Stock Market Modeling And Forecasting

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Stock Market Modeling and Forecasting

Author : Xiaolian Zheng
Publisher : Springer
ISBN 13 : 1447151550
Total Pages : 166 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Stock Market Modeling and Forecasting by : Xiaolian Zheng

Download or read book Stock Market Modeling and Forecasting written by Xiaolian Zheng and published by Springer. This book was released on 2013-04-05 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stock Market Modeling and Forecasting translates experience in system adaptation gained in an engineering context to the modeling of financial markets with a view to improving the capture and understanding of market dynamics. The modeling process is considered as identifying a dynamic system in which a real stock market is treated as an unknown plant and the identification model proposed is tuned by feedback of the matching error. Like a physical system, a financial market exhibits fast and slow dynamics corresponding to external (such as company value and profitability) and internal forces (such as investor sentiment and commodity prices) respectively. The framework presented here, consisting of an internal model and an adaptive filter, is successful at considering both fast and slow market dynamics. A double selection method is efficacious in identifying input factors influential in market movements, revealing them to be both frequency- and market-dependent. The authors present work on both developed and developing markets in the shape of the US, Hong Kong, Chinese and Singaporean stock markets. Results from all these sources demonstrate the efficiency of the model framework in identifying significant influences and the quality of its predictive ability; promising results are also obtained by applying the model framework to the forecasting of major market-turning periods. Having shown that system-theoretic ideas can form the core of a novel and effective basis for stock market analysis, the book is completed by an indication of possible and likely future expansions of the research in this area.

Introduction to Financial Forecasting in Investment Analysis

Author : John B. Guerard, Jr.
Publisher : Springer Science & Business Media
ISBN 13 : 1461452392
Total Pages : 245 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Introduction to Financial Forecasting in Investment Analysis by : John B. Guerard, Jr.

Download or read book Introduction to Financial Forecasting in Investment Analysis written by John B. Guerard, Jr. and published by Springer Science & Business Media. This book was released on 2013-01-04 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting—the art and science of predicting future outcomes—has become a crucial skill in business and economic analysis. This volume introduces the reader to the tools, methods, and techniques of forecasting, specifically as they apply to financial and investing decisions. With an emphasis on "earnings per share" (eps), the author presents a data-oriented text on financial forecasting, understanding financial data, assessing firm financial strategies (such as share buybacks and R&D spending), creating efficient portfolios, and hedging stock portfolios with financial futures. The opening chapters explain how to understand economic fluctuations and how the stock market leads the general economic trend; introduce the concept of portfolio construction and how movements in the economy influence stock price movements; and introduce the reader to the forecasting process, including exponential smoothing and time series model estimations. Subsequent chapters examine the composite index of leading economic indicators (LEI); review financial statement analysis and mean-variance efficient portfolios; and assess the effectiveness of analysts’ earnings forecasts. Using data from such firms as Intel, General Electric, and Hitachi, Guerard demonstrates how forecasting tools can be applied to understand the business cycle, evaluate market risk, and demonstrate the impact of global stock selection modeling and portfolio construction.

Modeling and Forecasting Stock Market Prices with Sigmoidal Curves

Author : Daniel Tran
Publisher :
ISBN 13 : 9781369846188
Total Pages : 150 pages
Book Rating : 4.8/5 (461 download)

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Book Synopsis Modeling and Forecasting Stock Market Prices with Sigmoidal Curves by : Daniel Tran

Download or read book Modeling and Forecasting Stock Market Prices with Sigmoidal Curves written by Daniel Tran and published by . This book was released on 2017 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pricing stock market data is difficult because it is inherently noisy and prone to unexpected events. However, stock market data generally exhibits trends in the medium and long term. A typical successful stock index exhibits an initiation phase, rapid growth, and then saturation whereby the price plateaus. Sigmoidal curves can effectively model and forecast stock market data because it can represent nonlinear stock behavior within confidence interval bounds. This thesis surveys various members of the sigmoidal family of curves and determines which curves best fit stock market data. We explore several techniques to filter our data, such as the moving average, single exponential smoothing, and the Hodrick-Prescott filter. We fit the sigmoidal curves to raw data using the Levenberg-Marquardt algorithm. This thesis aggregates these analysis techniques and apply them towards gauging the opportune time point to sell stocks.

