PsychSignal Trader Mood (DEPRECATED)¶

Point-In-Time¶

Starting in January 2016, PsychSignal data has been collected and surfaced in a point-in-time fashion on Quantopian. This corresponds to when Quantopian started downloading and storing PsychSignal data on a nightly basis. Timestamps for historical data prior to January 2016 are approximated by adding 24 hours to the asof_date of each record.

Import¶

from quantopian.pipeline.data.psychsignal import (
    aggregated_twitter_withretweets_stocktwits, #Psychsignal data from Twitter and Stocktwits.
    stocktwits,                                 #Psychsignal data from Stocktwits.
    twitter_noretweets,                         #Psychsignal data from Twitter (no retweets).
    twitter_withretweets,                       #Psychsignal data from Twitter (with retweets).
)

Example¶

This code snippet constructs and runs a pipeline that computes the percentage of total scanned messages that are classified as 'positive' by PsychSignal. Note that this example uses the twitter_withretweets dataset, importing it under the alias twitter_sentiment.

from quantopian.pipeline import Pipeline
from quantopian.pipeline.data.psychsignal import twitter_withretweets as twitter_sentiment
from quantopian.pipeline.domain import US_EQUITIES
from quantopian.research import run_pipeline

# Define a positive sentiment percent factor, dividing the number of bull
# scored messages by the total number of scanned messages for the equity.
positive_sentiment_pct = (
    twitter_sentiment.bull_scored_messages.latest
    / twitter_sentiment.total_scanned_messages.latest
)

# Add the factor as a column in the pipeline.
pipe = Pipeline(
    columns={
        'positive_sentiment_pct': positive_sentiment_pct,
    },
    domain=US_EQUITIES,
)

# Run the pipeline over one year and print the first few rows of the result.
df = run_pipeline(pipe, '2015-05-05', '2016-05-05')
print(df.head())

Datasets¶

• aggregated_twitter_withretweets_stocktwits - A pipeline dataset that provides access to trader mood data collected from StockTwits posts as well as Twitter posts, including retweets.
• stocktwits - A pipeline dataset that provides access to trader mood data collected from Stocktwits posts, including retweets.
• twitter_withretweets - A pipeline dataset that provides access to trader mood data collected from Twitter posts, including retweets.
• twitter_noretweets - A pipeline dataset that provides access to trader mood data collected from Twitter posts, excluding retweets.

Fields¶

Each PsychSignal dataset has the following fields (accessible as BoundColumn attributes):

• asof_date (dtype datetime64[ns]) - The effective date of the sentiment record (date when the record first applies).
• bear_scored_messages (dtype float) - Total count of bearish sentiment messages scored by PsychSignal's algorithm.
• bearish_intensity (dtype float) - Continuous value ranging from 0 to 4 representing the average intensity of bear scored messages.
• bull_bear_msg_ratio (dtype float) - Ratio of bull scored messages to bear scored messages.
• bull_minus_bear (dtype float) - Difference of bull scored messages minus bear scored messages.
• bull_scored_messages (dtype float) - Total count of bullish sentiment messages scored by PsychSignal's algorithm.
• bullish_intensity (dtype float) - Continuous value ranging from 0 to 4 representing the average intensity of bull scored messages.
• total_scanned_messages (dtype float) - Number of messages coming through PsychSignal's feeds, regardless of whether the PsychSignal sentiment engine can score them for bullish or bearish sentiment.