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AI After Hours Trading: A Comprehensive Guide
Author: Dr. Evelyn Reed, PhD in Computational Finance, 15+ years experience in algorithmic trading and AI applications in financial markets.
Publisher: Investopedia Insights – A leading provider of financial education and analysis, specializing in cutting-edge investment strategies.
Editor: Mark Johnson, CFA, 20+ years experience in financial journalism and market analysis.
Summary: This guide explores the burgeoning field of AI after hours trading, detailing its potential benefits and inherent risks. We examine best practices for leveraging AI algorithms in extended trading sessions, including data selection, model validation, and risk management. The guide also addresses common pitfalls and ethical considerations associated with this advanced trading strategy. By understanding the nuances of AI after hours trading, investors can make informed decisions about integrating this technology into their investment strategies.
Keywords: AI after hours trading, AI stock trading, after-hours trading strategies, algorithmic trading, extended hours trading, AI investment, artificial intelligence finance, machine learning finance, high-frequency trading, risk management in AI trading.
Introduction:
The financial markets are increasingly embracing artificial intelligence (AI) to enhance trading strategies. While AI-powered day trading is relatively well-established, the application of AI in after-hours trading presents unique opportunities and challenges. This guide delves into the intricacies of AI after hours trading, providing a comprehensive understanding of its potential and pitfalls. After-hours trading, encompassing the period between the regular trading session's close and the next day's opening, offers a unique environment for AI-driven strategies. However, navigating this market requires careful consideration of specific factors that differentiate it from regular market hours.
H1: Understanding the Unique Landscape of AI After Hours Trading
After-hours trading is characterized by lower liquidity and increased volatility compared to regular trading hours. This environment demands robust AI algorithms capable of adapting to these changing conditions. News announcements, earnings reports, and significant geopolitical events often trigger substantial price swings during after-hours trading, creating both opportunities and risks. AI algorithms can process and react to this information far faster than human traders, potentially capitalizing on fleeting price discrepancies. However, the reduced liquidity means that large trades might be difficult to execute without significant slippage.
H2: Data Selection and Preprocessing for AI After Hours Trading
The success of any AI after-hours trading strategy hinges on the quality and relevance of the data used to train the algorithms. This includes not only historical price data but also news sentiment analysis, social media data, and economic indicators. Preprocessing this data is crucial; noisy or incomplete data can lead to inaccurate predictions and significant losses. Techniques such as data cleaning, normalization, and feature engineering are essential for creating a reliable dataset for AI model training. The focus should be on data sources that are specifically relevant to after-hours trading activity, recognizing that the patterns and relationships might differ significantly from regular trading hours.
H3: Algorithm Selection and Model Validation
Various AI algorithms can be employed for after-hours trading, including recurrent neural networks (RNNs), long short-term memory networks (LSTMs), and reinforcement learning models. The choice depends on the specific trading strategy and the complexity of the market dynamics being modeled. Rigorous model validation is critical to ensure the algorithm's performance and avoid overfitting. Backtesting on historical after-hours data is essential, but it's crucial to account for the inherent limitations of backtesting, especially in a low-liquidity environment. Out-of-sample testing, using data not included in the training set, provides a more realistic evaluation of the model's predictive power.
H4: Risk Management in AI After Hours Trading
Risk management is paramount in AI after-hours trading, given the heightened volatility and lower liquidity. Strategies like position sizing, stop-loss orders, and diversification are crucial to mitigate potential losses. AI algorithms themselves can incorporate risk management parameters, adjusting trading positions based on real-time market conditions and risk thresholds. Regular monitoring and evaluation of the algorithm's performance and risk profile are essential. A robust risk management framework should incorporate both quantitative and qualitative aspects, considering not only potential financial losses but also the ethical implications of the AI's trading decisions.
H5: Common Pitfalls of AI After Hours Trading
Several pitfalls can hinder the effectiveness of AI after-hours trading strategies. Overfitting, as mentioned earlier, is a significant concern. Using insufficient or biased data can also lead to inaccurate predictions. Ignoring the limitations of backtesting and failing to account for the unique characteristics of after-hours trading can also lead to significant losses. Furthermore, the lack of liquidity can result in slippage and difficulty executing trades at desired prices. Finally, neglecting ethical considerations and the potential for market manipulation through algorithmic trading warrants careful attention.
H6: Ethical Considerations in AI After Hours Trading
The use of AI in after-hours trading raises ethical questions regarding fairness, transparency, and market manipulation. Ensuring algorithmic trading systems adhere to regulatory guidelines and prevent unfair advantages is critical. The potential for high-frequency trading (HFT) strategies using AI in after-hours trading necessitates robust regulatory frameworks to prevent market manipulation and ensure fair access for all participants.
Conclusion:
AI after-hours trading presents significant opportunities for sophisticated investors who understand the inherent complexities. By employing best practices in data selection, algorithm development, risk management, and ethical considerations, investors can leverage the power of AI to potentially improve their after-hours trading performance. However, it's crucial to remember that AI is a tool; its success hinges on the understanding, experience, and responsible application of the user. Continuous monitoring, adaptation, and a deep understanding of the market dynamics are vital for successful AI after-hours trading.
FAQs:
1. What are the main differences between AI day trading and AI after-hours trading? The key differences lie in liquidity, volatility, and the type of data relevant for prediction. After-hours trading has lower liquidity and higher volatility, requiring algorithms robust enough to handle these conditions. The data used may also differ, focusing on news events and announcements impacting overnight price movements.
2. What type of AI algorithms are best suited for after-hours trading? RNNs, LSTMs, and reinforcement learning models are suitable, but the choice depends on specific strategy needs.
3. How can I mitigate the risk of overfitting in my AI after-hours trading model? Employ rigorous model validation techniques like out-of-sample testing and cross-validation. Use regularization techniques to prevent overfitting.
4. What are the ethical concerns surrounding AI after-hours trading? Concerns include market manipulation, unfair access, and transparency issues regarding algorithmic decision-making.
5. What is the role of news sentiment analysis in AI after-hours trading? News sentiment analysis can identify market-moving information from news sources and social media, enabling quicker response to relevant events.