11th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions and Artificial Intelligence - ICSCCW-2021

Download 11th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions and Artificial Intelligence - ICSCCW-2021 PDF Online Free

Author : Rafik A. Aliev
Publisher : Springer Nature
ISBN 13 : 3030921271
Total Pages : 803 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis 11th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions and Artificial Intelligence - ICSCCW-2021 by : Rafik A. Aliev

Download or read book 11th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions and Artificial Intelligence - ICSCCW-2021 written by Rafik A. Aliev and published by Springer Nature. This book was released on 2022-01-04 with total page 803 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 11th Conference on Theory and Applications of Soft Computing, Computing with Words and Perceptions and Artificial Intelligence, ICSCCW-2021, held in Antalya, Turkey, on August 23–24, 2021. The general scope of the book covers uncertain computation, decision making under imperfect information, neuro-fuzzy approaches, natural language processing, and other areas. The topics of the papers include theory and application of soft computing, computing with words, image processing with soft computing, intelligent control, machine learning, fuzzy logic in data mining, soft computing in business, economics, engineering, material sciences, biomedical engineering, and health care. This book is a useful guide for academics, practitioners, and graduates in fields of soft computing and computing with words. It allows for increasing of interest in development and applying of these paradigms in various real-life fields.

Stock Market Prediction and Efficiency Analysis using Recurrent Neural Network

Author : Joish Bosco
Publisher : GRIN Verlag
ISBN 13 : 3668800456
Total Pages : 82 pages
Book Rating : 4.6/5 (688 download)

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Book Synopsis Stock Market Prediction and Efficiency Analysis using Recurrent Neural Network by : Joish Bosco

Download or read book Stock Market Prediction and Efficiency Analysis using Recurrent Neural Network written by Joish Bosco and published by GRIN Verlag. This book was released on 2018-09-18 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: Project Report from the year 2018 in the subject Computer Science - Technical Computer Science, , course: Computer Science, language: English, abstract: Modeling and Forecasting of the financial market have been an attractive topic to scholars and researchers from various academic fields. The financial market is an abstract concept where financial commodities such as stocks, bonds, and precious metals transactions happen between buyers and sellers. In the present scenario of the financial market world, especially in the stock market, forecasting the trend or the price of stocks using machine learning techniques and artificial neural networks are the most attractive issue to be investigated. As Giles explained, financial forecasting is an instance of signal processing problem which is difficult because of high noise, small sample size, non-stationary, and non-linearity. The noisy characteristics mean the incomplete information gap between past stock trading price and volume with a future price. The stock market is sensitive with the political and macroeconomic environment. However, these two kinds of information are too complex and unstable to gather. The above information that cannot be included in features are considered as noise. The sample size of financial data is determined by real-world transaction records. On one hand, a larger sample size refers a longer period of transaction records; on the other hand, large sample size increases the uncertainty of financial environment during the 2 sample period. In this project, we use stock data instead of daily data in order to reduce the probability of uncertain noise, and relatively increase the sample size within a certain period of time. By non-stationarity, one means that the distribution of stock data is various during time changing. Non-linearity implies that feature correlation of different individual stocks is various. Efficient Market Hypothesis was developed by Burton G. Malkiel in 1991.

