Game Options Analysis of the Information Role of Call Policies in Convertible Bonds

Abstract

In debt financing, existence of information asymmetry on the firm quality between the firm management and bond investors may lead to significant adverse selection costs. We develop the two-stage sequential dynamic two-person game option models to analyse the market signalling role of the callable feature in convertible bonds. We show that firms with positive private information on earning potential may signal their type to investors via the callable feature in a convertible bond. We present the variational inequalities formulation with respect to various equilibrium strategies in the two-person game option models via characterization of the optimal stopping rules adopted by the bond issuer and bondholders. The bondholders’ belief system on the firm quality may be revealed with the passage of time when the issuer follows his optimal strategy of declaring call or bankruptcy. Under separating equilibrium, the quality status of the firm is revealed so the information asymmetry game becomes a new game under complete information. To analyse pooling equilibrium, the corresponding incentive compatibility constraint is derived. We manage to deduce the sufficient conditions for the existence of signalling equilibrium of our game option model under information asymmetry. We analyse how the callable feature may lower the adverse selection costs in convertible bond financing. We show how a low-quality firm may benefit from information asymmetry and vice versa, underpricing of the value of debt issued by a high-quality firm.     

Robust optimization models for managing callable bond portfolios

A major sector of the bond markets is currently represented by instruments with embedded call options. The complexity of bonds with call features, coupled with the recent increase in volatility, has raised the risks as well as the potential rewards for bond holders. These complexities, however, make it difficult for the portfolio manager to evaluate individual securities and their associated risks in order to successfully construct bond portfolios. Traditional bond portfolio management methods are inadequate, particularly when interest-rate-dependent cashflows are involved. In this paper we integrate traditional simulation models for bond pricing with recent developments in robust optimization to develop tools for the management of portfolios of callable bonds. Two models are developed: a single-period model that imposes robustness by penalizing downside tracking error, and a multi-stage stochastic program with recourse. Both models are applied to create a portfolio to track a callable bond index. The models are backtested using ex poste market data over the period from January 1992 to March 1993, and they perform constistently well.     

A numerical PDE approach for pricing callable bonds

Many debt issues contain an embedded call option that allows the issuer to redeem the bond at specified dates for a specified price. The issuer is typically required to provide advance notice of a decision to exercise this call option. The valuation of these contracts is an interesting numerical exercise because discontinuities may arise in the bond value or its derivative at call and/or notice dates. Recently, it has been suggested that finite difference methods cannot be used to price callable bonds requiring notice. Poor accuracy was attributed to discontinuities and difficulties in handling boundary conditions. As an alternative, a semi-analytical method using Green's functions for valuing callable bonds with notice was proposed. Unfortunately, the Green's function method is limited to special cases. Consequently, it is desirable to develop a more general approach. This is provided by using more advanced techniques such as flux limiters to obtain an accurate numerical partial differential equation method. Finally, in a typical pricing model an inappropriate financial condition is required in order to properly specify boundary conditions for the associated PDE. It is shown that a small perturbation of such a model is free from such artificial conditions.     

Callable risky perpetual debt with protection period

Issuances in the USD 260 Bn global market of perpetual risky debt are often motivated by capital requirements for financial institutions. We analyze callable risky perpetual debt emphasizing an initial protection (‘grace’) period before the debt may be called. The total market value of debt including the call option is expressed as a portfolio of perpetual debt and barrier options with a time dependent barrier. We also analyze how an issuer’s optimal bankruptcy decision is affected by the existence of the call option by using closed-form approximations. The model quantifies the increased coupon and the decreased initial bankruptcy level caused by the embedded option. Examples indicate that our closed form model produces reasonably precise coupon rates compared to numerical solutions. The credit-spread produced by our model is in a realistic order of magnitude compared to market data.     

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??This paper studies the price of convertible bonds with counterparty credit risk in a reduced-form model. We suppose that the default intensity process and the interest rate process follow the Vasicek model, and derive the price expression of convertible bonds using the method of measure changes. Moreover, we make some numerical analysis on the explicit formulae to demonstrate the sensitivity of a convertible bond price to changes in the parameters of the model.     

The pricing and optimal strategies of callable warrants

In this paper, we introduce a valuation model of callable warrants under a setting of the optimal stopping problem between the holder (investor) and the issuer (firm). A warrant is the right to purchase new shares at a predetermined price. When the new stocks are issued, the value of the stock is diluted. We consider the model taking the dilution into account. After identifying optimal policies for the issuer and the investor, we explore the analytical properties of the optimal exercise and call boundaries for the holder and the issuer, respectively. Furthermore, the value of such a callable warrant and the optimal critical prices are examined numerically using the binomial method.     

Market implied volatilities for defaultable bonds

Typically, implied volatilities for defaultable instruments are not available in the financial market since quotations related to options on defaultable bonds or on credit default swaps are usually not quoted by brokers. However, an estimate of their volatilities is needed for pricing purposes. In this paper, we provide a methodology to infer market implied volatilities for defaultable bonds using equity implied volatilities and CDS spreads quoted by the market in relation to a specific issuer. The theoretical framework we propose is based on the Merton’s model under stochastic interest rates where the short rate is assumed to follow the Hull–White model. A numerical analysis is provided to illustrate the calibration process to be performed starting from financial market data. The market implied volatility calibrated according to the proposed methodology could be used to evaluate options where the underlying is a risky bond, i.e. callable bond or other types of credit-risk sensitive financial instruments.

     

Modelling Credit Risk in the Jump Threshold Framework

ABSTRACT

The jump threshold framework for credit risk modelling developed by Garreau and Kercheval enjoys the advantages of both structural- and reduced-form models. In their article, the focus is on multidimensional default dependence, under the assumptions that stock prices follow an exponential Lévy process (i.i.d. log returns) and that interest rates and stock volatility are constant. Explicit formulas for default time distributions and basket credit default swap (CDS) prices are obtained when the default threshold is deterministic, but only in terms of expectations when the default threshold is stochastic. In this article, we restrict attention to the one-dimensional, single-name case in order to obtain explicit closed-form solutions for the default time distribution when the default threshold, interest rate and volatility are all stochastic. When the interest rate and volatility processes are affine diffusions and the stochastic default threshold is properly chosen, we provide explicit formulas for the default time distribution, prices of defaultable bonds and CDS premia. The main idea is to make use of the Duffie–Pan–Singleton method of evaluating expectations of exponential integrals of affine diffusions.     

The Minimal Entropy Martingale Measure and Numerical Option Pricing for the Barndorff–Nielsen–Shephard Stochastic Volatility Model

Abstract

We develop and apply a numerical scheme for pricing options in the stochastic volatility model proposed by Barndorff–Nielsen and Shephard. This non-Gaussian Ornstein–Uhlenbeck type of volatility model gives rise to an incomplete market, and we consider the option prices under the minimal entropy martingale measure. To numerically price options with respect to this risk neutral measure, one needs to consider a Black and Scholes type of partial differential equation, with an integro-term arising from the volatility process. We suggest finite difference schemes to solve this parabolic integro-partial differential equation, and derive appropriate boundary conditions for the finite difference method. As an application of our algorithm, we consider price deviations from the Black and Scholes formula for call options, and the implications of the stochastic volatility on the shape of the volatility smile.     

Closed-form solutions for pricing credit-risky bonds and bond options

This paper proposes closed-form solutions for pricing credit-risky discount bonds and their European call and put options in the intensity-based reduced-form framework, assuming the stochastic dynamics of both the risk-free interest rate and the credit-spread are driven by two correlated Ho-Lee models [T.S.Y. Ho, S.B. Lee, Term structure movements and pricing interest rates contingent claims, Journal of Finance 41 (5) (1986) 1011-1029]. The results are easily to implement, and require very few parameters which are directly implied from market data.     

Online scheduling policies for multiclass call centers with impatient customers

We consider a call center with two classes of impatient customers: premium and regular classes. Modeling our call center as a multiclass GI/GI/s+M$\mathit{GI}/\mathit{GI}/s+M$ queue, we focus on developing scheduling policies that satisfy a target ratio constraint on the abandonment probabilities of premium customers to regular ones. The problem is inspired by a real call center application in which we want to reach some predefined preference between customer classes for any workload condition. The motivation for this constraint comes from the difficulty of predicting in a quite satisfying way the workload. In such a case, the traditional routing problem formulation with differentiated service levels for different customer classes would be useless. For this new problem formulation, we propose two families of online scheduling policies: queue joining and call selection policies. The principle of our policies is that we adjust their routing rules by dynamically changing their parameters. We then evaluate the performance of these policies through a numerical study. The policies are characterized by simplicity and ease of implementation.     

Optimal stopping in infinite horizon: An eigenfunction expansion approach

We develop an eigenfunction expansion based value iteration algorithm to solve discrete time infinite horizon optimal stopping problems for a rich class of Markov processes that are important in applications. We provide convergence analysis for the value function and the exercise boundary, and derive easily computable error bounds for value iterations. As an application we develop a fast and accurate algorithm for pricing callable perpetual bonds under the CIR short rate model.     

GENERALIZED BRAUER ALGEBRAS

ABSTRACT

Using some ideas of Brauer, we introduce what we call generalized Brauer algebras and, as a special case, Brauer orders. We show that many well-known classes of so-called crossed product algebras, and in particular, the well-known crossed product orders, can be obtained as special instances of our construction. We prove several results showing when Brauer orders are Azumaya, maximal, hereditary or Gorenstein.     

On Angles Whose Squared Trigonometric Functions Are Rational

We consider the rational linear relations between real numbers whose squared trigonometric functions have rational values, angles we call ``geodetic.' We construct a convenient basis for the vector space over Q generated by these angles. Geodetic angles and rational linear combinations of geodetic angles appear naturally in Euclidean geometry; for illustration we apply our results to equidecomposability of polyhedra. Received April 7, 1998, and in revised form September 2, 1998.     

