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Author: Henry E Parkins
Publisher: Independently Published
ISBN:
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
Unveil the Secrets of Profitable Trading with "AI in Stock Trading: The Secrets of Automated Investment Strategies"! Are you ready to unlock the power of artificial intelligence and revolutionize your approach to stock trading? Look no further than "AI in Stock Trading: The Secrets of Automated Investment Strategies." Dive into this comprehensive guide and embark on a transformative journey through the dynamic world of automated investment strategies. Discover the hidden secrets that top traders and hedge funds use to gain a competitive edge in today's fast-paced financial markets. From understanding the fundamentals of stock trading to mastering advanced AI algorithms, this book is your ultimate roadmap to success in the world of automated investing. Inside, you'll explore: Cutting-edge AI techniques: Learn how to harness the latest advancements in artificial intelligence, machine learning, and deep learning to develop powerful trading algorithms that outperform the competition. Data-driven strategies: Unlock the secrets of data preprocessing, feature engineering, and model optimization to extract actionable insights from financial data and make informed trading decisions. Practical applications: Dive into real-world case studies and examples that demonstrate how AI-driven trading systems can generate alpha, manage risk, and maximize returns in diverse market conditions. Ethical considerations: Navigate the ethical and regulatory challenges of AI in finance with confidence, ensuring compliance with industry standards and maintaining trust with investors. Whether you're a seasoned trader looking to enhance your strategies or a novice investor seeking to break into the world of automated trading, "AI in Stock Trading: The Secrets of Automated Investment Strategies" is your essential companion. Packed with actionable insights, expert advice, and proven techniques, this book is your key to unlocking the secrets of profitable trading in today's digital age. Don't miss out on this opportunity to transform your trading journey and take your investment strategies to new heights. Order your copy of "AI in Stock Trading: The Secrets of Automated Investment Strategies" today and embark on a path to financial success like never before!
Author: Henry E Parkins
Publisher: Independently Published
ISBN:
Category : Business & Economics
Languages : en
Pages : 0
Get Book
Book Description
Unveil the Secrets of Profitable Trading with "AI in Stock Trading: The Secrets of Automated Investment Strategies"! Are you ready to unlock the power of artificial intelligence and revolutionize your approach to stock trading? Look no further than "AI in Stock Trading: The Secrets of Automated Investment Strategies." Dive into this comprehensive guide and embark on a transformative journey through the dynamic world of automated investment strategies. Discover the hidden secrets that top traders and hedge funds use to gain a competitive edge in today's fast-paced financial markets. From understanding the fundamentals of stock trading to mastering advanced AI algorithms, this book is your ultimate roadmap to success in the world of automated investing. Inside, you'll explore: Cutting-edge AI techniques: Learn how to harness the latest advancements in artificial intelligence, machine learning, and deep learning to develop powerful trading algorithms that outperform the competition. Data-driven strategies: Unlock the secrets of data preprocessing, feature engineering, and model optimization to extract actionable insights from financial data and make informed trading decisions. Practical applications: Dive into real-world case studies and examples that demonstrate how AI-driven trading systems can generate alpha, manage risk, and maximize returns in diverse market conditions. Ethical considerations: Navigate the ethical and regulatory challenges of AI in finance with confidence, ensuring compliance with industry standards and maintaining trust with investors. Whether you're a seasoned trader looking to enhance your strategies or a novice investor seeking to break into the world of automated trading, "AI in Stock Trading: The Secrets of Automated Investment Strategies" is your essential companion. Packed with actionable insights, expert advice, and proven techniques, this book is your key to unlocking the secrets of profitable trading in today's digital age. Don't miss out on this opportunity to transform your trading journey and take your investment strategies to new heights. Order your copy of "AI in Stock Trading: The Secrets of Automated Investment Strategies" today and embark on a path to financial success like never before!
