Unlocking Financial Data: A Practical Guide to Technology for Equity and Fixed Income Analysts

Investors recognize that technology is a powerful tool for obtaining and interpreting financial data that could give them the one thing everyone on Wall Street wants: an edge. Yet, many don’t realize that you don’t need to be a programmer to access behind-the-scenes financial information from Bloomberg, IHS Markit, or other systems found at most banks and investment firms.

This practical guide teaches analysts a useful subset of Excel skills that will enable them to access and interpret financial information—without any prior programming experience. This book will show analysts, step-by-step, how to quickly produce professional reports that combine their views with Bloomberg or Markit data including historical financials, comparative analysis, and relative value. For portfolio managers, this book demonstrates how to create professional summary reports that contain a high-level view of a portfolio’s performance, growth, risk-adjusted return, and composition. If you are a programmer, this book also contains a parallel path that covers the same topics using C#.

Topics include:

  • Access additional data that isn’t visible on Bloomberg screens
  • Create tables containing corporate data that makes it possible to compare multiple companies, bonds, or loans side-by- side
  • Build one-page analytic (“Tear Sheet”) reports for individual companies that incorporates important financials, custom notes, relative value comparison of the company to its peers, and price trends with research analyst targets
  • Build two-page portfolio summary report that contains a high-level view of the portfolio’s performance, growth, risk-adjusted return, and composition
  • Explore daily prices and facility information for most of the tradable corporate bond and loan market
  • Determine the relationship between two securities (or index) using correlation and regression
  • Compare each security’s performance to a cohort made of up of securities with similar risk and return characteristics
  • Measure portfolio risk-adjusted return by calculating variance, standard deviation, and Sharpe ratio
  • Use Markit data to identify meaningful trends in prices, new issue spreads, and refinancings
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Unlocking Financial Data: A Practical Guide to Technology for Equity and Fixed Income Analysts

Investors recognize that technology is a powerful tool for obtaining and interpreting financial data that could give them the one thing everyone on Wall Street wants: an edge. Yet, many don’t realize that you don’t need to be a programmer to access behind-the-scenes financial information from Bloomberg, IHS Markit, or other systems found at most banks and investment firms.

This practical guide teaches analysts a useful subset of Excel skills that will enable them to access and interpret financial information—without any prior programming experience. This book will show analysts, step-by-step, how to quickly produce professional reports that combine their views with Bloomberg or Markit data including historical financials, comparative analysis, and relative value. For portfolio managers, this book demonstrates how to create professional summary reports that contain a high-level view of a portfolio’s performance, growth, risk-adjusted return, and composition. If you are a programmer, this book also contains a parallel path that covers the same topics using C#.

Topics include:

  • Access additional data that isn’t visible on Bloomberg screens
  • Create tables containing corporate data that makes it possible to compare multiple companies, bonds, or loans side-by- side
  • Build one-page analytic (“Tear Sheet”) reports for individual companies that incorporates important financials, custom notes, relative value comparison of the company to its peers, and price trends with research analyst targets
  • Build two-page portfolio summary report that contains a high-level view of the portfolio’s performance, growth, risk-adjusted return, and composition
  • Explore daily prices and facility information for most of the tradable corporate bond and loan market
  • Determine the relationship between two securities (or index) using correlation and regression
  • Compare each security’s performance to a cohort made of up of securities with similar risk and return characteristics
  • Measure portfolio risk-adjusted return by calculating variance, standard deviation, and Sharpe ratio
  • Use Markit data to identify meaningful trends in prices, new issue spreads, and refinancings
32.49 In Stock
Unlocking Financial Data: A Practical Guide to Technology for Equity and Fixed Income Analysts

Unlocking Financial Data: A Practical Guide to Technology for Equity and Fixed Income Analysts

by Justin Pauley
Unlocking Financial Data: A Practical Guide to Technology for Equity and Fixed Income Analysts

Unlocking Financial Data: A Practical Guide to Technology for Equity and Fixed Income Analysts

by Justin Pauley

eBook

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Overview

Investors recognize that technology is a powerful tool for obtaining and interpreting financial data that could give them the one thing everyone on Wall Street wants: an edge. Yet, many don’t realize that you don’t need to be a programmer to access behind-the-scenes financial information from Bloomberg, IHS Markit, or other systems found at most banks and investment firms.

This practical guide teaches analysts a useful subset of Excel skills that will enable them to access and interpret financial information—without any prior programming experience. This book will show analysts, step-by-step, how to quickly produce professional reports that combine their views with Bloomberg or Markit data including historical financials, comparative analysis, and relative value. For portfolio managers, this book demonstrates how to create professional summary reports that contain a high-level view of a portfolio’s performance, growth, risk-adjusted return, and composition. If you are a programmer, this book also contains a parallel path that covers the same topics using C#.

