Download or read book CINTRAFOR written by and published by . This book was released on 1986 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Machine Learning for Algorithmic Trading written by Stefan Jansen and published by Packt Publishing Ltd. This book was released on 2020-07-31 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.

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.

Download or read book Securities Markets written by Richard J. Hillman (au) and published by DIANE Publishing. This book was released on 2005-11 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: In early 2001, U.S. stock & option markets began quoting prices in decimal increments rather than fractions of a dollar. At the same time, the minimum price increment, or tick size, was reduced to a penny on the stock markets & to 10¢ & 5¢ on the option markets. Although many believe that decimal pricing has benefited small individual (retail) investors, concerns have been raised that the smaller tick sizes have made trading more challenging & costly for large institutional investors, including mutual funds & pension plans. The financial livelihood of market intermediaries may also have been negatively affected by the lower ticks. This report assesses the effect of decimal pricing on retail & institutional investors & on market intermediaries. Charts.

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.

Download or read book Financial Statistics and Data Analytics written by Shuangzhe Li and published by MDPI. This book was released on 2021-03-02 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics go hand in hand. The purpose of this book is to bring the state-of-art research in these three areas to the fore and especially research that juxtaposes these three.

Download or read book The Microstructure of Foreign Exchange Markets written by Jeffrey A. Frankel and published by University of Chicago Press. This book was released on 2009-05-15 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: The foreign exchange market is the largest, fastest-growing financial market in the world. Yet conventional macroeconomic approaches do not explain why people trade foreign exchange. At the same time, they fail to explain the short-run determinants of the exchange rate. These nine innovative essays use a microstructure approach to analyze the workings of the foreign exchange market, with special emphasis on institutional aspects and the actual behavior of market participants. They examine the volume of transactions, heterogeneity of traders, the time of day and location of trading, the bid-ask spread, and the high level of exchange rate volatility that has puzzled many observers. They also consider the structure of the market, including such issues as nontransparency, asymmetric information, liquidity trading, the use of automated brokers, the relationship between spot and derivative markets, and the importance of systemic risk in the market. This timely volume will be essential reading for anyone interested in the economics of international finance.

Download or read book Intermarket Trading Strategies written by Markos Katsanos and published by John Wiley & Sons. This book was released on 2010-03-11 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows traders how to use Intermarket Analysis to forecast future equity, index and commodity price movements. It introduces custom indicators and Intermarket based systems using basic mathematical and statistical principles to help traders develop and design Intermarket trading systems appropriate for long term, intermediate, short term and day trading. The metastock code for all systems is included and the testing method is described thoroughly. All systems are back tested using at least 200 bars of historical data and compared using various profitability and drawdown metrics.

Download or read book AI and Financial Markets written by Shigeyuki Hamori and published by MDPI. This book was released on 2020-07-01 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of “AI and Financial Markets”, and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets.

Download or read book Applied Econometrics with R written by Christian Kleiber and published by Springer Science & Business Media. This book was released on 2008-12-10 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.

Download or read book Nonparametric Econometric Methods and Application written by Thanasis Stengos and published by MDPI. This book was released on 2019-05-20 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present Special Issue collects a number of new contributions both at the theoretical level and in terms of applications in the areas of nonparametric and semiparametric econometric methods. In particular, this collection of papers that cover areas such as developments in local smoothing techniques, splines, series estimators, and wavelets will add to the existing rich literature on these subjects and enhance our ability to use data to test economic hypotheses in a variety of fields, such as financial economics, microeconomics, macroeconomics, labor economics, and economic growth, to name a few.

Download or read book Handbook of Cloud Computing written by Nayyar Dr. Anand and published by BPB Publications. This book was released on 2019-09-20 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Great POSSIBILITIES and high future prospects to become ten times folds in the near FUTUREKey features Comprehensively gives clear picture of current state-of-the-art aspect of cloud computing by elaborating terminologies, models and other related terms. Enlightens all major players in Cloud Computing industry providing services in terms of SaaS, PaaS and IaaS. Highlights Cloud Computing Simulators, Security Aspect and Resource Allocation. In-depth presentation with well-illustrated diagrams and simple to understand technical concepts of cloud. Description The book "e;Handbook of Cloud Computing"e; provides the latest and in-depth information of this relatively new and another platform for scientific computing which has great possibilities and high future prospects to become ten folds in near future. The book covers in comprehensive manner all aspects and terminologies associated with cloud computing like SaaS, PaaS and IaaS and also elaborates almost every cloud computing service model.The book highlights several other aspects of cloud computing like Security, Resource allocation, Simulation Platforms and futuristic trend i.e. Mobile cloud computing. The book will benefit all the readers with all in-depth technical information which is required to understand current and futuristic concepts of cloud computing. No prior knowledge of cloud computing or any of its related technology is required in reading this book. What will you learn Cloud Computing, Virtualisation Software as a Service, Platform as a Service, Infrastructure as a Service Data in Cloud and its Security Cloud Computing - Simulation, Mobile Cloud Computing Specific Cloud Service Models Resource Allocation in Cloud Computing Who this book is for Students of Polytechnic Diploma Classes- Computer Science/ Information Technology Graduate Students- Computer Science/ CSE / IT/ Computer Applications Master Class Students-Msc (CS/IT)/ MCA/ M.Phil, M.Tech, M.S. Researcher's-Ph.D Research Scholars doing work in Virtualization, Cloud Computing and Cloud Security Industry Professionals- Preparing for Certifications, Implementing Cloud Computing and even working on Cloud Security Table of contents1. Introduction to Cloud Computing2. Virtualisation3. Software as a Service4. Platform as a Service5. Infrastructure as a Service6. Data in Cloud7. Cloud Security 8. Cloud Computing - Simulation9. Specific Cloud Service Models10. Resource Allocation in Cloud Computing11. Mobile Cloud Computing About the authorDr. Anand Nayyar received Ph.D (Computer Science) in Wireless Sensor Networks and Swarm Intelligence. Presently he is working in Graduate School, Duy Tan University, Da Nang, Vietnam. He has total of fourteen Years of Teaching, Research and Consultancy experience with more than 250 Research Papers in various International Conferences and highly reputed journals. He is certified Professional with more than 75 certificates and member of 50 Professional Organizations. He is acting as "e;ACM DISTINGUISHED SPEAKER"e;

