Primary competition visual

Cryptocurrency Closing Price Prediction

Helping Global
$1 000 USD
Challenge completed ~4 years ago
Prediction
795 joined
354 active
Starti
Jun 25, 21
Closei
Sep 19, 21
Reveali
Sep 19, 21
About

This is a comprehensive dataset that captures the prices of a cryptocurrency along with the various features including social media attributes, trading attributes and time related attributes that were noted on an hourly basis during several months and that contribute directly or indirectly to the cryptocurrency volatile prices change.

A starter notebook is provided to help you make your first submission and land on the leaderboard.

Variable definitions

  • asset_id: An asset ID. We refer to all supported cryptocurrencies as assets
  • open: Open price for the time period
  • close: Close price for the time period
  • high: Highest price of the time period
  • low: Lowest price of the time period
  • volume: Number of tweets
  • market_cap: Total available supply multiplied by the current price in USD
  • url_shares: Every time an identified relevant URL is shared within relevant social posts that contain relevant terms
  • unique_url_shares: Number of unique url shares posted and collected on social media
  • reddit_posts: Number of latest Reddit posts for supported coins
  • reddit_posts_score: Reddit Karma score on individual posts
  • reddit_comments: Comments on Reddit that contain relevant terms
  • Reddit_comments_score: Reddit Karma score on comments
  • tweets: Number of crypto-specific tweets based on tuned search and filtering criteria
  • tweet_spam: Number of tweets classified as spam
  • tweet_followers: Number of followers on selected tweets
  • tweet_quotes: Number of quotes on selected tweets
  • tweet_retweets: Number of retweets of selected tweets
  • tweet_replies: Number of replies on selected tweets
  • tweet_favorites: Number of likes on an individual social post that contains a relevant term
  • tweet_sentiment1: Number of tweets which has a sentiment of “very bullish”
  • tweet_sentiment2: Number of tweets which has a sentiment of “bullish”
  • tweet_sentiment3: Number of tweets which has a sentiment of “neutral”
  • tweet_sentiment4: Number of tweets which has a sentiment of “bearish”
  • tweet_sentiment5: Number of tweets which has a sentiment of “very bearish”
  • tweet_sentiment_impact1: “Very bearish” sentiment impact
  • tweet_sentiment_impact2: “Bearish” sentiment impact
  • tweet_sentiment_impact3: “Neutral” sentiment impact
  • tweet_sentiment_impact4: “Bullish” sentiment impact
  • tweet_sentiment_impact5: “Very bullish” sentiment impact
  • social_score: Sum of followers, retweets, likes, reddit karma etc of social posts collected
  • average_sentiment: The average score of sentiments, an indicator of the general sentiment being spread about a coin
  • news: Number of news articles for supported coins
  • price_score: A score we derive from a moving average that gives the coin some indication of an upward or downward based solely on the market value
  • social_impact_score: A score of the volume/interaction/impact of social to give a sense of the size of the market or awareness of the coin
  • correlation_rank: The algorithm that determines the correlation of our social data to the coin price/volume
  • galaxy_score: An indicator of how well a coin is doing
  • volatility: Volatility indicator
  • market_cap_rank: The rank based on the total available supply multiplied by the current price in USD
  • percent_change_24h_rank: The rank based on the percent change in price since 24 hours ago
  • volume_24h_rank: The rank based on volume in the last 24 hours
  • social_volume_24h_rank: The rank based on the number of social posts that contain relevant terms in the last 24 hours
  • social_score_24h_rank: The rank based on the sum of followers, retweets, likes, reddit karma etc of social posts collected in the last 24 hours
  • medium: Number of Medium articles for supported coins
  • youtube: Number of videos with description that contains relevant terms
  • social_volume: Number of social posts that contain relevant terms
  • price_btc: Exchange rate with another coin
  • market_cap_global: Total available supply multiplied by the current price in USD
  • percent_change_24h: Percent change in price since 24 hours ago
Files
Description
Files
Contains the target. This is the dataset that you will use to train your model.
Resembles Train.csv but without the target-related columns. This is the dataset on which you will apply your model to.
Shows the submission format for this competition, with the ‘id’ column mirroring that of Test.csv and the close column containing your predictions. The order of the rows does not matter, but the names of the id must be correct.
This notebook will help you make your first submission to this competition. If when you click download it opens a different tab, ctrl-S and it will download for you.