6. How can I measure the performance of my AI after-hours trading strategy? Use metrics like Sharpe ratio, Sortino ratio, maximum drawdown, and win rate. Consider both absolute and risk-adjusted returns.
7. What is the impact of low liquidity on AI after-hours trading? Low liquidity can lead to slippage, impacting the execution of trades at desired prices. It also demands stricter risk management.
8. How does backtesting differ in AI after-hours trading? Backtesting requires a focus on historical after-hours data and should account for the distinct characteristics of this period (lower volume, higher volatility).
9. What are the regulatory considerations for AI after-hours trading? Regulatory compliance is critical, particularly concerning high-frequency trading and the prevention of market manipulation.
Related Articles:
1. "Optimizing LSTM Networks for AI After-Hours Trading": Explores the application of LSTMs and their hyperparameter tuning for superior after-hours trading performance.
2. "Risk Management Strategies for AI-Driven After-Hours Trading": A deep dive into advanced risk management techniques specific to the challenges of after-hours trading.
3. "The Role of News Sentiment Analysis in AI After-Hours Trading Algorithms": Details how sentiment analysis from news and social media can improve predictive accuracy.
4. "Ethical Considerations and Regulatory Frameworks for AI After-Hours Trading": Examines ethical and regulatory implications of AI algorithms in this market segment.
5. "Comparing Different AI Algorithms for After-Hours Trading: A Performance Analysis": A comparative study of various AI models and their suitability for after-hours trading.
6. "The Impact of Low Liquidity on Algorithmic After-Hours Trading Strategies": Focuses on how low liquidity affects algorithmic trading and strategies to mitigate the risks.
7. "Data Preprocessing Techniques for Enhanced AI After-Hours Trading Models": Detailed explanation of effective data preprocessing methods for improving model accuracy.
8. "Backtesting AI After-Hours Trading Strategies: Best Practices and Pitfalls": A guide on effective backtesting methodologies and how to avoid common errors.
9. "Case Studies: Successful AI After-Hours Trading Strategies": Presents real-world examples of successful AI applications in after-hours trading, detailing their methodologies and outcomes.
| ai after hours trading: Dark Pools Scott Patterson, 2012-06-12 A news-breaking account of the global stock market's subterranean battles, Dark Pools portrays the rise of the bots--artificially intelligent systems that execute trades in milliseconds and use the cover of darkness to out-maneuver the humans who've created them. In the beginning was Josh Levine, an idealistic programming genius who dreamed of wresting control of the market from the big exchanges that, again and again, gave the giant institutions an advantage over the little guy. Levine created a computerized trading hub named Island where small traders swapped stocks, and over time his invention morphed into a global electronic stock market that sent trillions in capital through a vast jungle of fiber-optic cables. By then, the market that Levine had sought to fix had turned upside down, birthing secretive exchanges called dark pools and a new species of trading machines that could think, and that seemed, ominously, to be slipping the control of their human masters. Dark Pools is the fascinating story of how global markets have been hijacked by trading robots--many so self-directed that humans can't predict what they'll do next. |
| ai after hours trading: The Front Office Tom Costello, 2021-02-05 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. |
| ai after hours trading: Overcome AI Scott Gamm, 2020-09-29 YOUR GUIDE TO SURVIVING AND THRIVING IN THE AI ECONOMY. No one can be completely sure what the future of work is going to look like, but it will likely be completely transformed by artificial intelligence. That means an uncertain future for Millennials, including the need to switch jobs, change occupations and learn new skills. Taking steps towards financial freedom and early retirement now, on your own terms, will put you in the driver's seat for what could be a bumpy road ahead. In OVERCOME AI, Wall Street expert Scott Gamm sets out a practical roadmap to financial freedom and early retirement. Discover: Why retiring early will become a necessity, not just a goal. How much money you'll need to live well without a steady 9-5 job. The importance of reducing or eliminating debt. How to invest in the stock market. How to use alternative retirement savings vehicles. OVERCOME AI is full of actionable investing information that can be applied within minutes of reading. This is truly the first book to provide a clear plan for wealth-building and financial security in the automation era. |
| ai after hours trading: Following the Trend Andreas F. Clenow, 2012-11-21 During bull and bear markets, there is a group of hedge funds and professional traders which have been consistently outperforming traditional investment strategies for the past 30 odd years. They have shown remarkable uncorrelated performance and in the great bear market of 2008 they had record gains. These traders are highly secretive about their proprietary trading algorithms and often employ top PhDs in their research teams. Yet, it is possible to replicate their trading performance with relatively simplistic models. These traders are trend following cross asset futures managers, also known as CTAs. Many books are written about them but none explain their strategies in such detail as to enable the reader to emulate their success and create their own trend following trading business, until now. Following the Trend explains why most hopefuls fail by focusing on the wrong things, such as buy and sell rules, and teaches the truly important parts of trend following. Trading everything from the Nasdaq index and T-bills to currency crosses, platinum and live hogs, there are large gains to be made regardless of the state of the economy or stock markets. By analysing year by year trend following performance and attribution the reader will be able to build a deep understanding of what it is like to trade futures in large scale and where the real problems and opportunities lay. Written by experienced hedge fund manager Andreas Clenow, this book provides a comprehensive insight into the strategies behind the booming trend following futures industry from the perspective of a market participant. The strategies behind the success of this industry are explained in great detail, including complete trading rules and instructions for how to replicate the performance of successful hedge funds. You are in for a potentially highly profitable roller coaster ride with this hard and honest look at the positive as well as the negative sides of trend following. |
