is similar to that of non-REIT securities with similar prices and return variance. In addition, percentage spreads are wider for REITs trading on the NASDAQ.     

Snapshot samples

We consider a coverage model where an initial event that occurs at some point in time triggers an activity of random duration that leads to some subsequent event. A snapshot sample is constructed at a fixed point in chronological time either by sampling only subjects where the initial event has occurred but the subsequent event has yet to occur (active subjects), or by sampling only subjects where both the initial and subsequent events have occurred (inactive subjects). The biases inherent in snapshot sampling can be neatly characterized by the properties of two random variables: the history (defined as the time the initial event occurs as measured into the past from the chronological point of sampling), and the active time (defined as the length of time between the initial and subsequent events). Though snapshot samples are biased, recognizing the biases enables correct inferences to be drawn from snapshot-sampled data. Considering only the case where and are independent random variables, this paper presents the probability models associated with snapshot sampling, demonstrates the problems that can occur, offers procedures for overcoming these problems, and applies the methods to interesting data sets.     

The Dynamics of Alliance Conditions in the Alliance Development Process

One of the key issues in understanding the developmental processes of strategic alliances is how the alliance conditions change over the different stages of alliance development. A related question concerns the nature of the co-evolutionary dynamics of alliances in terms of their constituent partner firms. In this article we propose an integrated process model of alliances that is based on alliance conditions, allianc developmental stages, and an alliance system comprising co-evolutionary elements. We suggest that alliance conditions, or the key characteristics of an alliance at any given moment, link the alliance environment (firm characteristics) and the alliance development process. We also explore how specific patterns of alliance conditions have differential impacts on the interactive elements of the alliance co-evolutionary system.     

On the E-optimality of truncated block designs

Sufficient conditions are found for designs, derived from completely symmetric designs by deleting binary blocks, to be E-optimal. Sufficient conditions are also found for E-optimality of designs obtained from other E-optimal designs by deleting all blocks forming a balanced incomplete block design on a subset of the treatments. The results include many binary and non-binary designs for which E-optimality was previously unknown.     

Combining information for prediction in linear regression

This article deals with the prediction problem in linear regression where the measurements are obtained using k different devices or collected from k different independent sources. For the case of k=2, a Graybill-Deal type combined estimtor for the regression parameters is shown to dominate the individual least squares estimators under the covariance criterion. Two predictors ŷ _c and ŷ _p are proposed. ŷ _c is based on a combined estimator of the regression coefficient vector, and ŷ _p is obtained by combining the individual predictors from different models. Prediction mean square errors of both predictors are derived. It is shown that the predictor ŷ _p is better than the individual predictors for k≥2 and the predictor ŷ _c is better than the individual predictors for k=2. Numerical comparison between ŷ _c and ŷ _p shows that the former is superior to the latter for the case k=2.     

A Study of Arbitrage Efficiency Between the FTSE‐100 Index Futures and Options Contracts

Despite the importance of the London markets and the significance of the relationship for market makers, little published research is available on arbitrage between the FTSE‐100 Index futures and the FTSE‐100 European index options contracts. This study uses the put–call–futures parity condition to throw light on the relationship between options and futures written against the FTSE Index. The arbitrage methodology adopted in this study avoids many of the problems that have affected prior research on the relationship between options or futures prices and the underlying index. The problems that arise from nonsynchroneity between options and futures prices are reduced by the matching of options and futures prices within narrow time intervals with time‐stamped transaction data. This study allows for realistic trading and market‐impact costs. The feasibility of strategies such as execute‐and‐hold and early unwinding is examined with both ex‐post and ex‐ante simulation tests that take into consideration possible execution time lags for the arbitrage trade. This study reveals that the occurrence of matched put–call–futures trios exhibits a U‐shaped intraday pattern with a concentration at both open and close, although the magnitude of observed mispricings has no discernible intraday pattern. Ex‐post arbitrage profits for traders facing transaction costs are concentrated in at‐the‐money options. As in other major markets, despite important microstructure differences, opportunities are generally rapidly extinguished in less than 3 min. The results suggest that arbitrage opportunities for traders facing transaction costs are small in number and confirm the efficiency of trading on the London International Financial Futures and Options Exchange. © 2002 John Wiley & Sons, Inc. Jrl Fut Mark 22:31–58, 2002     

Monopoly, competition and information acquisition

An incumbent monopolist is uncertain about its linear demand, but can acquire public information at a cost. We determine how an entry threat affects the firm's information acquisition. If returns to scale are constant and the state-contingent demands become more dispersed as output increases, then entry reduces information acquisition. If, however, either the incumbent or entrant has increasing returns; or if the state-contingent demands are nonlinear or fail increasing dispersion, then entry can increase information. Finally, entry can hurt consumers. Although entry always increases output, it can decrease information. Consumers sometimes prefer a better informed monopoly to a duopoly.     

Are Fundamentals Priced in the Bond Market?*

To date, the discussion of the Lev and Thiagarajan 1993 fundamentals in the prior literature has been exclusively in the context of the stock market. Our study is the first to examine the value‐relevance of these fundamentals for default risk. By focusing on the market for new bond issues, we examine the value‐relevance of the fundamental score using expected rather than realized returns. Also, by focusing on the bond market we provide a different perspective than that brought by prior studies relying solely on stock prices. We find the fundamentals to be priced in the market for new bond issues as indicators of expected future earnings and to be value‐relevant in enabling the market to discern differences in bond credit quality over and above the published bond ratings.     

Analysing Materials and Energy Flows in an Industrial District using an Enterprise Input–Output Model

Recent approaches to sustainable development leave much room for policies at a local level. In fact, it is becoming evident that targets such as increasing resource productivity, preserving natural cycles, or extending the present level of welfare, are best pursued within the confines of a local area. In particular, environmental changes are best brought about by considering local systems of firms as cornerstones of cooperative strategies and using data on materials and energy use in physical terms. In this paper, an enterprise input–output model is developed for an industrial district, i.e. a local group of firms specialized in the production of a single final output. The model allows for a detailed quantitative analysis of materials and energy flows and the consequent generation of waste and pollution. As a planning tool, the model may be used to evaluate alternative scenarios, such as the possibility of re- using waste taking account of sustainability requirements. An empirical case study applies the model to an industrial district in Southern Italy producing leather sofas.