Construction of Japanese candlestick chart and analysis of candlestick patterns constitute an amazing area of technical analysis. The advantage of candlesticks is that they represent data in such a manner that you can track the dynamics inside the data. In this article we analyze candlestick types, classification of candlestick patterns and present an indicator that can determine candlestick patterns.
The article provides the analysis of the following patterns: Flag, Pennant, Wedge, Rectangle, Contracting Triangle, Expanding Triangle. In addition to analyzing their similarities and differences, we will create indicators for detecting these patterns on the chart, as well as a tester indicator for the fast evaluation of their effectiveness.
This is the last article within the series devoted to the Reversing trading strategy. Here we will try to solve the problem, which caused the testing results instability in previous articles. We will also develop and test our own algorithm for manual trading in any market using the reversing strategy.
In this article, we continue to dwell on reversing techniques. We will try to reduce the maximum balance drawdown till an acceptable level for the instruments considered earlier. We will see if the measures will reduce the profit. We will also check how the reversing method performs on other markets, including stock, commodity, index, ETF and agricultural markets. Attention, the article contains a lot of images!
In this article, we will study the reverse martingale technique and will try to understand whether it is worth using, as well as whether it can help improve your trading strategy. We will create an Expert Advisor to operate on historic data and to check what indicators are best suitable for the reversing technique. We will also check whether it can be used without any indicator as an independent trading system. In addition, we will check if reversing can turn a loss-making trading system into a profitable one.
The article provides a review of an idea based on the analysis of prices' movement direction and their speed. We have performed its formalization in the MQL4 language presented as an expert advisor to explore viability of the strategy being under consideration. We also determine the best parameters via check, examination and optimization of an example given in the article.
In this article, we will analyze the concept of correlation between variables, as well as methods for the calculation of correlation coefficients and their practical use in trading. Correlation is a statistical relationship between two or more random variables (or quantities which can be considered random with some acceptable degree of accuracy). Changes in one ore more variables lead to systematic changes of other related variables.
There are multiple different approaches to market research and analysis. The main ones are technical and fundamental. In technical analysis, traders collect, process and analyze numerical data and parameters related to the market, including prices, volumes, etc. In fundamental analysis, traders analyze events and news affecting the markets directly or indirectly. The article deals with price velocity measurement methods and studies trading strategies based on that methods.
In this article, we will make an attempt to develop the best possible grid-based EA. As usual, this will be a cross-platform EA capable of working both with MetaTrader 4 and MetaTrader 5. The first EA was good enough, except that it could not make a profit over a long period of time. The second EA could work at intervals of more than several years. Unfortunately, it was unable to yield more than 50% of profit per year with a maximum drawdown of less than 50%.
The article deals with the concept of night trading, as well as trading strategies and their implementation in MQL5. We perform tests and make appropriate conclusions.
This article shows how price action and the monitoring of support and resistance levels can be used for well-timed market entry. It discusses a trading system that effectively combines the two for the determination of trade setups. Corresponding MQL4 code is explained that can be utilized in the EAs based on these trading concepts.
Trading in financial markets is associated with a whole range of risks that should be taken into account in the algorithms of trading systems. Reducing such risks is the most important task to make a profit when trading.
There are numerous trading strategies out there. Some of them look for a trend, while others define ranges of price fluctuations to trade within them. Is it possible to combine these two approaches to increase profitability?