| ai after hours trading: Advanced Techniques For Using AI to Master Crypto Jeffery W Long, 2024-08-21 Advanced Techniques For Using AI to Master Crypto Chapter 1: Introduction to Cryptocurrency Introduction to Cryptocurrency Cryptocurrency has emerged as one of the most revolutionary financial innovations of the 21st century. At its core, cryptocurrency represents digital or virtual currencies that rely on cryptographic principles to secure transactions, regulate issuance, and authenticate transfer of assets. Established in 2009 with the introduction of Bitcoin by an enigmatic figure known as Satoshi Nakamoto, cryptocurrency has since evolved into a multifaceted domain encompassing various aspects of finance and technology. Cryptocurrency owes its existence to the failure and limitations of traditional financial systems. In 2008, the financial crisis exposed the inherent vulnerabilities of centralized banking and the mistrust surrounding monetary institutions. It was against this backdrop that Bitcoin, the first decentralized cryptocurrency, was conceived. By implementing blockchain technology, Bitcoin established the foundation for a new kind of currency free from the control of central authorities and immune to the pitfalls of traditional financial institutions. The impact of cryptocurrencies on modern financial systems cannot be overstated. Cryptocurrencies facilitate peer-to-peer transactions independent of intermediaries, bringing about cost efficiency and speed in transferring funds. As the public becomes increasingly aware of the benefits and potential of cryptocurrencies, the landscape of global finance is undergoing a transformative shift, heralding the advent of a decentralized economy. |
| ai after hours trading: Introduction to Econometrics G. S. Maddala, 2001-05-08 Introduction to Econometrics has been significantly revised to include new developments in the field. The previous editions of this text were renowned for Maddala's clear exposition and the presentation of concepts in an easily accessible manner. Features: * New chapters have been included on panel data analysis, large sample inference and small sample inference * Chapter 14 Unit Roots and Cointegration has been rewritten to reflect recent developments in the Dickey-Fuller (DF), the Augmented Dickey-Fuller (ADF) tests and the Johansen procedure * A selection of data sets and the instructor's manual for the book can be found on our web site Comments on the previous edition: 'Maddala is an outstanding econometrician who has a deep understaning of the use and potential abuse of econometrics...' 'The strengths of the Maddala book are its simplicity, its accessibility and the large number of examples the book contains...' 'The second edition is well written and the chapters are focused and easy to follow from beginning to end. Maddala has an oustanding grasp of the issues, and the level of mathematics and statistics is appropriate as well.' |
| ai after hours trading: Intelligent Networks Dimitris N. Chorafas, 2019-08-08 Intelligent Networks: Telecommunications Solutions for the 1990s addresses the telecommunications perspective of the 1990s and the problems involved in the transition from where we are now to where we should be within the next decade. It will appeal to managers as well as specialists interested in how communications and information technologies will evolve during the coming five to seven years. Valuable information on how they can use the new products becoming available to their company's advantage is also provided. This book is divided into two parts: Part 1 focuses on the strategic aspects of Intelligent Networks, while Part 2 looks into the dynamics and mechanics of computer networks and focuses on transition. Topics discussed in Part 1 include a look into advanced projects currently under development in the U.S. and Japan; the next big steps in deregulation from the viewpoint of the Federal Communications Commission; Artificial Intelligence (AI) implementation in network operations; the establishment of global private networks with AI as the infrastructure; and a discussion regarding the merits of open architectures, ISDN, teleports and bypass, and photonics. Topics discussed in Part 2 include system integration; a case study of Union Bank of Switzerland and how an Intelligent Network documentation database can be used to increase the quality of network design, improve upon the reliability of its implementation, automate diagnostics and facilitate maintenance, provide quality histories for different vendors, and swamp the costs associated with networking. Part 2 also includes a discussion regarding the prerequisites for system reliability; management's role in cost-effectiveness; telecommunications tariffs and the architectural impact on costing; and how to tips for negotiating with vendors. |
| ai after hours trading: The Complete Penny Stock Course Jamil Ben Alluch, 2018-04-09 You can learn trading penny stocks from the masses and become part of the 90% of traders who lose money in the stock market, or you can learn from the Best. The Complete Penny Stock Course is based on Timothy Sykes’, various training programs. His strategies have helped individuals like Tim Grittani, Michael Goode and Stephen Dux become millionaires within a couple of years. This course aims to teach you how to become a consistently profitable trader, by taking Tim’s profit-making strategies with penny stocks and presenting them in a well-structured learning format. You’ll start by getting acquainted with the concepts of market and trading psychology. Then you’ll get into the basics of day trading, how to manage your risk and the tools that will help you become profitable. Along the way, you’ll learn strategies and techniques to become consistent in your gains and develop your own trading techniques. What’s inside: - Managing expectations and understanding the market, - Understanding the psychology of trading and how it affects you, - Learning the basics of day trading, - Learning the mechanics of trading penny stocks, - Risk management and how to take safe positions, - How to trade through advanced techniques - Developing your own profitable trading strategy - Real world examples and case studies No prior trading experience is required. |
| ai after hours trading: Machine Learning for Algorithmic Trading Stefan Jansen, 2020-07-31 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. |
| ai after hours trading: Aum Golly: Poems on Humanity by an Artificial Intelligence Gpt- Ai, Jukka Aalho, 2021-10-09 What does AI know about love, happiness and making a difference? Aum Golly is a book of poems written in 24 hours. It was made possible by GPT-3 - an advanced autoregressive language model published in 2020 by OpenAI. ... a collection that surprises with humor and delicateness... - Goodreads review ... I have to say reading it was a pleasure... - Finnish radio host Ruben Stiller on Yle ... a beautiful dialogue between man and machine... - a review of the Finnish audiobook The deep learning model can generate text that is virtually indistinguishable from text written by humans: poems, recipes, summaries, legal text and even pieces of code. GPT-3 is autofill on steroids. Good poetry makes us feel something and see the world differently. Despite the gut reaction some of us may have towards AI-enhanced creativity, Aum Golly is a book like any other. You will love some of the poems. You will hate others. Some will make you wonder, but all of them will make you think. Award-winning writer and TEDx speaker Jukka Aalho has guided the AI and chosen the poems for the collection. |
| ai after hours trading: AI and Financial Markets Shigeyuki Hamori, Tetsuya Takiguchi, 2020-07-01 Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of “AI and Financial Markets”, and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets. |
| ai after hours trading: SEC Docket United States. Securities and Exchange Commission, 2002 |
