Price: $29.99 - $64.99
(as of Feb 14, 2026 09:39:29 UTC – Details)
The financial sector is undergoing significant restructuring. Traders and portfolio managers are increasingly becoming financial data scientists. Banks, investment funds, and fintech are increasingly automating their investments by integrating machine learning and deep learning algorithms into their decision-making process. The book presents the benefits of portfolio management, statistics, and machine learning applied to live trading with MetaTrader 5.
•Learn portfolio management technics and how to implement your optimization criterion
•How to backtest a strategy using the most valuable metrics in trading
•Import data from your broker to be as close as possible to the market
•Learn statistical arbitrage through pair trading strategies
•Generate market predictions using machine learning, deep learning, and time series analysis
•Learn how to find the best take profit, stop loss, and leverage for your strategies
•Combine trading strategies using portfolio management to increase the robustness of the strategies
•Connect your Python algorithm to your MetaTrader 5 and run it with a demo or live trading account
•Use all codes in the book for live trading or screener if you prefer manual trading
ASIN : B09HHMDQWJ
Accessibility : Learn more
Publication date : September 28, 2021
Language : English
File size : 9.8 MB
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 287 pages
Page Flip : Enabled
Best Sellers Rank: #2,119,616 in Kindle Store (See Top 100 in Kindle Store) #369 in Financial Engineering (Kindle Store) #594 in Financial Engineering (Books) #3,539 in AI & Semantics
Customer Reviews: 3.8 3.8 out of 5 stars (29) var dpAcrHasRegisteredArcLinkClickAction; P.when(‘A’, ‘ready’).execute(function(A) { if (dpAcrHasRegisteredArcLinkClickAction !== true) { dpAcrHasRegisteredArcLinkClickAction = true; A.declarative( ‘acrLink-click-metrics’, ‘click’, { “allowLinkDefault”: true }, function (event) { if (window.ue) { ue.count(“acrLinkClickCount”, (ue.count(“acrLinkClickCount”) || 0) + 1); } } ); } }); P.when(‘A’, ‘cf’).execute(function(A) { A.declarative(‘acrStarsLink-click-metrics’, ‘click’, { “allowLinkDefault” : true }, function(event){ if(window.ue) { ue.count(“acrStarsLinkWithPopoverClickCount”, (ue.count(“acrStarsLinkWithPopoverClickCount”) || 0) + 1); } }); });
