Indicator Blocks - Tutorial

Overview

Indicator blocks calculate technical analysis values from price data. These blocks help you identify trends, momentum, overbought/oversold conditions, and potential reversal points. Indicators follow the timeframe and price value of their Data: Ticker input and update based on its price timing.

Indicator: SMA

BASIC

Simple Moving Average (SMA) - Calculates the average price over a specified period. Smooths out price action and identifies trend direction.

What it does

Averages the last N closing prices
Smooths out short-term price fluctuations
Identifies overall trend direction
Acts as support/resistance levels

When to use

Trend-following strategies
Moving average crossovers
Dynamic support/resistance identification
Position entry/exit signals

📋 Example: Golden Cross Strategy

Strategy: Buy when short-term SMA crosses above long-term SMA (bullish signal)

                  
                    1. source1 = Data: Ticker (SPY, 1d)

                    2. sma1 = Indicator: SMA (source1, length=50)

                    3. sma2 = Indicator: SMA (source1, length=200)

                    4. crossover1 = Condition: Cross Over (sma1, sma2)

                    5. crossover2 = Condition: Cross Over (sma2, sma1)

                    6. buy1 = Action: Buy (cash=$10,000, when=crossover1)

                    7. sell1 = Action: Sell (sell_all_from=buy1, when=crossover2)

💡 Common Periods: 20 (short-term), 50 (medium-term), 200 (long-term trend)

Indicator: EMA

BASIC

Exponential Moving Average (EMA) - Weighted average that gives more importance to recent prices. More responsive to price changes than SMA.

What it does

Weights recent prices more heavily
Responds faster to price changes than SMA
Reduces lag in trend identification
Better for fast-moving markets

When to use

Short-term trading strategies
Quick trend reversals
Day trading and scalping
Volatile markets requiring faster signals

📋 Example: EMA Crossover Day Trading

Strategy: Trade intraday EMA crossovers for quick profits

                  
                    1. source1 = Data: Ticker (AAPL, 1m)

                    2. ema1 = Indicator: EMA (source1, length=9)

                    3. ema2 = Indicator: EMA (source1, length=21)

                    4. crossover1 = Condition: Cross Over (ema1, ema2)

                    5. crossover2 = Condition: Cross Over (ema2, ema1)

                    6. buy1 = Action: Buy (symbol=AAPL, 100 shares, when=crossover1)

                    7. sell1 = Action: Sell (sell_all_from=buy1, when=crossover2)

💡 EMA vs SMA: Use EMA when you want faster signals. Use SMA for smoother, more stable trends.

Indicator: Kalman Filter

SMOOTHING

Kalman Filter - Adaptive smoothing filter that reduces noise while tracking trend shifts. Useful for cleaner signals in choppy markets.

What it does

Smooths price with adaptive weighting
Reduces whipsaw noise
Tracks trend changes faster than SMA
Outputs a filtered price series

When to use

Noisy or range-bound markets
Pre-smoothing before crossovers
Trend filters for intraday strategies
Signal cleanup for fast indicators

📋 Example: Filtered Trend Signal

Strategy: Use the filtered line as a trend guide

                  
                    1. source1 = Data: Ticker (QQQ, 1m)

                    2. kf1 = Indicator: Kalman Filter (source1, length=20)

                    3. sma1 = Indicator: SMA (source1, length=50)

                    4. gt1 = Condition: A > B (kf1, sma1)

                    5. lt1 = Condition: A < B (kf1, sma1)

                    6. buy1 = Action: Buy (cash=$10,000, when=gt1)

                    7. sell1 = Action: Sell (sell_all_from=buy1, when=lt1)

💡 Tip: Compare filtered price vs raw price to reduce false crossovers.

Indicator: RSI

BASIC

Relative Strength Index (RSI) - Momentum oscillator that measures the speed and magnitude of price changes. Values range from 0 to 100.

What it does

Identifies overbought (RSI > 70) conditions
Identifies oversold (RSI < 30) conditions
Detects potential reversal points
Measures momentum strength

When to use

Mean reversion strategies
Overbought/oversold trading
Divergence detection
Entry/exit timing

📋 Example: RSI Mean Reversion

Strategy: Buy oversold conditions, sell overbought conditions

                  
                    1. source1 = Data: Ticker (TSLA, 1m)

                    2. rsi1 = Indicator: RSI (source1, length=14)

                    3. lt1 = Condition: A < B (rsi1, 30)

                    4. gt1 = Condition: A > B (rsi1, 70)

                    5. buy1 = Action: Buy (cash=$5,000, when=lt1)

                    6. sell1 = Action: Sell (sell_all_from=buy1, when=gt1)

⚠️ Watch Out: In strong trends, RSI can stay overbought/oversold for extended periods. Combine with trend indicators for better accuracy.

Indicator: MACD

BASIC

Moving Average Convergence Divergence (MACD) - Trend-following momentum indicator showing the relationship between two EMAs. Consists of MACD line, Signal line, and Histogram.

What it does

MACD Line block = EMA(12) - EMA(26)
MACD Signal block = EMA(MACD, 9)
MACD Histogram block = MACD - Signal
Identifies trend direction and momentum

When to use

Trend following strategies
MACD/Signal crossovers
Divergence detection
Momentum confirmation

📋 Example: MACD Crossover Strategy

Strategy: Trade MACD line crossing signal line

                  
                    1. source1 = Data: Ticker (SPY, 1m)

                    2. macd1 = Indicator: MACD Line (source1, 12/26/9)

                    3. macd_signal1 = Indicator: MACD Signal (source1, 12/26/9)

                    4. macd_hist1 = Indicator: MACD Histogram (source1, 12/26/9)

                    5. crossover1 = Condition: Cross Over (macd1, macd_signal1)

                    6. crossover2 = Condition: Cross Over (macd_signal1, macd1)

                    7. buy1 = Action: Buy (cash=$10,000, when=crossover1)

                    8. sell1 = Action: Sell (sell_all_from=buy1, when=crossover2)

💡 MACD Components: Use all three (MACD, Signal, Histogram) together for best results. Histogram shows momentum strength.

Indicator: Stochastic

BASIC

Stochastic Oscillator - Momentum indicator comparing closing price to price range. Values range from 0 to 100. Available as Fast %K/%D and Slow %K/%D blocks.

What it does

%K line = current momentum
%D line = smoothed %K (signal line)
Fast %K/%D blocks are more sensitive
Slow %K/%D blocks are smoother

When to use

Overbought/oversold conditions
%K/%D crossovers
Range-bound markets
Short-term reversals

📋 Example: Stochastic Reversal Strategy

Strategy: Trade oversold bounces and overbought drops

                  
                    1. source1 = Data: Ticker (QQQ, 1m)

                    2. stoch_fast_k1 = Indicator: Stochastic (Fast) %K (source1, 14/3)

                    3. stoch_fast_d1 = Indicator: Stochastic (Fast) %D (source1, 14/3)

                    4. lt1 = Condition: A < B (stoch_fast_k1, 20)

                    5. gt1 = Condition: A > B (stoch_fast_k1, 80)

                    6. crossover1 = Condition: Cross Over (stoch_fast_k1, stoch_fast_d1)

                    7. crossover2 = Condition: Cross Over (stoch_fast_d1, stoch_fast_k1)

                    8. and1 = Condition: AND (lt1, crossover1)

                    9. and2 = Condition: AND (gt1, crossover2)

                    10. buy1 = Action: Buy (cash=$10,000, when=and1)

                    11. sell1 = Action: Sell (sell_all_from=buy1, when=and2)

💡 Fast vs Slow: Fast Stochastic (14,3) is more responsive. Slow Stochastic (14,3,3) is smoother with fewer false signals.