Author: Robert Harris
Publisher: Vintage
ISBN: 0307957950
Category : Fiction
Languages : en
Pages : 328
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Book Description
At the nexus of high finance and sophisticated computer programming, a terrifying future may be unfolding even now. Dr. Alex Hoffmann’s name is carefully guarded from the general public, but within the secretive inner circles of the ultrarich he is a legend. He has developed a revolutionary form of artificial intelligence that predicts movements in the financial markets with uncanny accuracy. His hedge fund, based in Geneva, makes billions. But one morning before dawn, a sinister intruder breaches the elaborate security of his lakeside mansion, and so begins a waking nightmare of paranoia and violence as Hoffmann attempts, with increasing desperation, to discover who is trying to destroy him. Fiendishly smart and suspenseful, The Fear Index gives us a searing glimpse into an all-too-recognizable world of greed and panic. It is a novel that forces us to confront the question of what it means to be human—and it is Robert Harris’s most spellbinding and audacious novel to date.
Author: Louis Mendelsohn
Publisher:
ISBN: 9781725871311
Category :
Languages : en
Pages : 180
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Book Description
This book explores the application of artificial intelligence - specifically deep machine learning neural networks - to intermarket analysis. It examines the role that intermarket analysis plays in assisting traders to identify trends and predict changes in trend directions and prices, in view of the unprecedented extent to which global financial markets have become interconnected and interdependent. This book will be of interest to both experienced traders and newcomers to the financial markets, who are inclined toward technical analysis and wish to benefit financially from the wealth creation opportunities in today's global financial markets.
Author: Laura Aubert
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
In the dynamic realm of financial markets, the intersection of artificial intelligence (AI) and stock trading has forged a formidable alliance, reshaping the landscape of investment strategies and market dynamics. "AI and Stock Trading: A Powerful Partnership" delves into the transformative synergy between cutting-edge artificial intelligence technologies and the intricate world of stock trading. This compelling exploration begins by unraveling the multifaceted ways in which AI has revolutionized traditional stock trading practices. The advent of machine learning algorithms, neural networks, and advanced data analytics has empowered investors with unprecedented insights and decision-making capabilities. From predictive analytics to sentiment analysis, AI-driven tools navigate the vast sea of financial data, uncovering hidden patterns and trends that elude human perception. The narrative unfolds with a spotlight on the diverse applications of AI in stock trading, showcasing how these technologies are employed to optimize trading strategies, mitigate risks, and maximize returns. Through algorithmic trading and robo-advisors, AI seamlessly integrates with financial systems, executing trades at lightning speed and adapting in real-time to market fluctuations. The symbiotic relationship between AI and stock trading transcends mere automation, fostering a dynamic ecosystem where human intuition and machine intelligence converge for enhanced financial outcomes. As the discussion progresses, the intricacies of AI-driven decision-making in stock trading are dissected. The role of natural language processing (NLP) in interpreting financial news and social media sentiment analysis provides a nuanced understanding of the factors influencing market behavior. The narrative navigates the ethical considerations and challenges associated with AI in stock trading, exploring questions of accountability, transparency, and the potential impact on market stability. "AI and Stock Trading: A Powerful Partnership" doesn't shy away from examining the limitations and risks inherent in this fusion of technology and finance. While AI augments decision-making capabilities, the unpredictability of financial markets and the complexity of human behavior pose ongoing challenges. The narrative also explores the role of regulatory frameworks in ensuring responsible AI integration in stock trading and maintaining market integrity. In conclusion, this comprehensive exploration offers a panoramic view of the evolving landscape where artificial intelligence and stock trading intersect. From the algorithms powering high-frequency trading to the ethical considerations shaping the future of financial markets, this title provides an insightful journey into the heart of a partnership that is reshaping the very foundations of stock trading. Investors, technologists, and financial enthusiasts alike will find "AI and Stock Trading: A Powerful Partnership" to be an indispensable guide to understanding the present and envisioning the future of finance.
