The informational content of subordinated debt and equity prices in the presence of bankruptcy costs

The paper extends the contingent valuation framework of Black and Cox [J. Finance 31(2) (1976) 351] to value subordinated debt by explicitly incorporating bankruptcy costs in the model. We show that the information from subordinated debt prices is complementary to the information from the equity prices only when the bankruptcy costs are taken into account. In fact, the joint use of equity and subordinated debt prices can provide information on magnitude of expected bankruptcy costs. Knowing the magnitude of expected bankruptcy costs is necessary for calculating variables underlying policy objectives. In particular, it is illustrated that the value of expected liability of a deposit insurer would be underestimated if the bankruptcy costs were not taken into account.     

Inflation and the optimal inventory replenishment schedule within a finite planning horizon

The subject of this paper is the problem of finding the optimal replenishment schedule for an inventory, subject to time-dependent demand and deterioration, within a finite time planning horizon. It is shown that taking inflation into account has a profound effect on the solution of the problem. For instance, there is a critical number of replenishment periods, in excess of which the optimal schedule is characterized by the inclusion of token orders at the end of the planning horizon. This and other conclusions, obtained via a careful mathematical analysis of the problem, rectify those of earlier studies.     

Predicting default of a small business using different definitions of financial distress

The paper introduces a number of risk-rating models for UK small businesses applying an accounting-based approach, which uses financial ratios to predict corporate bankruptcy. An enhancement to these models is considered through features typical to retail credit risk modelling. A common problem of default prediction consists in the relatively small number of bankruptcies or real defaults available for model-building. In order to expand the ‘default’ group beyond bankrupt companies, the paper considers adopting four different definitions of ‘a failing business’ by investigating combinations of financial distress levels. The impact of each default definition on the choice of predictor variables and on the model's predictive accuracy is explored. In addition, the paper examines the value of categorizing financial ratios used as predictor variables.     

The speed of adjustment of financial ratios: A hierarchical Bayesian approach using mixtures

This paper presents a hierarchical Bayesian analysis of the partial adjustment model of financial ratios using mixture models, an approach that allows us to estimate the distribution of the adjustment coefficients. More particularly, it enables us to analyse speed of reaction in the presence of shocks affecting financial ratios objectives as a basis to establish homogenous groups of firms. The proposed methodology is illustrated by examining a set of ratios for a sample of firms operating in the U.S. manufacturing sector. Copyright © 2007 John Wiley & Sons, Ltd.     

Optimal consumption of the finite time horizon Ramsey problem

In this paper, we study the stochastic Ramsey problem related to an economic growth model with the CES production function in a finite time horizon. By changing variables, the Hamilton-Jacobi-Bellman equation associated with this optimization problem is transformed. By the viscosity solution technique, we show the existence of a classical solution of the transformed Hamilton-Jacobi-Bellman equation, and then give an optimal consumption policy of the original problem.     

On the equivalence of financial structures with long-term assets

In a stochastic financial exchange economy, two financial structures are equivalent if, for each given state price, the marketable payoffs are identical for the associated asset prices. The key property of two equivalent financial structures is that, when associated with any standard exchange economy, they lead to the same financial equilibrium. We exhibit a sufficient condition for the equivalence of two financial structures without re-trading with possibly long-term assets. We then apply this result to financial structures built upon primitive assets and their re-trading. We also borrow an assumption from Bonnisseau and Chéry (Ann Financ 10:523–552, 2014) to prove the equivalence between a financial structure and its reduced forms.     

Monitoring the mean of multivariate financial time series

Timely detection of changes in the mean vector of multivariate financial time series is of great practical importance. In this paper, the covariance dynamics of the multivariate stochastic processes is assessed by either the RiskMetrics approach, the constant conditional correlation, or the dynamic conditional correlation models. For online monitoring of mean changes, we introduce several control schemes based on exponential smoothing and cumulative sums, which explicitly account for heteroscedasticity. The detecting ability of the introduced charts is compared for different processes in a Monte Carlo simulation study. The empirical study illustrates monitoring of changes in the mean vector of daily returns of exchange rates. Copyright © 2013 John Wiley & Sons, Ltd.     