| ai after hours trading: Artificial Intelligence and International Economic Law Shin-yi Peng, Ching-Fu Lin, Thomas Streinz, 2021-10-14 Artificial intelligence (AI) technologies are transforming economies, societies, and geopolitics. Enabled by the exponential increase of data that is collected, transmitted, and processed transnationally, these changes have important implications for international economic law (IEL). This volume examines the dynamic interplay between AI and IEL by addressing an array of critical new questions, including: How to conceptualize, categorize, and analyze AI for purposes of IEL? How is AI affecting established concepts and rubrics of IEL? Is there a need to reconfigure IEL, and if so, how? Contributors also respond to other cross-cutting issues, including digital inequality, data protection, algorithms and ethics, the regulation of AI-use cases (autonomous vehicles), and systemic shifts in e-commerce (digital trade) and industrial production (fourth industrial revolution). This title is also available as Open Access on Cambridge Core. |
| ai after hours trading: Artificial Intelligence in Financial Markets Christian L. Dunis, Peter W. Middleton, Andreas Karathanasopolous, Konstantinos Theofilatos, 2016-11-21 As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field. |
| ai after hours trading: Revolutionizing Business Practices Through Artificial Intelligence and Data-Rich Environments Gupta, Manisha, Sharma, Deergha, Gupta, Himani, 2022-09-07 Throughout the world, artificial intelligence is reshaping businesses, trade interfaces, economic activities, and society as a whole. In recent years, scholarly research on artificial intelligence has emerged from a variety of empirical and applied domains of knowledge. Computer scientists have developed advanced deep learning algorithms to leverage its utility in a variety of fields such as medicine, energy, travel, education, banking, and business management. Although a growing body of literature is shedding light on artificial intelligence-enabled difficulties, there is still much to be gained by applying fresh theory-driven techniques to this vital topic. Revolutionizing Business Practices Through Artificial Intelligence and Data-Rich Environments provides a comprehensive understanding of the business systems, platforms, procedures, and mechanisms that underpin different stakeholders' experiences with reality-enhancing technologies and their transformative application in management. The book also identifies areas in various business processes where artificial intelligence intervention would not only transform the business but would also make the business more sustainable. Covering key topics such as blockchain, business automation, and manufacturing, this reference work is ideal for computer scientists, business owners, managers, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students. |
| ai after hours trading: Handbook of Alternative Data in Finance, Volume I Gautam Mitra, Christina Erlwein-Sayer, Kieu Thi Hoang, Diana Roman, Zryan Sadik, 2023-07-12 Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, difference from conventional data, categories of Alternative Data, Alternative Data providers, and more. The book also offers a rigorous and detailed exploration of process, application and delivery that should be practically useful to researchers and practitioners alike. Features Includes cutting edge applications in machine learning, fintech, and more Suitable for professional quantitative analysts, and as a resource for postgraduates and researchers in financial mathematics Features chapters from many leading researchers and practitioners |
| ai after hours trading: Encyclopedia of Artificial Intelligence Philip L. Frana, Michael J. Klein, 2021-04-07 This authoritative reference work will provide readers with a complete overview of artificial intelligence (AI), including its historic development and current status, existing and projected AI applications, and present and potential future impact on the United States and the world. Some people believe that artificial intelligence (AI) will revolutionize modern life in ways that improve human existence. Others say that the promise of AI is overblown. Still others contend that AI applications could pose a grave threat to the economic security of millions of people by taking their jobs and otherwise rendering them obsolete-or, even worse, that AI could actually spell the end of the human race. This volume will help users understand the reasons AI development has both spirited defenders and alarmed critics; explain theories and innovations like Moore's Law, mindcloning, and Technological Singularity that drive AI research and debate; and give readers the information they need to make their own informed judgment about the promise and peril of this technology. All of this coverage is presented using language and terminology accessible to a lay audience. |
| ai after hours trading: Computerworld , 1989-04-17 For more than 40 years, Computerworld has been the leading source of technology news and information for IT influencers worldwide. Computerworld's award-winning Web site (Computerworld.com), twice-monthly publication, focused conference series and custom research form the hub of the world's largest global IT media network. |
| ai after hours trading: Computerworld , 1999-05-31 For more than 40 years, Computerworld has been the leading source of technology news and information for IT influencers worldwide. Computerworld's award-winning Web site (Computerworld.com), twice-monthly publication, focused conference series and custom research form the hub of the world's largest global IT media network. |
| ai after hours trading: Trading Price Action Trends Al Brooks, 2011-11-29 A practical guide to profiting from institutional trading trends The key to being a successful trader is finding a system that works and sticking with it. Author Al Brooks has done just that. By simplifying his trading system and trading only 5-minute price charts he's found a way to capture profits regardless of market direction or economic climate. His first book, Reading Price Charts Bar by Bar, offered an informative examination of his system, but it didn't allow him to get into the real nuts and bolts of the approach. Now, with this new series of books, Brooks takes you step by step through the entire process. By breaking down his trading system into its simplest pieces: institutional piggybacking or trend trading (the topic of this particular book in the series), trading ranges, and transitions or reversals, this three book series offers access to Brooks' successful methodology. Price Action Trends Bar by Bar describes in detail what individual bars and combinations of bars can tell a trader about what institutions are doing. This is critical because the key to making money in trading is to piggyback institutions and you cannot do that unless you understand what the charts are telling you about their behavior. This book will allow you to see what type of trend is unfolding, so can use techniques that are specific to that type of trend to place the right trades. Discusses how to profit from institutional trading trends using technical analysis Outlines a detailed and original trading approach developed over the author's successful career as an independent trader Other books in the series include Price Action Trading Ranges Bar by Bar and Price Action Reversals Bar by Bar If you're looking to make the most of your time in today's markets the trading insights found in Price Action Trends Bar by Bar will help you achieve this goal. |
| ai after hours trading: The Motley Fool Investment Guide David Gardner, Tom Gardner, 2001-01-02 For Making Sense of Investing Today...the Fully Revised and Expanded Edition of the Bestselling The Motley Fool Investment Guide Today, with the Internet, anyone can be an informed investor. Once you learn to tune out the hype and focus on meaningful factors, you can beat the Street. The Motley Fool Investment Guide, completely revised and updated with clear and witty explanations, deciphers all the new information -- from evaluating individual stocks to creating a diverse investment portfolio. David and Tom Gardner have investing ideas for you -- no matter how much time or money you have. This new edition of The Motley Fool Investment Guide is built for today's investor, sophisticate and novice alike, with updated information on: Finding high-growth stocks that will beat the market over the long term Identifying volatile young companies that traditional valuation measures may miss Using Fool.com and the Internet to locate great sources of useful information |
