The need for "back to basics" information about credit risk has not disappeared; in fact, it has grown among lenders and investors who have no easy ways to learn about their clients. This short and readable book guides readers through core risk/performance issues. Readers learn the ways and means of running more efficient businesses, review bank and investor requirements as they evaluate funding requests, gain knowledge selling themselves, confidence in business plans, and their ability to make good on loans. They can download powerful tools such as banker's cash flow models and forecast equations programmable into a cell or tablet. Readers can punch keys to ascertain financial needs, calculate sales growth rates calling for external financing, profits required to internally finance their firms, and ways to position revenue growth rates in equilibrium with their firm's capital structure - a rock-solid selling point among smart lenders and investors. The book's "how-to," practical and systematical guide to credit and risk analysis draws upon case studies and online tools, such as videos, spreadsheets, and slides in providing a concise risk/return methodology.

"Multi-Asset Risk Modeling" describes, in a single volume, the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. Beginning with the fundamentals of risk mathematics and quantitative risk analysis, the book moves on to discuss the laws in standard models that contributed to the 2008 financial crisis and talks about current and future banking regulation. Importantly, it also explores algorithmic trading, which currently receives sparse attention in the literature. By giving coherent recommendations about which statistical models to use for which asset class, this book makes a real contribution to the sciences of portfolio management and risk management.
Covers all asset classes Provides mathematical theoretical explanations of risk as well as practical examples with empirical dataIncludes sections on equity risk modeling, futures and derivatives, credit markets, foreign exchange, and commodities

More efficient credit portfolio engineering can increase the decision-making power of bankers and boost the market value of their banks. By implementing robust risk management procedures, bankers can develop comprehensive views of obligors by integrating fundamental and market data into a portfolio framework that treats all instruments similarly. Banks that can implement strategies for uncovering credit risk investments with the highest return per unit of risk can confidently build their businesses.

Through chapters on fundamental analysis and credit administration, authors Morton Glantz and Johnathan Mun teach readers how to improve their credit skills and develop logical decision-making processes. As readers acquire new abilities to calculate risks and evaluate portfolios, they learn how credit risk strategies and policies can affect and be affected by credit ratings and global exposure tracking systems. The result is a book that facilitates the discipline of market-oriented portfolio management in the face of unending changes in the financial industry.
Concentrates on the practical implementation of credit engineering strategies and tools Demonstrates how bankers can use portfolio analytics to increase their insights about different groups of obligorsInvestigates ways to improve a portfolio s return on risk while minimizing probability of insolvency"