Author: Tom Costello
Publisher: Https: //Www.Isbnservices.COM
ISBN: 9781637958476
Category :
Languages : en
Pages : 344
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Book Description
Getting into the Hedge Fund industry is hard, being successful in the hedge fund industry is even harder. But the most successful people in the hedge fund industry all have some ideas in common that often mean the difference between success and failure. The Front Office is a guide to those ideas. It's a manual for learning how to think about markets in the way that's most likely to lead to sustained success in the way that the top Institutions, Investment Banks and Hedge Funds do. Anyone can tell you how to register a corporation or how to connect to a lawyer or broker. This isn't a book about those 'back office' issues. This is a book about the hardest part of running a hedge fund. The part that the vast majority of small hedge funds and trading system developers never learn on their own. The part that the accountants, settlement clerks, and back office staffers don't ever see. It explains why some trading systems never reach profitability, why some can't seem to stay profitable, and what to do about it if that happens to you. This isn't a get rich quick book for your average investor. There are no easy answers in it. If you need someone to explain what a stock option is or what Beta means, you should look somewhere else. But if you think you're ready to reach for the brass ring of a career in the institutional investing world, this is an excellent guide. This book explains what those people see when they look at the markets, and what nearly all of the other investors never do.
Author: Yves Hilpisch
Publisher: O'Reilly Media
ISBN: 1492053325
Category : Computers
Languages : en
Pages : 380
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Book Description
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: Stefan Jansen
Publisher: Packt Publishing Ltd
ISBN: 1839216786
Category : Business & Economics
Languages : en
Pages : 822
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Book Description
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.
Author: Söhnke M. Bartram
Publisher: CFA Institute Research Foundation
ISBN: 195292703X
Category : Business & Economics
Languages : en
Pages : 95
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Book Description
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.
Author: Louis B. Mendelsohn
Publisher: Createspace Independent Publishing Platform
ISBN: 9781978216518
Category :
Languages : en
Pages : 168
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Book Description
This book explores the application of artificial intelligence - specifically deep machine learning neural networks - to intermarket analysis. It examines the role that intermarket analysis plays in assisting traders to identify trends and predict changes in trend directions and prices, in view of the unprecedented extent to which global financial markets have become interconnected and interdependent. This book will be of interest to both experienced traders and newcomers to the financial markets, who are inclined toward technical analysis and wish to benefit financially from the wealth creation opportunities in today's global financial markets.
Author: Gregory Zuckerman
Publisher: Penguin
ISBN: 0735217998
Category : Business & Economics
Languages : en
Pages : 401
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Book Description
NEW YORK TIMES BESTSELLER Shortlisted for the Financial Times/McKinsey Business Book of the Year Award The unbelievable story of a secretive mathematician who pioneered the era of the algorithm--and made $23 billion doing it. Jim Simons is the greatest money maker in modern financial history. No other investor--Warren Buffett, Peter Lynch, Ray Dalio, Steve Cohen, or George Soros--can touch his record. Since 1988, Renaissance's signature Medallion fund has generated average annual returns of 66 percent. The firm has earned profits of more than $100 billion; Simons is worth twenty-three billion dollars. Drawing on unprecedented access to Simons and dozens of current and former employees, Zuckerman, a veteran Wall Street Journal investigative reporter, tells the gripping story of how a world-class mathematician and former code breaker mastered the market. Simons pioneered a data-driven, algorithmic approach that's sweeping the world. As Renaissance became a market force, its executives began influencing the world beyond finance. Simons became a major figure in scientific research, education, and liberal politics. Senior executive Robert Mercer is more responsible than anyone else for the Trump presidency, placing Steve Bannon in the campaign and funding Trump's victorious 2016 effort. Mercer also impacted the campaign behind Brexit. The Man Who Solved the Market is a portrait of a modern-day Midas who remade markets in his own image, but failed to anticipate how his success would impact his firm and his country. It's also a story of what Simons's revolution means for the rest of us.
