CCI Woodie like - page 28

 
CCI Color Candles - indicator for MetaTrader 5


CCI Color Candles - indicator for MetaTrader 5

CCI Color Candles - indicator for MetaTrader 5

Using the DRAW_COLOR_CANDLES graphic style, color the candlesticks of the chart depending on the readings of the iCCI indicator (Commodity Channel Index, CCI).
 

CCI Level Filling - indicator for MetaTrader 5

CCI Level Filling - indicator for MetaTrader 5

Paint over the areas of the iCCI (Commodity Channel Index, CCI) indicator above the ' CCI Level Up (100) ' level and below the ' CCI Level Dn (-100) ' level

 

iCCI iAlligator - expert for MetaTrader 5

iCCI iAlligator - expert for MetaTrader 5

The EA uses two indicators: the standard iCCI (Commodity Channel Index, CCI) and iiAlligator (Alligator). Both indicators are created on the specified timeframe ' Working timeframe ' - the same timeframe is used to determine the moment of the birth of a new bar (if it is necessary for the parameters   'Trailing on ... ' and ' Search signals on ... '). Alligator acts as a signal filter.

 

Learn how to design a trading system by CCI

Learn how to design a trading system by CCI

Learn how to design a trading system by CCI

This is a new article from our series in which we learn how to design trading systems based on simple strategies using the most commonly used technical indicators.

We will start with detailed information about what the Commodity Channel Index (CCI), what it measures, how we can calculate it. When we understand the fundamentals and the roots of what we are doing, we will be able to use the tools more efficiently and find more ideas and insights about it. This is what we are going to discuss in the "CCI Definition" topic. Then, we will work on a simple strategy that can be used with CCI during different market trends or conditions — this is what we will learn in the "CCI Strategy" part. Then, we will learn how we can design a trading system based on this strategy by planning what we need to design and what we want the computer to do — part "CCI trading system blueprint". Then, we will learn how to design what we planned by the trading system blueprint — part "CCI trading system".
Learn how to design a trading system by CCI
Learn how to design a trading system by CCI
  • www.mql5.com
In this new article from our series for learning how to design trading systems, I will present the Commodities Channel Index (CCI), explain its specifics, and share with you how to create a trading system based on this indicator.
 

CCI indicator. Upgrade and new features


https://www.mql5.com/en/articles/11126

Commodity Channel Index (CCI) is familiar to every trader. It was developed by Donald Lambert and first published in the Commodities magazine (now – Modern Trader) in 1980. Since then, this indicator has gained well-deserved fame and has become very popular among traders. It is present in the MetaTrader trading platform toolkit and is used both in manual trading and as part of automated trading systems.
CCI indicator. Upgrade and new features
CCI indicator. Upgrade and new features
  • www.mql5.com
In this article, I will consider the possibility of upgrading the CCI indicator. Besides, I will present a modification of the indicator.
 

CCI indicator. Three transformation steps

CCI indicator. Three transformation steps

In the previous article, I have considered possible changes in the conventional Commodity Channel Index indicator. They concerned the methods of calculation, but did not affect the essence of this indicator. In this article, I will consider changing the indicator from a slightly different point of view by amending its calculation logic. Let's see how these changes will affect the indicator results. Of course, I will try to evaluate the validity of the implemented changes.
CCI indicator. Three transformation steps
CCI indicator. Three transformation steps
  • www.mql5.com
In this article, I will make additional changes to the CCI affecting the very logic of this indicator. Moreover, we will be able to see it in the main chart window.
 

Forum on trading, automated trading systems and testing trading strategies

All about MQL5 Wizard : create robots without programming.

Sergey Golubev, 2025.04.29 06:45

MQL5 Wizard Techniques you should know (Part 61): Using Patterns of ADX and CCI with Supervised Learning

MQL5 Wizard Techniques you should know (Part 61): Using Patterns of ADX and CCI with Supervised Learning

We continue our look at how indicator pairings that track different aspects of the markets can be paired with machine learning to build a trading system. For these next articles, we are looking at the pairing of the Average Directional Index (ADX) oscillator with the Commodity Channel Index (CCI). The ADX is a predominantly a trend confirmation indicator, while the CCI is a momentum indicator. We touched on these two properties when we were looking at the patterns for individual indicators in past articles like this one. To recap, though, trend confirmation measures how strong a given price trend is; with a strength pointing to suitability for entry. Momentum indicators on the other hand measure the rate of price change. The more rapidly price is changing in a given direction, the less likely one is to suffer adverse excursions.

 

Forum on trading, automated trading systems and testing trading strategies

All about MQL5 Wizard : create robots without programming.

Sergey Golubev, 2025.05.03 07:16

MQL5 Wizard Techniques you should know (Part 62): Using Patterns of ADX and CCI with Reinforcement-Learning TRPO

MQL5 Wizard Techniques you should know (Part 62): Using Patterns of ADX and CCI with Reinforcement-Learning TRPO

We continue our look at how technical indicators that track different parts of price action can be paired in machine learning. In the last piece, we saw how supervised learning in a Multi-Layer-Perceptron (MLP) lays the groundwork of forecasting price action. We refer to the inputs of the MLP as features and its forecast outputs as states. From the way we defined our features in the last article which was slightly different from our approach in pieces 57–60, we aimed at having a more continuos input vector as opposed to the discrete option we had used. The move towards continuous data and regression and away from discrete data and classification can perhaps best be argued if we look at our AI trends.