Topics include:

  • Access additional data that isn’t visible on Bloomberg screens
  • Create tables containing corporate data that makes it possible to compare multiple companies, bonds, or loans side-by- side
  • Build one-page analytic (“Tear Sheet”) reports for individual companies that incorporates important financials, custom notes, relative value comparison of the company to its peers, and price trends with research analyst targets
  • Build two-page portfolio summary report that contains a high-level view of the portfolio’s performance, growth, risk-adjusted return, and composition
  • Explore daily prices and facility information for most of the tradable corporate bond and loan market
  • Determine the relationship between two securities (or index) using correlation and regression
  • Compare each security’s performance to a cohort made of up of securities with similar risk and return characteristics
  • Measure portfolio risk-adjusted return by calculating variance, standard deviation, and Sharpe ratio
  • Use Markit data to identify meaningful trends in prices, new issue spreads, and refinancings

Product Details

ISBN-13: 9781491973202
Publisher: O'Reilly Media, Incorporated
Publication date: 10/06/2017
Sold by: Barnes & Noble
Format: eBook
Pages: 318
File size: 5 MB

About the Author

Justin Pauley is a Senior Structured Credit Analyst at Brigade Capital Management, an asset manager based in New York. At Brigade, Justin’s responsibilities include making investment recommendations, executing trades, and developing the systems used to analyze and value complex investments. Prior to joining Brigade, Justin headed CLO Strategy at the Royal Bank of Scotland where he published monthly reports to investors and developed bond analytic systems. Justin started his career in Wachovia’s technology department, developing front-office applications for analysts and traders. He has been published in The Journal of Structured Finance, quoted in publications such as the Wall Street Journal and Bloomberg News, and spoke on numerous panels at finance related conferences.

Table of Contents

Preface ix

1 Introduction 1

Overview 2

Section I Accessing Financial Data 3

Section II Financial Data Analysis 3

Section III Creating Financial Reports 4

Financial Markets 4

Equities 4

Corporate Loans (Bank Debt, Leveraged Loans) 5

Corporate Bonds 6

The Three Paths 7

Path 1 Microsoft Excel 7

Path 2 Microsoft Access 8

Path 3 C# 9

Online Files 9

Summary 9

2 Organizing Financial Data 11

Path 1 Excel 12

Excel Range Versus Excel Table 12

Adding Reference Columns 14

Data Validation 16

Paths 2 and 3: Tables in Access 17

Connecting the Data with Queries 19

Summary 20

3 Bloomberg 21

Identifying the Fields 22

The Mouse-Over 22

The FLDS Screen 23

Bloomberg Function Builder and Finding Fields in Excel 24

If All Else Fails… 26

Excel Examples 26

Pulling a Single Field (BDP) 26

Pulling Bulk Data (BDS) 29

Pulling Historical Data (BDH) 31

Comparable Securities 35

Indices 35

Peers 36

Related Securities 37

Paths 1 and 2 Excel and Access 39

Corporate Bonds, Loans, and Indices 39

Company Worksheet 44

References and Overrides 47

Path 3 Bloomberg C# API 48

Setting Up Microsoft Access for Use with C# 48

Bloomberg C# API 54

Basic Reference Example 55

Basic Historical Example 59

Populating Access Database 63

Summary 74

4 IHS Markit: Big Corporate Data 75

Corporate Loans 75

Data Request 76

Facility Information 76

Loan Pricing, Financials, and Analytics 81

Corporate and Sovereign Bonds 84

Path 1 Storing Markit Information in Excel 85

Path 2 Importing Markit Data into Microsoft Access 86

Path 3 Importing Markit Data Using C# 88

Summary 92

5 Financial Data Analysis 95

Data Integrity 96

Checking the Data 96

Sample Size 97

Outliers 98

Portfolio 99

Portfolio Worksheet 100

Portfolio Database Table 101

Linking Excel Worksheets to Microsoft Access 102

Keeping a History 103

Path 1 Excel 104

Path 2 Microsoft Access 107

Path 3 C# 109

Summary 112

6 Relative-Value Analysis 113

Path 1 Excel 114

Correlation and Regression in Excel 114

Peer Groups 120

Ratings 121

Stats Worksheets 122

Side by Side 125

Indices 127

Weighted Z-Score 127

Path 2 Access 130

Correlation and Regression in Access 131

Median in Access 132

Path 3 C# 134

Correlation and Regression 134

Peer Groups 138

Ratings 139

Stats Tables 139

Side by Side 147

Weighted Z-Score 148

Summary 149

7 Portfolio Risk Analysis 151

Path 1 Excel 152

Variance, Volatility, and Standard Deviation 152

Sharpe Ratio with Historical or Forecasted Returns 159

Portfolio Breakdown 163

Warning Signs 175

Path 2 Access 178

Portfolio Breakdown 178

Warning Signs 183

Path 3 C# 184

Sharpe Ratio with Historical or Forecasted Returns 184

Portfolio Breakdown and Warning Signs 193

Summary 193

8 Market Analysis 195

Path 1 Excel 196

New Issue Loan Analysis 196

Refinancings 199

Price History 202

Paths 2 and 3 Access and C# 207

New Issue Loan Analysis 208

Refinancings 209

Price History 210

A Step Further 213

Summary 216

9 Creating Reports 217

Path 1 Excel 218

Path 2 Microsoft Access 228

Path 3 C# and SSRS 232

Summary 246

10 Portfolio Reports 247

Monitoring Performance and Risk 247

Path 1 Microsoft Excel 248

Calculating Returns 249

Portfolio Report 257

Path 3 C# and SSRS 263

Summary 271

11 Conclusion 273

A Table Reference 275

Index 293

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