The text emphasises four themes to support evidence-based management decision making: 1. Setting the statistical landscape in a management context 2. Interpretative decision making based on patterns revealed by exploratory data analyses 3. Statistical decision making guided by the test-based findings of inferential analyses 4. Predictive decision making using statistical modelling evidence. The thread that links them is the role of data analytics as a management decision-support tool. This fifth edition builds on the strengths of the fourth edition by: - Highlighting newer trends in statistical applications in management practice - Strengthening the Excel-based generation of statistical evidence using a custom-built software product, called X-Static - Enhancing the graphic visualisation of statistical evidence. Target market: - Undergraduate students of Management at universities (BCom, BAcc, etc) - Management diploma students working towards professional qualifications at institutions such as the IMM, CSSA, CIMA, IAC, etc. - Postgraduate students (MBA and PGDip) of Management at business schools.

Relying on the existence, in a complete market, of a pricing kernel, this book covers the pricing of assets, derivatives, and bonds in a discrete time, complete markets framework. It is primarily aimed at advanced Masters and PhD students in finance. - Covers asset pricing in a single period model, deriving a simple complete market pricing model and using Stein's lemma to derive a version of the Capital Asset Pricing Model. - Looks more deeply into some of the utility determinants of the pricing kernel, investigating in particular the effect of non-marketable background risks on the shape of the pricing kernel. - Derives the prices of European-style contingent claims, in particular call options, in a one-period model; derives the Black-Scholes model assuming a lognormal distribution for the asset and a pricing kernel with constant elasticity, and emphasizes the idea of a risk-neutral valuation relationship between the price of a contingent claim on an asset and the underlying asset price. - Extends the analysis to contingent claims on assets with non-lognormal distributions and considers the pricing of claims when risk-neutral valuation relationships do not exist. - Expands the treatment of asset pricing to a multi-period economy, deriving prices in a rational expectations equilibrium. - Uses the rational expectations framework to analyse the pricing of forward and futures contracts on assets and derivatives. - Analyses the pricing of bonds given stochastic interest rates, and then uses this methodology to model the drift of forward rates, and as a special case the drift of the forward London Interbank Offer Rate in the LIBOR Market Model.