Finance
This dataset comes from the Wind database. This dataset includes a series of Shanghai Stock Exchange 50 ETF option data due in December 2022. This dataset also includes some economic variables.The data used in this article is the trading data of Shanghai Stock Exchange 50ETF call options. The time of option data is from April 28 to October 26, 2022, sourced from the WIND database. The exercise price range of the selected option is from 2.5 to 3.5 (European call options). In addition, the expiration date of the options in this experiment is December 28, 2022.
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The dataset tracks the performance of 4 major global stock market indexes over a 5 year period from August 2018 to August 2023. It includes the S&P 500 (USA), Nasdaq 100 (USA), Shanghai Composite (China), and Taiwan Weighted Index (Taiwan). The indexes represent key benchmarks for the US, Chinese, and Taiwanese equity markets. Analysis of the dataset can provide insights into relative performance, correlations, and volatility across these major markets.
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The process of dataset generation comprises three integral components: "Account Profiles," responsible for creating detailed account representations; "Transaction Generation," which simulates a diverse range of financial transactions; and the "Generation of Fraud Scenarios," which introduces predefined templates for identifying potential fraudulent transactions based on various criteria. