Author: Louis B. Mendelsohn
Publisher: Createspace Independent Publishing Platform
ISBN: 9781978216518
Category :
Languages : en
Pages : 168
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.
Profitable Trading with Artificial Intelligence
Author: Louis B. Mendelsohn
Publisher: Createspace Independent Publishing Platform
ISBN: 9781978216518
Category :
Languages : en
Pages : 168
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.
Publisher: Createspace Independent Publishing Platform
ISBN: 9781978216518
Category :
Languages : en
Pages : 168
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.
Machine Learning for Algorithmic Trading
Author: Stefan Jansen
Publisher: Packt Publishing Ltd
ISBN: 1839216786
Category : Business & Economics
Languages : en
Pages : 822
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.
Publisher: Packt Publishing Ltd
ISBN: 1839216786
Category : Business & Economics
Languages : en
Pages : 822
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.
The Front Office
Author: Tom Costello
Publisher: Https: //Www.Isbnservices.COM
ISBN: 9781637958476
Category :
Languages : en
Pages : 344
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.
Publisher: Https: //Www.Isbnservices.COM
ISBN: 9781637958476
Category :
Languages : en
Pages : 344
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.
Artificial Intelligence for Stock Traders: How XGPT is Changing the Game
Author: Jeffery W Long
Publisher: Jeffery William Long
ISBN:
Category : Computers
Languages : en
Pages : 59
Book Description
Artificial Intelligence for Stock Traders: How XGPT is Changing the Game Chapter 1. Introduction to XGTP and Stock Trading In this chapter, we will introduce you to the exciting world of XGPT artificial intelligence stock trading and explore how it is revolutionizing the game. Whether you are a seasoned trader looking to enhance your strategies or a beginner eager to learn more about the power of AI in the stock market, this chapter is the perfect place to start your journey into the future of trading. Join us as we delve deeper into the cutting-edge technology that is reshaping the way we approach investing, providing insights and tools that can help you navigate the ever-changing landscape of the stock market with confidence and success. Get ready to unlock the potential of AI in trading and take your financial goals to new heights with XGPT artificial intelligence. With the advancements in AI technology, traders can now leverage sophisticated algorithms and machine learning capabilities to make more informed decisions, optimize their trading strategies, and stay ahead of market trends. The integration of AI in stock trading not only enhances efficiency and accuracy but also opens up new opportunities for both experienced investors and newcomers to explore and capitalize on. By embracing the power of AI, traders can gain a competitive edge in the fast-paced world of stock market trading, allowing them to adapt to market changes swiftly and make smarter investment choices. The future of trading is here, and with XGPT artificial intelligence, the possibilities for success are endless.
Publisher: Jeffery William Long
ISBN:
Category : Computers
Languages : en
Pages : 59
Book Description
Artificial Intelligence for Stock Traders: How XGPT is Changing the Game Chapter 1. Introduction to XGTP and Stock Trading In this chapter, we will introduce you to the exciting world of XGPT artificial intelligence stock trading and explore how it is revolutionizing the game. Whether you are a seasoned trader looking to enhance your strategies or a beginner eager to learn more about the power of AI in the stock market, this chapter is the perfect place to start your journey into the future of trading. Join us as we delve deeper into the cutting-edge technology that is reshaping the way we approach investing, providing insights and tools that can help you navigate the ever-changing landscape of the stock market with confidence and success. Get ready to unlock the potential of AI in trading and take your financial goals to new heights with XGPT artificial intelligence. With the advancements in AI technology, traders can now leverage sophisticated algorithms and machine learning capabilities to make more informed decisions, optimize their trading strategies, and stay ahead of market trends. The integration of AI in stock trading not only enhances efficiency and accuracy but also opens up new opportunities for both experienced investors and newcomers to explore and capitalize on. By embracing the power of AI, traders can gain a competitive edge in the fast-paced world of stock market trading, allowing them to adapt to market changes swiftly and make smarter investment choices. The future of trading is here, and with XGPT artificial intelligence, the possibilities for success are endless.
