Description
Introducing a cAlgo algorithm for sale!
I am excited to share with you an innovative algorithm designed to operate in both trending and ranging markets. The highlight of this algorithm is its ability to utilize and optimize buy and sell zones, also known as thresholds.
The code provided is an example of a trading robot developed in the cAlgo programming language. The robot implements a trading strategy that uses several technical indicators, such as the ATR (Average True Range), EMA (Exponential Moving Average), MFI (Money Flow Index) and RSI (Relative Strength Index), to generate buy and sell signals based on predefined conditions. It also includes parameters for risk management, such as position size, take profit and stop loss level, and trading hours restrictions. The robot is responsible for opening and closing positions based on the signals generated by the indicators and manages risk according to the set paramethers.
As you know, volatility is one of the key market conditions. Therefore, this algorithm utilizes ATR to filter out signals that are truly worth trading. It also uses MFI to control trade volume, RSI to assess signal momentum, and EMA to identify trends. The algorithm has been optimized to maximize the potential of your computer.
In terms of monthly profitability, when used with appropriate leverage, this algorithm has shown an average expected return of around 5% on a $1000 account with 2x leverage. During optimization, it is recommended to set the oversold threshold between 20 and 30, and the overbought threshold between 70 and 80.
It is important to use this algorithm on 1-hour candlesticks or a 1-hour timeframe to achieve the best results. Additionally, regular training sessions over the weekends are necessary to ensure optimal performance. Training the algorithm with one year of data and conducting a one-month trial test are recommended to evaluate its performance.
An interesting feature of this algorithm is the ability to activate or deactivate indicators according to your needs. If you believe that the financial markets are trending or ranging, you can adjust the indicators accordingly. However, it is suggested to keep RSI, MFI, and ATR activated together to avoid losses and ensure signal effectiveness.
For optimal performance, a high-end processor is recommended. You can compare your computer's performance to the CPU used during training on websites like "cpubenchmark". The algorithm is versatile and adapts to different market conditions, but assigning the correct parameters is crucial.
For example, if the market is strongly trending on daily candlesticks, it is recommended to assign at least one EMA that accurately captures the trend on 1-hour candlesticks. This will provide precise signals on a 1-hour timeframe with RSI or MFI.
Don't miss the opportunity to acquire this unique algorithm that combines powerful indicators and a robust strategy. Get ready to increase your chances of success in the financial market!
using System;
using cAlgo.API;
using cAlgo.API.Indicators;
using cAlgo.API.Internals;
using cAlgo.Indicators;
namespace cAlgo.Robots
{
[Robot(TimeZone = TimeZones.UTC, AccessRights = AccessRights.None)]
public class Finwalt : Robot
{
// Your parameter properties and variables...
protected override void OnStart()
{
// Your OnStart method implementation...
}
protected override void OnStop()
{
// Your OnStop method implementation...
}
protected override void OnTick()
{
// Your OnTick method implementation...
}
private void OnPositionClosed(PositionClosedEventArgs args)
{
// Your OnPositionClosed method implementation...
}
private void OpenPosition(TradeType tradeType)
{
// Your OpenPosition method implementation...
}
private new void ClosePosition(Position position)
{
// Your ClosePosition method implementation...
}
private void ClosePositions(TradeType tradeType)
{
// Your ClosePositions method implementation...
}
// Other private helper methods...
}
}
x1379
Joined on 26.08.2020
- Distribution: Paid
- Language: C#
- Trading platform: cTrader Automate
- File name: EMAR.algo
- Rating: 5
- Installs: 68
- Modified: 10/06/2023 00:39
