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; ...
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.
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.
Section I: Introduction to Data Analytics for Corporate Debt Markets 1
Chapter 1: The Basics 3
Chapter 2: Corporate Debt Is Different 11
Chapter 3: Managing Projects and Managing People 23
Closing Comments on Section I 29 Section II: Terminology and Basic Tools 31
Chapter 4: Terms 33
Chapter 5: Basic Tools 45
Chapter 6: Data Mining 55
Closing Comments on Section II 61 Section III: The Markets and the Players 63
Chapter 7: The Markets 65
Chapter 8: The Participants 71
Closing Comments on Section III 83 Section IV: Indexes 85
Chapter 9: Index Basics 87
Chapter 10: Index Construction 97
Chapter 11: Other Topics in Corporate Bond Indexes 109
Closing Comments on Section IV 117 Section V: Analytics from Macro Market Data to Credit Selection 119
Chapter 12: Top Down Basics--Looking for Investment Themes Between Markets 121
Chapter 13: The Next Layer--Analyzing a Market 131
Chapter 14: Data Analytics for Credit Selection 139
Closing Comments on Section V 169 Section VI: Analysis of Market Technicals 171
Chapter 15: Market Demand Technicals 173
Chapter 16: Market Supply Technicals 177
Closing Comments on Section VI 189 Section VII: Special Vehicles--Liquid Bond Indexes, Credit Default Swaps, Indexes, and Exchange-Traded Funds 191
Chapter 17: Liquid Bond Indexes 193
Chapter 18: Credit Default Swaps and Indexes 199
Chapter 19: Corporate Debt Exchange-Traded Funds (ETFs) 213
Closing Comments on Section VII 221 Section VIII: Collateralized Loan Obligations (CLOs) 223
Chapter 20: Introduction to CLOs 225
Chapter 21: Structure of Typical CLOs 231
Closing Comments on Section VIII 235 Section IX: Tools for Portfolio Analysis 237
Chapter 22: The Why, What, and How of Portfolio Analysis 239
Chapter 23: Performance Attribution 249
Closing Comments on Section IX 263 Section X: The Future of Data Analytics and Closing Comments 265
Chapter 24: Some Thoughts on the Future of Data Analytics in Corporate Debt Markets 267
Chapter 25: Closing Remarks 275