Download or read book Empirical Finance written by Shigeyuki Hamori and published by MDPI. This book was released on 2019-03-25 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is no denying the role of empirical research in finance and the remarkable progress of empirical techniques in this research field. This Special Issue focuses on the broad topic of “Empirical Finance” and includes novel empirical research associated with financial data. One example includes the application of novel empirical techniques, such as machine learning, data mining, wavelet transform, copula analysis, and TV-VAR, to financial data. The Special Issue includes contributions on empirical finance, such as algorithmic trading, market efficiency, market microstructure, portfolio theory and asset allocation, asset pricing models, liquidity risk premium, currency crisis, return predictability, and volatility modeling.

Download or read book Recent Econometric Techniques for Macroeconomic and Financial Data written by Gilles Dufrénot and published by Springer Nature. This book was released on 2020-11-21 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a comprehensive overview of the latest econometric methods for studying the dynamics of macroeconomic and financial time series. It examines alternative methodological approaches and concepts, including quantile spectra and co-spectra, and explores topics such as non-linear and non-stationary behavior, stochastic volatility models, and the econometrics of commodity markets and globalization. Furthermore, it demonstrates the application of recent techniques in various fields: in the frequency domain, in the analysis of persistent dynamics, in the estimation of state space models and new classes of volatility models. The book is divided into two parts: The first part applies econometrics to the field of macroeconomics, discussing trend/cycle decomposition, growth analysis, monetary policy and international trade. The second part applies econometrics to a wide range of topics in financial economics, including price dynamics in equity, commodity and foreign exchange markets and portfolio analysis. The book is essential reading for scholars, students, and practitioners in government and financial institutions interested in applying recent econometric time series methods to financial and economic data.

Download or read book Empirical Market Microstructure written by Joel Hasbrouck and published by Oxford University Press. This book was released on 2007-01-04 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: The interactions that occur in securities markets are among the fastest, most information intensive, and most highly strategic of all economic phenomena. This book is about the institutions that have evolved to handle our trading needs, the economic forces that guide our strategies, and statistical methods of using and interpreting the vast amount of information that these markets produce. The book includes numerous exercises.

Download or read book The New Trading for a Living written by Alexander Elder and published by John Wiley & Sons. This book was released on 2014-09-29 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: The best-selling trading book of all time—updated for the new era The New Trading for a Living updates a modern classic, popular worldwide among both private and institutional traders. This revised and expanded edition brings time-tested concepts in gear with today's fast-moving markets, adding new studies and techniques for the modern trader. This classic guide teaches a calm and disciplined approach to the markets. It emphasizes risk management along with self-management and provides clear rules for both. The New Trading for a Living includes templates for rating stock picks, creating trade plans, and rating your own readiness to trade. It provides the knowledge, perspective, and tools for developing your own effective trading system. All charts in this book are new and in full color, with clear comments on rules and techniques. The clarity of this book's language, its practical illustrations and generous sharing of the essential skills have made it a model for the industry—often imitated but never duplicated. Both new and experienced traders will appreciate its insights and the calm, systematic approach to modern markets. The New Trading for a Living will become an even more valuable resource than the author's previous books: Overcome barriers to success and develop stronger discipline Identify asymmetrical market zones, where rewards are higher and risks lower Master money management as you set entries, targets and stops Use a record-keeping system that will make you into your own teacher Successful trading is based on knowledge, focus, and discipline. The New Trading for a Living will lift your trading to a higher level by sharing classic wisdom along with modern market tools.

Download or read book Nonlinear Time Series Analysis written by Ruey S. Tsay and published by John Wiley & Sons. This book was released on 2018-09-13 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and Bayesian as well as classical approaches to nonlinear time series analysis. The authors—noted experts in the field—explore the advantages and limitations of the nonlinear models and methods and review the improvements upon linear time series models. The need for this book is based on the recent developments in nonlinear time series analysis, statistical learning, dynamic systems and advanced computational methods. Parametric and nonparametric methods and nonlinear and non-Gaussian state space models provide a much wider range of tools for time series analysis. In addition, advances in computing and data collection have made available large data sets and high-frequency data. These new data make it not only feasible, but also necessary to take into consideration the nonlinearity embedded in most real-world time series. This vital guide: • Offers research developed by leading scholars of time series analysis • Presents R commands making it possible to reproduce all the analyses included in the text • Contains real-world examples throughout the book • Recommends exercises to test understanding of material presented • Includes an instructor solutions manual and companion website Written for students, researchers, and practitioners who are interested in exploring nonlinearity in time series, Nonlinear Time Series Analysis offers a comprehensive text that explores the advantages and limitations of the nonlinear models and methods and demonstrates the improvements upon linear time series models.