Profitable Trading Strategies
Author: Anil Hanegave
Publisher: ANIL HANEGAVE
ISBN:
Category : Business & Economics
Languages : en
Pages : 89
Book Description
This is Part Two of Profitable Trading Strategies This book is a beginner's guide to stock market investing and making a profit with Intraday Trading Strategies + Swing Trading Strategies. Benefits of Reading This Book: 1. Become profitable in stock market trading 2. Systematic approach to Intraday Trading. 3. Six secret trading strategies based on weekly and Daily CPR indicators + Advanced price action, moving averages 4. Weekly CPR and Daily Concept to identify trap zones. Who can Read this Book? 1. Beginners to full-time traders, 2. Dday traders, swing traders, and investors. Benefits of Premium secret trading Strategies : 1. Defined entry, stop loss, and take profit ( exit) rules, 2. More than 40 Charts & with real-life examples. Bonus 1. Build confident trading psychology 2. Make a fortune in the stock market
Publisher: ANIL HANEGAVE
ISBN:
Category : Business & Economics
Languages : en
Pages : 89
Book Description
This is Part Two of Profitable Trading Strategies This book is a beginner's guide to stock market investing and making a profit with Intraday Trading Strategies + Swing Trading Strategies. Benefits of Reading This Book: 1. Become profitable in stock market trading 2. Systematic approach to Intraday Trading. 3. Six secret trading strategies based on weekly and Daily CPR indicators + Advanced price action, moving averages 4. Weekly CPR and Daily Concept to identify trap zones. Who can Read this Book? 1. Beginners to full-time traders, 2. Dday traders, swing traders, and investors. Benefits of Premium secret trading Strategies : 1. Defined entry, stop loss, and take profit ( exit) rules, 2. More than 40 Charts & with real-life examples. Bonus 1. Build confident trading psychology 2. Make a fortune in the stock market
Cybernetic Trading Strategies
Author: Murray A. Ruggiero
Publisher: John Wiley & Sons
ISBN: 9780471149200
Category : Business & Economics
Languages : en
Pages : 344
Book Description
Ein Überblick über die aktuellsten Technologien zum Aufbau einer Handelsstrategie: neuronale Netzwerke, genetische Algorithmen, Expertensysteme, Fuzzy logic und statistische Mustererkennung. Gezeigt wird, wie diese neuen Methoden in klassische Analysenverfahren integriert werden können. Auch Erläuterungen zur Prüfung und Bewertung existierender Systeme kommen nicht zu kurz.
Publisher: John Wiley & Sons
ISBN: 9780471149200
Category : Business & Economics
Languages : en
Pages : 344
Book Description
Ein Überblick über die aktuellsten Technologien zum Aufbau einer Handelsstrategie: neuronale Netzwerke, genetische Algorithmen, Expertensysteme, Fuzzy logic und statistische Mustererkennung. Gezeigt wird, wie diese neuen Methoden in klassische Analysenverfahren integriert werden können. Auch Erläuterungen zur Prüfung und Bewertung existierender Systeme kommen nicht zu kurz.
MACHINE LEARNING FOR ALGORITHMIC TRADING
Author: Jason Test
Publisher:
ISBN: 9789918608003
Category : Computers
Languages : en
Pages : 424
Book Description
Master the best methods for PYTHON. Learn how to programming as a pro and get positive ROI in 7 days with data science and machine learning Are you looking for a super-fast computer programming course? Would you like to learn the Python Programming Language in 7 days? Do you want to increase your trading thanks to the artificial intelligence? If so, keep reading: this bundle book is for you! Today, thanks to computer programming and PYTHON we can work with sophisticated machines that can study human behavior and identify underlying human behavioral patterns. Scientists can predict effectively what products and services consumers are interested in. You can also create various quantitative and algorithmic trading strategies using Python. It is getting increasingly challenging for traditional businesses to retain their customers without adopting one or more of the cutting-edge technology explained in this book. MACHINE LEARNING FOR ALGORITHM TRADING will introduce you many selected tips and breaking down the basics of coding applied to finance. You will discover as a beginner the world of data science, machine learning and artificial intelligence with step-by-step guides that will guide you during the code-writing learning process. The following list is just a tiny fraction of what you will learn in this bundle PYTHON FOR BEGINNERS ✅ Differences among programming languages: Vba, SQL, R, Python ✅ 3 reasons why Python is fundamental for Data Science ✅ Introduction to some Python libraries like NumPy, Pandas, Matplotlib, ✅ 3 step system why Python is fundamental for Data Science ✅Describe the steps required to develop and test an ML-driven trading strategy. PYTHON DATA SCIENCE ✅ A Proven Method to Write your First Program in 7 Days ✅ 3 Common Mistakes to Avoid when You Start Coding ✅ Fit Python Data Analysis to your business ✅ 7 Most effective Machine Learning Algorithms ✅ Describe the methods used to optimize an ML-driven trading strategy. OPTIONS TRADING FOR BEGINNERS ✅ Options Trading Strategies that guarantee real results in all market conditions ✅ Top 7 endorsed indicators of a successful investment ✅ The Bull & Bear Game ✅ Learn about the 3 best charts patterns to fluctuations of stock prices DAY AND SWING TRADING ✅ How Swing trading differs from Day trading in terms of risk-aversion ✅ How your money should be invested and which trade is more profitable ✅ Swing and Day trading proven indicators to learn investment timing ✅ The secret DAY trading strategies leading to a gain of $ 9,000 per month and more than $100,000 per year. Even if you have never written a programming code before, you will quickly grasp the basics thanks to visual charts and guidelines for coding. Today is the best day to start programming like a pro. For those trading with leverage, looking for a way to take a controlled approach and manage risk, a properly designed trading system is the answer If you really wish to learn MACHINE LEARNING FOR ALGORITHMIC TRADING and master its language, please click the BUY NOW button.
