Real Time Detection Of Turning Points In Financial Time Series

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Real Time Detection of Turning Points in Financial Time Series

Author : Ueli Hartmann
Publisher : GRIN Verlag
ISBN 13 : 365639623X
Total Pages : 176 pages
Book Rating : 4.6/5 (563 download)

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Book Synopsis Real Time Detection of Turning Points in Financial Time Series by : Ueli Hartmann

Download or read book Real Time Detection of Turning Points in Financial Time Series written by Ueli Hartmann and published by GRIN Verlag. This book was released on 2013-03-22 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research Paper (undergraduate) from the year 2012 in the subject Mathematics - Applied Mathematics, grade: 5.5, ZHAW Zürcher Hochschule für Angewandte Wissenschaften, language: English, abstract: As a consequence of the recent financial crisis, institutions are increasingly interested in identifying turning points in financial time series. The accurate and early identification of these turning points can result in the optimal exploitation of the invested capital and profit maximization. Most existing methods for the real-time identification of turning points have proved unreliable and therefore the need to develop a cutting-edge model. The DFA methodology of Prof. Dr. Marc Wildi is one promising real-time procedure that seeks to solve this problem. The purpose of this thesis is the evaluation and comparison of different variants of the DFA procedure in order to find a method for the effective identification of turning points in important financial time series, such as the S\&P 500 and the EUROSTOXX 50 and their implied volatility indices (VIX and VSTOXX, resp.). Further, this thesis aims to develop a suitable investment strategy based on the obtained results. For the purpose of this thesis, the time series mentioned above were analyzed between the years 1990 and 2011, using the last year as out-of-sample data. Frequential analysis using Fourier transforms as well as different variants of the DFA-algorithm were applied in order to identify the desired turning points. The results obtained from these analyses of the S\&P 500 and EUROSTOXX 50 time series show a considerable out-of-sample investment return which verifies the validity of the model. On a second level of analysis, using the implied volatility indices it was possible to generalize the model and thereby verify the initial results. Moreover, with the help of the development of further investment strategies it was possible to normalize profit returns, maintaining a semi-constant growth, which is usually preferred by financial institutions. Finally, given the structural similarities of the two main financial series examined, whose clear profile was only observable using the DFA system, it was possible to combine both time series using the daily exchange rate as a cyclical and structural catalyst, thus achieving a deeper thrust of the model. This all was possible by highlighting the flexibility of the DFA model for real-time analysis of financial time series and its practical application as a tool for investment analysis. Therefore, the DFA Modell enables an accurate real-time identification of tuning points in financial series.

Detection of Financial Time Series Turning Points

Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (223 download)

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Book Synopsis Detection of Financial Time Series Turning Points by :

Download or read book Detection of Financial Time Series Turning Points written by and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Turning Points and Classification

Author : Jeremy Piger
Publisher :
ISBN 13 :
Total Pages : 40 pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Turning Points and Classification by : Jeremy Piger

Download or read book Turning Points and Classification written by Jeremy Piger and published by . This book was released on 2019 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic time-series data is commonly categorized into a discrete number of persistent regimes. I survey a variety of approaches for real-time prediction of these regimes and the turning points between them, where these predictions are formed in a data-rich environment. I place particular emphasis on supervised machine learning classification techniques that are common to the statistical classification literature, but have only recently begun to be widely used in economics. I also survey Markov-switching models, which are commonly used for unsupervised classification of economic data. The approaches surveyed are computationally feasible when applied to large datasets, and the machine learning algorithms employ regularization and cross-validation to prevent overfitting in the face of many predictors. A subset of the approaches conduct model selection automatically in forming predictions. I present an application to real-time identification of U.S. business cycle turning points based on a wide dataset of 136 macroeconomic and financial time-series.

The Detection of Turning-points in "noisy" Time-series (with Particular Reference to Share-price Time-series)

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Author : David John Smith
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (643 download)

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Book Synopsis The Detection of Turning-points in "noisy" Time-series (with Particular Reference to Share-price Time-series) by : David John Smith

Download or read book The Detection of Turning-points in "noisy" Time-series (with Particular Reference to Share-price Time-series) written by David John Smith and published by . This book was released on 1984 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Estimating Turning Points Using Large Data Sets

Author : James H. Stock
Publisher :
ISBN 13 :
Total Pages : 46 pages
Book Rating : 4.:/5 (682 download)

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Book Synopsis Estimating Turning Points Using Large Data Sets by : James H. Stock

Download or read book Estimating Turning Points Using Large Data Sets written by James H. Stock and published by . This book was released on 2010 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Dating business cycles entails ascertaining economy-wide turning points. Broadly speaking, there are two approaches in the literature. The first approach, which dates to Burns and Mitchell (1946), is to identify turning points individually in a large number of series, then to look for a common date that could be called an aggregate turning point. The second approach, which has been the focus of more recent academic and applied work, is to look for turning points in a few, or just one, aggregate. This paper examines these two approaches to the identification of turning points. We provide a nonparametric definition of a turning point (an estimand) based on a population of time series. This leads to estimators of turning points, sampling distributions, and standard errors for turning points based on a sample of series. We consider both simple random sampling and stratified sampling. The empirical part of the analysis is based on a data set of 270 disaggregated monthly real economic time series for the U.S., 1959-2010

Analysis of Financial Time Series

Author : Ruey S. Tsay
Publisher : Wiley
ISBN 13 : 0470644559
Total Pages : 712 pages
Book Rating : 4.4/5 (76 download)

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Book Synopsis Analysis of Financial Time Series by : Ruey S. Tsay

Download or read book Analysis of Financial Time Series written by Ruey S. Tsay and published by Wiley. This book was released on 2010-07-16 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: Analysis and application of univariate financial time series The return series of multiple assets Bayesian inference in finance methods Key features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.

