 +353-1-416-8900REST OF WORLD
+44-20-3973-8888REST OF WORLD
1-917-300-0470EAST COAST U.S
1-800-526-8630U.S. (TOLL FREE)

PRINTER FRIENDLY

Strategic Asset Allocation in Fixed Income Markets. A Matlab based user's guide. The Wiley Finance Series

• ID: 2242023
• Book
• 186 Pages
• John Wiley and Sons Ltd
1 of 4
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.

Note: Product cover images may vary from those shown
2 of 4
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.

9.6.3 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.

Note: Product cover images may vary from those shown
3 of 4   