Strategic Asset Allocation in Fixed Income Markets: A Matlab based user's guideISBN: 9780470753620
186 pages
October 2008

Description
 Matlab is used within nearly all investment banks and is a requirement in most quant job ads. There is no other book written for finance practitioners that covers this
 Enables readers to implement financial and econometric models in Matlab
 All central concepts and theories are illustrated by Matlab implementations which are accompanied by detailed descriptions of the programming steps needed
 All concepts and techniques are introduced from a basic level
 Chapter 1 introduces Matlab and matrix algebra, it serves to make the reader familiar with the use and basic capabilities if Matlab. The chapter concludes with a walkthrough of a linear regression model, showing how Matlab can be used to solve an example problem analytically and by the use of optimization and simulation techniques
 Chapter 2 introduces expected return and risk as central concepts in finance theory using fixed income instruments as examples, the chapter illustrates how risk measures such as standard deviation, Modified duration, VaR, and expected shortfall can be calculated empirically and in closed form
 Chapter 3 introduces the concept of diversification and illustrates how the efficient investment frontier can be derived  a Matlab is developed that can be used to calculate a given number of portfolios that lie on an efficient frontier, the chapter also introduces the CAPM
 Chapter 4 introduces econometric tools: principle component analysis is presented and used as a prelude to yieldcurve factor models. The NelsonSiegel model is used to introduce the KalmanFilter as a way to add timeseries dynamics to the evolution of yield curves over time, time series models such as Vector Autoregression and regimeswitching are also presented
 Supported by a website with online resources  www.kennyholm.com where all Matlab programs referred to in the text can be downloaded. The site also contains lecture slides and answers to end of chapter exercises
Table of Contents
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. FixedIncome 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 Valueatrisk and Expected Shortfall.
4.2.2 Duration and modified duration.
4.3 FixedIncome Returns.
5. Term Structure Models.
5.1 Introduction.
5.2 NotNecessarily Arbitrage FreeModels.
5.2.1 Nelson and Siegel.
5.2.2 Svensson and Soderlind.
5.3 ArbitrageFreeModels.
5.3.1 Vasicek.
5.3.2 Multifactormodels: 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 statespace form.
7.4.1 The NelsonSiegelmodel in statespace.
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.
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