16 datasets found

Real data for asset bubbles detection using LSTM network

Simulated data for asset bubbles detection using LSTM network

The dataset consists of historical prices of 19 popular cryptocurrencies.

The dataset used in this study contains daily pricing information and return values from January 1998 to June 2020 for hedge funds, banks, brokerages, and insurers.

Limit Order Book dataset from US market, containing buy and sell limit order information (prices and volumes) over 10 business days from 10 large-cap US stocks.

Limit Order Book dataset from Nordic market, containing buy and sell limit order information (prices and volumes) over 10 business days from 5 Finnish stocks traded in Helsinki...

Electricity, coal, gas, and fuel prices dataset for testing deep hedging strategies

The dataset used in the paper to calculate the cost of capital.

The dataset used in this paper is the Center for Research in Securities Prices (CRSP) database sampled between January 1963 and December 2018.

The dataset used in the paper is a sequence of financial markets with underlying assets (S(n))n∈N that are converging weakly to S.

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

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 used in this paper is a collection of Mid-Curve Calendar Spread (MCCS) trades, ranging from September 2006 to September 2016, with different expirations, forward and...

Portfolio management aims at maximizing the return on investment while minimizing risk by continuously reallocating the assets forming the portfolio. These assets are not...