Indicators Reference¶

Note: Indicator helpers now live in the optional cracktrader-extras package. Install it and fetch implementations via cracktrader.load("cracktrader.plugins.indicators"). The extras package restores the cracktrader.indicators namespace used in the examples below.

Complete reference for all available indicators in Cracktrader. Access indicators through cracktrader.indicators or ct.indicators.

Quick Start¶

import cracktrader as ct

# In your strategy
class MyStrategy(ct.bt.Strategy):
    def __init__(self):
        # Use indicators directly from cracktrader
        self.sma = ct.indicators.SMA(self.data.close, period=20)
        self.rsi = ct.indicators.RSI(self.data.close, period=14)
        self.bb = ct.indicators.BollingerBands(self.data.close, period=20)

Moving Averages¶

Simple Moving Average (SMA)¶

SMA(data, period=30)

Parameters: - data: Price series (usually close prices) - period: Number of periods for average calculation

Usage:

self.sma_short = ct.indicators.SMA(self.data.close, period=10)
self.sma_long = ct.indicators.SMA(self.data.close, period=30)

# Golden cross signal
if self.sma_short[0] > self.sma_long[0]:
    # Bullish signal

Exponential Moving Average (EMA)¶

EMA(data, period=30, alpha=None)

Parameters: - data: Price series - period: Number of periods - alpha: Smoothing factor (optional, calculated from period if not provided)

Usage:

self.ema_fast = ct.indicators.EMA(self.data.close, period=12)
self.ema_slow = ct.indicators.EMA(self.data.close, period=26)

Weighted Moving Average (WMA)¶

WMA(data, period=30)

Usage:

self.wma = ct.indicators.WMA(self.data.close, period=20)

Triple Exponential Moving Average (TEMA)¶

TEMA(data, period=30)

Usage:

self.tema = ct.indicators.TEMA(self.data.close, period=21)

Momentum Oscillators¶

Relative Strength Index (RSI)¶

RSI(data, period=14, upperband=70, lowerband=30, safediv=False)

Parameters: - period: Look-back period (default: 14) - upperband: Overbought level (default: 70) - lowerband: Oversold level (default: 30)

Usage:

self.rsi = ct.indicators.RSI(self.data.close, period=14)

# Trading signals
if self.rsi[0] < 30:
    # Oversold - potential buy signal
elif self.rsi[0] > 70:
    # Overbought - potential sell signal

Stochastic Oscillator¶

Stochastic(data, period=14, period_dfast=3, period_dslow=3,
           upperband=80, lowerband=20, safediv=False)

Lines: - percK: %K line (fast stochastic) - percD: %D line (slow stochastic)

Usage:

self.stoch = ct.indicators.Stochastic(self.data, period=14)

# %K crosses above %D
if self.stoch.percK[0] > self.stoch.percD[0]:
    # Bullish signal

MACD (Moving Average Convergence Divergence)¶

MACD(data, period_me1=12, period_me2=26, period_signal=9)

Lines: - macd: MACD line - signal: Signal line - histo: Histogram (MACD - Signal)

Usage:

self.macd = ct.indicators.MACD(self.data.close)

# MACD crosses above signal line
if self.macd.macd[0] > self.macd.signal[0]:
    # Bullish crossover

Commodity Channel Index (CCI)¶

CCI(data, period=20, factor=0.015)

Usage:

self.cci = ct.indicators.CCI(self.data, period=20)

# Extreme readings
if self.cci[0] > 100:
    # Overbought
elif self.cci[0] < -100:
    # Oversold

Williams %R¶

WilliamsR(data, period=14, upperband=-20, lowerband=-80)

Usage:

self.williams = ct.indicators.WilliamsR(self.data, period=14)

Volatility Indicators¶

Bollinger Bands¶

BollingerBands(data, period=20, devfactor=2.0, movav=SMA)

Lines: - top: Upper band - mid: Middle band (moving average) - bot: Lower band

Usage:

self.bb = ct.indicators.BollingerBands(self.data.close, period=20, devfactor=2.0)

# Price touches lower band
if self.data.close[0] <= self.bb.bot[0]:
    # Potential buy signal (oversold)

# Price touches upper band
if self.data.close[0] >= self.bb.top[0]:
    # Potential sell signal (overbought)

Average True Range (ATR)¶

ATR(data, period=14, movav=SMA)

Usage:

self.atr = ct.indicators.ATR(self.data, period=14)

# Use ATR for stop loss
stop_distance = self.atr[0] * 2  # 2 ATR stop

Standard Deviation¶

StdDev(data, period=20, movav=SMA)

Usage:

self.std = ct.indicators.StdDev(self.data.close, period=20)

