Essays In Forecasting Financial Markets With Predictive Analytics Techniques
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Essays In Forecasting Financial Markets With Predictive Analytics Techniques
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Author :
language : en
Publisher:
Release Date : 2018
Essays In Forecasting Financial Markets With Predictive Analytics Techniques written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Essays In Forecasting Financial Markets With Predictive Analytics Techniques
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Author : Azzam J. M. A. H. Alroomi
language : en
Publisher:
Release Date : 2018
Essays In Forecasting Financial Markets With Predictive Analytics Techniques written by Azzam J. M. A. H. Alroomi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Essays In Forecasting Financial Markets With Predictive Analytics Techniques
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Author : Azzam Alroomi
language : en
Publisher:
Release Date : 2018
Essays In Forecasting Financial Markets With Predictive Analytics Techniques written by Azzam Alroomi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
This PhD dissertation comprises four essays on forecasting financial markets with unsupervised predictive analytics techniques, most notably time series extrapolation methods and artificial neural networks. Key objectives of the research were reproducibility and replicability, which are fundamental principles in management science and, as such, the implementation of all of the suggested algorithms has been fully automated and completely unsupervised in R.As with any predictive analytics exercise, computational intensiveness is a significant challenge and criterion of performance and, thus, both forecasting accuracy and uncertainty as well as computational times are reported in all essays. Multiple horizons, multiple methods and benchmarks and multiple metrics are employed as dictated by good practice in empirical forecasting exercises.The essays evolve in nature as each one is based on the previous one, testing one more condition as the essays progress, outlined in sequence as follows: which method wins overall in a very extensive evaluation over five frequencies (yearly, quarterly, monthly, weekly and daily data) over 18 time series of stocks with the biggest capitalization from the FTSE 100, over the last 20 years (first essay); the impact of horizon in this exercise and how this promotes different winners for different horizons (second essay); the impact of using uncertainty in the form of maximum-minimum values per period, despite still being interested in forecasting the mean expected value over the next period; and introducing a second variable capturing all other aspects of the behavioural nature of the financial environment - the trading volume - and evaluating whether this improves forecasting performance or not.The whole endeavour required the use of the High Performance Computing Wales (HPC Wales) for a significant amount of time, incurring computational costs that ultimately paid off in terms of increased forecasting accuracy for the AI approaches; the whole exercise for one series can be repeated on a fast laptop device (i7 with 16 GB of memory).Overall (forecasting) horses for (data) courses were once again proved to perform best, and the fact that one method cannot win under all conditions was once more evidenced. The introduction of uncertainty (in terms of range for every period), as well as volume as a second variable capturing environmental aspects, was beneficial with regard to forecasting accuracy and, overall, the research provided empirical evidence that predictive analytics approaches have a future in such a forecasting context.Given this was a predictive analytics exercise, focus was placed on forecasting levels (monetary values) and not log-returns; and out-of-sample forecasting accuracy, rather than causality, was a primary objective, thus multiple regression models were not considered as benchmarks.As in any empirical predicting analytics exercise, more time series, more artificial intelligence methods, more metrics and more data can be employed so as to allow for full generalization of the results, as long as all of these can be fully automated and forecast unsupervised in a freeware environment - in this thesis that being R.
Forecasting Financial Markets
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Author : Tony Plummer
language : en
Publisher:
Release Date : 1990
Forecasting Financial Markets written by Tony Plummer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Business & Economics categories.
Takes the mystery out of financial markets by providing a straightforward analytical framework for trading. Offers a unifying rationale for technical analysis of markets, making it more of a ``science'' than ever before. Begins with a discussion of how emotional elements permeate economic and financial behaviors and how forecasters can remain independent from such behavior. The more reliable theories of natural systems and price pulse--continuously recurring price patterns--are introduced and examined in detail. The author shows analysts how to use these techniques to forecast price movement profile, extent, and timing of reversals, putting investors on the road to trading with minimum risk and maximum success.
Forecasting Financial Markets Using Neural Networks
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Author : Jason Kutsurelis
language : en
Publisher:
Release Date : 1998-09-01
Forecasting Financial Markets Using Neural Networks written by Jason Kutsurelis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-09-01 with categories.
