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Python library for Predicto API.

Predicto generates stock market signals and short-term forecasts daily. Powered by intelligible Deep Learning models, based on News & Options Data.

More info at


Start by installing required packages

pip install -r predicto_api/requirements.txt

To use predicto_api wrapper, you'll need a valid account at, and an api_key that you can find in your page.

from predicto_api_wrapper import PredictoApiWrapper

# retrieve api_key from your page
api_key = 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxx'

# prepare our predicto api wrapper
api = PredictoApiWrapper(api_key)

Retrieving Predicto Nasdaq-100 Signals

Predicto Nasdaq Signals are generated daily and are based on the combined forecasting power of hundreds of Deep Learning models.

Nasdaq Outlook Score gives you a stock market feeling with a 15-days ahead horizon.

Nasdaq Forecasted Volatility is the standard deviation of the forecasted 15-days ahead movements (percentage).

Nasdaq Models Uncertainty is a measurement of how uncertain our models are with current market conditions (percentage).

For detailed information, please check and

For detailed usage, check the predicto_api_nasdaq_signals.ipynb in the Notebooks folder.

# retrieve info for last 20 days
since_date = ( - timedelta(days=20)).strftime('%Y-%m-%d')

# get Nasdaq Outlook Score information
outlook_json = api.get_nasdaq_outlook_score_since(since_date)

# get Nasdaq Forecasted Volatility information
volatility_json = api.get_nasdaq_forecasted_volatility_since(since_date)

# get Models Uncertainty information
uncertainty_json = api.get_nasdaq_models_uncertainty_since(since_date)

Retrieving AutoTrader's stock forecasts and trade picks

For detailed usage, check the predicto_api_example_usage.ipynb in the Notebooks folder.

import pandas as pd

# get suppported tickers for which daily forecasts are available
tickers_json = api.get_supported_tickers()
tickers_df = pd.DataFrame(tickers_json)

# define the ticker and date we are interested in (use yesterday's date to get latest)
ticker = 'TSLA'
date = '2020-11-28'

# get forecast dataframe
forecast_json = api.get_forecast(ticker, date)
forecast_df = pd.read_json(forecast_json, orient='index')

# get trade pick based on that forecast (entry, exit, stop-loss price)
trade_pick_json = api.get_trade_pick(ticker, date)

Using Predicto with Alpaca to setup daily AutoTrader

Make sure you understand the risks if you are using real money! We recommend that you start by experimenting with an Alpaca Paper acccount.

from predicto_api_wrapper import PredictoApiWrapper, TradeAction, TradeOrderType
from alpaca_api_wrapper import AlpacaApiWrapper

# initialize alpaca api wrapper
alpaca_api_endpoint = '' # use paper money endpoint for now (test env)
alpaca_api_key_id = 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'
alpaca_api_secret_key = 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'

alpaca_wrapper = AlpacaApiWrapper(alpaca_api_endpoint, alpaca_api_key_id, alpaca_api_secret_key)

# initialize predicto api wrapper
predicto_api_key = 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'
api = PredictoApiWrapper(predicto_api_key)

# Option 1:
#   Execute Predicto AutoTrader
#   You can schedule this script to run daily just after market open (9.31am E.T.).
#   It will submit last day's Trade Picks matching your criteria.
#   Note: Make sure you understand the risks if you are using real money!
        abs_change_pct_threshold = 0.02,
        actions = [int(TradeAction.Buy), int(TradeAction.Sell)],
        average_uncertainty = 0.15,
        model_avg_roi = 0.0,
        symbols = None,

# Option 2:
#   Execute Predicto AutoTrader using "My Picks" as you picked them in Predicto website!
#   Manually pick them every night at
#   You can schedule this script to run daily just after market open (9.31am E.T.)
#   It will submit last day's "My Picks"
#   Note: Make sure you understand the risks if you are using real money!

AutoTrader daily script

Sample AutoTrader using Predicto Forecasts with Alpaca can be found in or in the samples folder.

Jupyter Notebook For Predicto API interactions

For detailed usage of PredictoApiWrapper, check the predicto_api_example_usage.ipynb in the Notebooks folder.

Jupyter Notebook for AutoTrader using Alpaca API

You can use latest Forecasts and Trade Picks generated by Predicto with Alpaca API. To see how, check the predicto_autotrader_example.ipynb in the Notebooks folder.

More info on Alpaca API and for documentation, check

More info

For more information on how our Deep Learning forecasts are generated, follow us on


Please read our disclaimer carefully:


Python library for predicto api








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