Analysis of efficient markets

A simple trading model is presented in which Bayes’ rule is used to aggregate traders’ forecasts about risky assets’ future returns. In this financial market, Bayes’ rule operates like an omnipotent market-maker performing functions that in 1776 Adam Smith attributed to an “invisible hand.” We have analyzed two distinct cases: in the first scenario, the traders’ forecast errors are uncorrelated, and in the second scenario, the traders’ forecast errors are correlated. The contribution of our paper is fourfold: first, we prove that the “efficient market” mean-return can be expressed as a complex linear combination of the traders’ forecasts. The weights depend on the forecast variances, as well as on the correlations among the traders’ forecasts. Second we show that the “efficient” variance is equal to the inverse of the sum of the traders’ precision errors, and is also related to the correlations among the traders’ forecast errors. Third, we prove that the efficient market return is the best linear minimum variance estimator (BLMVE) of the security’s mean return (in the sense that it minimizes the sum of the traders’ mean squared forecast errors). Thus, an efficient market aggregates traders’ heterogeneous information in an optimal way. Fourth, we prove that an efficient market produces a mean return (price) as a Blackwell sufficient (most informative) experiment among all possible aggregated expected return (price) forecasts.     

Valuation under imperfect information: Bayesian learning from the performance of the firm and the market

This paper develops a valuation model for a project or firm in the presence of uncertainty about the mean of the probability distribution of the cash flows generated by the project. Its major point is that in the presence of parameter uncertainty the value of the project is smaller than in the case where the mean cash flows is perfectly known. The second point is that when there is a known covariance between project cash flows and aggregate market cash flows investors can learn about the unknown mean cash flows by observing the market. This is referred to as ‘learning from the market’.     

A new paradigm for forecasting security returns in a market regulated by price limits

Numerous futures markets in the US and many stock markets around the world set a “limit” price before each trading session, based on the settlement price at the end of the previous trading day. Price limits are boundaries set by market regulators to restrict large daily fluctuations in the price of securities. Once the return limit is triggered, traders cannot observe the equilibrium return that would have prevailed in the absence of such regulation. We develop an innovative approach for forecasting security returns (and prices) in a market regulated by price limits. Our forecasting model allows for multiple limit-hits. The model is robust, straightforward and easy for practitioners to use. A few numerical predictions are provided for hypothetical securities, and for seven traded futures contracts.     

Learning by a dominant firm

This paper is concerned with the optimal output decisions of a dominant firm in the presence of imperfect information about the rival's reactions. The model is multi-period with the profits in each period being independent of those in other periods. Consequently, if the rival's reaction parameter were known to the dominant firm, a myopic policy would be optimal, In the presence of imperfect information about the rival's unknown reaction parameter, the dominant firm acts in a Bayesian manner by updating its prior distribution based on the observations of the rival's outputs. Because of the multiplicative shape of the rival's reaction function, the Bayesian updating rule is a function of the dominant firm's decision variable, i.e. its output decisions. This creates a dependence of the future value of the dominant firm on the present output decision, and hence a myopic policy is not, in general, optimal. It is shown that through output experimentation the dominant firm will tend to overproduce and, consequently, will increase its expected discounted profits (market value).     

Beyond workaholism: Towards a general model of heavy work investment

Although the term workaholism is widely used, little consensus exists about its meaning, and there is a great need for further theoretical and methodological advancement. We attempt to address this need by introducing the concept of Heavy Work Investment (HWI), and viewing workaholism as only one of its subtypes. Furthermore, we propose a model consisting of four main components: HWI, its possible predictors, its types, and its outcomes.In this model, using Weiner's (1985) attributional framework, we differentiate between situational and dispositional types of HWI, each with its own subtypes, as based on the predictors of such an investment. For example, financial-needs-based and employer-directed are situational subtypes, whereas workaholism and work-devotion are dispositional subtypes. Based on the proposed HWI model, we compare dispositional investors with situational investors.Finally, the measurement of HWI, as well as future research directions (study of situational investors, research across time and cultures, and exploration of inter-generational similarity/difference) is also discussed.     

Forecasting futures returns in the presence of price limits

In a futures market with a daily price‐limit rule, trading occurs only at prices within limits determined by the previous day's settlement price. Price limits are set in dollars but can be expressed as return limits. When the daily return limit is triggered, the true equilibrium futures return (and price) is unobservable. In such a market, investors may suffer from information loss if the return “moves the limit.” Assuming normally distributed futures returns with unknown means but known volatilities, we develop a Bayesian forecasting model in the presence of return limits and provide some numerical predictions. Our innovation is the derivation of the predictive density for futures returns in the presence of return limits. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:199–210, 2005     

Determinants of Israeli Judicial Discretion in Issuing Injunctions against Strikers

The study examines all cases (1990–7) in Israel in which employers petitioned the labour court to issue an injunction against striking workers, and identifies how judges use their discretion in deciding the petition. The findings indicate that, judicial rhetoric to the contrary, the labour court limits its considerations almost solely to the parties' formal compliance with the legal rule. The implications of these findings for the relationship of the legal and industrial relations systems are discussed, particularly with reference to the dual task of labour law: to govern the industrial relations system, and to facilitate its autonomy.