| ai after hours trading: MoneyGPT James Rickards, 2024-11-12 From the New York Times bestselling author of The New Great Depression and Currency Wars, a telling prediction for how AI will endanger global economic markets and security In November 2022, OpenAI released GPT-4 in a chatbot form to the public. In just two months, it claimed 100 million users—the fastest app to ever reach this benchmark. Since then, AI has become an all-consuming topic, popping up on the news, in ads, on your messenger apps, and in conversations with friends and family. But as AI becomes ubiquitous and grows at an ever-increasing pace, what does it mean for the financial markets? In MoneyGPT, Wall Street veteran and former advisor to the Department of Defense James Rickards paints a comprehensive picture of the danger AI poses to the global financial order, and the insidious ways in which AI will threaten national security. Rickards shows how, while AI is touted to increase efficiency and lower costs, its global implementation in the financial world will actually cause chaos, as selling begets selling and bank runs happen at lightning speed. AI further benefits malicious actors, Rickards argues, because without human empathy or instinct to intervene, threats like total nuclear war that once felt extreme are now more likely. And throughout all this, we must remain vigilant on the question of whose values will be promoted in the age of AI. As Rickards predicts, these systems will fail when we rely on them the most. MoneyGPT shows that the danger is not that AI will malfunction, but that it will function exactly as intended. The peril is not in the algorithms, but in ourselves. And it’s up to us to intervene with old-fashioned human logic and common sense before it’s too late. |
| ai after hours trading: Artificial Intelligence Harvard Business Review, 2019 Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business. |
| ai after hours trading: Deep Learning Tools for Predicting Stock Market Movements Renuka Sharma, Kiran Mehta, 2024-04-10 DEEP LEARNING TOOLS for PREDICTING STOCK MARKET MOVEMENTS The book provides a comprehensive overview of current research and developments in the field of deep learning models for stock market forecasting in the developed and developing worlds. The book delves into the realm of deep learning and embraces the challenges, opportunities, and transformation of stock market analysis. Deep learning helps foresee market trends with increased accuracy. With advancements in deep learning, new opportunities in styles, tools, and techniques evolve and embrace data-driven insights with theories and practical applications. Learn about designing, training, and applying predictive models with rigorous attention to detail. This book offers critical thinking skills and the cultivation of discerning approaches to market analysis. The book: details the development of an ensemble model for stock market prediction, combining long short-term memory and autoregressive integrated moving average; explains the rapid expansion of quantum computing technologies in financial systems; provides an overview of deep learning techniques for forecasting stock market trends and examines their effectiveness across different time frames and market conditions; explores applications and implications of various models for causality, volatility, and co-integration in stock markets, offering insights to investors and policymakers. Audience The book has a wide audience of researchers in financial technology, financial software engineering, artificial intelligence, professional market investors, investment institutions, and asset management companies. |
| ai after hours trading: The Little Book of Stock Market Cycles Jeffrey A. Hirsch, 2012-07-11 Jeffrey Hirsch discusses how to capture market-beating returns by following specific stock market cycles While predicting the direction of the stock market at any given point is difficult, it's a fact that the market exhibits well-defined and sometimes predictable patterns. While cycles do not repeat exactly all of the time, statistical evidence suggests that cyclical tendencies are very strong and should not be ignored by investors. The Little Book of Stock Market Cycles will show you how to profit from these recurring stock market patterns and cycles. Written by Jeffrey Hirsch, President of the Hirsch Organization and Editor-in-Chief of the Stock Trader's Almanac, this reliable resource explains why these cycles occur, provides the historical evidence behind them, and shows you how to capture consistent profits from them moving forward. In addition to describing his most widely followed cycles and patters, Hirsch also discusses both longer term boom-bust economic cycles and shorter term tendencies involving the best days, weeks, and months of the year to trade the market. The methods found here follow everything from presidential election cycles to the Santa Claus effect Written by Jeffrey Hirsch, the pre-eminent authority on market cycles and seasonal patterns The strategies explored are easy-to-implement, and based on research that has proven profitable over the course of time For investors looking to beat the buy-and-hold philosophy, The Little Book of Stock Market Cycles will provide simple, actionable ideas that have stood the test of time and consistently outperformed the market. |
| ai after hours trading: Market Mind Games: A Radical Psychology of Investing, Trading and Risk Denise Shull, 2011-12-30 Seize the advantage in every trade using your greatest asset—“psychological capital”! When it comes to investing, we're usually taught to “conquer” our emotions. Denise Shull sees it in reverse: We need to use our emotions. Combining her expertise in neuroscience with her extensive trading experience, Shull seeks to help you improve your decision making by navigating the shifting relationships among reason, analysis, emotion, and intuition. This is your “psychological capital”—and it's the key to making decisions calmly and rationally during the heat of trading. Market Mind Games explains the basics of neuroscience in language you understand, which is the first tool you need to manage the emotional ups and downs of the trading. It then provides you with a rock-solid trading system designed to take full advantage of your emotional assets. |
| ai after hours trading: Securities Market Issues for the 21st Century Merritt B. Fox, 2018 |
| ai after hours trading: The Fear Index Robert Harris, 2012-01-31 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. |