Turning Points in Economic Time Series, Loss Structures and Bayesian Forecasting

Author : Arnold Zellner
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (753 download)

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Book Synopsis Turning Points in Economic Time Series, Loss Structures and Bayesian Forecasting by : Arnold Zellner

Download or read book Turning Points in Economic Time Series, Loss Structures and Bayesian Forecasting written by Arnold Zellner and published by . This book was released on 1988 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation

Author : Estela Bee Dagum
Publisher : Springer
ISBN 13 : 3319318225
Total Pages : 293 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation by : Estela Bee Dagum

Download or read book Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation written by Estela Bee Dagum and published by Springer. This book was released on 2016-06-20 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.

The Recent Advances in Transdisciplinary Data Science

Author : Henry Han
Publisher : Springer Nature
ISBN 13 : 3031233875
Total Pages : 234 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis The Recent Advances in Transdisciplinary Data Science by : Henry Han

Download or read book The Recent Advances in Transdisciplinary Data Science written by Henry Han and published by Springer Nature. This book was released on 2023-01-28 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First Southwest Data Science Conference, on The Recent Advances in Transdisciplinary Data Science, SDSC 2022, held in Waco, TX, USA, during March 25–26, 2022. The 14 full papers and 2 short papers included in this book were carefully reviewed and selected from 72 submissions. They were organized in topical sections as follows: Business and social data science; Health and biological data science; Applied data science, artificial intelligence, and data engineering.

An Experiment with Turning Point Forecasts Using Hong Kong Time Series Data

Author : Kwai-lin Leung
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (52 download)

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Book Synopsis An Experiment with Turning Point Forecasts Using Hong Kong Time Series Data by : Kwai-lin Leung

Download or read book An Experiment with Turning Point Forecasts Using Hong Kong Time Series Data written by Kwai-lin Leung and published by . This book was released on 1989 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Analysis of Financial Time Series

Author : Ruey S. Tsay
Publisher : Wiley-Interscience
ISBN 13 : 9780471415442
Total Pages : 472 pages
Book Rating : 4.4/5 (154 download)

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Book Synopsis Analysis of Financial Time Series by : Ruey S. Tsay

Download or read book Analysis of Financial Time Series written by Ruey S. Tsay and published by Wiley-Interscience. This book was released on 2001-11-01 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamental topics and new methods in time series analysis Analysis of Financial Time Series provides a comprehensive and systematic introduction to financial econometric models and their application to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: analysis and application of univariate financial time series; the return series of multiple assets; and Bayesian inference in finance methods. Timely topics and recent results include: Value at Risk (VaR) High-frequency financial data analysis Markov Chain Monte Carlo (MCMC) methods Derivative pricing using jump diffusion with closed-form formulas VaR calculation using extreme value theory based on a non-homogeneous two-dimensional Poisson process Multivariate volatility models with time-varying correlations Ideal as a fundamental introduction to time series for MBA students or as a reference for researchers and practitioners in business and finance, Analysis of Financial Time Series offers an in-depth and up-to-date account of these vital methods.

SAS for Forecasting Time Series, Third Edition

Author : John C. Brocklebank, Ph.D.
Publisher : SAS Institute
ISBN 13 : 1629605441
Total Pages : 384 pages
Book Rating : 4.6/5 (296 download)

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Book Synopsis SAS for Forecasting Time Series, Third Edition by : John C. Brocklebank, Ph.D.

Download or read book SAS for Forecasting Time Series, Third Edition written by John C. Brocklebank, Ph.D. and published by SAS Institute. This book was released on 2018-03-14 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject. With this third edition of SAS for Forecasting Time Series, intermediate-to-advanced SAS users—such as statisticians, economists, and data scientists—can now match the most sophisticated forecasting methods to the most current SAS applications. Starting with fundamentals, this new edition presents methods for modeling both univariate and multivariate data taken over time. From the well-known ARIMA models to unobserved components, methods that span the range from simple to complex are discussed and illustrated. Many of the newer methods are variations on the basic ARIMA structures. Completely updated, this new edition includes fresh, interesting business situations and data sets, and new sections on these up-to-date statistical methods: ARIMA models Vector autoregressive models Exponential smoothing models Unobserved component and state-space models Seasonal adjustment Spectral analysis Focusing on application, this guide teaches a wide range of forecasting techniques by example. The examples provide the statistical underpinnings necessary to put the methods into practice. The following up-to-date SAS applications are covered in this edition: The ARIMA procedure The AUTOREG procedure The VARMAX procedure The ESM procedure The UCM and SSM procedures The X13 procedure The SPECTRA procedure SAS Forecast Studio Each SAS application is presented with explanation of its strengths, weaknesses, and best uses. Even users of automated forecasting systems will benefit from this knowledge of what is done and why. Moreover, the accompanying examples can serve as templates that you easily adjust to fit your specific forecasting needs. This book is part of the SAS Press program.

Selfsimilar Processes

Author : Paul Embrechts
Publisher : Princeton University Press
ISBN 13 : 1400825105
Total Pages : 125 pages
Book Rating : 4.4/5 (8 download)

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Book Synopsis Selfsimilar Processes by : Paul Embrechts

Download or read book Selfsimilar Processes written by Paul Embrechts and published by Princeton University Press. This book was released on 2009-01-10 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: The modeling of stochastic dependence is fundamental for understanding random systems evolving in time. When measured through linear correlation, many of these systems exhibit a slow correlation decay--a phenomenon often referred to as long-memory or long-range dependence. An example of this is the absolute returns of equity data in finance. Selfsimilar stochastic processes (particularly fractional Brownian motion) have long been postulated as a means to model this behavior, and the concept of selfsimilarity for a stochastic process is now proving to be extraordinarily useful. Selfsimilarity translates into the equality in distribution between the process under a linear time change and the same process properly scaled in space, a simple scaling property that yields a remarkably rich theory with far-flung applications. After a short historical overview, this book describes the current state of knowledge about selfsimilar processes and their applications. Concepts, definitions and basic properties are emphasized, giving the reader a road map of the realm of selfsimilarity that allows for further exploration. Such topics as noncentral limit theory, long-range dependence, and operator selfsimilarity are covered alongside statistical estimation, simulation, sample path properties, and stochastic differential equations driven by selfsimilar processes. Numerous references point the reader to current applications. Though the text uses the mathematical language of the theory of stochastic processes, researchers and end-users from such diverse fields as mathematics, physics, biology, telecommunications, finance, econometrics, and environmental science will find it an ideal entry point for studying the already extensive theory and applications of selfsimilarity.

Long/Short Market Dynamics

Author : Clive M. Corcoran
Publisher : John Wiley & Sons
ISBN 13 : 0470065311
Total Pages : 358 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Long/Short Market Dynamics by : Clive M. Corcoran

Download or read book Long/Short Market Dynamics written by Clive M. Corcoran and published by John Wiley & Sons. This book was released on 2007-02-06 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hedge funds are now the largest volume players in the capital markets. They follow a wide assortment of strategies but their activities have replaced and overshadowed the traditional model of the long only portfolio manager. Many of the traditional technical indicators and commonly accepted trading strategies have become obsolete or ineffective. The focus throughout the book is to describe the principal innovations that have been made within the equity markets over the last several years and that have changed the ground rules for trading activities. By understanding these changes the active trader is far better equipped to profit in today’s more complex and risky markets. Long/Short Market Dynamics includes: A completely new technique, Comparative Quantiles Analysis, for identifying market turning points is introduced. It is based on statistical techniques that can be used to recognize money flow and price/momentum divergences that can provide substantial profit opportunities. Power laws, regime shifts, self-organized criticality, phase transitions, network dynamics, econophysics, algorithmic trading and other ideas from the science of complexity are examined. All are described as concretely as possible and avoiding unnecessary mathematics and formalism. Alpha generation, portfolio construction, hedge ratios, and beta neutral portfolios are illustrated with case studies and worked examples. Episodes of financial contagion are illustrated with a proposed explanation of their origins within underlying market dynamics

Economic Forecasting and Policy

Author : N. Carnot
Publisher : Springer
ISBN 13 : 0230306446
Total Pages : 516 pages
Book Rating : 4.2/5 (33 download)

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Book Synopsis Economic Forecasting and Policy by : N. Carnot

Download or read book Economic Forecasting and Policy written by N. Carnot and published by Springer. This book was released on 2011-07-26 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic Forecasting provides a comprehensive overview of macroeconomic forecasting. The focus is first on a wide range of theories as well as empirical methods: business cycle analysis, time series methods, macroeconomic models, medium and long-run projections, fiscal and financial forecasts, and sectoral forecasting.

Introduction to Time Series and Forecasting

Author : Peter J. Brockwell
Publisher : Springer Science & Business Media
ISBN 13 : 1475725264
Total Pages : 429 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Introduction to Time Series and Forecasting by : Peter J. Brockwell

Download or read book Introduction to Time Series and Forecasting written by Peter J. Brockwell and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.

Analysis of Financial Time Series

Author : Ruey S. Tsay
Publisher : John Wiley & Sons
ISBN 13 : 1118017099
Total Pages : 724 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis Analysis of Financial Time Series by : Ruey S. Tsay

Download or read book Analysis of Financial Time Series written by Ruey S. Tsay and published by John Wiley & Sons. This book was released on 2010-10-26 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: Analysis and application of univariate financial time series The return series of multiple assets Bayesian inference in finance methods Key features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.