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Data Analytics for Corporate Debt Markets: Using Data for Investing, Trading, Capital Markets, and Portfolio Management

Book Description

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.

Table of Contents

  1. About This eBook
  2. Title Page
  3. Copyright Page
  4. Dedication Page
  5. Contents
  6. About the Author
  7. About the Contributors
  8. Section I: Introduction to Data Analytics for Corporate Debt Markets
    1. 1. The Basics
      1. Why Use Analytics?
      2. What Is Data Analytics?
      3. How Data Analytics Is Used and How It Differs from Credit Analysis
      4. An Example
      5. How This Book Is Structured
    2. 2. Corporate Debt Is Different
      1. The Unique Nature of Corporate Debt
      2. Sources of Data
      3. Pricing Data
      4. An Example
      5. Endnotes
    3. 3. Managing Projects and Managing People
      1. The Basics
      2. Communications
      3. Documentation
      4. Endnote
    4. Closing Comments on Section I
  9. Section II: Terminology and Basic Tools
    1. 4. Terms
      1. Valuation Terms
      2. When and How to Use Yield and Spread
      3. Volatility Terms
      4. Further Discussion on Duration
      5. Debt-Ranking Terms
      6. Credit Ratings Terms and Usage
      7. Industry Group Terms and Definitions
      8. Endnotes
    2. 5. Basic Tools
      1. Introduction
      2. Graphical Data
      3. Trend Lines
      4. Regression
      5. Correlation
      6. Backing Up Graphs with the Data in Tabular Form
      7. Queries and Sorts
      8. Endnotes
    3. 6. Data Mining
      1. What Is Data Mining?
      2. Neighbors and Neighborhoods
      3. Clustering
      4. Decision Trees and Neural Networks
      5. Summary Comments on Data Mining
    4. Closing Comments on Section II
  10. Section III: The Markets and the Players
    1. 7. The Markets
      1. Investment-Grade Corporate Bonds
      2. High-Yield Corporate Bonds
      3. Leveraged Loans
      4. Emerging Markets and International Bonds and Loans
      5. Credit Default Swaps (CDSs)
    2. 8. The Participants
      1. Introduction
      2. The Issuers
      3. Investment Banks and Broker-Dealers
      4. Money Managers and Institutional Investors
      5. Asset Allocators and Consultants
      6. Systems Managers and Programmers
    3. Closing Comments on Section III
  11. Section IV: Indexes
    1. 9. Index Basics
      1. Why Do Indexes Matter?
      2. Calculation Methodology
    2. 10. Index Construction
      1. Introduction
      2. Index Construction: Selection Criteria
      3. Index Construction: Requirements
    3. 11. Other Topics in Corporate Bond Indexes
      1. New Issues
      2. Defaults
      3. Issuer Size
      4. Liquid Indexes
      5. Investable Indexes
      6. Indexes Versus Portfolios
    4. Closing Comments on Section IV
  12. Section V: Analytics from Macro Market Data to Credit Selection
    1. 12. Top-Down Basics—Looking for Investment Themes Between Markets
      1. Market Comparisons—Returns
      2. Volatility
      3. Correlations
      4. Market Comparisons—Relative Value
      5. Dispersion
      6. Duration
      7. Some Other Comments—On Using Historical Data
      8. Some Other Comments—Weightings
    2. 13. The Next Layer—Analyzing a Market
      1. Introduction
      2. Risk Segments
      3. Bucketing Sectors
      4. Industry Analysis
      5. Building Industry Equity Monitors
      6. What Can Be Learned from Market Shocks
      7. The Crowded Trade
      8. Endnote
    3. 14. Data Analytics for Credit Selection
      1. Introduction
      2. Data for Credit Selection
      3. Comments about Sorts and Queries
      4. An Example
      5. Financial Metrics
      6. Operational Data
      7. Financial Liquidity and Some Differences Between Credit Analysis and Data Analytics
      8. Credit Scoring
      9. Analytics Used in Relative Value
      10. Price Movements
      11. Using Equity Data
      12. Maintenance Covenants
      13. Analytics and Nonfinancial Information
      14. Endnotes
    4. Closing Comments on Section V
  13. Section VI: Analysis of Market Technicals
    1. 15. Market Demand Technicals
      1. Introduction
      2. Demand Data
      3. Other Demand Impacts
    2. 16. Market Supply Technicals
      1. Introduction
      2. Use of Proceeds and Other Ways to Analyze Supply
      3. Analyzing Price Talk and Pricing
      4. Postplacement Trading
      5. Supply and Demand Impact the Face of the Market
      6. Endnote
    3. Closing Comments on Section VI
  14. Section VII: Special Vehicles—Liquid Bond Indexes, Credit Default Swaps, Indexes, and Exchange-Traded Funds
    1. 17. Liquid Bond Indexes
      1. Introduction
      2. Why a Liquid Bond Index and What Is It?
      3. What Are Benefits and Drawbacks of a Liquid Bond Index Versus a Full Index?
    2. 18. Credit Default Swaps and Indexes
      1. What Other Tools Do Investors Use to Measure the Corporate Bond Market?
      2. What Is CDS and What Is a CDS Index?
      3. Understanding CDS Pricing—Spreads Versus Prices
      4. CDS Indexes—How Are They Constructed?
      5. What Can We Gauge from CDX Pricing and Skew?
      6. Who Are the Participants?
      7. Implications and Limitations of CDX
    3. 19. Corporate Debt Exchange-Traded Funds (ETFs)
      1. What Are ETFs?
      2. Mechanics of ETF Construction
      3. ETFs in Asset Allocation
      4. ETFs Used as a Measure of the Market—What about Technicals?
    4. Closing Comments on Section VII
  15. Section VIII: Collateralized Loan Obligations (CLOs)
    1. 20. Introduction to CLOs
      1. What Is a CLO?
      2. Why Do They Matter for You?
      3. Some Basics Affecting CLO Issuance
      4. Types of CLOs
    2. 21. Structure of Typical CLOs
      1. Introduction
      2. More Analytics: Tests and Measures
      3. Endnotes
    3. Closing Comments on Section VIII
      1. What Does Analyzing CLO Data Tell Us?
      2. Endnote
  16. Section IX: Tools for Portfolio Analysis
    1. 22. The Why, What, and How of Portfolio Analysis
      1. Goals of Portfolio Analysis
      2. What Are Your Investment Goals and Objectives?
      3. Components of a Portfolio Analysis/Performance Measures
      4. Endnotes
    2. 23. Performance Attribution
      1. Introduction
      2. Allocation Effect
      3. Selection Effect
      4. Interaction Effect
      5. Interpreting the Total Effect
      6. Two-Factor Approach to Performance Attribution
      7. Challenges of Sector-Based Performance Attribution
      8. Endnotes
    3. Closing Comments on Section IX
  17. Section X: The Future of Data Analytics and Closing Comments
    1. 24. Some Thoughts on the Future of Data Analytics in Corporate Debt Markets
      1. Bond Data and Fundamental Data
      2. Third-Party Vendors of Financial Data
      3. Growing Use of Word Recognition
      4. Covenant Analysis
      5. Multiple Scenario Analysis
      6. Data Mining
      7. Indexes
      8. Pricing and Liquidity
      9. A Final Concern about the Future of Analytics
      10. Endnote
    2. 25. Closing Remarks
  18. Index