| ai after hours trading: Our Final Invention James Barrat, 2013-10-01 Elon Musk named Our Final Invention one of five books everyone should read about the future—a Huffington Post Definitive Tech Book of 2013. Artificial Intelligence helps choose what books you buy, what movies you see, and even who you date. It puts the “smart” in your smartphone and soon it will drive your car. It makes most of the trades on Wall Street, and controls vital energy, water, and transportation infrastructure. But Artificial Intelligence can also threaten our existence. In as little as a decade, AI could match and then surpass human intelligence. Corporations and government agencies are pouring billions into achieving AI’s Holy Grail—human-level intelligence. Once AI has attained it, scientists argue, it will have survival drives much like our own. We may be forced to compete with a rival more cunning, more powerful, and more alien than we can imagine. Through profiles of tech visionaries, industry watchdogs, and groundbreaking AI systems, Our Final Invention explores the perils of the heedless pursuit of advanced AI. Until now, human intelligence has had no rival. Can we coexist with beings whose intelligence dwarfs our own? And will they allow us to? “If you read just one book that makes you confront scary high-tech realities that we’ll soon have no choice but to address, make it this one.” —The Washington Post “Science fiction has long explored the implications of humanlike machines (think of Asimov’s I, Robot), but Barrat’s thoughtful treatment adds a dose of reality.” —Science News “A dark new book . . . lays out a strong case for why we should be at least a little worried.” —The New Yorker |
| ai after hours trading: The Little Book That Still Beats the Market Joel Greenblatt, 2010-09-07 In 2005, Joel Greenblatt published a book that is already considered one of the classics of finance literature. In The Little Book that Beats the Market—a New York Times bestseller with 300,000 copies in print—Greenblatt explained how investors can outperform the popular market averages by simply and systematically applying a formula that seeks out good businesses when they are available at bargain prices. Now, with a new Introduction and Afterword for 2010, The Little Book that Still Beats the Market updates and expands upon the research findings from the original book. Included are data and analysis covering the recent financial crisis and model performance through the end of 2009. In a straightforward and accessible style, the book explores the basic principles of successful stock market investing and then reveals the author’s time-tested formula that makes buying above average companies at below average prices automatic. Though the formula has been extensively tested and is a breakthrough in the academic and professional world, Greenblatt explains it using 6th grade math, plain language and humor. He shows how to use his method to beat both the market and professional managers by a wide margin. You’ll also learn why success eludes almost all individual and professional investors, and why the formula will continue to work even after everyone “knows” it. While the formula may be simple, understanding why the formula works is the true key to success for investors. The book will take readers on a step-by-step journey so that they can learn the principles of value investing in a way that will provide them with a long term strategy that they can understand and stick with through both good and bad periods for the stock market. As the Wall Street Journal stated about the original edition, “Mr. Greenblatt…says his goal was to provide advice that, while sophisticated, could be understood and followed by his five children, ages 6 to 15. They are in luck. His ‘Little Book’ is one of the best, clearest guides to value investing out there.” |
| ai after hours trading: AI Time Series Control System Modelling Chuzo Ninagawa, 2022-09-02 This book describes the practical application of artificial intelligence (AI) methods using time series data in system control. This book consistently discusses the application of machine learning to the analysis and modelling of time series data of physical quantities to be controlled in the field of system control. Since dynamic systems are not stable steady states but changing transient states, the changing transient states depend on the state history before the change. In other words, it is essential to predict the change from the present to the future based on the time history of each variable in the target system, and to manipulate the system to achieve the desired change. In short, time series is the key to the application of AI machine learning to system control. This is the philosophy of this book: time series data + AI machine learning = new practical control methods. This book can give my helps to undergradate or graduate students, institute researchers and senior engineers whose scientific background are engineering, mathematics, physics and other natural sciences. |
| ai after hours trading: Understanding Options Michael Sincere, 2006-09-22 This straightforward, accessible guide clearly explains what options are and how they work, their pros and cons, their relationship with stocks, and how to use them to gain leverage, generate extra income, and protect against adverse price movements. |
| ai after hours trading: Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance El Bachir Boukherouaa, Mr. Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S Iskender, Mr. Alin T Mirestean, Rangachary Ravikumar, 2021-10-22 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. |
| ai after hours trading: Quantitative Hedge Funds: Discretionary, Systematic, Ai, Esg And Quantamental Richard Bateson, 2022-10-04 Welcome to the secretive club of modern hedge funds, where important players in the world of investing and capital markets have invested close to $4 trillion globally.If you're intrigued by the inner workings of hedge funds, investment techniques and technologies they use to source investment alpha, this book is for you. Focusing on the author's three decades of trading experience at leading banks and hedge funds, it covers both discretionary and computer-driven strategies and perspectives on AI-based and quantamental investing using new alternative data, which includes numerous examples and insights of real trades and investment strategies. No mathematical knowledge is required, with the relevant algorithms detailed in the appendices.Discretionary investing details equity and credit investing across the corporate capital structure. Through trading equities, bonds and loans, event-driven trades can target profitable special situations and relative value opportunities. Systematic trading involves computer-driven strategies derived from a scientific and statistical analysis of liquid markets. The investment strategies of both commodity trading advisors (CTAs) and long/short equity funds are detailed, from trend-following to factor-based approaches. AI investing is fashionable but does the reality for hedge funds correspond to the AI hype present in other non-financial domains? AI using neural nets and other machine learning techniques are outlined along with their practical application in regards to investing.Quantitative Hedge Funds also discusses environmental, social and governance (ESG) investing, which has rapidly evolved as the public and institutions demand solutions to global problems such as climate change, pollution and unethical labour practices. ESG investment strategies are migrating out of the long-only space and into hedge funds.Finally, the advent of big data has led to multiple alternative datasets available for hedge fund managers. The integration of alternative data into the investment process is discussed, together with the rise of so-called quantamental investing, a hybrid of the best of human skill and computer-based technologies.Related Link(s) |
