Technical Analysis Time Series for Machine Learning
Project description
tatspy
A package to calculate time series of technical analysis indicators for stocks
Description
tatspy is a package you can use to get information such as:
- the historical prices of a stock over a given period
- the values of technical analysis indicators (such as MACD, bollinger bands etc.) over a given period.
It features not only american stocks, but also stocks from around the globe, featuring countries such as Brazil, Spain, and others.
For example...
For example, you could use tatspy to get the daily values of the MACD, bollinger bands, parabolic SAR and ATR (among other) for Brazilian's oil giant Petrobras.
How?
The tatspy package defines a class called stock.
It receives two attributes: the stock's ticker and its country
This stock has a couple of useful methods:
get_stock_historical_prices: returns the historical prices (OHLC) of a stock for a given period, defined by the user.get_technical_indicators: returns a dataframe with time series for a set of technical analysis indicatorslag_indicators: returns a dataframe with specified lags of technical analysis indicators, for Time Series analysis
The outputs of these methods are also saved as class attributes within each instance.
Available Technical Analysis Indicators
At present, the following technical analysis indicators are made available by tatspy:
- 'simple_moving_average' : simple moving average of stock price
- 'exponential_moving_average': exponential moving average of stock price
- 'RSI': Relative Strength Index
- 'bollinger_bands': Bollinger Bands
- 'bollinger_bands_indicator': Indicates if stock price close to bands, suggesting price reversal
- 'MACD' : Moving Average Convergence-Divergence
- 'stochastic': Stochastic Oscillator
- 'VWAP': Volume Weighted Average Price
- 'ATR': Average True Range
- 'ADX': Average Directional Index
- 'parabolic_SAR': Parabolic SAR
- 'parabolic_SAR_indicator: Indicates if parabolic SAR suggests a price reversal upwards (+1) or downwards (-1)
- 'TRIX': Triple Exponential Average
Citations
I am grateful for the authors of the following packages, which have been very helpful in building tatspy:
- Alvaro Bartolome del Canto. (2018-2020). investpy - Financial Data Extraction from Investing.com with Python. https://github.com/alvarobartt/investpy.
- DarÃo López Padial (aka Bukosabino). ta. https://github.com/bukosabino/ta.
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