CryptoTA

Technical Analysis on Cryptocurrency

install

pip install cryptota

example usage

import cryptota
import vectorbt as vbt

binance_data = vbt.BinanceData.download(
    "BTCUSDT",
    start='1 day ago UTC',
    end='now UTC',
    interval='1m'
)
binance_data = binance_data.update()
price = binance_data.get()

ta = cryptota.TA_Features()
ta.get_all_indicators(price)

last 10 result:

Supported DataSource

Binance

import cryptota
import vectorbt as vbt

binance_data = vbt.BinanceData.download(
    "BTCUSDT",
    start='1 day ago UTC',
    end='now UTC',
    interval='1m'
)
binance_data = binance_data.update()
price = binance_data.get()

Alpaca

import cryptota
import vectorbt as vbt
alpaca_data = vbt.AlpacaData.download(
    "AAPL",
    start='2 hours ago UTC',
    end='15 minutes ago UTC',
    interval='1m',
)
alpaca_data = alpaca_data.update()
price = alpaca_data.get()
alpaca_data.get()

CCXT

ccxt_data = vbt.CCXTData.download(
     "BTC/USDT",
     start='2 hours ago UTC',
     end='now UTC',
     timeframe='1m'
)
ccxt_data = ccxt_data.update()
price = ccxt_data.get()

Yfinance

yf_data = vbt.YFData.download(
    "TSLA",
    start='2022-02-25 09:30:00 -0400',
    end='2022-03-01 09:35:00 -0400',
    interval='1m'
)
price = yf_data.get()

Supported Metric

Momentum

• Awesome Oscillator: ao
• Absolute Price Oscillator: apo
• Balance of Power: bop
• Commodity Channel Index: cci
• Chande Momentum Oscillator: cmo
  • A wrapper for ta.linreg(series, r=True)
• Momentum: mom
• Percentage Price Oscillator: ppo
• Rate of Change: roc
• Relative Strength Index: rsi
  • Default is John Carter's. Enable Lazybear's with lazybear=True
  • Excluded from df.ta.strategy().
• Trix: trix
• Williams %R: willr

Overlap

• Double Exponential Moving Average: dema
• Exponential Moving Average: ema
  • Commonly known as 'Typical Price' in Technical Analysis literature
• Hull Exponential Moving Average: hma
  • Use: help(ta.ichimoku). Returns two DataFrames.
  • Drop the Chikou Span Column, the final column of the first resultant DataFrame, remove potential data leak.
• Kaufman's Adaptive Moving Average: kama
• Linear Regression: linreg
• Simple Moving Average: sma
• Triple Exponential Moving Average: tema
• Triangular Moving Average: trima
• Variable Index Dynamic Average: vidya
• Volume Weighted Moving Average: vwma
• Weighted Moving Average: wma

Trend

• Average Directional Movement Index: adx
• Detrended Price Oscillator: dpo
  • Set centered=False to remove potential data leak.
• Parabolic Stop and Reverse: psar
• Q Stick: qstick
• Vertical Horizontal Filter: vhf

Volatility

• Average True Range: atr
• Normalized Average True Range: natr

Volume

• Accumulation/Distribution Index: ad
• Accumulation/Distribution Oscillator: adosc
• Klinger Volume Oscillator: kvo
• Money Flow Index: mfi
• Negative Volume Index: nvi
• On-Balance Volume: obv
• Positive Volume Index: pvi
• Price-Volume: pvol
• Price Volume Trend: pvt

Indicator

• Average Directional Movement Rating: adxr
• Aroon: aroon
• Chaikins Volatility: cvi
• Directional Movement Index: dx
• Ease of Movement: emv
• Forecast Oscillator: fosc
• Linear Regression Intercept: linregintercept
• Linear Regression Slope: linregslope
• Market Facilitation Index: marketfi
• Mass Index: mass
• Rate of Change Ratio: rocr
• True Range: tr
• Ultimate Oscillator: ultosc
• Volume Oscillator: vosc
• Williams Accumulation/Distribution: wad

Overlay

• Average Price: avgprice
• Bollinger Bands: bbands
• Time Series Forecast: tsf
• Typical Price: typprice
• Weighted Close Price: wcprice
• Wilders Smoothing: wilders
• Zero-Lag Exponential Moving Average: zlema

Math

• Mean Deviation Over Period: md
• Standard Error Over Period: stderr

Ref: https://tulipindicators.org/list
Ref: https://github.com/twopirllc/pandas-ta~~