Prediction of International Stock Market Movements Using a Statistical Time Series Analysis Method

Author : Jehan Shareef
Publisher :
ISBN 13 : 9780692498101
Total Pages : 112 pages
Book Rating : 4.4/5 (981 download)

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Book Synopsis Prediction of International Stock Market Movements Using a Statistical Time Series Analysis Method by : Jehan Shareef

Download or read book Prediction of International Stock Market Movements Using a Statistical Time Series Analysis Method written by Jehan Shareef and published by . This book was released on 2015-07-24 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Forecasting Volatility in the Financial Markets

Author : John L. Knight
Publisher : Butterworth-Heinemann
ISBN 13 : 9780750655156
Total Pages : 428 pages
Book Rating : 4.6/5 (551 download)

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Book Synopsis Forecasting Volatility in the Financial Markets by : John L. Knight

Download or read book Forecasting Volatility in the Financial Markets written by John L. Knight and published by Butterworth-Heinemann. This book was released on 2002 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Volatility in the Financial Markets

Author : Stephen Satchell
Publisher : Elsevier
ISBN 13 : 0080471420
Total Pages : 428 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Forecasting Volatility in the Financial Markets by : Stephen Satchell

Download or read book Forecasting Volatility in the Financial Markets written by Stephen Satchell and published by Elsevier. This book was released on 2011-02-24 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting Volatility in the Financial Markets, Third Edition 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 modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition:* What good is a volatility model? Engle and Patton* Applications for portfolio variety Dan diBartolomeo* A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish* Volatility modeling and forecasting in finance Xiao and Aydemir* An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey - Leading thinkers present newest research on volatility forecasting - International authors cover a broad array of subjects related to volatility forecasting - Assumes basic knowledge of volatility, financial mathematics, and modelling

Modeling and Forecasting Primary Commodity Prices

Author : Walter C. Labys
Publisher : Routledge
ISBN 13 : 1351917080
Total Pages : 247 pages
Book Rating : 4.3/5 (519 download)

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Book Synopsis Modeling and Forecasting Primary Commodity Prices by : Walter C. Labys

Download or read book Modeling and Forecasting Primary Commodity Prices written by Walter C. Labys and published by Routledge. This book was released on 2017-03-02 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent economic growth in China and other Asian countries has led to increased commodity demand which has caused price rises and accompanying price fluctuations not only for crude oil but also for the many other raw materials. Such trends mean that world commodity markets are once again under intense scrutiny. This book provides new insights into the modeling and forecasting of primary commodity prices by featuring comprehensive applications of the most recent methods of statistical time series analysis. The latter utilize econometric methods concerned with structural breaks, unobserved components, chaotic discovery, long memory, heteroskedasticity, wavelet estimation and fractional integration. Relevant tests employed include neural networks, correlation dimensions, Lyapunov exponents, fractional integration and rescaled range. The price forecasting involves structural time series trend plus cycle and cyclical trend models. Practical applications focus on the price behaviour of more than twenty international commodity markets.

A Practical Guide to Forecasting Financial Market Volatility

Author : Ser-Huang Poon
Publisher : John Wiley & Sons
ISBN 13 : 0470856157
Total Pages : 236 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis A Practical Guide to Forecasting Financial Market Volatility by : Ser-Huang Poon

Download or read book A Practical Guide to Forecasting Financial Market Volatility written by Ser-Huang Poon and published by John Wiley & Sons. This book was released on 2005-08-19 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.

Stock Price Predictions

Author : Azhar Ul Haque Sario
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.8/5 (521 download)

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Book Synopsis Stock Price Predictions by : Azhar Ul Haque Sario

Download or read book Stock Price Predictions written by Azhar Ul Haque Sario and published by Independently Published. This book was released on 2023-07-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Stock Price Predictions: An Introduction to Probabilistic Models" is a comprehensive guide that delves into the intricate world of stock market prediction models. This book is a treasure trove of knowledge for both novice and seasoned investors, providing detailed explanations of traditional and modern approaches used to predict stock prices. In the first part of the book, "Traditional Approaches, " the author examines the most commonly used techniques for estimating share prices, such as Fundamental Analysis, Technical Analysis, and Quantitative Analysis. It also delves into more specific methods like Sentiment Analysis, Time Series Analysis, and Machine Learning Algorithms, among others. Each method is meticulously explained, providing readers with a sound understanding of the strengths and limitations of each approach. The second part, "Understanding the World of Probability-Based Models," introduces readers to the realm of probability models, explaining their role and different types. It covers a wide range of models like ARIMA, GARCH, VAR, MGARCH, Stochastic Volatility Models, and many more. Each model is discussed in depth, with explanations of how they can be used to estimate future share prices. This section serves as an excellent resource for those seeking to expand their knowledge and skills in using probability-based models for stock price prediction. The final section, "Instances of Successful Forecasts Using Probability-Based Models," provides real-world examples of successful forecasts using these models. It includes well-known models like the Black-Scholes Model, Monte Carlo Simulations, Brownian Motion Model, ARIMA, and GARCH Model. The book concludes with a discussion on the success of more contemporary models like LSTM and Facebook's Prophet.

Modeling and Forecasting Electricity Loads and Prices

Author : Rafal Weron
Publisher : John Wiley & Sons
ISBN 13 : 0470059990
Total Pages : 192 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Modeling and Forecasting Electricity Loads and Prices by : Rafal Weron

Download or read book Modeling and Forecasting Electricity Loads and Prices written by Rafal Weron and published by John Wiley & Sons. This book was released on 2007-01-30 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an in-depth and up-to-date review of different statistical tools that can be used to analyze and forecast the dynamics of two crucial for every energy company processes—electricity prices and loads. It provides coverage of seasonal decomposition, mean reversion, heavy-tailed distributions, exponential smoothing, spike preprocessing, autoregressive time series including models with exogenous variables and heteroskedastic (GARCH) components, regime-switching models, interval forecasts, jump-diffusion models, derivatives pricing and the market price of risk. Modeling and Forecasting Electricity Loads and Prices is packaged with a CD containing both the data and detailed examples of implementation of different techniques in Matlab, with additional examples in SAS. A reader can retrace all the intermediate steps of a practical implementation of a model and test his understanding of the method and correctness of the computer code using the same input data. The book will be of particular interest to the quants employed by the utilities, independent power generators and marketers, energy trading desks of the hedge funds and financial institutions, and the executives attending courses designed to help them to brush up on their technical skills. The text will be also of use to graduate students in electrical engineering, econometrics and finance wanting to get a grip on advanced statistical tools applied in this hot area. In fact, there are sixteen Case Studies in the book making it a self-contained tutorial to electricity load and price modeling and forecasting.

Advanced Data Mining and Applications

Author : Shuigeng Zhou
Publisher : Springer Science & Business Media
ISBN 13 : 3642355277
Total Pages : 812 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Advanced Data Mining and Applications by : Shuigeng Zhou

Download or read book Advanced Data Mining and Applications written by Shuigeng Zhou and published by Springer Science & Business Media. This book was released on 2012-12-09 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on Advanced Data Mining and Applications, ADMA 2012, held in Nanjing, China, in December 2012. The 32 regular papers and 32 short papers presented in this volume were carefully reviewed and selected from 168 submissions. They are organized in topical sections named: social media mining; clustering; machine learning: algorithms and applications; classification; prediction, regression and recognition; optimization and approximation; mining time series and streaming data; Web mining and semantic analysis; data mining applications; search and retrieval; information recommendation and hiding; outlier detection; topic modeling; and data cube computing.

