Algorithmic Trading And Investment Automation

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ALGORITHMIC TRADING AND INVESTMENT AUTOMATION

Author : Marcel Souza
Publisher : Gavea
ISBN 13 :
Total Pages : 109 pages
Book Rating : 4./5 ( download)

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Book Synopsis ALGORITHMIC TRADING AND INVESTMENT AUTOMATION by : Marcel Souza

Download or read book ALGORITHMIC TRADING AND INVESTMENT AUTOMATION written by Marcel Souza and published by Gavea. This book was released on with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the future of finance with Algorithmic Trading and Investment Automation, your comprehensive guide to mastering the world of automated trading. This book introduces you to the cutting-edge techniques used by top traders and investors to develop algorithmic strategies, offering a deep dive into the technology that powers today’s financial markets. Whether you're a beginner eager to learn the basics or an experienced trader looking to fine-tune your systems, this guide provides invaluable insights into creating, testing, and optimizing algorithms that maximize returns while minimizing risk. In this book, you'll explore a range of algorithmic strategies, from simple moving averages to more complex machine learning models. Each chapter is designed to build your knowledge step by step, offering practical examples and real-world case studies. You'll learn how to structure algorithms for various markets—stocks, cryptocurrencies, forex—and understand how to analyze large datasets for profitable patterns. Additionally, we explore the role of risk management in automated systems, ensuring your trading strategies remain resilient in volatile markets. One of the key features of Algorithmic Trading and Investment Automation is its focus on real-world application. With hands-on exercises and coding examples in popular programming languages like Python, this book helps you transform theoretical knowledge into practical trading systems. You’ll also gain insights into backtesting and simulation techniques, so you can test your strategies in a safe environment before going live with real capital. The book ensures that your journey into algorithmic trading is well-supported by the necessary tools and skills. Finally, this book highlights the future trends in algorithmic trading, including AI-driven decision-making, sentiment analysis, and advanced data analytics. Algorithmic Trading and Investment Automation is not just a book but a roadmap to becoming a sophisticated trader in the ever-evolving financial landscape. Whether you're looking to automate your trades or invest in AI-driven strategies, this book will give you the knowledge and confidence to stay ahead of the curve in the world of finance.

Building Automated Trading Systems

Author : Benjamin Van Vliet
Publisher : Elsevier
ISBN 13 : 0080476252
Total Pages : 331 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Building Automated Trading Systems by : Benjamin Van Vliet

Download or read book Building Automated Trading Systems written by Benjamin Van Vliet and published by Elsevier. This book was released on 2007-03-07 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the next few years, the proprietary trading and hedge fund industries will migrate largely to automated trade selection and execution systems. Indeed, this is already happening. While several finance books provide C++ code for pricing derivatives and performing numerical calculations, none approaches the topic from a system design perspective. This book will be divided into two sections: programming techniques and automated trading system ( ATS ) technology and teach financial system design and development from the absolute ground up using Microsoft Visual C++.NET 2005. MS Visual C++.NET 2005 has been chosen as the implementation language primarily because most trading firms and large banks have developed and continue to develop their proprietary algorithms in ISO C++ and Visual C++.NET provides the greatest flexibility for incorporating these legacy algorithms into working systems. Furthermore, the .NET Framework and development environment provide the best libraries and tools for rapid development of trading systems. The first section of the book explains Visual C++.NET 2005 in detail and focuses on the required programming knowledge for automated trading system development, including object oriented design, delegates and events, enumerations, random number generation, timing and timer objects, and data management with STL.NET and .NET collections. Furthermore, since most legacy code and modeling code in the financial markets is done in ISO C++, this book looks in depth at several advanced topics relating to managed/unmanaged/COM memory management and interoperability. Further, this book provides dozens of examples illustrating the use of database connectivity with ADO.NET and an extensive treatment of SQL and FIX and XML/FIXML. Advanced programming topics such as threading, sockets, as well as using C++.NET to connect to Excel are also discussed at length and supported by examples. The second section of the book explains technological concerns and design concepts for automated trading systems. Specifically, chapters are devoted to handling real-time data feeds, managing orders in the exchange order book, position selection, and risk management. A .dll is included in the book that will emulate connection to a widely used industry API ( Trading Technologies, Inc.'s XTAPI ) and provide ways to test position and order management algorithms. Design patterns are presented for market taking systems based upon technical analysis as well as for market making systems using intermarket spreads. As all of the chapters revolve around computer programming for financial engineering and trading system development, this book will educate traders, financial engineers, quantitative analysts, students of quantitative finance and even experienced programmers on technological issues that revolve around development of financial applications in a Microsoft environment and the construction and implementation of real-time trading systems and tools. - Teaches financial system design and development from the ground up using Microsoft Visual C++.NET 2005 - Provides dozens of examples illustrating the programming approaches in the book - Chapters are supported by screenshots, equations, sample Excel spreadsheets, and programming code

