LEADER 07827nam 2200589 a 450 001 9910971112703321 005 20251116181929.0 010 $a1-61324-765-6 035 $a(CKB)2550000001044207 035 $a(EBL)3022152 035 $a(SSID)ssj0000860672 035 $a(PQKBManifestationID)12391420 035 $a(PQKBTitleCode)TC0000860672 035 $a(PQKBWorkID)10898042 035 $a(PQKB)10885221 035 $a(MiAaPQ)EBC3022152 035 $a(Au-PeEL)EBL3022152 035 $a(CaPaEBR)ebr10687809 035 $a(OCoLC)923667982 035 $a(BIP)33090358 035 $a(EXLCZ)992550000001044207 100 $a20101126d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aProgress in financial markets research /$fCatherine Kyrtsou and Costas Vorlow, editors 205 $a1st ed. 210 $aHauppauge, N.Y. $cNova Science Publishers$dc2012 215 $a1 online resource (370 p.) 225 1 $aFinancial institutions and services 300 $aDescription based upon print version of record. 311 08$a1-61122-864-6 320 $aIncludes bibliographical references and index. 327 $aIntro -- PROGRESS IN FINANCIAL MARKETS RESEARCH -- PROGRESS IN FINANCIAL MARKETS RESEARCH -- LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA -- CONTENTS -- EDITORIAL INTRODUCTION -- Chapter 1: LEARNING AND CONDITIONAL HETEROSCEDASTICITY IN ASSET RETURNS -- 1.1. Introduction -- 1.2. GARCH in the Linear Regression Model -- 1.3. A Model of Asset Pricing and Learning -- 1.4. The Covariance Structure of the Residuals -- 1.5. Finite Sample Properties -- 1.6. An Empirical Example -- Conclusion -- References -- Chapter 2: MODELLING AND MEASURING THE SOVEREIGN BORROWER'S OPTION TO DEFAULT -- 2.1. Introduction -- 2.2. Modeling Country Risk -- 2.3. Implementation -- Conclusion -- References -- Chapter 3: SUCCESS AND FAILURE OF TECHNICAL ANALYSIS IN THE COCOA FUTURES MARKET -- 3.1. Introduction -- 3.2. Forecasting Techniques in Technical Analysis -- 3.3. From Technical Forecasting Rule to Technical Trading Strategy -- 3.4. Effectiveness of Technical Analysis: Standard Statistical Tests -- 3.5. Effectiveness of Technical Analysis: The Bootstrap Method -- 3.6. Success and Failure of Technical Analysis -- 3.7. Concluding Remarks -- Appendix -- References -- Chapter 4: WHEN NONRANDOMNESS APPEARS RANDOM: A CHALLENGE TO FINANCIAL ECONOMICS -- 4.1. Introduction -- 4.2. Deterministic versus Random Models -- 4.3. The Lorenz Equations -- 4.4. The Experiment -- Evaluation and Conclusion -- References -- Chapter 5: FINITE SAMPLE PROPERTIES OF TESTS FOR STGARCH MODELS AND APPLICATION TO THE US STOCK RETURNS -- 5.1. Introduction -- 5.2. STGARCH Models and Test Statistics -- 5.3. Monte Carlo Experiment -- 5.4. An Application to the US Stock Returns -- Concluding Remarks -- References -- Chapter 6: A STATISTICAL TEST OF CHAOTIC PURCHASING POWER PARITY DYNAMICS -- 6.1. Introduction -- 6.2. PPP and the Real Exchange Rate -- 6.3. A Statistical Test for Chaos. 327 $a6.4. Data and Results -- 6.5. Robustness -- 6.6. Conclusion -- References -- Chapter 7: A METHODOLOGY FOR THE IDENTIFICATION OF TRADING PATTERNS -- 7.1. Introduction -- 7.2. Methodology -- 7.3. Application to the Dow Jones Index Closing Values -- 7.4. Application to the Pound-dollar Exchange Rate Series -- Conclusion -- References -- Chapter 8: TECHNICAL RULES BASEDON NEAREST-NEIGHBOUR PREDICTIONS OPTIMISED BY GENETIC ALGORITHMS: EVIDENCE FROM THE MADRID STOCK MARKET -- 8.1. Introduction -- 8.2. KNN Predictions -- 8.3. Trading Rules -- 8.4. Optimization of Technical Rules by Genetic Algorithms -- 8.5. Empirical Results -- Conclusion -- References -- Chapter 9: MODERN ANALYSIS OF FLUCTUATIONSIN FINANCIAL TIME SERIES AND BEYOND -- 9.1. Introduction -- 9.2. Why Wavelets? -- 9.3. The Wavelet y -- 9.4. The H¨older Exponent -- 9.5. Multifractal Formalism on the WTMM Tree -- 9.6. Estimation of the Local, Effective H¨older Exponent Using the Multiplicative Cascade Model -- 9.7. Employing the Local Effective H¨older Exponent in the Characterisation of Time Series -- 9.8. Breaking with the Universality Picture: Reasoning from Non-stationarity -- 9.9. Discovering Structure Through the Analysis of Collective Properties of Non-stationary Behaviour -- Conclusion -- References -- Chapter 10: SYNCHRONICITY BETWEEN MACROECONOMIC TIME SERIES -- 10.1. Introduction -- 10.2. Cointegration Testing Using the Ranges -- References -- Chapter 11: CONTAGION BETWEEN THE FINANCIAL SPHERE AND THE REAL ECONOMY. PARAMETRIC AND NON PARAMETRIC TOOLS: A COMPARISON -- 11.1. Introduction -- 11.2. Contagion's Concept -- 11.3. Parametric Models -- 11.4. Non Parametric Framework -- 11.5. Applications -- 11.6. Conclusion -- References -- Chapter 12: A MACRODYNAMIC MODEL OF REAL-FINANCIAL INTERACTION: IMPLICATIONS OF BUDGET EQUATIONS AND CAPITAL ACCUMULATION -- 12.1. Introduction. 327 $a12.2. The Blanchard (1981) Model with Intrinsic Stock-flow Dynamics -- 12.3. Intensive Form of the Model -- 12.4. Analysis -- 12.5. Outlook: Jump-variable Conundrum vs. Global Boundedness through Switching Phase Diagrams in the Real-financial Interaction -- 12.6. Appendix: Adding the Dynamics of the Government Budget Constraint -- References -- Chapter 13: MODELLING BENCHMARK GOVERNMENT BONDS VOLATILITY: DO SWAPTION RATES HELP? -- 13.1. Introduction -- 13.2. Literature Review -- 13.3. Bond Return and Bond Volatility Data -- 13.4. Volatility and Benchmark Models -- 13.5. The AR(p) Time Series and 'Mixed' Models -- 13.6. The Out-of-Sample Estimation Results -- Conclusion -- Appendix 1: Historical and Implied 10-Year Volatilites -- Appendix 2: Out-Of-Sample Forecasting Accuracy (SimpleModels) -- Appendix 3: Out-Of-Sample Forecasting Accuracy ('Mixed'Models) -- References -- Chapter 14: NONLINEAR COINTEGRATION USING LYAPUNOV STABILITY THEORY -- 14.1. Introduction -- 14.2. Methodology -- 14.3. Empirical Application -- Conclusions -- References -- Chapter 15: ACTIVE PORTFOLIO MANAGEMENT: THE POWER OF THE TREYNOR-BLACK MODEL -- 15.1. Introduction -- 15.2. The Treynor-Black Framework -- 15.3. The Forecast Database and Sampling Procedures -- 15.4. Estimation of Beta Coefficients and Realized Abnormal Returns -- 15.5. Calibration of Alpha Forecasts -- 15.6. Out-of-Sample Test Procedures -- 15.7. Portfolio Performance Evaluation -- Summary and Conclusions -- References -- Chapter 16: STOCK PRICE CLUSTERING AND DISCRETENESS: THE "COMPASS ROSE" AND COMPLEX DYNAMICS -- 16.1. Introduction -- 16.2. The Compass Rose in Scientific Literature -- 16.3. Methodology and Results -- 16.4. Conclusion and Future Research -- References -- INDEX. 330 $aNumerous empirical studies have analysed the identification and nature of the underlying process of an economic system, as well as the influence of information on financial time series. The standard financial theory of efficient markets assumes identical investors having rational expectations of future stock prices. This means that there are no opportunities for speculative profit, and both trading volume and price volatility are not serially correlated. This book presents information on financial markets and covers topics such as time series and asset pricing methods, data mining, non-linear analysis, chaos and wavelet-based techniques. 410 0$aFinancial institutions and services. 606 $aFinance$xResearch 615 0$aFinance$xResearch. 676 $a332.072 701 $aKyrtsou$b Catherine$01867346 701 $aVorlow$b Costas$01867347 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910971112703321 996 $aProgress in financial markets research$94474835 997 $aUNINA