Pairs Trading A Bayesian Example
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Pairs Trading A Bayesian Example
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Author : Stefan Hollos
language : en
Publisher: Abrazol Publishing
Release Date : 2012-08-31
Pairs Trading A Bayesian Example written by Stefan Hollos and has been published by Abrazol Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-31 with Business & Economics categories.
Have you ever wondered whether Bayesian analysis can be applied toward the stock market? We did, and set out to investigate. This book shows you how to find relationships between stocks or exchange traded funds (ETFs) using Bayesian analysis. A relationship that most traders are probably familiar with is linear correlation. This is sometimes used as the basis for pairs trading. But linear correlation is just one way that stocks or ETFs can be related. The analysis we present in this book can be used to exploit almost any kind of relationship that may exist between stocks or ETFs. The book will show how to calculate the probability of a stock or ETF ending the day up or down based on what other stocks or ETFs are doing. A probability is more useful than a simple up or down signal. It quantifies the certainty of a prediction and allows a trader to take a position consistent with a given level of risk. Any active trader should find the techniques presented in this book useful. We are only going to examine the relationships in one small group of ETFs as an example of what is possible but the same techniques will work for any set of stocks, ETFs, or even bonds. The tool we use to calculate the probability of a positive or negative return on a stock or ETF is called a Bayesian classifier. It is called a classifier because it calculates probabilities for only two discrete outcomes: positive or negative. The method we use to calculate these probabilities is called Bayes' Theorem.
Pairs Trading
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Author : Ganapathy Vidyamurthy
language : en
Publisher: John Wiley & Sons
Release Date : 2011-02-02
Pairs Trading written by Ganapathy Vidyamurthy 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 2011-02-02 with Business & Economics categories.
The first in-depth analysis of pairs trading Pairs trading is a market-neutral strategy in its most simple form. The strategy involves being long (or bullish) one asset and short (or bearish) another. If properly performed, the investor will gain if the market rises or falls. Pairs Trading reveals the secrets of this rigorous quantitative analysis program to provide individuals and investment houses with the tools they need to successfully implement and profit from this proven trading methodology. Pairs Trading contains specific and tested formulas for identifying and investing in pairs, and answers important questions such as what ratio should be used to construct the pairs properly. Ganapathy Vidyamurthy (Stamford, CT) is currently a quantitative software analyst and developer at a major New York City hedge fund.
The Handbook Of Pairs Trading
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Author : Douglas S. Ehrman
language : en
Publisher: John Wiley & Sons
Release Date : 2006-01-24
The Handbook Of Pairs Trading written by Douglas S. Ehrman 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 2006-01-24 with Business & Economics categories.
Learn both the theory and practice of pairs trading, why it is consistently profitable, and how you can apply the strategies in your own trading with this valuable guide. Author Douglas Ehrman covers pairs trading involving stocks, options on stocks, and futures contracts, and explains how this type of trading allows you to profit from the changing price relationship of securities. In addition to a comprehensive discussion of the theories involved, he also includes practical examples that will to help you put what you've learned into practice. Douglas S. Ehrman is a hedge fund manager and a leading authority on pairs trading. He is one of the founders and the Chief Executive Officer of AlphAmerica Asset Management LLC in Chicago. He also served as the chief executive officer of AlphAmerica Financial, Inc., the company that operated PairsTrading.com prior to its merger with PairTrader.com.
Trading Pairs
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Author : Mark Whistler
language : en
Publisher: John Wiley & Sons
Release Date : 2004-07-29
Trading Pairs written by Mark Whistler 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 2004-07-29 with Business & Economics categories.
An accessible guide to the pairs trading technique A leading arbitrage expert gives traders real tools for using pairs trading, including customizable Excel worksheets available on the companion website. Mark Whistler (Denver, CO) is the key developer of pairstrader.com as well as a licensed securities trader and broker and leading arbitrage expert.
Statistical Arbitrage
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Author : Andrew Pole
language : en
Publisher: LibreDigital
Release Date : 2008-03-31
Statistical Arbitrage written by Andrew Pole and has been published by LibreDigital this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-31 with Business & Economics categories.
While statistical arbitrage has faced some tough times?as markets experienced dramatic changes in dynamics beginning in 2000?new developments in algorithmic trading have allowed it to rise from the ashes of that fire. Based on the results of author Andrew Pole?s own research and experience running a statistical arbitrage hedge fund for eight years?in partnership with a group whose own history stretches back to the dawn of what was first called pairs trading?this unique guide provides detailed insights into the nuances of a proven investment strategy. Filled with in-depth insights and expert advice, Statistical Arbitrage contains comprehensive analysis that will appeal to both investors looking for an overview of this discipline, as well as quants looking for critical insights into modeling, risk management, and implementation of the strategy.