Automation of Trading Machine for Traders

Author : Jacinta Chan
Publisher : Springer Nature
ISBN 13 : 981139945X
Total Pages : 130 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Automation of Trading Machine for Traders by : Jacinta Chan

Download or read book Automation of Trading Machine for Traders written by Jacinta Chan and published by Springer Nature. This book was released on 2019-12-02 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Palgrave Pivot innovatively combines new methods and approaches to building dynamic trading systems to forecast future price direction in today’s increasingly difficult and volatile financial markets. The primary purpose of this book is to provide a structured course for building robust algorithmic trading models that forecast future price direction. Chan provides insider information and insights on trading strategies; her knowledge and experience has been gained over two decades as a trader in foreign exchange, stock and derivatives markets. She guides the reader to build, evaluate, and test the predictive ability and the profitability of abnormal returns of new hybrid forecasting models.

Disrupting Wall Street

Author : Greg Kolodziejzyk
Publisher :
ISBN 13 : 9781549519956
Total Pages : 148 pages
Book Rating : 4.5/5 (199 download)

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Book Synopsis Disrupting Wall Street by : Greg Kolodziejzyk

Download or read book Disrupting Wall Street written by Greg Kolodziejzyk and published by . This book was released on 2017-08-26 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn:1. Why do automated algorithmic investments outperform stocks and mutual funds?2. How do algorithmic trading systems work?3. Step by step tutorials on developing 3 algorithmic systems: a. Does the full moon effect investor emotions? The result will surprise you! b. Why "buying low" & "selling high" doesn't work. c. How to develop a "seemingly" profitable trading strategy based on random price data! Don't be fooled by over optimization. d. Learn about the dangers of curve fitting, and how to avoid it using a Monte Carlo simulation. e. How to develop a highly profitable trading approach based on breakouts from trading ranges.4. How AlgoLab Automated Trading in the Cloud makes investing in these lucrative algorithmic trading strategies easy.5. A close-up look at the phenomenal 69% return from our first year of trading AlgoLab.I've been trading the markets for decades. So many years of trial and error and I can't even begin to estimate how many trading books I've devoured over the years. Finally I feel like I have a very solid understanding of the markets, and algorithmic trading strategies and most importantly have learned how to interpret the difference between bogus curve fitted magical systems that are less than useless (they are destructive because they can cost you a fortune), and valuable strategies that extract profits from tradable markets. In fact, I've even developed an entire software platform that automates the trading of my strategies. Part 1 of this book tells the story of how I got here, and the fallacy of investing in Wall Street's mutual funds. I also explain what algorithmic investing actually is, and then describe the steps required to develop an algorithmic strategy, while taking the reader through the development and testing of an entire trading strategy - a strategy based on taking trades during certain moon phases. Yes - that sounds silly, but I chose that because my original goal was to use a bogus trading methodology that my curve fitting test would identify as such. But I was in for a surprise, and I'm sure you will be just as shocked as I was. Note that I just said "development AND TESTING". The testing part of a new trading strategy is far more important than the development of it. You will see why in the chapters ahead.Part 2 of this book is where we use the development and testing steps that we learned in Part 1 and develop 2 complete algorithmic trading strategies from scratch with tutorials. The remainder of part 2 describes some of the software packages available if you wanted to actually author and test your own strategies, as well as a list of software vendors who publish solutions required to process trading system rules, backtest strategies using historical data, and place orders through a broker.Today's investing industry professionals have learned that there are many highly respectable algorithmic investing firms that have proven the profitability of an objective, backtested algorithmic approach to investing.Take Renaissance technologies' Medallion Fund for example. The fund, which used mathematical models to explore correlations from which they could profit is famed for one of the best records in investing history, returning more than 35 percent annually over a 20-year span. From 1994 through 2014 the fund averaged a 71.8% annual return. Medallion is now closed to outside investors. Along with Renaissance, the funds that are earning the best returns today are doing so using computer models. According to Alpha magazine, eight of the ten top earners on Alpha's rich list are algorithmic based, and half of the 25 richest of the year are quants. And when you compare the incredible performance of the algorithmic based funds to the lackluster mutual funds that I talked about in chapter 2, it becomes obvious that we are in the midst of one historic hell of a disruption.

