Oil is the most important commodity on the face of the earth. Crude oil in its original form is useless; however, after it is refined, it is used across industries, from as simple as agriculture to as complex as pharmaceuticals. Oil is one of a handful of commodities that are truly demanded across all industries. The price of oil is a key econometric indicator of global production levels and economic growth levels.
Global crude trade is dominated by two benchmarks, West Texas Intermediate (WTI) which is the North American benchmark and Brent which is used to quote the majority of the world's crude.
In this discussion, we will revisit a classic crude oil spread trading strategy, with the hopes that we will be able to find an optimal machine learning strategy to make this classic strategy more palatable in a modern oil market that is dominated by algorithms.
In this article, we revisit a classic crude oil trading strategy with the aim of enhancing it by leveraging supervised machine learning algorithms. We will construct a least-squares model to predict future Brent crude oil prices based on the spread between Brent and WTI crude oil prices. Our goal is to identify a leading indicator of future changes in Brent prices.
Oil is the most important commodity on earth. In its original form, crude oil is useless, but once refined, it is used in all industries, from simple ones like agriculture to complex ones like pharmaceuticals. Oil is one of the few commodities that is truly in demand in all industries. The price of oil is a key econometric indicator of the level of global output and economic growth.
Two benchmarks dominate the global oil trade: West Texas Intermediate (WTI), which is the North American benchmark, and Brent, which is used to quote most of the world's oil.
In this paper, we will examine a classical strategy for trading spreads on crude oil in hopes of finding an optimal machine learning strategy that will make this classical strategy more acceptable in today's algorithm-dominated oil market.
The most important commodities on Earth: bread, milk and honey.
Without everything else, humanity will survive. And nature will be clean.
In the fast-paced world of foreign exchange trading, having a reliable and efficient trading system is crucial for success. Trading in general has plenty of terms, concepts, and strategies. Often at times it can be over whelming, especially for new traders who are still trying to find their footing in the trading industry. Smart Money Concept(SMC) is one of the trending concepts in forex trading, but it can be difficult at times for new traders or for anyone to use smart money concepts in their trading.
To solve this problem, there should be a robust tool for automating trading decision based on market structure and price action. The solution is to couple the Smart Money Concept (Break Of Structure) with the popular Relative Strength Index(RSI) indicator. This combination provides a strategic edge by leveraging both price action and momentum analysis, which enhances the accuracy of trade entries and exits, aiming to optimize trading performance.
In the fast-paced world of currency trading, having a reliable and effective trading system is critical to success. Trading in general has many terms, concepts and strategies. At times it can be too complicated, especially for new traders who are still trying to find their footing in the trading industry. The smart money concept (SMC) is one of the trending concepts in forex trading, but at times it can be difficult for new traders or anyone to utilise the smart money concept in their trading.
To solve this problem, a robust tool is needed to automate trading decisions based on market structure and price action. The solution is to combine the smart money concept (Break Of Structure) with the popular Relative Strength Index (RSI) indicator. This combination provides a strategic advantage by leveraging both price action and momentum analysis to improve the accuracy of trade entries and exits to optimise trading performance.
I would simply add the 50 and 200 muving to the chart, and base it on that.
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.
The SMC (Order Block) are key areas where institutional traders initiate significant buying or selling. After a significant price move, fibonacci helps to identify potential retracement from a recent swing high to a swing low to identify optimal trade entry.
After the "Account disabled" error occurs (this error on the weekends, when trade servers of exchanges are offline), it is necessary to manually log in to the trading account. To do that, go to "File" and select "Login to trade account". But doing this manually is uncomfortable and tedious. It also manually keeps track of connection loss after the "Account disabled" error.
The "LoginToTradeAccount.mqh" library allows to automate the process of connecting to a trade server.
The Kalman filter is a recursive algorithm used in algorithmic trading to estimate the true state of a financial time series by filtering out noise from price movements. It dynamically updates predictions based on new market data, making it valuable for adaptive strategies like mean reversion. This article first introduces the Kalman filter, covering its calculation and implementation. Next, we apply the filter to a classic mean-reversion forex strategy as an example. Finally, we conduct various statistical analyses by comparing the filter with a moving average across different forex pairs.
The Kalman filter is a recursive algorithm used in algorithmic trading to estimate the true state of a financial time series by filtering out noise from price movements. It dynamically updates predictions based on new market data, making it valuable for adaptive strategies like mean reversion. This article first introduces the Kalman filter, covering its calculation and implementation. Next, we apply the filter to a classic mean-reversion forex strategy as an example. Finally, we conduct various statistical analyses by comparing the filter with a moving average across different forex pairs.