Trading Stategies For Capital Markets Chapter 20 Pairs Trading
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Author : Joseph Benning
language : en
Publisher: McGraw Hill Professional
Release Date : 2007-08-07
Trading Stategies For Capital Markets Chapter 20 Pairs Trading written by Joseph Benning and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-07 with Business & Economics categories.
This chapter comes from a book written by Joseph Benning, a Moody's Vice President and former Senior Economist at the Chicago Board of Trade. Trading Strategies for Capital Markets provides examples of successful trading strategies, guidance on when and why to use them, and revealing discussions of trading psychology and risk management. With his trademark lively and engaging style, Dr. Benning cuts through the complexities of the capital markets, making them accessible, practical, interesting, and easy to understand.
Machine Learning For Algorithmic Trading
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Author : Stefan Jansen
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-07-31
Machine Learning For Algorithmic Trading written by Stefan Jansen and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-31 with Business & Economics categories.
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.
Pairs Trading
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Author : Ganapathy Vidyamurthy
language : en
Publisher: John Wiley & Sons
Release Date : 2004-08-30
Pairs Trading written by Ganapathy Vidyamurthy 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 2004-08-30 with Business & Economics categories.
The first in-depth analysis of pairs trading Pairs trading is a market-neutral strategy in its most simple form. The strategy involves being long (or bullish) one asset and short (or bearish) another. If properly performed, the investor will gain if the market rises or falls. Pairs Trading reveals the secrets of this rigorous quantitative analysis program to provide individuals and investment houses with the tools they need to successfully implement and profit from this proven trading methodology. Pairs Trading contains specific and tested formulas for identifying and investing in pairs, and answers important questions such as what ratio should be used to construct the pairs properly. Ganapathy Vidyamurthy (Stamford, CT) is currently a quantitative software analyst and developer at a major New York City hedge fund.
The Coin Toss
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Author : Stefan Hollos
language : en
Publisher: Abrazol Publishing
Release Date : 2012-11-20
The Coin Toss written by Stefan Hollos and has been published by Abrazol Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-20 with Mathematics categories.
The coin toss is really just a metaphor for a random event that has only two possible outcomes. The actual tossing of a real coin is just one way to realize such an event. There are many examples of questions that are equivalent to a coin toss. For example: Will the stock market close up or down tomorrow? Will a die roll come up with an even or odd number? Will we make contact with extraterrestrials within the next ten years? Will a car drive by in the next minute? Will tomorrow be sunny or cloudy? Will my medical test result be negative or positive? Will I enjoy this movie? Will the next joke be funny? Will the Earth's average temperature go up next year?Because a coin toss is equivalent to such a wide variety of questions, the results in this book are widely applicable.Because the coin toss is the simplest random event you can imagine, many questions about coin tossing can be asked and answered in great depth. The simplicity of the coin toss also opens the road to more advanced probability theories dealing with events with an infinite number of possible outcomes.This book is very mathematical. Some knowledge of calculus, discrete math, and generating functions is helpful to get the most out of it. A review of discrete math is provided in the index,
Bayesian Inference Of State Space Models
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Author : Kostas Triantafyllopoulos
language : en
Publisher: Springer Nature
Release Date : 2021-11-12
Bayesian Inference Of State Space Models written by Kostas Triantafyllopoulos and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-12 with Mathematics categories.
Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models. The celebrated Kalman filter, with its numerous extensions, takes centre stage in the book. Univariate and multivariate models, linear Gaussian, non-linear and non-Gaussian models are discussed with applications to signal processing, environmetrics, economics and systems engineering. Over the past years there has been a growing literature on Bayesian inference of state space models, focusing on multivariate models as well as on non-linear and non-Gaussian models. The availability of time series data in many fields of science and industry on the one hand, and the development of low-cost computational capabilities on the other, have resulted in a wealth of statistical methods aimed at parameter estimation and forecasting. This book brings together many of these methods, presenting an accessible and comprehensive introduction to state space models. A number of data sets from different disciplines are used to illustrate the methods and show how they are applied in practice. The R package BTSA, created for the book, includes many of the algorithms and examples presented. The book is essentially self-contained and includes a chapter summarising the prerequisites in undergraduate linear algebra, probability and statistics. An up-to-date and complete account of state space methods, illustrated by real-life data sets and R code, this textbook will appeal to a wide range of students and scientists, notably in the disciplines of statistics, systems engineering, signal processing, data science, finance and econometrics. With numerous exercises in each chapter, and prerequisite knowledge conveniently recalled, it is suitable for upper undergraduate and graduate courses.