Markov Chain Monte Carlo Convergence Assessment via Two-Way Analysis of Variance

Abstract

In this article we discuss the problem of assessing the performance of Markov chain Monte Carlo (MCMC) algorithms on the basis of simulation output. In essence, we extend the original ideas of Gelman and Rubin and, more recently, Brooks and Gelman, to problems where we are able to split the variation inherent within the MCMC simulation output into two distinct groups. We show how such a diagnostic may be useful in assessing the performance of MCMC samplers addressing model choice problems, such as the reversible jump MCMC algorithm. In the model choice context, we show how the reversible jump MCMC simulation output for parameters that retain a coherent interpretation throughout the simulation, can be used to assess convergence. By considering various decompositions of the sampling variance of this parameter, we can assess the performance of our MCMC sampler in terms of its mixing properties both within and between models and we illustrate our approach in both the graphical Gaussian models and normal mixtures context. Finally, we provide an example of the application of our diagnostic to the assessment of the influence of different starting values on MCMC simulation output, thereby illustrating the wider utility of our method beyond the Bayesian model choice and reversible jump MCMC context.     

On reduced-form intensity-based model with ‘trigger’ events

Corporate defaults may be triggered by some major market news or events such as financial crises or collapses of major banks or financial institutions. With a view to develop a more realistic model for credit risk analysis, we introduce a new type of reduced-form intensity-based model that can incorporate the impacts of both observable ‘trigger’ events and economic environment on corporate defaults. The key idea of the model is to augment a Cox process with ‘trigger’ events. Both single-default and multiple-default cases are considered in this paper. In the former case, a simple expression for the distribution of the default time is obtained. Applications of the proposed model to price defaultable bonds and multi-name Credit Default Swaps are provided.     

Evaluating corporate bonds with complicated liability structures and bond provisions

This paper presents a general and numerically accurate lattice methodology to price risky corporate bonds. It can handle complex default boundaries, discrete payments, various asset sales assumptions, and early redemption provisions for which closed-form solutions are unavailable. Furthermore, it can price a portfolio of bonds that accounts for their complex interaction, whereas traditional approaches can only price each bond individually or a small portfolio of highly simplistic bonds. Because of the generality and accuracy of our method, it is used to investigate how credit spreads are influenced by the bond provisions and the change in a firm’s liability structure due to bond repayments.     

Lifting results for rational points on Hurwitz moduli spaces

Hurwitz moduli spaces for G-covers of the projective line have two classical variants whether G-covers are considered modulo the action of PGL₂ on the base or not. A central result of this paper is that, given an integer r ≥ 3 there exists a bound d(r) ≥ 1 depending only on r such that any rational point p ^rd of a reduced (i.e., modulo PGL₂) Hurwitz space can be lifted to a rational point p on the nonreduced Hurwitz space with [κ(p): κ(p ^rd)] ≤ d(r). This result can also be generalized to infinite towers of Hurwitz spaces. Introducing a new Galois invariant for G-covers, which we call the base invariant, we improve this result for G-covers with a nontrivial base invariant. For the sublocus corresponding to such G-covers the bound d(r) can be chosen depending only on the base invariant (no longer on r) and ≤ 6. When r = 4, our method can still be refined to provide effective criteria to lift k-rational points from reduced to nonreduced Hurwitz spaces. This, in particular, leads to a rigidity criterion, a genus 0 method and, what we call an expansion method to realize finite groups as regular Galois groups over ℚ. Some specific examples are given.     

Deep Reinforcement Learning for Market Making in Corporate Bonds: Beating the Curse of Dimensionality

ABSTRACT

In corporate bond markets, which are mainly OTC markets, market makers play a central role by providing bid and ask prices for bonds to asset managers. Determining the optimal bid and ask quotes that a market maker should set for a given universe of bonds is a complex task. The existing models, mostly inspired by the Avellaneda-Stoikov model, describe the complex optimization problem faced by market makers: proposing bid and ask prices for making money out of the difference between them while mitigating the market risk associated with holding inventory. While most of the models only tackle one-asset market making, they can often be generalized to a multi-asset framework. However, the problem of solving the equations characterizing the optimal bid and ask quotes numerically is seldom tackled in the literature, especially in high dimension. In this paper, we propose a numerical method for approximating the optimal bid and ask quotes over a large universe of bonds in a model à la Avellaneda–Stoikov. As classical finite difference methods cannot be used in high dimension, we present a discrete-time method inspired by reinforcement learning techniques, namely, a model-based deep actor-critic algorithm.     

具有动态信用风险的可转债的定价研究

本文基于鞅方法的定价理论,在全面考虑赎回条款、回售条款、公司不具稳定性的信用风险以及转股时股市受到稀释作用对可转债价值的影响后,给出可转换债券一个比较精确的定价公式。应用这些公式对南京水运公司可转换债券做实证分析,结果表明:定价公式的数值与实际市场可转债的价格波动情况吻合相当好,能反映出良好的预测效果.因此该可转债定价结果将有助于发行公司、投资者、监管机构和中介机构更准确的了解可转债的定价机制,而发行公司、投资者、监管机构和中介机构对可转债定价机制的熟悉将有助于在我国证券市场建立起一种成熟稳健的避险工具,从而推动证券市场的发展。