The Algorithmic Trading Guide How To Leverage Technology To Make Money In Finance Markets
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| Author | : Lyron Foster |
| Publisher | : Career Kick Start Books, LLC |
| Total Pages | : 174 |
| Release | : 2023-03-26 |
| Genre | : Business & Economics |
| ISBN | : |
The Algorithmic Trading Guide: How To Leverage Technology To Make Money In Finance Markets is a comprehensive guidebook for anyone interested in algorithmic trading, covering everything from basic concepts to advanced strategies and techniques. This book provides practical examples and case studies, demonstrating how to apply the concepts and techniques discussed in real-world trading scenarios. The book begins with an overview of algorithmic trading, its importance in financial markets, and the terminology and concepts related to it. It then moves on to cover popular trading strategies used in algorithmic trading and the installation and configuration of a trading platform. The book also delves into data analysis and visualization techniques, using Python and popular data analysis libraries, creating trading signals and indicators, and backtesting trading strategies using historical data. Readers will learn about building trading models using machine learning and reinforcement learning techniques, as well as backtesting and evaluating these models. Additionally, the book covers implementing trading strategies, developing trading algorithms using Python, and integrating these algorithms with a trading platform. It also explores market microstructure, high-frequency trading, and trading in different market conditions, as well as best practices for algorithmic trading and market microstructure. Risk management is a crucial aspect of algorithmic trading, and the book includes techniques for measuring and managing risk in trading strategies, using portfolio optimization techniques for risk management, and best practices for risk management in algorithmic trading. Finally, the book covers the regulatory landscape of algorithmic trading, compliance requirements, and best practices for complying with regulatory requirements in algorithmic trading. It also discusses future trends and challenges in algorithmic trading and regulation. The Algorithmic Trading Guide: How To Leverage Technology To Make Money In Finance Markets is an essential resource for traders and financial professionals looking to expand their knowledge and skills in the field of algorithmic trading. It is also suitable for novice traders just starting to explore algorithmic trading.
| Author | : Kendall Kim |
| Publisher | : Academic Press |
| Total Pages | : 224 |
| Release | : 2010-07-27 |
| Genre | : Computers |
| ISBN | : 0080548865 |
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
| Author | : Yves Hilpisch |
| Publisher | : O'Reilly Media |
| Total Pages | : 380 |
| Release | : 2020-11-12 |
| Genre | : Computers |
| ISBN | : 1492053325 |
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
| Author | : Michael Lewis |
| Publisher | : W. W. Norton & Company |
| Total Pages | : 288 |
| Release | : 2014-03-31 |
| Genre | : Business & Economics |
| ISBN | : 0393244660 |
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.
| Author | : Ernie Chan |
| Publisher | : John Wiley & Sons |
| Total Pages | : 230 |
| Release | : 2013-05-28 |
| Genre | : Business & Economics |
| ISBN | : 1118460146 |
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
| Author | : Yves Hilpisch |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 750 |
| Release | : 2014-12-11 |
| Genre | : Computers |
| ISBN | : 1491945389 |
The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance. Using practical examples through the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks, with topics that include: Fundamentals: Python data structures, NumPy array handling, time series analysis with pandas, visualization with matplotlib, high performance I/O operations with PyTables, date/time information handling, and selected best practices Financial topics: mathematical techniques with NumPy, SciPy and SymPy such as regression and optimization; stochastics for Monte Carlo simulation, Value-at-Risk, and Credit-Value-at-Risk calculations; statistics for normality tests, mean-variance portfolio optimization, principal component analysis (PCA), and Bayesian regression Special topics: performance Python for financial algorithms, such as vectorization and parallelization, integrating Python with Excel, and building financial applications based on Web technologies
| Author | : Roy Hope |
| Publisher | : Richards Education |
| Total Pages | : 173 |
| Release | : |
| Genre | : Computers |
| ISBN | : |
In a world increasingly driven by technology, understanding and harnessing the power of Artificial Intelligence (AI) has become paramount. "Harnessing the Power of AI: A Guide to Making Technology Work for You" offers a comprehensive exploration of AI from its fundamental concepts to its real-world applications and societal implications. From businesses seeking growth opportunities to healthcare professionals revolutionizing patient care, educators shaping the future of learning, and policymakers navigating the complexities of governance, AI has the potential to transform every facet of our lives. This book serves as a roadmap for individuals and organizations looking to navigate the AI landscape effectively. Covering topics such as AI basics, implementation strategies, industry-specific applications, ethical considerations, and the future of AI, this guide provides practical insights and actionable advice. Whether you're a seasoned professional or a curious newcomer, "Harnessing the Power of AI" equips you with the knowledge and tools needed to leverage AI effectively while ensuring ethical and responsible use. Discover how AI can enhance productivity, drive innovation, and solve complex challenges while navigating the ethical and societal implications of this transformative technology. With "Harnessing the Power of AI" as your companion, unlock the full potential of AI and make technology work for you.
| Author | : Irene Aldridge |
| Publisher | : John Wiley and Sons |
| Total Pages | : 258 |
| Release | : 2009-12-22 |
| Genre | : Business & Economics |
| ISBN | : 0470579773 |
A hands-on guide to the fast and ever-changing world of high-frequency, algorithmic trading Financial markets are undergoing rapid innovation due to the continuing proliferation of computer power and algorithms. These developments have created a new investment discipline called high-frequency trading. This book covers all aspects of high-frequency trading, from the business case and formulation of ideas through the development of trading systems to application of capital and subsequent performance evaluation. It also includes numerous quantitative trading strategies, with market microstructure, event arbitrage, and deviations arbitrage discussed in great detail. Contains the tools and techniques needed for building a high-frequency trading system Details the post-trade analysis process, including key performance benchmarks and trade quality evaluation Written by well-known industry professional Irene Aldridge Interest in high-frequency trading has exploded over the past year. This book has what you need to gain a better understanding of how it works and what it takes to apply this approach to your trading endeavors.
| Author | : El Bachir Boukherouaa |
| Publisher | : International Monetary Fund |
| Total Pages | : 35 |
| Release | : 2021-10-22 |
| Genre | : Business & Economics |
| ISBN | : 1589063953 |
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
| Author | : Robert Kissell |
| Publisher | : Academic Press |
| Total Pages | : 492 |
| Release | : 2013-10-01 |
| Genre | : Business & Economics |
| ISBN | : 0124016936 |
The Science of Algorithmic Trading and Portfolio Management, with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind. Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems. This valuable book summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. Readers learn the underlying details and mathematics of customized trading algorithms, as well as advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects. - Prepares readers to evaluate market impact models and assess performance across algorithms, traders, and brokers. - Helps readers design systems to manage algorithmic risk and dark pool uncertainty. - Summarizes an algorithmic decision making framework to ensure consistency between investment objectives and trading objectives.
