Murugappa Krishnan

Imperfect Competition in a Multi-security Market with Risk Neutrality

THE CENTRAL PURPOSE OF THIS PAPER is to develop a model of insider trading (i.e., trading based on private information) in the context of an imperfectly competitive multi-security market with risk-neutral agents. Imperfect competition allows us to consider strategic behavior, and a multi-security market lets us study the effect of a correlated environment on equilibrium. We employ the informational assumption that market makers can observe all order flows, and so portfolio diversification arises in this model for strategic reasons. Given correlated fundamentals, market makers can potentially learn about every security from each order flow. This causes even a risk neutral trader who does not face short-selling restrictions to refrain from determining the demand for each security independently. This contrasts with traditional multi-asset models, which focus on the incentive to reduce portfolio variance, or the effect of short-selling restrictions or budget constraints. Under imperfect competition, correlation has two effects. One, ceteris paribus, it allows the uninformed to learn from additional variables since each order flow could potentially have information about all payoffs. On the other hand, it creates an incentive for informed traders to restrict what others can learn from public information. Thus, our analysis can be viewed as an application to the multi-security, heterogeneous-information model in Admati (1985) of the imperfectly competitive equilibrium concept which Kyle (1985) first applied to the single-security, homogeneous-information model of Grossman and Stiglitz (1980). Our principal results include an explicit characterization of a linear equilibrium as a function of three general covariance matrices associated with payoffs, noise trading, and errors in private signals. Under general covariance structures, we show that there always exists an equilibrium in which the relationship between the vector of prices and the vector of order flows is governed by a symmetric positive definite matrix. The plan of the paper is as follows. In Section 2, we introduce our model. We derive the equilibrium in Section 3, and Section 4 comments on the properties of the equilibrium. The proofs of the results are in the Appendix.

Skewness of Earnings and the Believability Hypothesis: How Does The Financial Market Discount Accounting Earnings Disclosures?

When firms attempt to manage their earnings disclosures by presenting evidence selectively, sophisticated inference on the part of financial market participants entails a positive association between the market to bood ratio of a firm and the skewness of the distribution of its announced earnings. In this paper, we put this hypothesis to the test, and confirm its main predictions.

How Do Shop-Floor Supervisors Allocate Their Time?

A shop-floor supervisor or team leader can raise productivity either directly, by contributing on the line, or indirectly, by helping other team members via training and problem-solving. In this paper, we address the issue of how supervisors allocate their discretionary time between these two responsibilities. We model a simple sequential game under perfect information, designed to capture salient incentives of worker and supervisor. The degree of productivity increase depends on complementary inputs; in addition to the time a first-line supervisor contributes to indirect effort by helping the worker, the effort of the worker is also required. Implications of the model are tested using data on time allocations of supervisors from a Japanese automobile plant in the U.S. We find that the supervisory time allocations have a significant effect on productivity in this Just-In-Time production environment of a capital-intensive auto assembly plant. Empirical results provide evidence consistent with both selected premises and implications of the model.

Do supervisory inputs matter in a capital-intensive industry? Some evidence from a Japanese car transplant

We estimate a translog production function based on data from a Japanese automobile plant in the Midwest where output is determined by capital and different supervisory time inputs. We fit a model which allows for heteroskedastic errors, where this heteroskedasticity is a function of various variables affecting perceived target severity. We find that while, as expected, capital inputs are important, each supervisory time input is also significant in this capital-intensive industry. Linear homogeneity in these inputs is rejected. We find evidence of asymmetry in substitution among different components of supervisory time. This asymmetry has implications for the design and allocation of supervisory tasks.

Measuring firm-specific informational efficiency without conditioning on a public announcement

We exploit the availability of active single-stock futures on Indias National Stock Exchange (NSE) to provide estimates of overall informational efficiency, without conditioning on a public announcement. The key is the estimation of the primitive parameters of an asset pricing model with private information and noise. The variance–covariance parameters governing futures prices and terminal values can be inverted to obtain the Maximum Likelihood Estimators (MLEs) of the precision of private information and the variance of liquidity motivated trades. The Signal-to Signal-plus-Noise (SSN) ratio – our measure of overall informational efficiency – is a function of these primitive parameters. Our primary findings show that there is considerable variation across firms in these parameters despite only large active firms being available for futures trading. We also examine the cross-sectional relationship of this measure of informational efficiency and corporate governance. Overall informational efficiency increases in promoters’ and foreign institutional investors’ shareholding, and if the board of directors has a majority that is independent, and decreases if the chairman of the board is also the CEO, and if overall trading activity is fragmented across domestic and international markets. The NIFTY index shows a higher SSN ratio than for any of the firms. This is consistent with the idea that less manipulability is associated with greater informational efficiency.