Technical Analysis Library (TA-LIB)
TA-Lib is widely used by quantitative researchers and software engineers developing automated trading systems and charts. This freely available tool allows you to gather information on over 200 stock market indicators.
The Best Part
You don't need to develop software to find these financial indicators. You can spend your time working with the information to develop trading strategies and not on figuring out how to write code to correctly calculate a formula.
TA-LIB
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Includes 200 indicators such as ADX, MACD, RSI, Stochastic, Bollinger Bands etc
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Candlestick pattern recognition
Video Introduction
Those unfamiliar with TALIB may want to watch our introduction video.
Important Note
If using TA-LIB in CQLIVE live trading environment, you may get an error. Try converting your array to a Numpy array before passing to TALIB.
import talib
import numpy as np
close = md.bar.daily(start=-255).close
close_np = np.array(close)
output = talib.SMA(close_np)
Each function returns an output array and has default values for their parameters unless specified as keyword arguments. Typically, these functions will have an initial "lookback" period (a required number of observations before an output is generated) set to NaN.
All of the following examples use the Function API:
import talib
close = md.bar.daily(start=-255).close
Calculate a simple moving average of the close prices:
output = talib.SMA(close)
Calculating bollinger bands, with triple exponential moving average:
from talib import MA_Type
upper, middle, lower = talib.BBANDS(close, matype=MA_Type.T3)
Calculating momentum of the close prices, with a time period of 5:
output = talib.MOM(close, timeperiod=5)
If you're already familiar with using the function API, you should feel right at home using the Abstract API.
Every function takes a collection of named inputs, either a dict of bar attribute array.
For example, inputs could be provided for the typical "OHLCV" data:
bar = md.bar.daily(start=-255)
# note that all arrays must be the same length!
inputs = {
'open': bar.open,
'high': bar.high,
'low': bar.low,
'close': bar.close,
'volume': bar.volume
}
Functions can either be imported directly or instantiated by name:
from talib import abstract
# directly
sma = abstract.SMA
# or by name
sma = abstract.Function('sma')
From there, calling functions is basically the same as the function API:
from talib.abstract import *
# uses close prices (default)
output = SMA(inputs, timeperiod=25)
# uses open prices
output = SMA(inputs, timeperiod=25, price='open')
# uses close prices (default)
upper, middle, lower = BBANDS(inputs, 20, 2, 2)
# uses high, low, close (default)
slowk, slowd = STOCH(inputs, 5, 3, 0, 3, 0) # uses high, low, close by default
# uses high, low, open instead
slowk, slowd = STOCH(inputs, 5, 3, 0, 3, 0, prices=['high', 'low', 'open'])
We can show all the TA functions supported by TA-Lib, either as a list or as a dict sorted by group (e.g. "Overlap Studies", "Momentum Indicators", etc):
import talib
# list of functions
print talib.get_functions()
# dict of functions by group
print talib.get_function_groups()
Indicator Groups
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Overlap Studies The overlap studies cover data typically used in common "overlays" to stock market charts. The most common of these are the moving averages and trendlines.
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Momentum Indicators Indicators for the speed or velocity of a price change in each security. This is easily thought of as a measurement of the rate of change (increase/decrease) in the market price of the security.
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Volume Indicators Volume is the quantity of a security that has been traded in the specified time (day, hour, minute, ...). Volume can be used to judge the strength or weakness of a market move.
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Volatility Indicators Volatility is the amount of dispersion or fluctuation in the price of a security. Volatility indicators are useful for determining the amount of risk or potential profit that exists in the security. The volatility indicators in TA-LIB can be thought of as "Range" indicators.
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Price Transform Statistical information about how a price is changing (average, median, ...)
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Cycle Indicators Cycle Indicators are used by technical analysts to analyze variations in the amplitude of securities. These are commonly called Hilbert Transform Price Cycles.
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Pattern Recognition Charting patterns have been around for a very long time. They go by many names including Japanese Candlesticks. Chart patterns look at the overall market typically assuming the market price is the best indicator of all other statistics. The patterns that are found in stock charts give a technical analyst an indicator of likely future changes.