Forum on trading, automated trading systems and testing trading strategies
Zigzag indicators
Sergey Golubev, 2024.04.08 15:27
Candle ZigZag - indicator for MetaTrader 5
Candle ZigZag is an indicator which changes its leg if a candlestick color changes
It supports Period of 1 while default ZigZag in Example folder does not work for period 1.
it helps trader to analyze chart in flat mode unlike line chart which has curve in price movement. Close mode can be enabled disabled.
Reimagining Classic Strategies: Crude Oil
Oil is the most important commodity on the face of the earth. Crude oil in its original form is useless; however, after it is refined, it is used across industries, from as simple as agriculture to as complex as pharmaceuticals. Oil is one of a handful of commodities that are truly demanded across all industries. The price of oil is a key econometric indicator of global production levels and economic growth levels.
Global crude trade is dominated by two benchmarks, West Texas Intermediate (WTI) which is the North American benchmark and Brent which is used to quote the majority of the world's crude.
In this discussion, we will revisit a classic crude oil spread trading strategy, with the hopes that we will be able to find an optimal machine learning strategy to make this classic strategy more palatable in a modern oil market that is dominated by algorithms.
Rethinking classic strategies:Oil
Oil is the most important commodity on earth. In its original form, crude oil is useless, but once refined, it is used in all industries, from simple ones like agriculture to complex ones like pharmaceuticals. Oil is one of the few commodities that is truly in demand in all industries. The price of oil is a key econometric indicator of the level of global output and economic growth.
Two benchmarks dominate the global oil trade: West Texas Intermediate (WTI), which is the North American benchmark, and Brent, which is used to quote most of the world's oil.
In this paper, we will examine a classical strategy for trading spreads on crude oil in hopes of finding an optimal machine learning strategy that will make this classical strategy more acceptable in today's algorithm-dominated oil market.
The most important commodities on Earth: bread, milk and honey.
Without everything else, humanity will survive. And nature will be clean.
The most important commodities on Earth: bread, milk and honey.
Without everything else, mankind will survive. And nature will be clean.
Maybe it will survive, of course, but the numbers will be reduced by several orders of magnitude.
Most of the consumer category, which is the current generation, will dienot from hunger, but from lack of adaptation.
How to Integrate Smart Money Concepts (BOS) Coupled with the RSI Indicator into an EA
In the fast-paced world of foreign exchange trading, having a reliable and efficient trading system is crucial for success. Trading in general has plenty of terms, concepts, and strategies. Often at times it can be over whelming, especially for new traders who are still trying to find their footing in the trading industry. Smart Money Concept(SMC) is one of the trending concepts in forex trading, but it can be difficult at times for new traders or for anyone to use smart money concepts in their trading.
To solve this problem, there should be a robust tool for automating trading decision based on market structure and price action. The solution is to couple the Smart Money Concept (Break Of Structure) with the popular Relative Strength Index(RSI) indicator. This combination provides a strategic edge by leveraging both price action and momentum analysis, which enhances the accuracy of trade entries and exits, aiming to optimize trading performance.
How to integrate Smart Money Concepts (BOS) in combination with RSI indicator into an Expert Advisor
In the fast-paced world of currency trading, having a reliable and effective trading system is critical to success. Trading in general has many terms, concepts and strategies. At times it can be too complicated, especially for new traders who are still trying to find their footing in the trading industry. The smart money concept (SMC) is one of the trending concepts in forex trading, but at times it can be difficult for new traders or anyone to utilise the smart money concept in their trading.
To solve this problem, a robust tool is needed to automate trading decisions based on market structure and price action. The solution is to combine the smart money concept (Break Of Structure) with the popular Relative Strength Index (RSI) indicator. This combination provides a strategic advantage by leveraging both price action and momentum analysis to improve the accuracy of trade entries and exits to optimise trading performance.
I would simply add the 50 and 200 muving to the chart, and base it on that.
How to integrate Smart Money Concepts (OB) coupled with Fibonacci indicator for Optimal Trade Entry
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.
Interesting tool -
Login To Trade Account - library for MetaTrader 5
After the "Account disabled" error occurs (this error on the weekends, when trade servers of exchanges are offline), it is necessary to manually log in to the trading account. To do that, go to "File" and select "Login to trade account". But doing this manually is uncomfortable and tedious. It also manually keeps track of connection loss after the "Account disabled" error.
The "LoginToTradeAccount.mqh" library allows to automate the process of connecting to a trade server.
The Kalman Filter for Forex Mean-Reversion Strategies