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Regime Switching And Technical Trading With Dynamic Bayesian Networks In High Frequency Stock Markets
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Book Synopsis Regime Switching and Technical Trading with Dynamic Bayesian Networks in High-frequency Stock Markets by : Aditya Tayal
Download or read book Regime Switching and Technical Trading with Dynamic Bayesian Networks in High-frequency Stock Markets written by Aditya Tayal and published by . This book was released on 2009 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technical analysis has been thwarted in academic circles, due to the Efficient Market Hypothesis, which had significant empirical support early on. However recently, there is accumulating evidence that the markets are not as efficient and a new theory of price discovery, Heterogenous Market Hypothesis, is being proposed. As such, there is renewed interest and possibility in technical analysis, which identifies trends in price and volume based on aggregate repeatable human behavioural patterns. In this thesis we propose a new approach for modeling and working with technical analysis in high-frequency markets: dynamic Bayesian networks (DBNs). DBNs are a statistical modeling and learning framework that have had successful applications in other domains such as speech recognition, bio-sequencing, visual interpretation. It provides a coherent probabilistic framework (in a Bayesian sense), that can be used for both learning technical rules and inferring the hidden state of the system. We design a DBN to learn price and volume patterns in TSE60 stock market and find that our model is able to successfully identify runs and reversal out-of-sample in a statistically significant way.
Book Synopsis Artificial Intelligence Applications and Innovations by : Lazaros Iliadis
Download or read book Artificial Intelligence Applications and Innovations written by Lazaros Iliadis and published by Springer. This book was released on 2016-09-02 with total page 719 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2016, and three parallel workshops, held in Thessaloniki, Greece, in September 2016. The workshops are the Third Workshop on New Methods and Tools for Big Data, MT4BD 2016, the 5th Mining Humanistic Data Workshop, MHDW 2016, and the First Workshop on 5G - Putting Intelligence to the Network Edge, 5G-PINE 2016.The 30 revised full papers and 8 short papers presented at the main conference were carefully reviewed and selected from 65 submissions. The 17 revised full papers and 7 short papers presented at the 3 parallel workshops were selected from 33 submissions. The papers cover a broad range of topics such as artificial neural networks, classification, clustering, control systems - robotics, data mining, engineering application of AI, environmental applications of AI, feature reduction, filtering, financial-economics modeling, fuzzy logic, genetic algorithms, hybrid systems, image and video processing, medical AI applications, multi-agent systems, ontology, optimization, pattern recognition, support vector machines, text mining, and Web-social media data AI modeling.
Book Synopsis High Frequency Trading in a Regime-switching Model by : Yoontae Jeon
Download or read book High Frequency Trading in a Regime-switching Model written by Yoontae Jeon and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis High Frequency Trading and Limit Order Book Dynamics by : Ingmar Nolte
Download or read book High Frequency Trading and Limit Order Book Dynamics written by Ingmar Nolte and published by Routledge. This book was released on 2016-04-14 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together the latest research in the areas of market microstructure and high-frequency finance along with new econometric methods to address critical practical issues in these areas of research. Thirteen chapters, each of which makes a valuable and significant contribution to the existing literature have been brought together, spanning a wide range of topics including information asymmetry and the information content in limit order books, high-frequency return distribution models, multivariate volatility forecasting, analysis of individual trading behaviour, the analysis of liquidity, price discovery across markets, market microstructure models and the information content of order flow. These issues are central both to the rapidly expanding practice of high frequency trading in financial markets and to the further development of the academic literature in this area. The volume will therefore be of immediate interest to practitioners and academics. This book was originally published as a special issue of European Journal of Finance.
Book Synopsis The Secret Science of Price and Volume by : Tim Ord
Download or read book The Secret Science of Price and Volume written by Tim Ord and published by John Wiley & Sons. This book was released on 2012-06-26 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: In The Secret Science of Price and Volume, leading market timer Tim Ord outlines a top-down approach to trading—identifying the trend, picking the strongest sectors, and focusing on the best stocks within those sectors—that will allow you to excel in a variety of markets. With this book as your guide, you’ll quickly become familiar with Ord’s proven method and discover how it can be used to make more profitable trading decisions.
Book Synopsis Time Series Models by : Andrew C. Harvey
Download or read book Time Series Models written by Andrew C. Harvey and published by Financial Times/Prentice Hall. This book was released on 1993 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: A companion volume to The Econometric Analysis of Time series, this book focuses on the estimation, testing and specification of dynamic models which are not based on any behavioural theory. It covers univariate and multivariate time series and emphasizes autoregressive moving-average processes.
Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner
Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2014-07-17 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2014, held in St. Petersburg, Russia in July 2014. The 40 full papers presented were carefully reviewed and selected from 128 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.
Book Synopsis Machine Learning for Algorithmic Trading by : Stefan Jansen
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.
Book Synopsis Multi-Period Trading Via Convex Optimization by : Stephen Boyd
Download or read book Multi-Period Trading Via Convex Optimization written by Stephen Boyd and published by . This book was released on 2017-07-28 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph collects in one place the basic definitions, a careful description of the model, and discussion of how convex optimization can be used in multi-period trading, all in a common notation and framework.