Overlap Studies
BBANDS Bollinger Bands
DEMA Double Exponential Moving Average
EMA Exponential Moving Average
HT_TRENDLINE Hilbert Transform - Instantaneous Trendline
KAMA Kaufman Adaptive Moving Average
MA Moving average
MAMA MESA Adaptive Moving Average
MAVP Moving average with variable period
MIDPOINT MidPoint over period
MIDPRICE Midpoint Price over period
SAR Parabolic SAR
SAREXT Parabolic SAR - Extended
SMA Simple Moving Average
T3 Triple Exponential Moving Average (T3)
TEMA Triple Exponential Moving Average
TRIMA Triangular Moving Average
WMA Weighted Moving Average
Momentum Indicators
ADX Average Directional Movement Index
ADXR Average Directional Movement Index Rating
APO Absolute Price Oscillator
AROON Aroon
AROONOSC Aroon Oscillator
BOP Balance Of Power
CCI Commodity Channel Index
CMO Chande Momentum Oscillator
DX Directional Movement Index
MACD Moving Average Convergence/Divergence
MACDEXT MACD with controllable MA type
MACDFIX Moving Average Convergence/Divergence Fix 12/26
MFI Money Flow Index
MINUS_DI Minus Directional Indicator
MINUS_DM Minus Directional Movement
MOM Momentum
PLUS_DI Plus Directional Indicator
PLUS_DM Plus Directional Movement
PPO Percentage Price Oscillator
ROC Rate of change : ((price/prevPrice)-1)*100
ROCP Rate of change Percentage: (price-prevPrice)/prevPrice
ROCR Rate of change ratio: (price/prevPrice)
ROCR100 Rate of change ratio 100 scale: (price/prevPrice)*100
RSI Relative Strength Index
STOCH Stochastic
STOCHF Stochastic Fast
STOCHRSI Stochastic Relative Strength Index
TRIX 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA
ULTOSC Ultimate Oscillator
WILLR Williams' %R
Volume Indicators
AD Chaikin A/D Line
ADOSC Chaikin A/D Oscillator
OBV On Balance Volume
Cycle Indicators
HT_DCPERIOD Hilbert Transform - Dominant Cycle Period
HT_DCPHASE Hilbert Transform - Dominant Cycle Phase
HT_PHASOR Hilbert Transform - Phasor Components
HT_SINE Hilbert Transform - SineWave
HT_TRENDMODE Hilbert Transform - Trend vs Cycle Mode
Price Transform
AVGPRICE Average Price
MEDPRICE Median Price
TYPPRICE Typical Price
WCLPRICE Weighted Close Price
Volatility Indicators
ATR Average True Range
NATR Normalized Average True Range
TRANGE True Range
Pattern Recognition
CDL2CROWS Two Crows
CDL3BLACKCROWS Three Black Crows
CDL3INSIDE Three Inside Up/Down
CDL3LINESTRIKE Three-Line Strike
CDL3OUTSIDE Three Outside Up/Down
CDL3STARSINSOUTH Three Stars In The South
CDL3WHITESOLDIERS Three Advancing White Soldiers
CDLABANDONEDBABY Abandoned Baby
CDLADVANCEBLOCK Advance Block
CDLBELTHOLD Belt-hold
CDLBREAKAWAY Breakaway
CDLCLOSINGMARUBOZU Closing Marubozu
CDLCONCEALBABYSWALL Concealing Baby Swallow
CDLCOUNTERATTACK Counterattack
CDLDARKCLOUDCOVER Dark Cloud Cover
CDLDOJI Doji
CDLDOJISTAR Doji Star
CDLDRAGONFLYDOJI Dragonfly Doji
CDLENGULFING Engulfing Pattern
CDLEVENINGDOJISTAR Evening Doji Star
CDLEVENINGSTAR Evening Star
CDLGAPSIDESIDEWHITE Up/Down-gap side-by-side white lines
CDLGRAVESTONEDOJI Gravestone Doji
CDLHAMMER Hammer
CDLHANGINGMAN Hanging Man
CDLHARAMI Harami Pattern
CDLHARAMICROSS Harami Cross Pattern
CDLHIGHWAVE High-Wave Candle
CDLHIKKAKE Hikkake Pattern
CDLHIKKAKEMOD Modified Hikkake Pattern
CDLHOMINGPIGEON Homing Pigeon
CDLIDENTICAL3CROWS Identical Three Crows
CDLINNECK In-Neck Pattern
CDLINVERTEDHAMMER Inverted Hammer
CDLKICKING Kicking
CDLKICKINGBYLENGTH Kicking - bull/bear determined by the longer marubozu
CDLLADDERBOTTOM Ladder Bottom
CDLLONGLEGGEDDOJI Long Legged Doji
CDLLONGLINE Long Line Candle
CDLMARUBOZU Marubozu
CDLMATCHINGLOW Matching Low
CDLMATHOLD Mat Hold
CDLMORNINGDOJISTAR Morning Doji Star
CDLMORNINGSTAR Morning Star
CDLONNECK On-Neck Pattern
CDLPIERCING Piercing Pattern
CDLRICKSHAWMAN Rickshaw Man
CDLRISEFALL3METHODS Rising/Falling Three Methods
CDLSEPARATINGLINES Separating Lines
CDLSHOOTINGSTAR Shooting Star
CDLSHORTLINE Short Line Candle
CDLSPINNINGTOP Spinning Top
CDLSTALLEDPATTERN Stalled Pattern
CDLSTICKSANDWICH Stick Sandwich
CDLTAKURI Takuri (Dragonfly Doji with very long lower shadow)
CDLTASUKIGAP Tasuki Gap
CDLTHRUSTING Thrusting Pattern
CDLTRISTAR Tristar Pattern
CDLUNIQUE3RIVER Unique 3 River
CDLUPSIDEGAP2CROWS Upside Gap Two Crows
CDLXSIDEGAP3METHODS Upside/Downside Gap Three Methods
Many backtesters use Pandas and NUMPY while researching quantitative strategies. This is quite OK for the research loop. Please keep in mind that strategies using numpy/pandas will not be able to be used in forward testing or live trading