Markov: A methodology for the solution of infinite time horizon markov decision processes

Algorithms are described for determining optimal policies for finite state, finite action, infinite discrete time horizon Markov decision processes. Both value-improvement and policy-improvement techniques are used in the algorithms. Computing procedures are also described. The algorithms are appropriate for processes that are either finite or infinite, deterministic or stochastic, discounted or undiscounted, in any meaningful combination of these features. Computing procedures are described in terms of initial data processing, bound improvements, process reduction, and testing and solution. Application of the methodology is illustrated with an example involving natural resource management. Management implications of certain hypothesized relationships between mallard survival and harvest rates are addressed by applying the optimality procedures to mallard population models.     

Contagion modeling between the financial and insurance markets with time changed processes

This study analyzes the impact of contagion between financial and non-life insurance markets on the asset–liability management policy of an insurance company. The indirect dependence between these markets is modeled by assuming that the assets return and non-life insurance claims are led respectively by time-changed Brownian and jump processes, for which stochastic clocks are integrals of mutually self-exciting processes. This model exhibits delayed co-movements between financial and non-life insurance markets, caused by events like natural disasters, epidemics, or economic recessions.     

Instantaneous self-fulfilling of long-term prophecies on the probabilistic distribution of financial asset values

Our goal here is to present various examples of situations where a “large” investor (i.e. an investor whose “size” challenges the liquidity or the depth of the market) sees his long-term guesses on some important financial parameters instantaneously confirmed by the market dynamics as a consequence of his trading strategy, itself based upon his guesses. These examples are worked out in the context of a model (i.e. a quantitative framework) which attempts to provide a rigorous basis for the qualitative intuitions of many practitioners. Our results may be viewed as some kind of reverse Black–Scholes paradigm where modifications of option prices affect today's real volatility.     

Optimal dividend and capital injection problem with a random time horizon and a ruin penalty in the dual model

In the dual risk model, we consider the optimal dividend and capital injection problem, which involves a random time horizon and a ruin penalty. Both fixed and proportional costs from the transactions of capital injection are considered. The objective is to maximize the total value of the expected discounted dividends, and the penalized discounted both capital injections and ruin penalty during the horizon, which is described by the minimum of the time of ruin and an exponential random variable. The explicit solutions for optimal strategy and value function are obtained, when the income jumps follow a hyper-exponential distribution.Besides, some numerical examples are presented to illustrate our results.     

Multiscale recurrence analysis of long-term nonlinear and nonstationary time series

Recurrence analysis is an effective tool to characterize and quantify the dynamics of complex systems, e.g., laminar, divergent or nonlinear transition behaviors. However, recurrence computation is highly expensive as the size of time series increases. Few, if any, previous approaches have been capable of quantifying the recurrence properties from a long-term time series, while which is often collected in the real-time monitoring of complex systems. This paper presents a novel multiscale framework to explore recurrence dynamics in complex systems and resolve computational issues for a large-scale dataset. As opposed to the traditional single-scale recurrence analysis, we characterize and quantify recurrence dynamics in multiple wavelet scales, which captures not only nonlinear but also nonstationary behaviors in a long-term time series. The proposed multiscale recurrence approach was utilized to identify heart failure subjects from the 24-h time series of heart rate variability (HRV). It was shown to identify the conditions of congestive heart failure with an average sensitivity of 92.1% and specificity of 94.7%. The proposed multiscale recurrence framework can be potentially extended to other nonlinear dynamic methods that are computationally expensive for large-scale datasets.     

Determination of the number and locations of time points in transit schedule design — Case of a single run

An analytical model for the determination of the number and locations of time points as well as the amount of slack times in transit schedule design is developed. The model considers a bus route with a special passenger demand pattern in which all boarding passengers coordinate their arrivals at each stop in such a way that they never miss their intended bus, and therefore designing the schedule separately a single run at a time, becomes possible. The model employs the dynamic programming method to deal with the trade-offs among various cost components associated with the schedule quantitatively, and yet is flexible enough to incorporate the existing rules of thumb as well as transit operators' policies. Numerical examples that illustrate the applications of the model are given. The model, although not quite applicable to bus routes with general passenger demand patterns, is useful in the analysis of the contributing factors to the design of an economical, reliable, and operational transit schedule, and is likely to be adaptable for more realistic cases.     

Optimal dividends and bankruptcy procedures: Analysis of the Ornstein-Uhlenbeck process

This paper investigates the impact of bankruptcy procedures on optimal dividend barrier policies. We specifically focus on Chapter 11 of the US Bankruptcy Code, which allows a firm in default to continue its business for a certain period of time. Our model is based on the surplus of a firm that earns investment income at a constant rate of credit interest when it is in a creditworthy condition. The firm pays a debit interest rate that depends on the deficit level when it is in financial distress. Thus, the surplus follows an Ornstein-Uhlenbeck (OU) process with a negative surplus-dependent mean-reverting rate. Default and liquidation are modeled as distinguishable events by using an excursion time or occupation time framework. This paper demonstrates how the optimal dividend barrier can be obtained by deriving a closed-form solution for the dividend value function. It also characterizes the distributional property and expectation of bankruptcy time subject to the bankruptcy procedure. Our numerical examples show that under an optimal dividend barrier strategy, the bankruptcy procedure may not prolong the expected bankruptcy time in some situations.     

On the ruin probability in a dependent discrete time risk model with insurance and financial risks

This paper considers the discrete-time risk model with insurance risk and financial risk in some dependence structures. Under assumptions that the insurance risks are heavy tailed (belong to the intersection of the long-tailed class and the dominatedly varying-tailed class) and the financial risks satisfy some moment conditions, the asymptotic and uniformly asymptotic relations for the finite-time and ultimate ruin probabilities are derived.     

Characterization of the Reverse Talmud bankruptcy rule by Exemption and Exclusion properties

The Reverse Talmud rule for bankruptcy problems applies the Constrained Equal Awards rule (CEA rule) for ‘large’ amounts of the estate, while it applies the Constrained Equal Losses rule (CEL rule) for ‘small’ amounts of the estate. The CEA rule, respectively CEL rule, can be axiomatized using the Exemption and Exclusion properties respectively. There is no rule that satisfies both these two properties. In this paper we axiomatize the Reverse Talmud rule by using compatible weaker versions of the Exemption and Exclusion properties.     

Detecting the impact area of BP deepwater horizon oil discharge: an analysis by time varying coefficient logistic models and boosted trees

The Deepwater Horizon oil discharge in the Gulf of Mexico is considered to be one of the worst environmental disasters to date. The spread of the oil spill and its consequences thereof had various environmental impacts. The National Oceanic and Atmospheric Administration (NOAA) in conjunction with the Environmental Protection Agency (EPA), the US Fish and Wildlife Service, and the American Statistical Association (ASA) have made available a few datasets containing information of the oil spill. In this paper, we analyzed four of these datasets in order to explore the use of applied statistics and machine learning methods to understand the spread of the oil spill. In particular, we analysed the “gliders, floats, boats” and “birds” data. The former contains various measurements on sea water such as salinity, temperature, spacial locations, depth and time. The latter contains information on the living conditions of birds, such as living status, oil conditions, locations and time. A varying-coefficients logistic regression was fitted to the birds data. The result indicated that the oil was spreading more quickly along the East–West direction. Analysis via boosted trees and logistic regression showed similar results based on the information provided by the above data.     

Two storage inventory problem with dynamic demand and interval valued lead-time over finite time horizon under inflation and time-value of money

A finite time horizon inventory problem for a deteriorating item having two separate warehouses, one is a own warehouse (OW) of finite dimension and other a rented warehouse (RW), is developed with interval-valued lead-time under inflation and time value of money. Due to different preserving facilities and storage environment, inventory holding cost is considered to be different in different warehouses. The demand rate of item is increasing with time at a decreasing rate. Shortages are allowed in each cycle and backlogged them partially. Shortages may or may not be allowed in the last cycle and under this circumstance, there may be three different types of model. Here it is assumed that the replenishment cycle lengths are of equal length and the stocks of RW are transported to OW in continuous release pattern. For each model, different scenarios are depicted depending upon the re-order point for the next lot. Representing the lead-time by an interval number and using the interval arithmetic, the single objective function for profit is changed to corresponding multi-objective functions. These functions are maximized and solved by Fast and Elitist Multi-objective Genetic Algorithm (FEMGA). The models are illustrated numerically and the results are presented in tabular form.