Astock
(1) provide financial news for each specific stock. (2) provide various stock technical factors and fundamental factors for each stock.
Papers with Code 아카이브
Stock Price Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 1
- 보존된 평가 기록
- 1
Stock Price Prediction is the task of forecasting future stock prices based on historical data and various market indicators. It involves using statistical models and machine learning algorithms to analyze financial data and make predictions about the future performance of a stock. The goal of stock price prediction is to help investors make informed investment decisions by providing a forecast of future stock prices.
데이터셋
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
EDT
The EDT dataset is designed for corporate event detection and text-based stock prediction (trading strategy) benchmark. 1. Corporate Event Detection It includes 9721 news articles with token-level event labels. Including 11 event types: Acquisitions, Clinical Trials, Guidance Changes, New Contracts, Stock Repurchases, Stock Split, Reverse Stock Split/ADS Ratio Change, Regular Dividend, Special Dividend, Dividend Cut, Dividend Increase 2. Text-Based Stock Prediction Benchmark It includes 303893 first-hand news articles from high-quality sources. Each news article is assigned a minute-level timestamp and comprehensive stock price labels. Please see this Github Link and paper for more details.
TRADES-LOB
TRADES-LOB comprises simulated TRADES market data for Tesla and Intel, for 29/01 and 30/01. Specifically, the dataset is structured into four CSV files, each containing 50 columns. The initial six columns delineate the order features, followed by 40 columns that represent a snapshot of the LOB across the top 10 levels. The concluding four columns provide key financial metrics: mid-price, spread, order volume imbalance, and Volume-Weighted Average Price (VWAP), which can be useful for downstream financial tasks, such as stock price prediction. In total, the dataset is composed of 265,986 rows and 13,299,300 cells, which is similar in size to the benchmark FI-2010 dataset.
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.