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Material on this website referred to in Malcolm Kemp's book on Market Consistency

[this page | pdf | references | back links]

See pages linked to Market Consistency for further information on this book.

 

Section

Section Title

Description

Hyperlink?

1.5 [foot] and 4.2.2.1 [foot]

Introduction

Annualisation (annualization) conventions

yes

4.3.1.6

Derivative pricing and hedging

Optimised trinomial lattices

yes

4.3.1.6(b)

Derivative pricing and hedging

Semi-analytic lattice integrator approaches

yes

4.3.1.6(c)

Derivative pricing and hedging

Numerical integration techniques

no

4.3.2.2

Derivative pricing and hedging

Deriving the Black-Scholes pricing formulae using stochastic calculus if r, q and sigma are constant

yes

4.3.2.6

Derivative pricing and hedging

Derivative pricing where there are multiple underlying price processes

no

4.3.4

Derivative pricing and hedging

Analytical formulae for option pricing greeks for Black-Scholes formulae

yes

4.13

Derivative pricing and hedging

Calibrating an assumed multivariate prior (Normal) distribution to the 'nearest' alternative multivariate Normal distribution that reproduces the calibration points

yes

5.3.4 [foot]

Yield curve analysis

Extrapolating present values from yield curves

no

7.1

Risk measurement

A more in depth mathematical treatment of risk management

yes

7.2

Risk measurement

Analysis of potential difference between weighted average of instrument specific durations and the equivalent 'whole portfolio' duration

no

7.3.2.5

Risk measurement

Risk measurement techniques that involve analysing fund returns through time

no

7.3.2.5 [foot]

Risk measurement

Example of snail trails

no

7.4.3

Risk measurement

Principal components analysis and other similar techniques

yes

7.4.4

Risk measurement

Expression of multivariate regression analysis in matrix algebra form

yes

7.4.8

Risk measurement

Time series based risk modelling as a special case of forecasting the characteristics of return series

yes

7.5.1

Risk measurement

The sparcity of the data available and how using weekly data does not appear to add many more significant principal components

no

7.5.1 [foot]

Risk measurement

Random matrix theory

yes

7.7.1

Risk attribution

Grouping individual instrument contributions to risk

yes

7.7.1

Risk attribution

Beta adjusted risk attribution

yes

9.3.3(a)

Backtesting risk models

Standard statistical tests relevant to backtesting VaR and equivalents

yes

9.3.3(b)

Testing backtest quality

Standard statistical tests relevant to backtesting the entire distributional form

yes

9.4

Fitting observed distributional forms

Generalised beta distribution of the second kind, and other generalised distributional forms

yes

9.4

Fitting observed distributional forms

Levy stable distributions (also known as stable Paretian distributions)

yes

9.5.3

Fat tails

Derivation of Cornish-Fisher asymptotic expansion

yes

9.5.4

Fat tails

How the Cornish-Fisher asymptotic expansion lacks a desirable invariance property

no

9.5.5 [foot]

Fat tails

How polynomial curve-fits to quantile-quantile plots simplify computation of expected shortfall

yes

9.5.6

Fat tails

How mixtures of normal distributions can lead to fat-tails

yes

9.5.6

Fat tails

Typically greater sensitivity of expected shortfall versus VaR to magnitude of fat-tailed behaviour

yes

9.6.4

Fat tails (in multiple return series simultaneously)

Box counting algorithms

no

12.1

Portfolio construction

Taking account of ‘what the market has to say’ within investment idea generation

yes

12.2.3

Portfolio construction

Algorithms for solving (mean-variance) constrained quadratic optimisation problems

yes

12.4.2

Portfolio construction

Why statistical tests of manager skill based on past data typically depend on information ratios

yes

12.4.2

Portfolio construction

What might constitute upper quartile skill levels?

yes

12.4.4

Portfolio construction

Clustering techniques for universe selection

yes

12.7.1

Portfolio construction

Practical ways of catering better for non-Normality in return distributions in portfolio optimisation

yes

12.8.2

Robust optimisation: Re-sampling

For what mathematical problem are re-sampled optimised portfolios actually optimal?

yes

13.4.10

Market consistent liability valuations

Summary of techniques used in non-life insurance reserving

no

13.6.2

Solvency add-ons

Impact that division between base liability and solvency add-on can have within current regulatory frameworks

no

 

 


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