This Trading Journal Log Diary is a perfect way to help you track your overall trades as you make them. All successful traders keep a journal and reflect on their trading style and strategies to help them improve over time. Great for tracking your progress. Each 2-page layout includes a section to record the following: Date - Log the date of your trade. Time - Record the time of your trade. Currency Pair - Write the quotation for different currencies. Sell/ Buy - Log whether you plan to buy or sell and price. Lot Size - Record the lot size. Number Of Trades Placed - Write the # of trades you made. PIP Gain- Log the Point in Percentage gain. How Long? - Record how long you plan to hold. Strategy Used - Write the strategy or strategies you used, swing, position, etc. Trends Noticed - Log any trends you may see. Notes - For writing any important information you want such as notes on market conditions, profit targets, stops, trading rules, future plans & goals, and more. Designed with active stock, options, futures, and forex traders in mind. Can also be for successful traders & beginners. Will also make the best gift. Books can be great tools to keep track of records and activities. It's a great way to keep you organized. Simple and easy to use every day. Size is 8.5x11 inches, 150 pages, quality white paper, black ink, soft matte finish cover, paperback. Get one today!

Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms

The Perfect Log Book For Keeping Track Of Your Trades! Track up to 500 trades with this trading log book designed with traders in mind. Write down trading notes, your own personal trading rules, you overall trading strategy, and log each individual trade whether it be stocks, options, forex, or crypto. It also serves as a good reminder for you to stay disciplined and to not give in to the FOMO or the Fear Of Missing Out. Features: Over 100 pages 500 Trading logs - Record up to 500 trades! 8.5 x 11in size Slots for trading data such as: Entry and exit date/time Entry and exit price Trade/position size Profit/loss Balance Notes Start Recording Your Trades. Buy This Trading Log Notebook Now!

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.

EAT SLEEP TRADE REPEAT NOTEBOOK This can be used as a Journal, Notebook, Log or Composition book. Product Details: 8x10 Inches 120 pages Printed on High Quality, Bright White paper Matte Cover Soft Cover Glued Spine Size: 8 x10 inches with 120 pages

Comprehensive coverage of the four major trading styles Evolution of a Trader explores the four trading styles that people use when learning to trade or invest in the stock market. Often, beginners enter the stock market by: Buying and holding onto a stock (value investing). That works well until the trend ends or a bear market begins. Then they try Position trading. This is the same as buy-and-hold, except the technique sells positions before a significant trend change occurs. Swing trading follows when traders increase their frequency of trading, trying to catch the short-term up and down swings. Finally, people try Day trading by completing their trades in a single day. This series provides comprehensive coverage of the four trading styles by offering numerous tips, sharing discoveries, and discussing specific trading setups to help you become a successful trader or investor as you journey through each style. Trading Basics takes an in-depth look at money management, stops, support and resistance, and offers dozens of tips every trader should know. Fundamental Analysis and Position Trading discusses when to sell a buy-and-hold position, uncovers which fundamentals work best, and uses them to find stocks that become 10-baggers—stocks that climb by 10 times their original value. Swing and Day Trading reveals methods to time the market swings, including specific trading setups, but it covers the basics as well, such as setting up a home trading office and how much money you can make day trading.