Quantitative Analytics in Debt Valuation and Management

ISBN-13: 9780071790611 / Angielski / Twarda / 2012 / 336 str.

M Guthner

Opis

A breakthrough methodology for profiting in the high-yield and distressed debt market Global advances in technology give investors and asset managers more information at their fingertips than ever before. With Quantitative Analytics in Debt Valuation and Management, you can join the elite club of quantitative investors who know how to use that information to beat the market and their competitors. This powerful guide shows you how to sharpen your analytical process by considering valuable information hidden in the prices of related assets. Quantitative Analytics in Debt Valuation and Management reveals a progressive framework incorporating debt valuation based on the interrelationships among the equity, bond, and options markets. Using this cutting-edge method in conjunction with traditional debt and equity analysis, you will reduce portfolio risk, find assets with the highest returns, and generate dramatically greater profits from your transactions. This book's "fat-free" presentation and easy-to-navigate format jump-starts busy professionals on their way to mastering proven techniques to:

• Determine the "equity risk" inherent in corporate debt to establish the causal relationship between a company's debt, equity, and asset values
• Price and analyze corporate debt in real time by going beyond traditional methods for computing capital requirements and anticipated losses
• Look with an insider's eye at risk management challenges facing banks, hedge funds, and other institutions operating with financial leverage
• Avoid the mistakes of other investors who contribute to the systemic risk in the financial system

Additionally, you will be well prepared for the real world with the book's focus on practical application and clear case studies. Step-by-step, you will see how to improve bond pricing and hedge debt with equity, and how selected investment management strategies perform when the model is used to drive decision making.