05047nam 2200673 450 991082116130332120230808192424.01-118-59340-5(CKB)3710000000635590(EBL)4462505(SSID)ssj0001639810(PQKBManifestationID)16399345(PQKBTitleCode)TC0001639810(PQKBWorkID)14875710(PQKB)11716866(MiAaPQ)EBC4462505(DLC) 2016000501(Au-PeEL)EBL4462505(CaPaEBR)ebr11189903(CaONFJC)MIL909394(OCoLC)934101877(EXLCZ)99371000000063559020151130h20162016 uy| 0engur|n|---|||||txtccrHandbook of high-frequency trading and modeling in finance /edited by Ionut Florescu, Maria C. Mariani, H. Eugene Stanley, Frederi G. ViensHoboken, New Jersey :John Wiley & Sons, Incorporated,[2016]©20161 online resource (455 p.)Wiley handbooks in financial engineering and econometricsIncludes index.1-118-59348-0 1-118-44398-5 Includes bibliographical references and index.Handbook of High-Frequency Trading and Modeling in Finance; Contents; Notes on Contributors; Editors; List of Contributors; Preface; 1 Trends and Trades; 1.1 Introduction; 1.2 A trend-based trading strategy; 1.2.1 signaling and trends; 1.2.2 gain over a subperiod; 1.3 CUSUM timing; 1.3.1 cusum process and stopping time; 1.3.2 a cusum timing scheme; 1.3.3 us treasury notes, cusum timing; 1.4 Example: Random walk on ticks; 1.4.1 random walk expected gain over a subperiod; 1.4.2 simple random walk, CUSUM timing; 1.4.3 lazy simple random walk, cusum timing; 1.5 CUSUM strategy Monte Carlo1.6 The effect of the threshold parameter1.7 Conclusions and future work; Appendix: Tables; References; 2 Gaussian Inequalities and Tranche Sensitivities; 2.1 Introduction; 2.2 The tranche loss function; 2.3 A sensitivity identity; 2.4 Correlation sensitivities; Acknowledgment; References; 3 A Nonlinear Lead Lag Dependence Analysis of Energy Futures: Oil, Coal, and Natural Gas; 3.1 Introduction; 3.1.1 causality analysis; 3.2 Data; 3.3 Estimation techniques; 3.4 Results; 3.5 Discussion; 3.6 Conclusions; Acknowledgments; References; 4 Portfolio Optimization: Applications in Quantum Computing4.1 Introduction4.2 Background; 4.2.1 Portfolios And Optimization; 4.2.2 Algorithmic Complexity; 4.2.3 Performance; 4.2.4 Ising Model; 4.2.5 Adiabatic Quantum Computing; 4.3 The models; 4.3.1 Financial Model; 4.3.2 Graph-Theoretic Combinatorial Optimization Models; 4.3.3 Ising And Qubo Models; 4.3.4 Mixed Models; 4.4 Methods; 4.4.1 Model Implementation; 4.4.2 Input Data; 4.4.3 Mean-Variance Calculations; 4.4.4 Implementing The Risk Measure; 4.4.5 Implementation Mapping; 4.5 Results; 4.5.1 The Simple Correlation Model; 4.5.2 The Restricted Minimum-Risk Model4.5.3 The WMIS Minimum-Risk, Max Return Model4.6 Discussion; 4.6.1 Hardware Limitations; 4.6.2 Model Limitations; 4.6.3 Implementation Limitations; 4.6.4 Future Research; 4.7 Conclusion; Acknowledgments; Appendix 4.A: WMIS Matlab Code; References; 5 Estimation Procedure for Regime Switching Stochastic Volatility Model and Its Applications; 5.1 Introduction; 5.1.1 the original motivation; 5.1.2 the model and the problem; 5.1.3 a brief historical note; 5.2 The methodology; 5.2.1 obtaining filtered empirical distributions at ; 5.2.2 obtaining the parameters of the markov chain5.3 Results obtained applying the model to real data5.3.1 part i: financial applications; 5.3.2 part ii: physical data application. temperature data; 5.3.3 part iii: analysis of seismometer readings during an earthquake; 5.3.4 analysis of the earthquake signal: beginning; 5.3.5 analysis: during the earthquake; 5.3.6 analysis: end of the earthquake signal, aftershocks; 5.4 Conclusion; Appendix 5.A:Theoretical results and empirical testing; 5.A.1 how does the particle filter work?; 5.A.2 theoretical results about convergence and parameter estimates; 5.A.3 markov chain parameter estimates5.A.4 empirical testingWiley handbooks in financial engineering and econometrics.Investment analysisMathematical modelsInvestmentsMathematical modelsFinanceMathematical modelsInvestment analysisMathematical models.InvestmentsMathematical models.FinanceMathematical models.332.64/20285Florescu Ionuţ1973-MiAaPQMiAaPQMiAaPQBOOK9910821161303321Handbook of high-frequency trading and modeling in finance3968928UNINA