| ai after hours trading: A Beginner's Guide to the Stock Market Matthew R Kratter, 2019-05-21 Learn to make money in the stock market, even if you've never traded before.The stock market is the greatest opportunity machine ever created.Are you ready to get your piece of it?This book will teach you everything that you need to know to start making money in the stock market today.Don't gamble with your hard-earned money.If you are going to make a lot of money, you need to know how the stock market really works.You need to avoid the pitfalls and costly mistakes that beginners make.And you need time-tested trading and investing strategies that actually work.This book gives you everything that you will need.It's a simple road map that anyone can follow.In this book, you will learn: How to grow your money the smart and easy way The best place to open up a brokerage account How to buy your first stock How to generate passive income in the stock market How to spot a stock that is about to explode higher How to trade momentum stocks Insider tricks used by professional traders The one thing you should never do when buying value stocks (don't start investing until you read this) How to pick stocks like Warren Buffett How to create a secure financial future for you and your family And much, much more Even if you know nothing about the stock market, this book will get you started investing and trading the right way.Join the thousands of smart traders and investors who have profited from this ultimate guide to the stock market.Amazon best-selling author and retired hedge fund manager, Matthew Kratter will teach you the secrets that he has used to trade and invest profitably for the last 20 years.Even if you are a complete beginner, this book will have you trading stocks in no time.Are you ready to get started creating real wealth in the stock market?Then scroll up and click BUY NOW to get started today. |
| ai after hours trading: Practical Graph Mining with R Nagiza F. Samatova, William Hendrix, John Jenkins, Kanchana Padmanabhan, Arpan Chakraborty, 2013-07-15 Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a do-it-yourself approach to extracting interesting patterns from graph data. It covers many basic and advanced techniques for the identification of anomalous or frequently recurring patterns in a graph, the discovery of groups or cluste |
| ai after hours trading: How to Start Day Trading Futures, Options, and Indices Jeffrey Katz, Jeffrey Owen Katz, Donna McCormick, 2001 The same electronic trading forces that are changing the face of stock trading, are moving into the futures and options market, where traders can trade the entire stock market rather than just one stock at a time. Some of the richest opportunities to trade the stock market can be found at the futures and options exchanges. This work aims to teach the novice trader everything necessary to get started in electronically day trading the equity index markets. |
| ai after hours trading: Coronavirus News, Markets and AI Pankaj Sharma, 2020-12-27 Coronavirus News, Markets and AI explores the analysis of unstructured data from coronavirus-related news and the underlying sentiment during its real-time impact on the world and on global financial markets, in particular. In an age where information - both real and fake - travels in the blink of an eye and significantly alters market sentiment daily, this book is a blow by blow account of economic impact of the COVID-19 pandemic. The volume: Details how AI driven machines capture, analyse and score relevant on-ground news sentiment to analyse the dynamics of market sentiment, how markets react to good or bad news across ‘short term’ and ‘long term’; Investigates what have been the most prevalent news sentiment during the pandemic, and its linkages to crude oil prices, high profile cases, impact of local news, and even the impact of Trump’s policies; Discusses the impact on what people think and discuss, how the COVID-19 crisis differs from the Global Financial Crisis of 2008, the unprecedented disruptions in supply chains and our daily lives; Showcases how easy accessibility to big data methods, cloud computing, and computational methods and the universal applicability of these tool to any topic can help analyse extract the related news sentiment in allied fields. Accessible, nuanced and insightful, this book will be invaluable for business professionals, bankers, media professionals, traders, investors, and investment consultants. It will also be of great interest to scholars and researchers of economics, commerce, science and technology studies, computer science, media and culture studies, public policy and digital humanities. |
| ai after hours trading: How AI Ate the World Chris Stokel-Walker, 2024-05-09 'An excellent starter for those who want to gain an insight into how AI works and why it's likely to shape our lives.' – The Daily Telegraph Artificial intelligence will shake up our lives as thoroughly as the arrival of the internet. This popular, up-to-date book charts AI’s rise from its Cold War origins to its explosive growth in the 2020s. Tech journalist Chris Stokel-Walker (TikTok Boom and YouTubers) goes into the laboratories of the Silicon Valley innovators making rapid advances in ‘large language models’ of machine learning. He meets the insiders at Google and OpenAI who built Gemini and ChatGPT and reveals the extraordinary plans they have for them. Along the way, he explores AI’s dark side by talking to workers who have lost their jobs to bots and engages with futurologists worried that a man-made super-intelligence could threaten humankind. He answers critical questions about the AI revolution, such as what humanity might be jeopardising and the professions that will win and lose – and whether the existential threat technologists Elon Musk and Sam Altman are warning about is realistic – or a smokescreen to divert attention away from their growing power. How AI Ate the World is a ‘start here’ guide for anyone who wants to know more about the world we have just entered. Reviews 'An excellent starter for those who want to gain an insight into how AI works and why it's likely to shape our lives.' The Daily Telegraph 'How AI Ate the World prodigiously captures the key issues and concerns around artificial intelligence.' Azeem Azhar, Exponential View 'From ancient China to Victorian England, How AI Ate The World is the story of the characters, moments, technologies, and relationships that populate the rich history of artificial intelligence... How AI Ate The World grapples with what the age of automation means for the people living through it.' Harry Law, University of Cambridge 'A witty, engaging book that takes us through AI's bumpy past to help us understand its present, and future, impacts. I highly recommend it to anyone who is impacted by AI tech – which is to say, everyone on the planet.' Sasha Luccioni, Hugging Face 'Easily the most comprehensive book on AI I have read so far, covering all the key issues' Peter Hunt, Business & Tech Correspondent, Evening Standard 'A comprehensive and compelling look at the technology that's transforming our world. It's an essential guide, full of surprises, to the technology you need to know.' Matt Navarra, social media expert 'Whether you are new to AI or have been following the AI hype for years, Chris Stokel-Walker offers an entertaining balance of history, context and insight that has something for everyone. The story of AI’s evolution is a complex one, but Stokel-Walker tackles it in a clear, direct way that will bring you up to speed while helping you grapple with what it all means — for individuals, the workplace, society and the planet.' Sharon Goldman, VentureBeat 'This book is a wild, brilliant ride through centuries of thinking about and decades of developing machines that can learn. As a crash course in how we got to this current point of thrilling chaos, it will take some beating. Whether or not you agree with Stokel-Walker’s solutions or not, How AI Ate The World is essential reading to understand where we are and how we got here' Ciaran Martin, former CEO, UK National Cyber Security Centre Buy the book to discover your future |
