Numerous empirical studies have analysed the identification and nature of the underlying process of an economic system, as well as the influence of information on financial time series. The standard financial theory of efficient markets assumes identical investors having rational expectations of future stock prices. This means that there are no opportunities for speculative profit, and both trading volume and price volatility are not serially correlated. This book presents information on financial markets and covers topics such as time series and asset pricing methods, data mining, non-linear analysis, chaos and wavelet-based techniques
Learning & Conditional Heteroscedasticity in Asset Returns; Modelling & Measuring the Sovereign Borrowers Option to Default; Success & Failure of Technical Analysis in the Cocoa Futures Market; When Nonrandomness Appears Random: A Challenge to Financial Economics; Finite sample properties of tests for STGARCH models & application to the US stock returns; A Statistical Test of Chaotic Purchasing Power Parity Dynamics; A methodology for the identification of trading patterns; Technical rules based on nearest-neighbour predictions optimised by genetic algorithms: Evidence from the Madrid stock market; Modern Analysis of Fluctuations in Financial Time Series & Beyond; Synchronicity between macroeconomic time series; Contagion Between the Financial Sphere & the Real Economy. Parametric & non Parametric Tools: A Comparison; A Macrodynamic Model of Real-Financial Interaction: Implications of budget equations & capital accumulation; Modelling Benchmark Government Bonds Volatility: Do Swaption Rates Help?; Nonlinear Cointegration using Lyapunov Stability Theory; Active Portfolio Management: The Power of the Treynor-Black Model; Stock price Clustering & Discreteness: The Compass Rose & Complex Dynamics; Index.