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In the paper “Predicting the Outcome of Tender Offers: An Endogeneity Problem”, we argue that previous econometric models designed to predict the outcome of tender offers have been estimated incorrectly. We illustrate that the source of the estimation error comes from variables which are posited to explain the outcome of tender offers and treated as exogenous when in fact they are endogenous. We discuss the possibility, using the Nelson‐Olson simultaneous equation model, to solve the endogeneity problem. Although correct at the theoretical level we did not actually estimate the model using the Nelson‐ Olson technique. The complexity of applying the Nelson‐ Olson technique motivated us to search for an alternative solution to the endogeneity problem.

This paper proposes an alternative method of estimating a model that predicts the outcome of a tender offer. We argue that previous econometric models designed to predict the outcome of a tender offer have been estimated incorrectly. Explanatory variables which are endogenous have been treated as though they were exogenous. Ignoring the endogeneity problem results in estimates of re‐gression coefficients which are inconsistent. In order to derive consistent estimates of the regression coefficients, we construct a simultaneous equation model to explain the outcome of a tender offer. Since two of the three dependent variables in the simultaneous equation model are dichotomous, it is necessary to use the two stage limited dependent variable estimator (2SLDV) to find consistent estimates of the regression coefficients.

In a world where the objectives of managers differ from the objectives of shareholders, the analysis of management response to a tender offer must consider the possibility that management's response is a function of their equity interest in the company.

One of the main risks to investors in securitized reverse mortgages is that the value of the reverse mortgage exceeds that of the property. The purpose of this paper is to develop a model that determines paths of constant cross‐over points across any pairs of interest and inflation rate.

To study the behavior of hyper‐surfaces, multivariate calculus was used.

Knowing that the value of a reverse mortgage increases above that of the property value once it goes beyond the cross‐over point t*, it is possible to construct a pool of reverse mortgages, such that for any pairs of inflation rate and interest rate (x, r), these reverse mortgages move along lines of constant cross‐over points t*.

The paper develops a model that determines paths of constant cross‐over points across any pairs of interest and inflation rate, which can be used when structuring pools of reverse mortgage‐backed securities, to credit‐enhance investors.

The purpose of this paper is to present an innovative model that helps create a portfolio of m‐fixed‐income securities, each with the optimal weight, in order for the portfolio to be δ‐ and γ‐hedged against small changes in interest rates. Re‐balancing a portfolio on a periodic basis is necessary, but also very costly. The model presented in this paper minimizes the necessity of rebalancing a portfolio, by choosing the optimal δ‐hedge ratios when constructing the initial portfolio to be hedged against interest rate risk.

In this paper, a general model is developed to obtain the optimal δ hedge for a portfolio of m‐fixed‐income‐securities (a₁, a₂, a₃,…; a_i, … , a_m), each, a function of the market interest rate y, such that when the value of each of the individual securities changes up or down, because of changes in market rates y, the total value of the portfolio is unchanged. The delta hedge is developed under the constraint of a zero‐gamma, in order to avoid costs related to the re‐balancing of such portfolio.

An innovative model is developed that helps create a portfolio of m‐fixed‐income securities, each with the optimal weight, in order for the portfolio to be δ‐ and γ‐hedged against small changes in interest rates.

The model minimizes the necessity of rebalancing a portfolio, by choosing the optimal δ‐hedge ratios when constructing the initial portfolio to be hedged against interest rate risk.

An innovative model has been developed that helps create a portfolio of m‐fixed‐income securities, each with the optimal weight, in order for the portfolio to be delta‐ and gamma‐hedged against small changes in interest rates.

Interest only strips are created by stripping the interest portion of cash flows generated in mortgage‐backed securities or simply by servicing portfolios of mortgages. A number of financial institutions have significant amounts of mortgage‐servicing rights (MSR) which need to be delta (dynamic) hedged. Because MSR have a positive duration when prepayment effect is stronger than discount effect, it is possible to delta hedge a portfolio of MSR with other fixed income securities such that the value of the portfolio is not affected by increases or decreases in market rates. The purpose of this paper is to address this issue.

The paper develops the delta‐hedge‐ratio of MSR within a dynamic approach, using three different securities. To lower the cost of the delta hedge, the authors compare three hedge ratios dynamically, in order to obtain the portfolio that needs the least delta hedge.

The model enables the reduction of the amount of portfolio rebalancing and therefore reduces the cost of MSR portfolio hedging.

The paper develops the gamma‐hedge‐ratio function for each of the three securities. The lowest gamma corresponds to the hedged portfolio that needs the least re‐balancing.

This paper is innovative with the introduction of a delta‐hedge‐ratio function of interest and prepayment rates.

The aim of this paper is to develop the optimal delta hedge for a portfolio of mortgage servicing rights (MSR) under the constraint of a zero‐gamma in order to avoid costs related to the rebalancing of such portfolio.

The paper develops the optimal delta hedge ratio with gamma and vega constraints for an MSR portfolio by finding the different combinations of coupon/maturity bonds (c, n) that satisfy the constraints under different yields (y). Rather than search for the available fixed income securities and see by trial and error which one should be added to the portfolio of MSR such that when market rates go up and down, the value of the portfolio is not affected, the model finds the optimal pairs of coupon/maturity bonds over a range of yields, that satisfy the constraints. It develops the conditions for a delta‐hedged portfolio of bonds and MSR under an investor's or a portfolio manager's value constraint K. The share α of the MSR's value and the share β of the bond's value had to be such that a zero‐delta portfolio that satisfies the constant value of the portfolio can be created. The paper “optimized” α by requiring simultaneously that α′=0 and also that α″=0, for a fixed y given by the market that will guarantee that the function α satisfies simultaneously the two conditions: α′=0 and α″=0. These two conditions will yield equations in the parameters of c and n. The “optimization” problem for arbitrary y's is solved, and n and c for the appropriate bond are found to be added to the MSR portfolio.

Maple software is used to simulate a portfolio of MSR that is delta hedged with bonds, whose appropriate coupon and maturity are found with the model developed under the constraint of a zero‐gamma, in order to avoid costs related to the rebalancing of such portfolio. The optimal hedge ratio with gamma and vega constraints for an MSR portfolio is developed by finding the different combinations of coupon/maturity bonds that satisfy the constraints under different yields (the “triples”).

The optimal triples (c, n, y) are obtained in order to optimize α and simultaneously α′=0 and α″=0. For example, for a yield of 16.1 percent, a bank with a portfolio of MSR based on the data used, should add to it, bonds with a 6.33 percent coupon that matures in 7.55 years.

This paper is the first to the authors' knowledge to derive the different triples (yield, coupon, maturity) of bonds that when combined with MSR create a portfolio that is dynamically hedged against interest rate risk and prepayment risk, and therefore eliminates the need of periodic rebalancing of a portfolio of MSR, which is costly.