Manage your assets with algorithms optimized for various market conditions
Algo-T.net provides algorithms based on various trading strategies and technical indicators. Each algorithm is designed for specific market conditions, and you can access more algorithms according to your membership level. Our algorithms pursue consistent returns through objective trading that eliminates emotions.
QFL (Quickfingers Luc) is a trading strategy that focuses on buying low and selling high. It uses a combination of technical indicators to identify optimal entry and exit points.
Volatility based algorithms measure market volatility and make trading decisions based on this. They identify highs and lows in low volatility areas to find efficient entry and exit points. The BB (Bollinger Bands) series utilizes statistical volatility ranges.
Monthly Average Return
TV signal based algorithms utilize technical indicators and signals from the TradingView platform. They analyze verified indicator combinations used by multiple experts in real-time to capture trading opportunities. The TV series automates various indicators and alerts from TradingView.
Monthly Average Return
Monthly Average Return
Monthly Average Return
Monthly Average Return
Technical indicator combination algorithms comprehensively analyze signals from various technical indicators. They capture more accurate trading timing through confirmation signals from multiple indicators rather than a single indicator. The COM (Combined Indicators) series is a comprehensive algorithm that combines various technical indicators.
Monthly Average Return
Monthly Average Return
Explanation of major technical indicators used in algorithms
RSI is an indicator that compares the magnitude of recent price gains and losses over a specified time period to measure momentum, presented as a value between 0 and 100. Generally, values above 70 indicate overbought conditions, while values below 30 indicate oversold conditions. Overbought suggests prices may have risen too high, while oversold suggests they may have fallen too low.
The Ultimate Oscillator is a momentum indicator that combines price movements across three different timeframes: short, medium, and long-term. By considering multiple timeframes together, it provides more balanced signals than single timeframe indicators. Values below 30 are interpreted as oversold, while values above 70 are considered overbought.
MACD calculates the difference between short-term and long-term moving averages to show the direction and strength of a trend. Crossovers between the MACD line and signal line are interpreted as buy or sell signals, while the histogram visualizes the difference between these two lines to show momentum changes.
Bollinger Bands visualize price volatility, consisting of a middle band (typically a 20-day moving average) and upper and lower bands that add and subtract standard deviations from the middle band. Narrowing bands indicate decreasing volatility, while widening bands indicate increasing volatility.
Stochastic RSI applies the stochastic formula to RSI values, representing the relative position within the RSI trend as a value between 0 and 100. It reacts more sensitively than the traditional RSI, with values below 20 considered oversold and values above 80 considered overbought.
Fibonacci Retracement applies ratios derived from the Fibonacci sequence (23.6%, 38.2%, 50%, 61.8%, 78.6%) between important highs and lows to identify potential support and resistance levels. These levels often act as psychological points where prices react during corrections.
ATR measures the average trading range over a specified time period, objectively quantifying volatility. Higher values indicate higher volatility. It's useful for setting appropriate stop-loss levels or position sizing.
Volume Profile displays trading volume at specific price levels as a horizontal histogram. Price levels with high trading volume are likely to act as important support or resistance areas, helping to identify areas of market interest.
Common questions and answers about trading algorithms
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