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  FIXED INCOME MATHEMATICS 3/E
   Analytical & Statistical Techniques
    저자 Frank Fabozzi
    출판사 McGraw-Hill
    출판년도 1997 / 456 pages
    ISBN 0-7863-1121-5        판매가 45,000원
  
 
TITLE INFORMATION
Dont let the conservative nature of many fixed income intruments mislead you!
These are complex, potentially risky investments, and Fixed Income Mathematics is required reading if you are to maximize both income and capital growth from fixed income investing.
An expert, thorough analysis of this volatile markets latest developments is presented in the straight-forward, comprehensive style that has become a Fabozzi trademark. It will leave you with a greater ability to utilize and take advantage of basic strategies as well as the newest advances in fixed income analysis and research.
Table of Contents
Chapter 1 Introduction

PART 1 TIME VALUE OF MONEY
Chapter 2 Future Value
Chapter 3 Present Value
Chapter 4 Yield

PART 2 BOND PRICING YIELD MEASURES FOR OPTION-FREE BONDS
Chapter 5 The Price of Bond
Chapter 6 Conventional Yield Measures for Bonds
Chapter 7 The Yield Curve,Spot Rate Curve, and Forward Rates

PART 3 RETURN ANALYSIS
Chapter 8 Potential Sources of Dollar Return
Chapter 9 Total Return
Chapter 10 Measuring Historical Performance

PART 4 PRICE VOLATILITY FOR OPTION-FREE BONDS
Chapter 11 Price Volatility for Option-Free Bonds
Chapter 12 Price Volatility Measures : PVBP and YV of a Price Change
Chapter 13 Price Volatility Measures : Duration
Chapter 14 Price Volatility Measures : Convexity
Chapter 15 Duration and the Yield Curve

PART 5 ANALYZING BONDS WITH EMBEDDED OPTIONS
Chapter 16 Call Options : Investment and Price Characteristics
Chapter 17 Valuation and Price Volatility of Bonds with Embedded Options

PART 6 ANALYZING MORTGATE-BACKED SECURITIES
Chapter 18 Cash Flow Characteristics of Mortgages
Chapter 19 Cash Flow Characteristics of Mortgage-Backed Securities
Chapter 20 Analysis of Mortgage-Backed Securities

PART 7 STATISTICAL AND OPTMIZATION TECHNIQUES
Chapter 21 Probability Theory
Chapter 22 Simulation
Chapter 23 Regression Analysis
Chapter 24 Optimization Models



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