69 datasets found

The dataset used in this paper is a time series of monthly excess returns and volatility from 1927 to 2019.

Dataset of 11,762,646 trades on 45 equities

Dataset of 24,964,980 trades made through the Budapest Stock Exchange between 2 January 2008 and 31 December 2008

The dataset contains high-frequency news sentiment and volatility of the S&P 500.

The dataset used in the paper is an equity market dataset, which contains daily prices and trading volumes of approximately 3,600 stocks between 2009 and 2018.

The dataset used in the paper is the Episode Filter dataset, which is a real-time API that facilitates easier experimentation with the KOSPI and KOSDAQ stock market data.

The dataset used in the paper is the KOSPI and KOSDAQ stock market data, which includes order book data and price and trade volume data.

The dataset contains Bitcoin price history from April 2019 to June 2020, with daily returns, volatility, and jump sizes.

The dataset is used to estimate the parameters of a Markov-Modulated Jump-Diffusion Model (MMJDM) for stock prices.

The dataset is used to estimate the parameters of a Markov-Modulated Jump-Diffusion Model (MMJDM) for stock prices.

The dataset used in this paper is the China stock market data, which includes daily technical data like open, close, high, low, returns, volume, vwap, cap, and fundamental data...

US stock prices listed on Standard & Poor’s 500 (S&P 500) Stock Index and UK stock prices from the London Stock Exchange (LSE)

The dataset used in this paper is a collection of synthetic market data generated via a Merton jump diffusion.

The dataset used in this paper is a collection of synthetic market data generated via a geometric Brownian motion.

The dataset used in this paper is a collection of one-hourly log-returns rS associated to the SPY index from 2005-01-03 to 2020-12-31.

The dataset contains daily forced liquidation data of BitMEX perpetual futures, daily volume, forced liquidation, open interest and daily OHLC prices.

The dataset contains daily return of five stock market indices: Nasdaq (US), Straits Times Index (STI, Singapore), Hang Seng Index (Hong Kong), Corea SE (Corea) and AEX (Holland).

The dataset used in this paper is a high-frequency order book data, specifically BUND futures data.

The dataset used in the paper is a financial market dataset, containing price data, technical analysis indicators, and hand-crafted features.

The dataset employed in this study is sourced from Yahoo Finance using Python and focuses exclusively on the equity market.