Strategic Asset Allocation in Fixed Income Markets: A Matlab Based Users Guide

Strategic Asset Allocation in Fixed Income Markets explains financial and econometrical modelling techniques that can be used to implement strategic asset allocation methods in practice using MATLAB.
Written by experienced Economist, Ken Nyholm, the book begins by introducing the reader to strategic asset allocation and its definition and applications before going on to explain how to use MATLAB in fixed–income investments and risk measurement using introductory matrix algebra, linear regression, spot rates and yields, forward rates and bond pricing functions. The second part of the book goes on to explain term structure models using examples of arbitrage–free and not necessarily arbitrage–free models; asset allocation models using the efficient frontier as a central concept; and introduces various econometric techniques such as vector autoregressive and regime–switching models.
All financial concepts used in the book are introduced from a basic level and are subsequently extended into more complicated solution models making the book both accessible and straight–forward. Framed in the context of strategic asset allocation for a fixed–income investment universe, all the tools, techniques and examples relate to bond investments. All examples are supported by annotated MATLAB code and mathematical derivations as a means to aid the reader’s effort to implement their own model specifications.


Spis treści:
1. Introduction.
1.1 Strategic Asset Allocation.
1.2 Outline of the Book.
2. Essential Elements of Matlab.
2.1 Introduction.
2.2 Getting started.
2.3 Introductorymatrix algebra.
2.4 Organising data.
2.5 Creating functions.
2.5.1 Branching and looping.
2.5.2 An example of a simple function.
2.5.3 Calling functions in Matlab Rø.
2.6 The linear regression.
2.6.1 The basic setup.
2.6.2 Maximumlikelihood.
2.7 Some estimation examples.
2.8 A brief introduction to simulations.
2.8.1 Generating correlated randomnumbers.
3. Fixed–Income Preliminaries.
3.1 Introduction.
3.2 Spot rates and yields.
3.3 Forward rates.
3.4 Bond pricing functions.
4. Risk and Return Measures.
4.1 Introduction.
4.2 RiskMeasures.
4.2.1 Value–at–risk and Expected Shortfall.
4.2.2 Duration and modified duration.
4.3 Fixed–Income Returns.
5. Term Structure Models.
5.1 Introduction.
5.2 Not–Necessarily Arbitrage FreeModels.
5.2.1 Nelson and Siegel.
5.2.2 Svensson and Soderlind.
5.3 Arbitrage–FreeModels.
5.3.1 Vasicek.
5.3.2 Multi–factormodels: an example.
6. Asset Allocation.
6.1 Introduction.
6.2 Efficient portfolios.
6.3 Diversification.
6.4 Theminimumvariance portfolio.
6.5 Asset weight constraints.
6.6 The Capital Asset PricingModel.
7. Statistical Tools.
7.1 Introduction.
7.2 The Vector Auto Regression.
7.2.1 Order of integration.
7.3 Regime switchingmodels.
7.3.1 Introduction.
7.4 Yield curvemodels in state–space form.
7.4.1 The Nelson–Siegelmodel in state–space.
7.5 Importance Sampling.
7.5.1 Some theory.
7.5.2 An example.
8. Building graphical user interfaces.
8.1 Introduction.
8.2 The "guide" development environment.
8.3 Creating a simple GUI.
8.3.1 Plotting the yield curve.
8.3.2 Estimating λ and yield curve factors.
9. Useful Formulas and Expressions.
9.1 Introduction.
9.2 Matrix operations.
9.2.1 Definitions.
9.2.2 Sum.
9.2.3 Product.
9.2.4 Transpose.
9.2.5 Symmetricmatrix.
9.2.6 The Identitymatrix.
9.2.7 Determinant.
9.2.8 Rank.
9.2.9 Inverse.
9.2.10 Trace.
9.2.11 Powers.
9.2.12 Eigenvalues and eigenvectors.
9.2.13 Positive definite.
9.2.14 Matrix differentiation.
9.3 Decompositions.
9.3.1 Triangular.
9.3 .2 Cholesky.
9.3.3 Eigenvalue.
9.4 Basic rules.
9.4.1 Index rules.
9.4.2 Logarithmrules.
9.4.3 Simple derivatives.
9.4.4 Simple integrals.
9.5 Distributions.
9.5.1 Normal.
9.5.2 Multivariate normal.
9.5.3 Vasicek’s limiting distribution.
9.6 Functions.
9.6.1 Linear (affine) function.
9.6.2 Quadratic function.
9.6.3 General polynominals.
9.6.4 Exponential.
9.6.5 Logarithm.
9.6.6 Error function.
9.6.7 Inverse.
9.7 Taylor series approximation.
9.8 Interest rates, returns and portfolio statistics.
9.8.1 Cummulative arithmetic return.
9.8.2 Average arithmetic return.
9.8.3 Cummulative geometric return.
9.8.4 Average geometric return.
9.8.5 Compounding of interest rates.
9.8.6 Portfolio statistics.

Nota biograficzna:
Ken Nyholm works in the Risk Management Division of the European Central Bank, focusing on the practical implementation of financial and quantitative techniques in the area of fixed income strategic asset allocation for the bank′s domestic and foreign currency portfolios, as well as asset and liability management for pensions. Ken holds a PhD in finance and has published numerous articles on yield curve modelling and financial market microstructure. Ken has extensive teaching and communication experience obtained from university courses at the master level, as well as conference speaking engagements, and central banking seminars. 

Okładka tylna:
Strategic Asset Allocation in Fixed Income Markets explains financial and econometrical modelling techniques that can be used to implement strategic asset allocation methods in practice using MATLAB.
Written by experienced Economist, Ken Nyholm, the book begins by introducing the reader to strategic asset allocation and its definition and applications before going on to explain how to use MATLAB in fixed–income investm ents and risk measurement using introductory matrix algebra, linear regression, spot rates and yields, forward rates and bond pricing functions. The second part of the book goes on to explain term structure models using examples of arbitrage–free and not necessarily arbitrage–free models; asset allocation models using the efficient frontier as a central concept; and introduces various econometric techniques such as vector autoregressive and regime–switching models.
All financial concepts used in the book are introduced from a basic level and are subsequently extended into more complicated solution models making the book both accessible and straight–forward. Framed in the context of strategic asset allocation for a fixed–income investment universe, all the tools, techniques and examples relate to bond investments. All examples are supported by annotated MATLAB code and mathematical derivations as a means to aid the reader’s effort to implement their own model specifications.