# Volatility-based position sizing
if self.std[0] > average_volatility:
    position_size *= 0.5  # Reduce size in high volatility

Donchian Channel¶

DonchianChannel(data, period=20)

Lines: - dcm: Middle line - dch: Upper channel - dcl: Lower channel

Usage:

self.donchian = ct.indicators.DonchianChannel(self.data, period=20)

# Breakout strategy
if self.data.close[0] > self.donchian.dch[-1]:
    # Upside breakout

Keltner Channel¶

KeltnerChannel(data, period=20, devfactor=2.0)

Lines: - top: Upper channel - mid: Middle line (EMA) - bot: Lower channel

Trend Indicators¶

Average Directional Index (ADX)¶

ADX(data, period=14)

Lines: - adx: ADX line (trend strength) - plusDI: +DI line - minusDI: -DI line

Usage:

self.adx = ct.indicators.ADX(self.data, period=14)

# Strong trend
if self.adx.adx[0] > 25:
    # Trend is strong, use trend-following strategies
    if self.adx.plusDI[0] > self.adx.minusDI[0]:
        # Uptrend

Parabolic SAR¶

ParabolicSAR(data, af=0.02, afmax=0.20)

Usage:

self.psar = ct.indicators.ParabolicSAR(self.data)

# Trend reversal
if self.data.close[0] > self.psar[0]:
    # Price above SAR - uptrend

Aroon Oscillator¶

AroonOscillator(data, period=14)

Lines: - aroon: Aroon oscillator - aroonup: Aroon up - aroondown: Aroon down

Usage:

self.aroon = ct.indicators.AroonOscillator(self.data, period=14)

Volume Indicators¶

On Balance Volume (OBV)¶

OnBalanceVolume(data)

Usage:

self.obv = ct.indicators.OnBalanceVolume(self.data)

# Divergence analysis
if price_making_new_high and obv_not_making_new_high:
    # Bearish divergence

Volume Weighted Average Price (VWAP)¶

VWAP(data, period=30)

Usage:

self.vwap = ct.indicators.VWAP(self.data, period=30)

# Price relative to VWAP
if self.data.close[0] > self.vwap[0]:
    # Above VWAP - bullish

Accumulation/Distribution Line¶

AccumulationDistribution(data)

Usage:

self.ad = ct.indicators.AccumulationDistribution(self.data)

Money Flow Index (MFI)¶

MoneyFlowIndex(data, period=14)

Usage:

self.mfi = ct.indicators.MoneyFlowIndex(self.data, period=14)

# Overbought/oversold with volume
if self.mfi[0] > 80:
    # Overbought with volume
elif self.mfi[0] < 20:
    # Oversold with volume

Statistical Indicators¶

Linear Regression¶

LinearRegression(data, period=14)

Usage:

self.lr = ct.indicators.LinearRegression(self.data.close, period=14)

Correlation¶

Correlation(data0, data1, period=30)

Usage:

self.corr = ct.indicators.Correlation(
    self.datas[0].close,  # BTC
    self.datas[1].close,  # ETH
    period=30
)

# High correlation
if abs(self.corr[0]) > 0.8:
    # Assets moving together

Covariance¶

Covariance(data0, data1, period=30)

Beta¶

Beta(data0, data1, period=30)

Usage:

# Bitcoin as market benchmark
self.beta = ct.indicators.Beta(
    self.data.close,     # Alt coin
    self.btc_data.close, # Bitcoin
    period=30
)

Custom Crypto Indicators¶

Funding Rate (Custom)¶

class FundingRate(ct.bt.Indicator):
    """8-hour funding rate for perpetual futures"""
    lines = ('funding',)
    params = (('period', 8),)  # 8 hours

    def __init__(self):
        # Implementation depends on exchange data
        pass

Exchange Premium¶

class ExchangePremium(ct.bt.Indicator):
    """Price premium between exchanges"""
    lines = ('premium',)

    def __init__(self, data1, data2):
        self.lines.premium = (data1.close - data2.close) / data2.close * 100

Liquidation Levels¶

class LiquidationLevels(ct.bt.Indicator):
    """Calculate liquidation prices for leveraged positions"""
    lines = ('long_liq', 'short_liq')
    params = (('leverage', 3.0), ('maintenance_margin', 0.05))

    def __init__(self):
        # Long liquidation price
        self.lines.long_liq = self.data.close * (1 - (1 / self.params.leverage - self.params.maintenance_margin))

        # Short liquidation price  
        self.lines.short_liq = self.data.close * (1 + (1 / self.params.leverage - self.params.maintenance_margin))

Composite Indicators¶

Ichimoku Kinko Hyo¶

Ichimoku(data, tenkan=9, kijun=26, senkou=52, senkou_lead=26, chikou=26)

