Financial Economics and Quantitative Analysis Series – serie

Quantitative Financial Economics Quantitative Financial Economics provides a comprehensive introduction to models of economic behaviour in financial markets, focusing on analysis in discrete time. Following the huge success of the first edition, this second edition has been fully revised and updated to reflect new developments in theory and practice, including: Behavioural finance: Preferences, arbitrage and learningMean-variance and intertemporal asset allocationPerformance of mutual and hedge fundsMomentum, value-glamour strategies, style investing, market timing.Stochastic discount factor models: Equity premium and volatility puzzlesAffine and cash-in-advance modelsValue at risk: Monte Carlo simulation, bootstrapping.Market microstructure: FX markets, technical trading, chartismCalibration, regime switching, data snooping, non-linear models.The authors provide theories and tests of competing ideas in financial markets using examples from the stock, bond and foreign exchange markets. Emphasis is placed on how models inform real-world decisions, making this book accessible to both students and quants practitioners studying the behaviour of asset returns and prices. REVIEWS FOR 1ST EDITION Review of 1st edition in Journal of Banking and Finance (22, pp 121-124): “In general the book is well written with a lucid exposition and Cuthbertson is eager on giving intuitive explanations whenever possible. Thus students and empirical researchers in macroeconomics and finance will undoubtedly find the book very valuable.”Tom Engsted, Aarhus School of Business, Aarhus, Denmark Review of 1st edition in Journal of Finance (53(1), pp. 417-420): “I found the book accessible and informative on a variety of topics. It provided me with a different perspective on some of the recent empirical literature. I believe that many finance doctoral student and academics would find it to be a useful resource and a handy reference.”Robert F. Whitelaw, Stern School of Business, NYU The book has a supporting website http://www.wiley.co.uk/cuthbertson which includes questions and answers, illustrative Excel and GAUSS programmes and econometrics notes.

Developments in Forecast Combination and Portfolio Choice focuses on the following three themes: model and forecast combinations; structural change and long memory, controlling downside risk and investment strategies. Written by leading international researchers and practitioners, his book deals efficiently with three key questions facing portfolio managers. How to achieve greater forecasting accuracy; how to deal with structural change in asset allocation models and how to control downside risk, i.e. the risk of loss, in portfolio management.

Over the quarter of a century with which this book is concerned,the UK has had an extraordinarily diverse experience of monetarypolicy and monetary regimes. Monetary policy has been transformed,from attempts to control broad money from the supply side with theuse of indirect controls on banks' lending, to an almost exclusivefocus on interest rates in a context of inflation targeting. Theexchange rate has at times been fixed, at other times almostperfectly flexible, and at other times again more or less managed.Meanwhile the real economy has experienced large variations ingrowth, together with what most observers have seen as a sharp riseand then a gradual decline in the NAIRU; inflation has variedbetween 25% and 2%. This is a book about the making of monetary policy in the UK,about how and why the monetary regimes changed over the period, andhow and why the monetary authorities took the decisions they didabout monetary growth, interest rates and the exchange rate. Itincludes separate chapters on monetary targeting, on policy in thesecond half of the 1980s, on the UK's brief membership of the ERM,on inflation targeting between 1993 and 1997, and on inflationtargeting with instrument independence since 1997. It also containsa detailed analysis of the factors that influenced interest ratedecisions and monetary policy with particular reference to theexchange rate, and an investigation of the nature and reasons forinterest rate smoothing in the UK. "David Cobham has written an excellent history of British monetarypolicy over the final quarter of the 20th Century. His judgement ofthe political and economic context is sound and sensible. It iswell written with clear and helpful tables and charts. Besides thecareful historical reporting, Cobham adds some valuable extraresearch of his own, notably on the interaction between monetarypolicy and the exchange rate (Chapter 9) and on the reasons forinterest rate 'smoothing' (Chapter 10)."Charles Goodhart, Norman Sosnow Professor of Banking and Financeat the London School of Economics "...an essential guide covering everything the reader could everwant to know about the UK's turbulent monetary history over thelast quarter century"Charles Bean, Chief Economist, Bank of England

In the theory and practice of econometrics the model, the methodand the data are all interdependent links in informationrecovery-estimation and inference. Seldom, however, are theeconomic and statistical models correctly specified, the datacomplete or capable of being replicated, the estimation rulesoptimal and the inferences free of distortion. Faced with theseproblems, Maximum Entropy Economeirics provides a new basis forlearning from economic and statistical models that may benon-regular in the sense that they are ill-posed or underdeterminedand the data are partial or incomplete. By extending the maximumentropy formalisms used in the physical sciences, the authorspresent a new set of generalized entropy techniques designed torecover information about economic systems. The authors compare thegeneralized entropy techniques with the performance of the relevanttraditional methods of information recovery and clearly demonstratetheories with applications including* Pure inverse problems that include first order Markov processes,and input-output, multisectoral or SAM models to* Inverse problems with noise that include statistical modelssubject to ill-conditioning, non-normal errors, heteroskedasticity,autocorrelation, censored, multinomial and simultaneous responsedata, as well as model selection and non-stationary and dynamiccontrol problemsMaximum Entropy Econometrics will be of interest to econometricianstrying to devise procedures for recovering information from partialor incomplete data, as well as quantitative economists in financeand business, statisticians, and students and applied researchersin econometrics, engineering and the physical sciences.

The authors reconsider the problem of parametrically specifying distribution suitable for asset-return models. They describe alternative distributions, showing how they can be estimated and applied to stock-index and exchange-rate data. The implications for options pricing are also investigated.

Today s financial markets are characterised by a large number ofparticipants, with different appetites for risk, different timehorizons, different motivations and reactions to unexpected news.The mathematical techniques and models used in the forecasting offinancial markets have therefore grown ever more sophisticated astraders, analysts and investors seek to gain an edge on theircompetitors. Written by leading international researchers andpractitioners, this book focuses on three major themes of today sstate of the art financial research: modelling with high frequencydata, the information content of volatility markets, andapplications of neural networks and genetic algorithms to financialtime series. Forecasting Financial Markets includes empiricalapplications to present the very latest thinking on these complextechniques, including:* High frequency exchange rates * Intraday volatility * Autocorrelation and variance ratio tests * Conditional volatility * GARCH processes * Chaotic systems * Nonlinearity * Stochastic and EXPAR models * Artificial neural networks * Genetic algorithms

Nonlinear Modelling of High Frequency Financial Time Series Edited by Christian Dunis and Bin Zhou In the competitive and risky environment of today's financial markets, daily prices and models based upon low frequency price series data do not provide the level of accuracy required by traders and a growing number of risk managers. To improve results, more and more researchers and practitioners are turning to high frequency data. Nonlinear Modelling of High Frequency Financial Time Series presents the latest developments and views of leading international researchers and market practitioners, in modelling high frequency data in finance. Combining both nonlinear modelling and intraday data for financial markets, the editors provide a fascinating foray into this extremely popular discipline. This book evolves around four major themes. The first introductory section focuses on high frequency financial data. The second part examines the exact nature of the time series considered: several linearity tests are presented and applied and their modelling implications assessed. The third and fourth parts are dedicated to modelling and forecasting these financial time series.