Indicators Guide
In the AlgoLift ecosystem, an indicator is not a "crystal ball"—it is a Market Sensor. Just as a car has sensors for speed, temperature, and pressure, a systematic strategy uses indicators to quantify specific characteristics of price action.
To build a professional strategy, you must understand the four primary dimensions of market data and which "sensors" are best suited to measure them.
Avoid Multicollinearity
One of the most common design errors is using multiple indicators that measure the same thing (e.g., using both RSI and Stochastics). This is called multicollinearity. It doesn't give you "more confirmation"—it just gives you redundant data that can lead to over-optimization.
Dimension 1: Trend (Lagging Sensors)
Trend indicators smooth out price noise to identify the primary direction of the market. Because they rely on past data, they are "Lagging"—they tell you what has happened.
- Simple Moving Average (SMA): The most basic tool for identifying the "Mean" over a specific window.
- Hull Moving Average (HMA): Designed to reduce lag while maintaining smoothness.
- SuperTrend: A volatility-adjusted trend sensor that identifies directional shifts.
- AlgoLift Usage: Use these as "Regime Filters." If Price > SMA, only permit Long signals.
Dimension 2: Momentum (Leading Sensors)
Momentum indicators (Oscillators) measure the speed and change of price movements. They are designed to identify when a move is accelerating or reaching exhaustion.
- RSI (Relative Strength Index): Measures the velocity of price changes to identify overextended conditions.
- MACD (Moving Average Convergence Divergence): Tracks the relationship between two moving averages to find trend "Ignition" points.
- AlgoLift Usage: Use these as "Triggers." For example, enter a mean-reversion trade only when RSI crosses back above 30.
Under the Hood: Rich Node Outputs
Standard platforms only give you the "Value" of an indicator. In AlgoLift, Indicator Nodes provide multiple data streams:
- Current Value: The standard numerical output.
- Slope: The rate of change of the indicator itself (instantly see if the average is flattening).
- Distance to Price: Automatically calculates how many ticks or points price is currently "stretched" from the average.
Dimension 3: Volatility (Dispersion Sensors)
Volatility indicators don't tell you direction; they tell you the "Heat" or "Range" of the market.
- ATR (Average True Range): The gold standard for measuring market range. Vital for setting dynamic stops.
- Standard Deviation: Measures the "Dispersion" of prices from the mean.
- AlgoLift Usage: Use these for "Risk Normalization." A 10-point stop might be safe in low volatility but "suicidal" in high volatility. Use ATR to calculate your stop distance dynamically.
Dimension 4: Volume & Liquidity
Volume provides the "Conviction" behind a move. It tells you how many participants are backing a specific price action.
- VWAP (Volume Weighted Average Price): The "Institutional Mean." Many algorithmic orders are programmed to execute only near VWAP.
- Relative Volume (RVOL): Compares current volume to the average for that specific time of day.
- AlgoLift Usage: Use volume as a "Validation Filter." Only take a breakout trade if the RVOL is greater than 1.5, ensuring the move has institutional "fuel."
The 'Signal-to-Noise' Ratio
When choosing indicators, focus on the Signal-to-Noise Ratio. High-period indicators (e.g., 200-SMA) have high signal but high lag. Low-period indicators (e.g., 9-RSI) have low lag but high noise. The "sweet spot" is usually found by combining a high-period filter with a low-period trigger.
Pro Tip: Custom Indicators
AlgoLift allows you to combine standard nodes to create proprietary indicators. For example, by subtracting a 50-SMA from a 20-SMA and dividing by the ATR, you can create a custom "Trend Intensity" oscillator tailored to your specific asset class.