Publisher:
ISBN: 9789918608003
Category : Computers
Languages : en
Pages : 424
Book Description
Master the best methods for PYTHON. Learn how to programming as a pro and get positive ROI in 7 days with data science and machine learning Are you looking for a super-fast computer programming course? Would you like to learn the Python Programming Language in 7 days? Do you want to increase your trading thanks to the artificial intelligence? If so, keep reading: this bundle book is for you! Today, thanks to computer programming and PYTHON we can work with sophisticated machines that can study human behavior and identify underlying human behavioral patterns. Scientists can predict effectively what products and services consumers are interested in. You can also create various quantitative and algorithmic trading strategies using Python. It is getting increasingly challenging for traditional businesses to retain their customers without adopting one or more of the cutting-edge technology explained in this book. MACHINE LEARNING FOR ALGORITHM TRADING will introduce you many selected tips and breaking down the basics of coding applied to finance. You will discover as a beginner the world of data science, machine learning and artificial intelligence with step-by-step guides that will guide you during the code-writing learning process. The following list is just a tiny fraction of what you will learn in this bundle PYTHON FOR BEGINNERS ✅ Differences among programming languages: Vba, SQL, R, Python ✅ 3 reasons why Python is fundamental for Data Science ✅ Introduction to some Python libraries like NumPy, Pandas, Matplotlib, ✅ 3 step system why Python is fundamental for Data Science ✅Describe the steps required to develop and test an ML-driven trading strategy. PYTHON DATA SCIENCE ✅ A Proven Method to Write your First Program in 7 Days ✅ 3 Common Mistakes to Avoid when You Start Coding ✅ Fit Python Data Analysis to your business ✅ 7 Most effective Machine Learning Algorithms ✅ Describe the methods used to optimize an ML-driven trading strategy. OPTIONS TRADING FOR BEGINNERS ✅ Options Trading Strategies that guarantee real results in all market conditions ✅ Top 7 endorsed indicators of a successful investment ✅ The Bull & Bear Game ✅ Learn about the 3 best charts patterns to fluctuations of stock prices DAY AND SWING TRADING ✅ How Swing trading differs from Day trading in terms of risk-aversion ✅ How your money should be invested and which trade is more profitable ✅ Swing and Day trading proven indicators to learn investment timing ✅ The secret DAY trading strategies leading to a gain of $ 9,000 per month and more than $100,000 per year. Even if you have never written a programming code before, you will quickly grasp the basics thanks to visual charts and guidelines for coding. Today is the best day to start programming like a pro. For those trading with leverage, looking for a way to take a controlled approach and manage risk, a properly designed trading system is the answer If you really wish to learn MACHINE LEARNING FOR ALGORITHMIC TRADING and master its language, please click the BUY NOW button.
Automation of Trading Machine for Traders
Author: Jacinta Chan
Publisher: Springer Nature
ISBN: 981139945X
Category : Business & Economics
Languages : en
Pages : 143
Book Description
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.
Publisher: Springer Nature
ISBN: 981139945X
Category : Business & Economics
Languages : en
Pages : 143
Book Description
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.
Artificial Intelligence in Finance
Author: Yves Hilpisch
Publisher: "O'Reilly Media, Inc."
ISBN: 1492055387
Category : Business & Economics
Languages : en
Pages : 478
Book Description
The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about
Publisher: "O'Reilly Media, Inc."
ISBN: 1492055387
Category : Business & Economics
Languages : en
Pages : 478
Book Description
The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about
The Man Who Solved the Market
Author: Gregory Zuckerman
Publisher: Penguin
ISBN: 0735217998
Category : Business & Economics
Languages : en
Pages : 401
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.
Publisher: Penguin
ISBN: 0735217998
Category : Business & Economics
Languages : en
Pages : 401
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.