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Offers insights into what it means to trade in knowledge in today's technological and commercial environment.
Trading Companies and Travel Knowledge in the Early Modern World explores the links between trade, empire, exploration, and global information trans>fer during the early modern period. By charting how the leaders, members, employees, and supporters of different trading companies gathered, pro>cessed, employed, protected, and divulged intelligence about foreign lands, peoples, and markets, this book throws new light on the internal uses of information by corporate actors and the ways they engaged with, relied on, and supplied various external publics. This ranged from using secret knowl>edge to beat competitors, to shaping debates about empire, and to forcing Europeans to reassess their understandings of specific environments due to contacts with non-European peoples. Reframing our understanding of trading companies through the lens of travel literature, this volume brings together thirteen experts in the field to facilitate a new understanding of how European corporations and empires were shaped by global webs of information exchange
This text deals with the alignment of IT and business in order to introduce IT professionals to the concepts of trading in the financial markets.
For more than a century, from about 1600 until the early eighteenth century, the Dutch dominated world trade. Via the Netherlands the far reaches of the world, both in the Atlantic and in the East, were connected. Dutch ships carried goods, but they also opened up opportunities for the exchange of knowledge. The commercial networks of the Dutch trading companies provided an infrastructure which was accessible to people with a scholarly interest in the exotic world. The present collection of essays brings together a number of studies about knowledge construction that depended on the Dutch trading networks. Contributors include: Paul Arblaster, Hans den Besten, Frans Blom, Britt Dams, Adrien Delmas, Alette Fleischer, Antje Flüchter, Michiel van Groesen, Henk de Groot, Julie Berger Hochstrasser, Grégoire Holtz, Siegfried Huigen, Elspeth Jajdelska, Maria-Theresia Leuker, Edwin van Meerkerk, Bruno Naarden, and Christina Skott.
Douglas uncovers the underlying reasons for lack of consistency and helps traders overcome the ingrained mental habits that cost them money. He takes on the myths of the market and exposes them one by one teaching traders to look beyond random outcomes, to understand the true realities of risk, and to be comfortable with the "probabilities" of market movement that governs all market speculation.
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.
As someone who has spent hundreds of hours helping run a Binary Options trade and training room, I know how confusing the topic can be. Most people have heard of Forex, but are unsure how it differs from Binary Options. After participating in the traderoom, one of the questions I would hear frequently had been; "Are there any resources to help guide me, I'm confused!" It was after hearing this I decided to write a no-nonsense, practical guide for beginners. My goal was to help demystify many aspects of the trading world, and include everything I wish I had known before I started trading.Some of the questions I receive from our website are: Where can I download the necessary MT4 software?How to use the software?What are the best currency pairs to watch?What are the best times to trade?How do I recognize and avoid scams?How do I spot winning and losing setups?Just to name a few...
Trading for a Living Successful trading is based on three M's: Mind, Method, and Money. Trading for a Living helps you master all of those three areas: * How to become a cool, calm, and collected trader * How to profit from reading the behavior of the market crowd * How to use a computer to find good trades * How to develop a powerful trading system * How to find the trades with the best odds of success * How to find entry and exit points, set stops, and take profits Trading for a Living helps you discipline your Mind, shows you the Methods for trading the markets, and shows you how to manage Money in your trading accounts so that no string of losses can kick you out of the game. To help you profit even more from the ideas in Trading for a Living, look for the companion volume--Study Guide for Trading for a Living. It asks over 200 multiple-choice questions, with answers and 11 rating scales for sharpening your trading skills. For example: Question Markets rise when * there are more buyers than sellers * buyers are more aggressive than sellers * sellers are afraid and demand a premium * more shares or contracts are bought than sold * I and II * II and III * II and IV * III and IV Answer B. II and III. Every change in price reflects what happens in the battle between bulls and bears. Markets rise when bulls feel more strongly than bears. They rally when buyers are confident and sellers demand a premium for participating in the game that is going against them. There is a buyer and a seller behind every transaction. The number of stocks or futures bought and sold is equal by definition.
Gives readers the information on mastering the markets, including: decimalization of stock prices; trading products such as E-minis and Exchange Traded Funds (ETFs); precision entries and exits; and the breed of trader. This edition shows how to day trade stocks in market.
The best-selling trading book of all time—updated for the new era The New Trading for a Living updates a modern classic, popular worldwide among both private and institutional traders. This revised and expanded edition brings time-tested concepts in gear with today's fast-moving markets, adding new studies and techniques for the modern trader. This classic guide teaches a calm and disciplined approach to the markets. It emphasizes risk management along with self-management and provides clear rules for both. The New Trading for a Living includes templates for rating stock picks, creating trade plans, and rating your own readiness to trade. It provides the knowledge, perspective, and tools for developing your own effective trading system. All charts in this book are new and in full color, with clear comments on rules and techniques. The clarity of this book's language, its practical illustrations and generous sharing of the essential skills have made it a model for the industry—often imitated but never duplicated. Both new and experienced traders will appreciate its insights and the calm, systematic approach to modern markets. The New Trading for a Living will become an even more valuable resource than the author's previous books: Overcome barriers to success and develop stronger discipline Identify asymmetrical market zones, where rewards are higher and risks lower Master money management as you set entries, targets and stops Use a record-keeping system that will make you into your own teacher Successful trading is based on knowledge, focus, and discipline. The New Trading for a Living will lift your trading to a higher level by sharing classic wisdom along with modern market tools.