Sanjiv Jaggia

An analysis of second time around bankruptcies using a split-population duration model

Abstract A significant proportion of firms that reorganize under Chapter 11 file for a second Chapter 11 protection or liquidate. We use a “split-population” duration model that provides useful information regarding factors that could lead to a second bankruptcy. We find that the probability (hazard) of a firm re-entering bankruptcy is lower for firms that take a long time to reorganize, reduce their debt-to-assets ratio, do not divest, belong to an industry that has low capacity utilization and low demand growth. We also find that the probability of an average firm re-entering bankruptcy increases for about 4 years before declining.

Contested Tender Offers: An Estimate of the Hazard Function

In this paper, the authors estimate the hazard function for firms that are targets in unsolicited tender offers. The data support a Weibull-gamma specification and imply a hazard rate that increases sharply in the initial period following the bid announcement, after which it declines steadily. In explaining the hazard, the authors find that the initial bid premium has no explanatory power, while the onset of an auction and the proportion of institutional ownership in the target firm significantly enhance the hazard. Legal and financial restructuring actions by target management are effective in reducing the hazard, thereby prolonging the contest.

The Medium-Term Aftermarket in High-Tech IPOs: Patterns and Implications

A number of theoretical models, loosely characterized under the rubric of behavioral finance, suggest that price convergence to value is far from instantaneous and possibly involves interplay between noise and informed traders. These models are motivated by documented anomalous patterns in equity markets and assume some form of psychological bias that affects investor behavior. With the benefit of hindsight it seems clear that the technology sector went through a bubble-like pattern in the late 1990s and that investor biases (if indeed they exist and can be inferred) may have been even more pronounced. Accordingly, our study focuses on the medium-term aftermarket in high-tech US IPOs during this period. Using both ordered logit regression and split-population hazard modeling approaches, we document momentum and reversal patterns that are consistent with the predictions of some behavioral finance models. Our findings indicate that momentum variables are important while fundamental variables have at best weak explanatory power.

Joint and separate score tests for state dependence and unobserved heterogeneity

Abstract The paper compares separate, conditional, and joint score tests of duration dependence and unobserved heterogeneity when the null is the exponential model and the alternative is the heterogeneous Weibull model. The score tests based on the conditional score function include the Neyman C (α) test as a special case. An examination of the non-null distribution of the joint test explains when all score tests have low power in the presence of multiple misspecifications. Monte Carlo experiments show that the conditional score tests are superior to the standard separate tests which confound unobserved heterogeneity and duration dependence.

Risk Aversion and the Investment Horizon: A New Perspective on the Time Diversification Debate

Investment managers generally subscribe to the principle of time diversification. This implies that a larger portion of the portfolio should be devoted to risky assets as the investment horizon increases. In contrast, academics have shown that for investors with utility functions characterized by constant relative risk aversion, the optimal asset-allocation strategy is independent of the investment horizon. The relative risk aversion in these studies is assumed to be constant both with respect to wealth as well as investment horizon. We suggest a utility function that explicitly captures the notion that individuals are more risk tolerant when the investment horizon is long, thereby validating the intuitively appealing time diversification argument.

Multiple bids as a consequence of target management resistance: A count data approach

In this article, we focus on the question of target management resistance and the incidence of subsequent bids. A Poisson count data model is used where the dependent variable represents the number of bids (count) received and the independent variables comprise target management actions and firm specific characteristics. Of the target management actions considered, legal defense and the entry of a white knight are associated with additional bids. With respect to firm specific characteristics, we find that a high initial bid premium deters subsequent bids. Firm size is also significant and has an interesting relationship with the number of bids received. Larger target firms tend to receive more bids; however, the number of bids tails off for firms with assets exceedng

Tests of moment restrictions in parametric duration models

12 billion.

Practical Considerations when Estimating in the Presence of Autocorrelation

Abstract In the following paper, tests of moment restrictions are motivated for parametric duration models. Tests based on specified parametric models as well as general specification tests are derived for a Weibull model using the Tauchen-Newey framework.

A Valuation Framework for Rent-to-Own Housing Contracts

When correcting for autocorrelation, most econometrics texts suggest using a quasi-differencing procedure. A number of issues arise. First, it is found that the results from popular two-step procedures may differ dramatically from those obtained from iterative processes. Second, while it is true that most regression packages implement an iterative procedure, the methodology itself is not conveyed in a straightforward manner to students of econometrics. Third, given the various iterative methods in the literature, it is not always clear which method is superior. Fourth, for autocorrelated errors, the importance of the correction factor in simple forecasting is often overlooked. Finally, regression packages report an R2 that is not comparable to that from the Ordinary Least Squares (OLS) estimation. This paper succinctly outlines the procedure for performing iterative procedures, explicitly accounts for autocorrelation among errors when generating forecasts, and identifies the necessary transformations for making proper comparisons relating to R2.

Identifiability of the misspecified split hazard models

The housing market crash in 2007 followed by a banking crisis and deep recession led to many underwater mortgages and a large shadow inventory of unsold properties. An innovative mechanism that may be playing a role in lowering inventories is the emergence of rent-to-own (RTO) housing contracts. RTO is potentially an attractive alternative to traditional financing for would-be buyers who cannot qualify for a mortgage due to an inadequate credit score, insufficient savings etc. These transactions, however, carry risks for both renters and owners. In this paper, we explore the contours of an RTO arrangement and suggest a binomial tree option valuation framework. In particular, we solve for the zero-profit purchase price at national and metro levels. We evaluate cases where the buyer can and cannot prematurely terminate the contract. We also consider scenarios in which both seller and buyer have deadweight costs that affect the contract outcome in a Nash bargaining framework. To the best of our knowledge, our model is the first analytical attempt to focus on the RTO housing contract.