Quick Reference

Indicator	Type	Best For	Key Signals
SMA	Trend	Smooth trends, crossovers	Price above/below, MA crossovers
EMA	Trend	Fast-moving markets, day trading	EMA crossovers, price touches
Kalman Filter	Smoothing	Noise reduction, trend filtering	Filtered price slope, crossovers
RSI	Momentum	Overbought/oversold, divergence	<30 oversold, >70 overbought
MACD (Line/Signal/Histogram)	Trend/Momentum	Trend confirmation, crossovers	MACD/Signal cross, histogram
Stochastic (Fast/Slow %K/%D)	Momentum	Range-bound, short-term reversals	%K/%D cross, <20 or >80

Common Indicator Strategies

1. Trend Following (SMA/EMA Crossover)

                
                  source1 = Data: Ticker (SPY, 1d)

                  sma1 = Indicator: SMA (source1, length=50)

                  sma2 = Indicator: SMA (source1, length=200)

                  gt1 = Condition: A > B (sma1, sma2)  # uptrend bias

                  lt1 = Condition: A < B (sma1, sma2)  # downtrend bias

Classic trend identification using golden/death cross

2. Mean Reversion (RSI Extremes)

                
                  source1 = Data: Ticker (SPY, 1m)

                  rsi1 = Indicator: RSI (source1, length=14)

                  lt1 = Condition: A < B (rsi1, 25)

                  gt1 = Condition: A > B (rsi1, 75)

                  gt2 = Condition: A > B (rsi1, 50)

                  or1 = Condition: OR (gt1, gt2)

                  buy1 = Action: Buy (cash=$10,000, when=lt1)

                  sell1 = Action: Sell (sell_all_from=buy1, when=or1)

Trade extremes in oscillating markets

3. Momentum Confirmation (MACD + RSI)

                
                  source1 = Data: Ticker (SPY, 1m)

                  macd1 = Indicator: MACD Line (source1, 12/26/9)

                  macd_signal1 = Indicator: MACD Signal (source1, 12/26/9)

                  rsi1 = Indicator: RSI (source1, length=14)

                  gt1 = Condition: A > B (macd1, macd_signal1)

                  gt2 = Condition: A > B (rsi1, 50)

                  lt1 = Condition: A < B (macd1, macd_signal1)

                  lt2 = Condition: A < B (rsi1, 50)

                  and1 = Condition: AND (gt1, gt2)

                  and2 = Condition: AND (lt1, lt2)

                  buy1 = Action: Buy (cash=$10,000, when=and1)

                  sell1 = Action: Sell (sell_all_from=buy1, when=and2)

Combine multiple indicators for stronger signals

4. MACD Histogram Zero Cross

                
                  source1 = Data: Ticker (SPY, 1m)

                  macd_hist1 = Indicator: MACD Histogram (source1, 12/26/9)

                  gt1 = Condition: A > B (macd_hist1, 0)

                  lt1 = Condition: A < B (macd_hist1, 0)

                  buy1 = Action: Buy (cash=$10,000, when=gt1)

                  sell1 = Action: Sell (sell_all_from=buy1, when=lt1)

Use the histogram crossing zero as a momentum shift signal

Best Practices

✅ Do:

Combine multiple indicators for confirmation
Adjust periods based on your trading timeframe
Backtest indicator settings before going live
Use trend indicators with momentum indicators
Wait for clear signals, avoid overtrading

❌ Don't:

Use too many indicators at once (causes confusion)
Ignore price action - indicators are secondary
Overtrade on every indicator signal
Use default settings without testing
Ignore market context and fundamentals

📈 Indicator Blocks Reference

Overview

Indicator: SMA

What it does

When to use

📋 Example: Golden Cross Strategy

Indicator: EMA

What it does

When to use

📋 Example: EMA Crossover Day Trading

Indicator: Kalman Filter

What it does

When to use

📋 Example: Filtered Trend Signal

Indicator: RSI

What it does

When to use

📋 Example: RSI Mean Reversion

Indicator: MACD

What it does

When to use

📋 Example: MACD Crossover Strategy

Indicator: Stochastic

What it does

When to use

📋 Example: Stochastic Reversal Strategy

Quick Reference

Common Indicator Strategies

1. Trend Following (SMA/EMA Crossover)

2. Mean Reversion (RSI Extremes)

3. Momentum Confirmation (MACD + RSI)

4. MACD Histogram Zero Cross

Best Practices

✅ Do:

❌ Don't: