Black and Scholes (1973) and Merton (1973, 1974) (hereafter referred to as BSM) introduced the contingent claim approach (CCA) to the valuation of corporate debt and equity. The BSM modeling framework is also named the 'structural' approach to risky debt valuation. The CCA considers all stakeholders of the corporation as holding contingent claims on the assets of the corporation. Each claim holder has different priorities, maturities and conditions for payouts. It is based on the principle that all the assets belong to all the liability holders.The BSM modeling framework gives the basic fundamental version of the structural model where default is assumed to occur when the net asset value of the firm at the maturity of the pure-discount debt becomes negative, i.e., market value of the assets of the firm falls below the face value of the firm's liabilities. In a regime of limited liability, the shareholders of the firm have the option to default on the firm's debt. Equity can be viewed as a European call option on the firm's assets with a strike price equal to the face value of the firm's debt. Actually, CCA can be used to value all the components of the firm's liabilities, equity, warrants, debt, contingent convertible debt, guarantees, etc.In the four volumes we present the major academic research on CCA in corporate finance starting from 1973, with seminal papers of Black and Scholes (1973) and Merton (1973, 1974). Volume I covers the foundation of CCA and contributions on equity valuation. Volume II focuses on corporate debt valuation and the capital structure of the firm. Volume III presents empirical evidence on the valuation of debt instruments as well as applications of the CCA to various financial arrangements. The papers in Volume IV show how to apply the CCA to analyze sovereign credit risk, contingent convertible bonds (CoCos), deposit insurance and loan guarantees. Volume 1: Foundations of CCA and Equity ValuationVolume 1 presents the seminal papers of Black and Scholes (1973) and Merton (1973, 1974). This volume also includes papers that specifically price equity as a call option on the corporation. It introduces warrants, convertible bonds and taxation as contingent claims on the corporation. It highlights the strong relationship between the CCA and the Modigliani-Miller (M&M) Theorems, and the relation to the Capital Assets Pricing Model (CAPM). Volume 2: Corporate Debt Valuation with CCAVolume 2 concentrates on corporate bond valuation by introducing various types of bonds with different covenants as well as introducing various conditions that trigger default. While empirical evidence indicates that the simple Merton's model underestimates the credit spreads, additional risk factors like jumps can be used to resolve it. Volume 3: Empirical Testing and Applications of CCAVolume 3 includes papers that look at issues in corporate finance that can be explained with the CCA approach. These issues include the effect of dividend policy on the valuation of debt and equity, the pricing of employee stock options and many other issues of corporate governance. Volume 4: Contingent Claims Approach for Banks and Sovereign DebtVolume 4 focuses on the application of the contingent claim approach to banks and other financial intermediaries. Regulation of the banking industry led to the creation of new financial securities (e.g., CoCos) and new types of stakeholders (e.g., deposit insurers).

V.1. Foundations of CCA and equity valuation -- v. 2. Corporate debt valuation with CCA -- v. 3. Empirical testing and applications of CCA -- v. 4. Contingent claims approach for banks and sovereign debt.

Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, difference from conventional data, categories of Alternative Data, Alternative Data providers, and more. The book also offers a rigorous and detailed exploration of process, application and delivery that should be practically useful to researchers and practitioners alike. Features Includes cutting edge applications in machine learning, fintech, and more Suitable for professional quantitative analysts, and as a resource for postgraduates and researchers in financial mathematics Features chapters from many leading researchers and practitioners

The 4-volumes set of LNCS 13529, 13530, 13531, and 13532 constitutes the proceedings of the 31st International Conference on Artificial Neural Networks, ICANN 2022, held in Bristol, UK, in September 2022. The total of 255 full papers presented in these proceedings was carefully reviewed and selected from 561 submissions. ICANN 2022 is a dual-track conference featuring tracks in brain inspired computing and machine learning and artificial neural networks, with strong cross-disciplinary interactions and applications.

A book combining the rigour of academic finance with the pragmatism of hands-on finance.

In today’s competitive market, a manager must be able to look at data, understand it, analyze it, and then interpret it to design a smart business strategy. Big data is also a valuable source of information on how customers interact with firms through various mediums such as social media platforms, online reviews, and many more. The applications and uses of business analytics are numerous and must be further studied to ensure they are utilized appropriately. Data-Driven Approaches for Effective Managerial Decision Making investigates management concepts and applications using data analytics and outlines future research directions. The book also addresses contemporary advancements and innovations in the field of management. Covering key topics such as big data, business intelligence, and artificial intelligence, this reference work is ideal for managers, business owners, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.

This book explains the vocabulary of cost-volume-profit (breakeven) analysis (CVP), explores the breadth of applications of CVP, and illustrates the use of CVP concepts in a broad range of management and marketing scenarios. The book examines the proper identification of a 'unit', the various formulations of breakeven, profit planning using the breakeven formulas, and the application of CVP in sensitivity analysis. Each chapter will offer several important ingredients for a practical 'how to' approach: the type of data needed, the formula, how to calculate and interpret the math, a specific example followed by a brief review of the assumptions and limitations of that method.

This paper runs the gamut of qualitative and quantitative analyses to examine the performance of French banks during 2006-2008 and the financial support measures taken by the French government. French banks were not immune but proved relatively resilient to the global financial crisis reflecting their business and supervision features. An event study of the impact of government measures on CDS, debt, and equity markets points to the reduction of credit risk and financing cost as well as the redistribution of resources. With the crisis still unfolding, uncertainties remain and challenges lie ahead, calling for continued vigilance and enhanced risk management.