Electronic and Algorithmic Trading Technology

Author : Kendall Kim
Publisher : Academic Press
ISBN 13 : 0080548865
Total Pages : 224 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Electronic and Algorithmic Trading Technology by : Kendall Kim

Download or read book Electronic and Algorithmic Trading Technology written by Kendall Kim and published by Academic Press. This book was released on 2010-07-27 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electronic and algorithmic trading has become part of a mainstream response to buy-side traders' need to move large blocks of shares with minimum market impact in today's complex institutional trading environment. This book illustrates an overview of key providers in the marketplace. With electronic trading platforms becoming increasingly sophisticated, more cost effective measures handling larger order flow is becoming a reality. The higher reliance on electronic trading has had profound implications for vendors and users of information and trading products. Broker dealers providing solutions through their products are facing changes in their business models such as: relationships with sellside customers, relationships with buyside customers, the importance of broker neutrality, the role of direct market access, and the relationship with prime brokers. Electronic and Algorithmic Trading Technology: The Complete Guide is the ultimate guide to managers, institutional investors, broker dealers, and software vendors to better understand innovative technologies that can cut transaction costs, eliminate human error, boost trading efficiency and supplement productivity. As economic and regulatory pressures are driving financial institutions to seek efficiency gains by improving the quality of software systems, firms are devoting increasing amounts of financial and human capital to maintaining their competitive edge. This book is written to aid the management and development of IT systems for financial institutions. Although the book focuses on the securities industry, its solution framework can be applied to satisfy complex automation requirements within very different sectors of financial services – from payments and cash management, to insurance and securities. Electronic and Algorithmic Trading: The Complete Guide is geared toward all levels of technology, investment management and the financial service professionals responsible for developing and implementing cutting-edge technology. It outlines a complete framework for successfully building a software system that provides the functionalities required by the business model. It is revolutionary as the first guide to cover everything from the technologies to how to evaluate tools to best practices for IT management. - First book to address the hot topic of how systems can be designed to maximize the benefits of program and algorithmic trading - Outlines a complete framework for developing a software system that meets the needs of the firm's business model - Provides a robust system for making the build vs. buy decision based on business requirements

Machine Learning for Algorithmic Trading

Author : Stefan Jansen
Publisher : Packt Publishing Ltd
ISBN 13 : 1839216786
Total Pages : 822 pages
Book Rating : 4.8/5 (392 download)

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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.

Python for Algorithmic Trading

Author : Yves Hilpisch
Publisher : O'Reilly Media
ISBN 13 : 1492053325
Total Pages : 380 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Python for Algorithmic Trading by : Yves Hilpisch

Download or read book Python for Algorithmic Trading written by Yves Hilpisch and published by O'Reilly Media. This book was released on 2020-11-12 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms

Algorithmic Trading

Author : Ernie Chan
Publisher : John Wiley & Sons
ISBN 13 : 1118460146
Total Pages : 230 pages
Book Rating : 4.1/5 (184 download)

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Book Synopsis Algorithmic Trading by : Ernie Chan

Download or read book Algorithmic Trading written by Ernie Chan and published by John Wiley & Sons. This book was released on 2013-05-28 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Algorithmic TRADING “Algorithmic Trading is an insightful book on quantitative trading written by a seasoned practitioner. What sets this book apart from many others in the space is the emphasis on real examples as opposed to just theory. Concepts are not only described, they are brought to life with actual trading strategies, which give the reader insight into how and why each strategy was developed, how it was implemented, and even how it was coded. This book is a valuable resource for anyone looking to create their own systematic trading strategies and those involved in manager selection, where the knowledge contained in this book will lead to a more informed and nuanced conversation with managers.” —DAREN SMITH, CFA, CAIA, FSA, Managing Director, Manager Selection & Portfolio Construction, University of Toronto Asset Management “Using an excellent selection of mean reversion and momentum strategies, Ernie explains the rationale behind each one, shows how to test it, how to improve it, and discusses implementation issues. His book is a careful, detailed exposition of the scientific method applied to strategy development. For serious retail traders, I know of no other book that provides this range of examples and level of detail. His discussions of how regime changes affect strategies, and of risk management, are invaluable bonuses.” —ROGER HUNTER, Mathematician and Algorithmic Trader

