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Data Analytics for Corporate Debt Markets: Using Data for Investing, Trading, Capital Markets, and Portfolio Management - Rilegato
Use state-of-the-art data analytics to optimize your evaluation and selection of corporate debt investments. Data Analytics for Corporate Debt Markets introduces the most valuable data analytics tools, methods, and applications for today's corporate debt market. Robert Kricheff shows how data analytics can improve and accelerate the process of proper investment selection, and guides market participants in focusing their credit work. Kricheff demonstrates how to use analytics to position yourself for the future; to assess how your current portfolio or trading desk is currently positioned relative to the marketplace; and to pinpoint which part of your holdings impacted past performance. He outlines how analytics can be used to compare markets, develop investment themes, and select debt issues that fit (or do not fit) those themes. He also demonstrates how investors seek to analyze short term supply and demand, and covers some special parts of the market that utilize analytics. For all corporate debt portfolio managers, traders, analysts, marketers, investment bankers, and others who work with structured financial products.
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Robert S. Kricheff (Bob) is a senior vice president and portfolio manager at Shenkman Capital Management. Before joining Shenkman Capital, he worked for more than 25 years at Credit Suisse in Leveraged Finance. Prior to leaving Credit Suisse, he was a managing director and head of the Americas High Yield Sector Strategy.
He has worked doing credit analysis in several industries, including media, cable, satellite, telecommunications, health care, gaming, and energy, and has worked with corporate bonds, loans, convertibles, preferred stocks, and credit default swaps as well as emerging market corporate bonds. He has also run strategy and has overseen portfolio analytics.
Bob is the author of A Pragmatist’s Guide to Leveraged Finance: Credit Analysis for Bonds and Bank Debt and two e-book shorts, The Role of Credit Default Swaps in Leveraged Finance Analysis with Joel S. Kent and How to Analyze and Use Leveraged Finance Bonds for Project Finance , all published by FT Press. He also contributed to the book High-Yield Bonds: Market Structure, Valuation, and Portfolio Strategies by Theodore M. Barnhill Jr., William F. Maxwell, and Mark R. Shenkman, published by McGraw-Hill.
Bob graduated from New York University School of Arts & Science with a BA in journalism and economics and received an MSc in financial economics from the University of London School of Oriental and African Studies.
Use State-of-the-Art Data Analytics to Optimize the Evaluation and Selection of Corporate Debt Investments
Data Analytics for Corporate Debt Markets introduces today’s most valuable data analytics tools, methods, and applications for corporate debt markets. Robert Kricheff and his expert contributors show how data analytics can help you target credit work, compare markets, choose investments, assess portfolios, and optimize your positioning in the markets.
They explain how innovative investment teams are currently applying data analytics in corporate debt markets and how diverse specialists work together to develop and run the analytics that are used and the related concepts.
Readers will gain deep insight into the key indexes used in corporate debt analysis, discover a “top-down” approach to data analytics, learn how to develop lists of potential investments that fit with the strategic themes developed by their analytics, and review how the analysis is utilized in some of the most widely used special vehicles in the market today.
The book concludes with expert insights on portfolio and performance attribution and a preview of emerging trends in data analysis for corporate debt.
Whatever your role in the global corporate debt markets, if you do not use data analytics, you are increasingly vulnerable to fall behind those who do. While fundamental credit work remains indispensable, data analytics offers powerful opportunities to improve and accelerate the process. It can guide you in focusing credit analysis, gaining forward-looking insights for market positioning, and more effectively analyzing your current positions.
This unique guidebook explains how data analytics tools and methods are being applied most successfully in current corporate debt markets and also previews future applications.
With contributions from experts, Robert Kricheff explains why corporate debt data analysis is unique and how it integrates techniques from both government debt and equity markets. Kricheff shows how data analytics is used to identify both high-level themes and specific investments, explores indexes and collateralized loan obligations, and guides you in analyzing multiple special vehicles--including some that offer crucial early insight into shifting markets.
- Develop investment themes and identify debt issues to support them
- Analyze changes in the markets and relative value opportunities
- Analyze special vehicles, including liquid bond indexes, credit default swaps and indexes, and corporate debt ETFs
Data Analytics for Corporate Debt Markets introduces today’s most valuable data analytics tools, methods, and applications for corporate debt markets. Robert Kricheff and his expert contributors show how data analytics can help you target credit work, compare markets, choose investments, assess portfolios, and optimize your positioning in the markets.
They explain how innovative investment teams are currently applying data analytics in corporate debt markets and how diverse specialists work together to develop and run the analytics that are used and the related concepts.
Readers will gain deep insight into the key indexes used in corporate debt analysis, discover a “top-down” approach to data analytics, learn how to develop lists of potential investments that fit with the strategic themes developed by their analytics, and review how the analysis is utilized in some of the most widely used special vehicles in the market today.
The book concludes with expert insights on portfolio and performance attribution and a preview of emerging trends in data analysis for corporate debt.
Whatever your role in the global corporate debt markets, if you do not use data analytics, you are increasingly vulnerable to fall behind those who do. While fundamental credit work remains indispensable, data analytics offers powerful opportunities to improve and accelerate the process. It can guide you in focusing credit analysis, gaining forward-looking insights for market positioning, and more effectively analyzing your current positions.
This unique guidebook explains how data analytics tools and methods are being applied most successfully in current corporate debt markets and also previews future applications.
With contributions from experts, Robert Kricheff explains why corporate debt data analysis is unique and how it integrates techniques from both government debt and equity markets. Kricheff shows how data analytics is used to identify both high-level themes and specific investments, explores indexes and collateralized loan obligations, and guides you in analyzing multiple special vehicles--including some that offer crucial early insight into shifting markets.
- Use indexes to compare markets and attribute portfolio performance
Understand the strengths and limits of corporate debt indexes--and how not to use them - Master a top-down macro approach to corporate debt data analytics
Examine performance and relative value at market level and then drill down to key subsectors - Identify potential investments that fit your macro themes
Successfully apply data analytics in credit selection--and learn some common pitfalls to avoid - Effectively analyze technical supply and demand trends
Use data analytics to optimize your timing and weighting decisions
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- EditoreFt Pr
- Data di pubblicazione2014
- ISBN 10 0133553655
- ISBN 13 9780133553659
- RilegaturaCopertina rigida
- Numero edizione1
- Numero di pagine288
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