Author :Radhakrishnan Nagarajan Publisher :Springer Science & Business Media ISBN 13 :1461464463 Total Pages :168 pages Book Rating :4.4/5 (614 download)
Book Synopsis Bayesian Networks in R by : Radhakrishnan Nagarajan
Download or read book Bayesian Networks in R written by Radhakrishnan Nagarajan and published by Springer Science & Business Media. This book was released on 2014-07-08 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Networks in R with Applications in Systems Biology is unique as it introduces the reader to the essential concepts in Bayesian network modeling and inference in conjunction with examples in the open-source statistical environment R. The level of sophistication is also gradually increased across the chapters with exercises and solutions for enhanced understanding for hands-on experimentation of the theory and concepts. The application focuses on systems biology with emphasis on modeling pathways and signaling mechanisms from high-throughput molecular data. Bayesian networks have proven to be especially useful abstractions in this regard. Their usefulness is especially exemplified by their ability to discover new associations in addition to validating known ones across the molecules of interest. It is also expected that the prevalence of publicly available high-throughput biological data sets may encourage the audience to explore investigating novel paradigms using the approaches presented in the book.
Book Synopsis The Foreign Exchange Market by : Richard T. Baillie
Download or read book The Foreign Exchange Market written by Richard T. Baillie and published by Cambridge University Press. This book was released on 1989 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: The flotation of exchange rates in the early 1970s saw a significant increase in the importance of foreign exchange markets and in the interest shown in them. Apart from the consequent institutional changes, this period also witnessed a revolution in macroeconomic analysis and finance theory based on the concept of rational expectations. This book provides an integrated approach to recent developments in the understanding of foreign exchange markets. It begins by charting the institutional background and looks at the recent history of movements in some of the major exchange rates. The theoretical sections focus on the economic and finance theory of the asset market approach, the macroeconomic models developed from this approach, and on interest rate parity theory. The empirical chapters draw on the authors' own research from a high quality set of exchange rate and interest rate data. The statistical properties of exchange rates are analysed; the relationship between spot and forward rates is examined; and the modelling and impact of new information on the forward and spot relationship is considered. The final chapter is devoted to the estimation and testing of exchange rate models.
Book Synopsis Hidden Markov Models for Time Series by : Walter Zucchini
Download or read book Hidden Markov Models for Time Series written by Walter Zucchini and published by CRC Press. This book was released on 2017-12-19 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations. The book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations. Features Presents an accessible overview of HMMs Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology Includes numerous theoretical and programming exercises Provides most of the analysed data sets online New to the second edition A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal movement, rainfall occurrence and capture-recapture data
Book Synopsis Artificial Intelligence in Asset Management by : Söhnke M. Bartram
Download or read book Artificial Intelligence in Asset Management written by Söhnke M. Bartram and published by CFA Institute Research Foundation. This book was released on 2020-08-28 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.
Book Synopsis Bayesian Networks by : Olivier Pourret
Download or read book Bayesian Networks written by Olivier Pourret and published by John Wiley & Sons. This book was released on 2008-04-30 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.
Book Synopsis State-space Models with Regime Switching by : Chang-Jin Kim
Download or read book State-space Models with Regime Switching written by Chang-Jin Kim and published by Mit Press. This book was released on 1999 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data.The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a new index of coincident economic indicators, approaches to modeling monetary policy uncertainty, Friedman's "plucking" model of recessions, the detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with heteroskedastic disturbances, fads and crashes in financial markets, long-run real exchange rates, and mean reversion in asset returns.
Book Synopsis Swing Pricing and Fragility in Open-end Mutual Funds by : Dunhong Jin
Download or read book Swing Pricing and Fragility in Open-end Mutual Funds written by Dunhong Jin and published by International Monetary Fund. This book was released on 2019-11-01 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to prevent runs on open-end mutual funds? In recent years, markets have observed an innovation that changed the way open-end funds are priced. Alternative pricing rules (known as swing pricing) adjust funds’ net asset values to pass on funds’ trading costs to transacting shareholders. Using unique data on investor transactions in U.K. corporate bond funds, we show that swing pricing eliminates the first-mover advantage arising from the traditional pricing rule and significantly reduces redemptions during stress periods. The positive impact of alternative pricing rules on fund flows reverses in calm periods when costs associated with higher tracking error dominate the pricing effect.
Book Synopsis Efficiency and Anomalies in Stock Markets by : Wing-Keung Wong
Download or read book Efficiency and Anomalies in Stock Markets written by Wing-Keung Wong and published by Mdpi AG. This book was released on 2022-02-17 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Efficient Market Hypothesis believes that it is impossible for an investor to outperform the market because all available information is already built into stock prices. However, some anomalies could persist in stock markets while some other anomalies could appear, disappear and re-appear again without any warning. A Special Issue on "Efficiency and Anomalies in Stock Markets" will be devoted to advancements in the theoretical development of market efficiency and anomaly in the Stock Market, as well as applications in Stock Market efficiency and anomalies.