Lines: - tenkan_sen: Conversion line - kijun_sen: Base line - senkou_span_a: Leading span A - senkou_span_b: Leading span B - chikou_span: Lagging span

Usage:

self.ichimoku = ct.indicators.Ichimoku(self.data)

# Bullish signal
if (self.data.close[0] > self.ichimoku.senkou_span_a[0] and
    self.data.close[0] > self.ichimoku.senkou_span_b[0]):
    # Above cloud - bullish

Multi-Timeframe Indicators¶

# Higher timeframe data
class MultiTimeFrameStrategy(ct.bt.Strategy):
    def __init__(self):
        # Daily SMA on 1-hour chart
        self.daily_sma = ct.indicators.SMA(
            self.data.close,
            period=24  # 24 hours = 1 day on hourly chart
        )

        # Weekly RSI on daily chart
        self.weekly_rsi = ct.indicators.RSI(
            self.data.close,
            period=7  # 7 days = 1 week on daily chart
        )

Indicator Combinations¶

Confluence Strategy¶

class ConfluenceIndicators(ct.bt.Strategy):
    def __init__(self):
        # Multiple indicators for confluence
        self.sma_20 = ct.indicators.SMA(self.data.close, period=20)
        self.rsi = ct.indicators.RSI(self.data.close, period=14)
        self.bb = ct.indicators.BollingerBands(self.data.close, period=20)
        self.macd = ct.indicators.MACD(self.data.close)

    def check_bullish_confluence(self):
        """Check for bullish signal confluence"""
        signals = 0

        # Price above SMA
        if self.data.close[0] > self.sma_20[0]:
            signals += 1

        # RSI oversold but recovering
        if 30 < self.rsi[0] < 50:
            signals += 1

        # Bollinger Band bounce
        if self.data.close[0] > self.bb.bot[0]:
            signals += 1

        # MACD bullish
        if self.macd.macd[0] > self.macd.signal[0]:
            signals += 1

        return signals >= 3  # Require 3+ bullish signals

Indicator Utilities¶

List Available Indicators¶

# Get all available indicators
all_indicators = ct.indicators.get_all_indicators()
print(f"Available indicators: {len(all_indicators)}")

# Get indicators by category
trend_indicators = ct.indicators.get_trend_indicators()
momentum_indicators = ct.indicators.get_momentum_indicators()
volatility_indicators = ct.indicators.get_volatility_indicators()

Indicator Information¶

# Get indicator documentation
info = ct.indicators.get_indicator_info('RSI')
print(f"RSI parameters: {info['params']}")
print(f"RSI description: {info['description']}")

Performance Tips¶

Minimize Indicator Creation: Create indicators in __init__(), not in next()
Use Efficient Indicators: Some indicators are more computationally expensive
Cache Results: Store frequently used indicator values
Vectorized Operations: Use NumPy operations when possible

# Good: Create once in __init__
def __init__(self):
    self.sma = ct.indicators.SMA(self.data.close, period=20)

def next(self):
    sma_value = self.sma[0]  # Fast access

# Bad: Create in next() - very slow
def next(self):
    sma = ct.indicators.SMA(self.data.close, period=20)  # Don't do this!

Indicators Reference¶

Quick Start¶

Moving Averages¶

Simple Moving Average (SMA)¶

Exponential Moving Average (EMA)¶

Weighted Moving Average (WMA)¶

Triple Exponential Moving Average (TEMA)¶

Momentum Oscillators¶

Relative Strength Index (RSI)¶

Stochastic Oscillator¶

MACD (Moving Average Convergence Divergence)¶

Commodity Channel Index (CCI)¶

Williams %R¶

Volatility Indicators¶

Bollinger Bands¶

Average True Range (ATR)¶

Standard Deviation¶

Donchian Channel¶

Keltner Channel¶

Trend Indicators¶

Average Directional Index (ADX)¶

Parabolic SAR¶

Aroon Oscillator¶

Volume Indicators¶

On Balance Volume (OBV)¶

Volume Weighted Average Price (VWAP)¶

Accumulation/Distribution Line¶

Money Flow Index (MFI)¶

Statistical Indicators¶

Linear Regression¶

Correlation¶

Covariance¶

Beta¶

Custom Crypto Indicators¶

Funding Rate (Custom)¶

Exchange Premium¶

Liquidation Levels¶

Composite Indicators¶

Ichimoku Kinko Hyo¶

Multi-Timeframe Indicators¶

Indicator Combinations¶

Confluence Strategy¶

Indicator Utilities¶

List Available Indicators¶

Indicator Information¶

Performance Tips¶

See Also¶