Deep Learning Tools for Predicting Stock Market Movements

Author : Renuka Sharma
Publisher : John Wiley & Sons
ISBN 13 : 1394214308
Total Pages : 500 pages
Book Rating : 4.3/5 (942 download)

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Book Synopsis Deep Learning Tools for Predicting Stock Market Movements by : Renuka Sharma

Download or read book Deep Learning Tools for Predicting Stock Market Movements written by Renuka Sharma and published by John Wiley & Sons. This book was released on 2024-05-14 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: DEEP LEARNING TOOLS for PREDICTING STOCK MARKET MOVEMENTS The book provides a comprehensive overview of current research and developments in the field of deep learning models for stock market forecasting in the developed and developing worlds. The book delves into the realm of deep learning and embraces the challenges, opportunities, and transformation of stock market analysis. Deep learning helps foresee market trends with increased accuracy. With advancements in deep learning, new opportunities in styles, tools, and techniques evolve and embrace data-driven insights with theories and practical applications. Learn about designing, training, and applying predictive models with rigorous attention to detail. This book offers critical thinking skills and the cultivation of discerning approaches to market analysis. The book: details the development of an ensemble model for stock market prediction, combining long short-term memory and autoregressive integrated moving average; explains the rapid expansion of quantum computing technologies in financial systems; provides an overview of deep learning techniques for forecasting stock market trends and examines their effectiveness across different time frames and market conditions; explores applications and implications of various models for causality, volatility, and co-integration in stock markets, offering insights to investors and policymakers. Audience The book has a wide audience of researchers in financial technology, financial software engineering, artificial intelligence, professional market investors, investment institutions, and asset management companies.

Modeling and Forecasting Jakarta Stock Exchange

Author : Erie Febrian
Publisher :
ISBN 13 :
Total Pages : 28 pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Modeling and Forecasting Jakarta Stock Exchange by : Erie Febrian

Download or read book Modeling and Forecasting Jakarta Stock Exchange written by Erie Febrian and published by . This book was released on 2008 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Various techniques have been introduced by earlier academicians, from random walk model to GARCH model with its univariate and multi-variate derivations. The models have proven their strength and weakness in forecast accuracy and mean square error (MSE). On this paper, we try to conduct simulations on forecasting model for capital market. The research is aimed at finding forecast model that fits Jakarta Stock Exchange (JSX) the best. JSX is used as sample, which represents real circumstance of emerging market (microstructure).In general, outlier data is found on JSX return as the consequence of many events causing data shock. We try to compare mean model with volatility model to examine capability of a model in predicting return. Finally, we find that combination of autoregressive (AR) model, and the addition of regime independent variable, which is represented by a dummy variable, is suitable to JSX data return characteristic. This, in turn, can increase the value of R2-adj and be therefore meaningful. At the end, the assessment on the relationship between return and risk reveals that there is positive relationship between market return and the associated volatility.

Machine Learning for Asset Management

Author : Emmanuel Jurczenko
Publisher : John Wiley & Sons
ISBN 13 : 1786305445
Total Pages : 460 pages
Book Rating : 4.7/5 (863 download)

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Book Synopsis Machine Learning for Asset Management by : Emmanuel Jurczenko

Download or read book Machine Learning for Asset Management written by Emmanuel Jurczenko and published by John Wiley & Sons. This book was released on 2020-10-06 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of machine learning for asset management. The chapters introduce the reader to some of the latest research developments in the area of equity, multi-asset and factor investing. Each chapter deals with new methods for return and risk forecasting, stock selection, portfolio construction, performance attribution and transaction costs modeling. This volume will be of great help to portfolio managers, asset owners and consultants, as well as academics and students who want to improve their knowledge of machine learning in asset management.

Computational Methods in Decision-Making, Economics and Finance

Author : Erricos John Kontoghiorghes
Publisher : Springer Science & Business Media
ISBN 13 : 1475736134
Total Pages : 626 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Computational Methods in Decision-Making, Economics and Finance by : Erricos John Kontoghiorghes

Download or read book Computational Methods in Decision-Making, Economics and Finance written by Erricos John Kontoghiorghes and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computing has become essential for the modeling, analysis, and optimization of systems. This book is devoted to algorithms, computational analysis, and decision models. The chapters are organized in two parts: optimization models of decisions and models of pricing and equilibria.