This research examines and analyzes the use of neural networks as a forecasting tool. Specifically a neural network's ability to predict future trends of Stock Market Indices is tested. Accuracy is compared against a traditional forecasting method, multiple linear regression analysis. Finally, the probability of the model's forecast being correct is calculated using conditional probabilities. While only briefly discussing neural network theory, this research determines the feasibility and practicality of using neural networks as a forecasting tool for the individual investor. This study builds upon the work done by Edward Gately in his book Neural Networks for Financial Forecasting. This research validates the work of Gately and describes the development of a neural network that achieved a 93.3 percent probability of predicting a market rise, and an 88.07 percent probability of predicting a market drop in the S&P500. It was concluded that neural networks do have the capability to forecast financial markets and, if properly trained, the individual investor could benefit from the use of this forecasting tool.
Forecasting Volatility In The Financial Markets
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Author : John L. Knight
language : en
Publisher: Butterworth-Heinemann
Release Date : 2002
Forecasting Volatility In The Financial Markets written by John L. Knight and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Business & Economics categories.
This text assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting edge modeling and forecasting techniques. It then uses a technical survey to explain the different ways to measure risk and define the different models of volatility and return.
Forecasting Expected Returns In The Financial Markets
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Author : Stephen Satchell
language : en
Publisher: Elsevier
Release Date : 2011-04-08
Forecasting Expected Returns In The Financial Markets written by Stephen Satchell and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-08 with Business & Economics categories.
Forecasting returns is as important as forecasting volatility in multiple areas of finance. This topic, essential to practitioners, is also studied by academics. In this new book, Dr Stephen Satchell brings together a collection of leading thinkers and practitioners from around the world who address this complex problem using the latest quantitative techniques. *Forecasting expected returns is an essential aspect of finance and highly technical *The first collection of papers to present new and developing techniques *International authors present both academic and practitioner perspectives
Trend Forecasting With Intermarket Analysis
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Author : Louis B. Mendelsohn
language : en
Publisher: John Wiley & Sons
Release Date : 2012-10-15
Trend Forecasting With Intermarket Analysis written by Louis B. Mendelsohn and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-15 with Business & Economics categories.
In this groundbreaking new edition, Mendelsohn gives you the weapon to conquer the limitations of traditional technical trading-intermarket analysis. To compete in today's rapidly changing economy, you need a method that can identify reoccurring patterns within individual financial markets and between related global markets. You need tools that lead, not lag. Step by step, Mendelsohn shows how combining technical, fundamental, and intermarket analysis into one powerful framework can give you an early edge to accurately forecasting trends. Inside, you'll discover: Precise trading strategies that can be used by both day traders and position traders. The limitations of traditional technical analysis methods-and how to overcome them. How neural network computational modeling can create leading, not lagging, moving averages for more accurate forecasting. Innovative, quantitative trend forecasting indicators at the cutting edge of market analysis. PLUS-an introduction to VantagePoint Software, which makes Mendelsohn's "new economy" trading methods work simply-and effectively. This software applies the pattern recognition capabilities of advanced neural networks to analyze intermarket data on literally hundreds of global financial markets each day.
Essays On Forecasting Financial Markets Using Decomposition Constraints And Extreme Learning Machines
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Author : Zhou Xi
language : en
Publisher:
Release Date : 2013
Essays On Forecasting Financial Markets Using Decomposition Constraints And Extreme Learning Machines written by Zhou Xi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Density functionals categories.
Chapter 1 and 2 discuss how to use a decomposition model to make a density forecast of the financial return and how to improve this density forecast by imposing matching moment constraints. The density forecast model is based on a decomposition of financial returns into the absolute return and the sign of the return. We also use the maximum entropy principle for the out-of-sample density forecast subject to the constraint that matches the mean forecasts from the decomposition model and a simple regression model. In Chapter 1 (joint with Professor Tea-Hwy Lee), We show that when the mean forecast from the decomposition model deviates from that of the mean return, imposing the matching mean forecast constraint will tilt the density forecast of the decomposition model and improve over the density forecast of the original decomposition model. In Chapter 2 (joint with Professor Tae-Hwy Lee and Ru Zhang), we further improve the decomposition model by using dependent copula functions, and we show that the risk forecast produced by the decomposition density forecast model is superior to RiskMetrics in terms of giving higher coverage probability and lower predictive quanitle loss in extreme events of large loss for monthly returns.
Financial Forecasting Tools And Techniques For Stability
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Author : George Wilton
language : en
Publisher: Az Boek
Release Date : 2024-04-27
Financial Forecasting Tools And Techniques For Stability written by George Wilton and has been published by Az Boek this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-27 with Social Science categories.