News Trading Made Easy (Part 2): Risk Management
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A quick refresher for
the previous article in the News Trading Made Easy series. In part 1, we went through the concept of DST(Daylight Savings Time) and the various versions for different countries that essentially change their time zones by an hour ahead and behind during a financial year. This will change trading schedules for the related brokers using DST. The reasons for creating a database and the benefits were addressed. A database was created to store the news events from the
MQL5 Economic Calendar with subsequent changes to the event time data to reflect the broker's DST schedule for accurate back-testing in the future. In the project files, an SQL script results in an Excel format was provided for all the unique events accessible through the MQL5 Calendar for all the different countries.
However, in this article, we will make a few changes to our previous code in part 1. Firstly by implementing inheritance to the existing code and upcoming new code, the previous news/calendar database will get a revamp into something more useable and practical. Additionally, we will tackle risk management and create different risk profiles to choose from for users with different risk appetites or preferences.
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How to integrate Smart Money Concepts (OB) coupled with Fibonacci indicator for Optimal Trade Entry
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Smart Money Concepts (SMC) and Order Blocks are critical areas on the chart where institutional traders typically execute large buying or selling orders. These zones often mark the origins of significant price movements, making them vital for traders seeking to align their strategies with institutional market activity. Understanding how these key levels influence price action can provide retail traders with more profound insight into the underlying market dynamics, allowing them to anticipate high-probability moves.
When combined with tools like the Fibonacci retracement, traders can further refine their entry strategies. The Fibonacci retracement identifies potential pullback levels between a recent swing high and swing low, offering a way to measure how far price may retrace before continuing its trend. This approach helps traders pinpoint optimal entry points by aligning institutional order flow with areas of market interest, enhancing the precision of their trades.
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News Trading Made Easy (Part 4): Performance Enhancement
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In the
previous article, we went through the processes of implementing trades based on the news event's impact. We were successful in this mission, but a key disadvantage to the article's last code was its back-testing speed which is relatively slow. This is mainly due to frequently accessing the database in memory while back-testing the strategy, to resolve this issue we will reduce the number of times the database is accessed during the back-testing procedure. We will get all the information we need from the database in memory for the current day, this means that we will only access the database ideally once per day.
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Trading with the MQL5 Economic Calendar (Part 4): Implementing Real-Time News Updates in the Dashboard
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In this article, we advance our work on the
MetaQuotes Language 5 (MQL5)
Economic Calendar dashboard by adding functionality for live updates, allowing us to maintain a continuously refreshed display of critical economic news events. In the
previous part, we designed and implemented a dashboard panel to filter news based on currency, importance, and time, giving us a tailored view of relevant events. Now, we take it further by enabling real-time updates, ensuring that our calendar displays the latest data for timely decision-making.
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Trading with the MQL5 Economic Calendar (Part 8): Optimizing News-Driven Backtesting with Smart Event Filtering and Targeted Logs
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In this article, we propel the
MQL5 Economic Calendar series forward by optimizing our trading system for lightning-fast, visually intuitive backtesting, seamlessly integrating data visualization for both live and offline modes to enhance news-driven strategy development. Building on
Part 7’s foundation of resource-based event analysis for Strategy Tester compatibility, we now introduce smart event filtering and targeted logging to streamline performance, ensuring we can efficiently visualize and test strategies across real-time and historical environments with minimal clutter.
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