| ai after hours trading: Charting and Technical Analysis Fred McAllen, 2012-04-06 To invest successfully or trade in Stocks, Options, Forex, or even Mutual Funds, it is imperative to know AND understand price and market movements that can only be learned from Technical Analysis. You should NEVER attempt Trading or Investing without it!My 25 years experience has taught me that 'every book on the market' regarding Charting and Technical Analysis is seemingly worthless. All seem to find yet another creative way to tell you to Buy Low and Sell High. And they offer NO in-depth understanding or analysis about WHO is buying and WHO is selling, and when.Point is, anyone, experienced or not, can show you a picture of a Chart and tell you to buy at the bottom and sell at the top. That is simple 'hindsight, ' and is always 20/20.This book is different! It is IN-DEPTH - EXPLAINED and you WILL learn price movements and technical analysis from this information!You will understand and recognize tops and bottoms in the market and in particular stocks, AS they are forming. This is highly valuable information, and you should NEVER attempt to trade or invest without this knowledge.Mutual Funds? Most people think they do not need this information because the have a Mutual Fund. That could not be farther from the truth. Investing your hard-earned money should be done with your own knowledge of market direction, when to buy, and when to move your money to safety. Without this knowledge you are at the mercy of a salesperson hungry to earn a commission. Thus, invariably entering the market at the wrong time and in the wrong investment. No one else has your best interest in mind. So learn to protect your money or keep it in the bank. It's that simple. The next move is yours. |
A Primer on Artificial Intelligence in Financial Markets
regulator, the CFTC could leverage AI to: • “Read” a complex marketplace and distinguish salient activity. • Use data to develop market models and identify risk factors. • Apply the models to …
Ai After Hours Trading (Download Only) - x-plane.com
The use of AI in after-hours trading raises ethical questions regarding fairness, transparency, and market manipulation. Ensuring algorithmic trading systems adhere to regulatory guidelines and …
Artificial Intelligence for Trading
In this program, learners will analyze real data and build financial models for trading. Whether learners want to level up in finance, obtain new skills in quant trading, or learn the latest AI …
Machine Learning in Algorithmic Trading - AFM
This AFM aims to do exactly that with this publication: report about the actual use of machine learning as reported by a subset of Dutch proprietary trading firms, and report about the …
Environments CHONG ZHANG XINYI LIU …
Our work attempts to solve this problem through large language model based agents. We have developed a multi-agent AI system called StockAgent, driven by LLMs, designed to simulate …
The human touch in AI-aided trading - Infosys
Banks and hedge funds are deploying artificial intelligence as a competitive trading tool, moving away from human input. Yet humans will remain essential to oversee and manage AI-aided …
Ai After Hours Trading (PDF) - x-plane.com
The use of AI in after-hours trading raises ethical questions regarding fairness, transparency, and market manipulation. Ensuring algorithmic trading systems adhere to regulatory guidelines and …
Transforming Financial Services: The Impact of AI on JP …
3. Algorithmic Trading AI trading algorithms can analyze market data, identify opportunities, and execute trades at optimal times. This has boosted JP Morgan Chase's trading performance. 4. …
The Use of Artificial Intelligence in Building Automated …
AI (mainly genetic algorithms and neural networks) to find the best solutions, while the use of artificial intelligence principles gives traders a powerful tool in building robust trading systems.
Ai After Hours Trading [PDF] - x-plane.com
Ai After Hours Trading: Dark Pools Scott Patterson,2012-06-12 A news breaking account of the global stock market s subterranean battles Dark Pools portrays the rise of the bots artificially …
When AI Meets Finance (StockAgent): Large Language …
By simulating stock trading, we aim to understand how AI agents make decisions based on diverse sources of information and how their behaviors affect market outcomes, such as price...
AI-based Trading Methods and Processes: A …
Through a comprehensive review of existing literature and analysis of real-world case studies, we examine the efficacy of AI-based trading strategies compared to traditional methods. Our …
Investor Bulletin - SEC.gov
investors about after-hours trading for stocks. After-hours trading, also known as extended-hours trading, refers to trading that occurs outside of regular trading hours. Regular trading hours for …
Algorithmic Trading and AI: A Review of Strategies and …
From high-frequency trading to machine learning-driven predictive analytics, this review unveils the multifaceted landscape of algorithmic trading in the era of AI, presenting both opportunities …
Trading and Corporate News in After Hours Market - The …
This paper documents new evidence on after hours trading (AHT) activity in U.S. equity markets. We show that the landscape for AHT changes substantially over time.
Ai After Hours Trading (2024) - x-plane.com
trading options Chapter 1 Introduction to AI and Option Trading Welcome to the exciting world of AI powered trading bots for executing options trades In this subchapter we will explore the …
When AI Meets Finance (StockAgent): Large Language …
Our work attempts to solve this problem through large language model based agents. We have developed a multi-agent AI system called StockAgent, driven by LLMs, designed to simulate …
PRE- AND POST- MARKET TRADING FOR US STOCKS
Figure 3 shows an example of pre-open and post-close trading on a intraday price chart using the Bloomberg Professional® service. For this ticker, JC Penney, we observe a 17% jump in after …
Ai After Hours Trading (2024) - x-plane.com
Ai After Hours Trading: How To Invest In AI? Tobi Pendola,2021-03-18 Have you ever thought of investing your budget in the AI stock market You want to try stock after pandemic but you don …
Ai After Hours Trading (Download Only) - x-plane.com
explore and download free Ai After Hours Trading PDF books and manuals is the internets largest free library. Hosted online, this catalog compiles a vast assortment of documents, making it a …
A Primer on Artificial Intelligence in Financial Ma…
regulator, the CFTC could leverage AI to: • “Read” a complex marketplace and distinguish salient activity. • Use data to develop market models and identify …
Ai After Hours Trading (Download Only) - x-plane.c…
The use of AI in after-hours trading raises ethical questions regarding fairness, transparency, and market manipulation. Ensuring algorithmic …
Artificial Intelligence for Trading
In this program, learners will analyze real data and build financial models for trading. Whether learners want to level up in finance, obtain new skills in …
Machine Learning in Algorithmic Trading - AFM
This AFM aims to do exactly that with this publication: report about the actual use of machine learning as reported by a subset of Dutch proprietary …
Environments CHONG ZHANG XINYI LIU arXiv:240…
Our work attempts to solve this problem through large language model based agents. We have developed a multi-agent AI system called …