Automated Option Trading

Author : Sergey Izraylevich
Publisher : FT Press
ISBN 13 : 0132478668
Total Pages : 302 pages
Book Rating : 4.1/5 (324 download)

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Book Synopsis Automated Option Trading by : Sergey Izraylevich

Download or read book Automated Option Trading written by Sergey Izraylevich and published by FT Press. This book was released on 2012 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first and only book of its kind, Automated Options Trading describes a comprehensive, step-by-step process for creating automated options trading systems. Using the authors' techniques, sophisticated traders can create powerful frameworks for the consistent, disciplined realization of well-defined, formalized, and carefully-tested trading strategies based on their specific requirements. Unlike other books on automated trading, this book focuses specifically on the unique requirements of options, reflecting philosophy, logic, quantitative tools, and valuation procedures that are completely different from those used in conventional automated trading algorithms. Every facet of the authors' approach is optimized for options, including strategy development and optimization; capital allocation; risk management; performance measurement; back-testing and walk-forward analysis; and trade execution. The authors' system reflects a continuous process of valuation, structuring and long-term management of investment portfolios (not just individual instruments), introducing systematic approaches for handling portfolios containing option combinations related to different underlying assets. With these techniques, it is finally possible to effectively automate options trading at the portfolio level. This book will be an indispensable resource for serious options traders working individually, in hedge funds, or in other institutions.

Hands-On Machine Learning for Algorithmic Trading

Author : Stefan Jansen
Publisher : Packt Publishing Ltd
ISBN 13 : 1789342716
Total Pages : 668 pages
Book Rating : 4.7/5 (893 download)

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Book Synopsis Hands-On Machine Learning for Algorithmic Trading by : Stefan Jansen

Download or read book Hands-On Machine Learning for Algorithmic Trading written by Stefan Jansen and published by Packt Publishing Ltd. This book was released on 2018-12-31 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key FeaturesImplement machine learning algorithms to build, train, and validate algorithmic modelsCreate your own algorithmic design process to apply probabilistic machine learning approaches to trading decisionsDevelop neural networks for algorithmic trading to perform time series forecasting and smart analyticsBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You'll practice the ML workflow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learnImplement machine learning techniques to solve investment and trading problemsLeverage market, fundamental, and alternative data to research alpha factorsDesign and fine-tune supervised, unsupervised, and reinforcement learning modelsOptimize portfolio risk and performance using pandas, NumPy, and scikit-learnIntegrate machine learning models into a live trading strategy on QuantopianEvaluate strategies using reliable backtesting methodologies for time seriesDesign and evaluate deep neural networks using Keras, PyTorch, and TensorFlowWork with reinforcement learning for trading strategies in the OpenAI GymWho this book is for Hands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory.

Flash Boys: A Wall Street Revolt

Author : Michael Lewis
Publisher : W. W. Norton & Company
ISBN 13 : 0393244660
Total Pages : 288 pages
Book Rating : 4.3/5 (932 download)

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Book Synopsis Flash Boys: A Wall Street Revolt by : Michael Lewis

Download or read book Flash Boys: A Wall Street Revolt written by Michael Lewis and published by W. W. Norton & Company. This book was released on 2014-03-31 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Argues that post-crisis Wall Street continues to be controlled by large banks and explains how a small, diverse group of Wall Street men have banded together to reform the financial markets.

Dark Pools and High Frequency Trading For Dummies

Author : Jay Vaananen
Publisher : John Wiley & Sons
ISBN 13 : 1118879198
Total Pages : 253 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Dark Pools and High Frequency Trading For Dummies by : Jay Vaananen

Download or read book Dark Pools and High Frequency Trading For Dummies written by Jay Vaananen and published by John Wiley & Sons. This book was released on 2015-02-23 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: A plain English guide to high frequency trading and off-exchange trading practices In Dark Pools & High Frequency Trading For Dummies, senior private banker Jukka Vaananen has created an indispensable and friendly guide to what really goes on inside dark pools, what rewards you can reap as an investor and how wider stock markets and pricing may be affected by dark pools. Written with the classic For Dummies style that has become a hallmark of the brand, Vaananen makes this complex material easy to understand with an insider's look into the topic. The book takes a detailed look at the pros and the cons of trading in dark pools, and how this type of trading differs from more traditional routes. It also examines how dark pools are currently regulated, and how the regulatory landscape may be changing. Learn what types of dark pools exist, and how a typical transaction works Discover the rules and regulations for dark pools, and some of the downsides to trading Explore how dark pools can benefit investors and banks, and who can trade in them Recognize the ins and outs of automated and high frequency trading Because dark pools allow companies to trade stocks anonymously and away from the public exchange, they are not subject to the peaks and troughs of the stock market, and have only recently begun to take off in a big way. Written with investors and finance students in mind, Dark Pools & High Frequency Trading For Dummies is the ultimate reference guide for anyone looking to understand dark pools and dark liquidity, including the different order types and key HFT strategies.

Volatility Trading, + website

Author : Euan Sinclair
Publisher : John Wiley & Sons
ISBN 13 : 0470181990
Total Pages : 228 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Volatility Trading, + website by : Euan Sinclair

Download or read book Volatility Trading, + website written by Euan Sinclair and published by John Wiley & Sons. This book was released on 2008-06-23 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Volatility Trading, Sinclair offers you a quantitative model for measuring volatility in order to gain an edge in your everyday option trading endeavors. With an accessible, straightforward approach. He guides traders through the basics of option pricing, volatility measurement, hedging, money management, and trade evaluation. In addition, Sinclair explains the often-overlooked psychological aspects of trading, revealing both how behavioral psychology can create market conditions traders can take advantage of-and how it can lead them astray. Psychological biases, he asserts, are probably the drivers behind most sources of edge available to a volatility trader. Your goal, Sinclair explains, must be clearly defined and easily expressed-if you cannot explain it in one sentence, you probably aren't completely clear about what it is. The same applies to your statistical edge. If you do not know exactly what your edge is, you shouldn't trade. He shows how, in addition to the numerical evaluation of a potential trade, you should be able to identify and evaluate the reason why implied volatility is priced where it is, that is, why an edge exists. This means it is also necessary to be on top of recent news stories, sector trends, and behavioral psychology. Finally, Sinclair underscores why trades need to be sized correctly, which means that each trade is evaluated according to its projected return and risk in the overall context of your goals. As the author concludes, while we also need to pay attention to seemingly mundane things like having good execution software, a comfortable office, and getting enough sleep, it is knowledge that is the ultimate source of edge. So, all else being equal, the trader with the greater knowledge will be the more successful. This book, and its companion CD-ROM, will provide that knowledge. The CD-ROM includes spreadsheets designed to help you forecast volatility and evaluate trades together with simulation engines.

Hands-On Algorithmic Trading with Python

Author : Deepak Kanungo
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (113 download)

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Book Synopsis Hands-On Algorithmic Trading with Python by : Deepak Kanungo

Download or read book Hands-On Algorithmic Trading with Python written by Deepak Kanungo and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence in general and specifically machine learning are becoming increasingly important tools for many industries and enterprises. But one business sector in particular has long since adopted and benefitted from these powerful computing paradigms: investment services. In fact, over the past decade, few other industries and sectors have experienced the frenetic pace of automation as that of the investment management industry, the direct result of algorithmic trading and machine learning technologies. Industry experts estimate that today as much as 70% of the daily trading volume in the United States equity markets is executed algorithmically-by computer programs following a set of predefined rules that span the entire trading process, from idea generation to execution and portfolio management. But although all algorithmic trading is executed by computers, the rules for generating trades are either designed by humans or discovered by machine learning algorithms from training data. Not surprisingly, the ability to create these algorithms, particularly using Python, is in high demand. In this video course, designed for those with a basic level of experience and expertise in trading, investing, and writing code in Python, you learn about the process and technological tools for developing algorithmic trading strategies. You'll examine the pros and cons of algorithmic trading as well as the first steps you'll need to take to "level the playing field" for retail equity investors. You'll explore some of the models that you can apply to formulate trading and investment strategies. You'll also learn about the Pandas library to import, analyze, and visualize data from market, fundamental, and alternative, no-cost sources that are available online. You'll even see how to prepare for competitions that can fund your algorithmic trading strategies. (Note that live trading is beyond the scope of the course.) What you'll learn-and how you can apply it By the end of this video course you'll understand: The advantages and disadvantages of algorithmic trading The different types of models used to generate trading and investment strategies The process and tools used for researching, designing, and developing them Pitfalls of backtesting algorithmic strategies Risk-adjusted metrics for evaluating their performance The paramount importance of risk management and position sizing And you'll be able to: Use the Pandas library to import, analyze, and vis...

Essays on Algorithmic Trading

Author : Markus Gsell
Publisher : Columbia University Press
ISBN 13 : 3838201140
Total Pages : 228 pages
Book Rating : 4.8/5 (382 download)

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Book Synopsis Essays on Algorithmic Trading by : Markus Gsell

Download or read book Essays on Algorithmic Trading written by Markus Gsell and published by Columbia University Press. This book was released on 2010-07-09 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological innovations are altering the traditional value chain in securities trading. Hitherto the order handling, i.e. the appropriate implementation of a general trading decision into particular orders, has been a core competence of brokers. Labeled as Algorithmic Trading, the automation of this task recently found its way both into the brokers' portfolio of service offerings as well as to their customers' trading desks. The software performing the order handling thereby constantly monitors the market(s) in real-time and further evaluates historical data to dynamically determine appropriate points in time for trading. Within only a few years, this technology propagated itself among market participants along the entire value chain and has nowadays gained a significant market share on securities markets worldwide. Surprisingly, there has been only little research analyzing the impact of this special type of trading on markets. Markus Gsell's book aims at closing this gap by analyzing the drivers for adoption of this technology, the impact the application of this technology has on markets on a macro level, i.e. how the market outcome is affected, as well as on a micro level, i.e. how the exhibited trading behavior of these automated traders differs from normal traders' behavior.

An Introduction to Algorithmic Trading

Author : Edward Leshik
Publisher : John Wiley & Sons
ISBN 13 : 1119975093
Total Pages : 273 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis An Introduction to Algorithmic Trading by : Edward Leshik

Download or read book An Introduction to Algorithmic Trading written by Edward Leshik and published by John Wiley & Sons. This book was released on 2011-09-19 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in algorithmic trading is growing massively – it’s cheaper, faster and better to control than standard trading, it enables you to ‘pre-think’ the market, executing complex math in real time and take the required decisions based on the strategy defined. We are no longer limited by human ‘bandwidth’. The cost alone (estimated at 6 cents per share manual, 1 cent per share algorithmic) is a sufficient driver to power the growth of the industry. According to consultant firm, Aite Group LLC, high frequency trading firms alone account for 73% of all US equity trading volume, despite only representing approximately 2% of the total firms operating in the US markets. Algorithmic trading is becoming the industry lifeblood. But it is a secretive industry with few willing to share the secrets of their success. The book begins with a step-by-step guide to algorithmic trading, demystifying this complex subject and providing readers with a specific and usable algorithmic trading knowledge. It provides background information leading to more advanced work by outlining the current trading algorithms, the basics of their design, what they are, how they work, how they are used, their strengths, their weaknesses, where we are now and where we are going. The book then goes on to demonstrate a selection of detailed algorithms including their implementation in the markets. Using actual algorithms that have been used in live trading readers have access to real time trading functionality and can use the never before seen algorithms to trade their own accounts. The markets are complex adaptive systems exhibiting unpredictable behaviour. As the markets evolve algorithmic designers need to be constantly aware of any changes that may impact their work, so for the more adventurous reader there is also a section on how to design trading algorithms. All examples and algorithms are demonstrated in Excel on the accompanying CD ROM, including actual algorithmic examples which have been used in live trading.

Algo Bots and the Law

Author : Gregory Scopino
Publisher : Cambridge University Press
ISBN 13 : 1107164796
Total Pages : 485 pages
Book Rating : 4.1/5 (71 download)

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Book Synopsis Algo Bots and the Law by : Gregory Scopino

Download or read book Algo Bots and the Law written by Gregory Scopino and published by Cambridge University Press. This book was released on 2020-10-15 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: An exploration of how financial market laws and regulations can - and should - govern the use of artificial intelligence.