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Optiver Competition Leaderboard Scores
Data Science and Analytics
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About
This collection provides detailed public leaderboard scores originating from the Kaggle Optiver Realised Volatility Prediction competition. The data offers insights into team performance and rankings throughout the duration of the challenge, which focused on predicting financial market volatility. The product includes a set of raw CSV files, along with a unified, pre-merged score file suitable for immediate analysis. This resource is essential for evaluating competitor strategies and understanding the dynamics of quantitative finance prediction tournaments.
Columns
The dataset includes critical metadata for competitor analysis, typically featuring four distinct fields:
- TeamId: A unique identifier assigned to each competing team.
- TeamName: The name provided by the participants for their team, with 3809 unique entries observed.
- PrivateLeaderboardRank: The final ranking of the team based on their performance against the private test set, ranging from 1 up to 3809.
- PrivateLeaderboardScore: The final metric score achieved by the team, showcasing a wide distribution with scores ranging from 0.2 up to 240.
Distribution
The information is provided as a collection of raw data files, with the primary component being in CSV format. The data set structure is defined by 4 columns, and records typically include 3809 valid rows, representing the number of competing teams. For instance, the
PrivateLeaderboardRank.csv file has a size of approximately 145.08 kB. This data product is static and is not expected to receive future updates.Usage
Ideal applications include performance benchmarking and competitive analysis in machine learning challenges. Users can leverage the data for evaluating the effectiveness of various modelling techniques applied to financial market data. It is highly suitable for research into prediction contest dynamics and volatility forecasting assessment.
Coverage
The scope of this data is defined entirely by the participants and results of the Kaggle Optiver Realised Volatility Prediction competition. It captures results relating to financial modelling and quantitative finance, focused on the specific time period and competitive environment of the tournament. No geographical or demographic scope is applicable beyond the global participation in the Kaggle event.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Analysts: For conducting post-competition performance reviews and modelling shakeup analysis.
- Financial Researchers: To study prediction success rates and score distribution in volatility forecasting tasks.
- Kaggle Participants: To compare their own performance metrics against the broader competitive field.
Dataset Name Suggestions
- Optiver Competition Leaderboard Scores
- Kaggle Optiver Volatility Predictor Results
- Realised Volatility Prediction Leaderboard Archive
- Optiver Team Performance Data
Attributes
Original Data Source:[Optiver Competition Leaderboard Scores](Optiver Competition Leaderboard Scores)
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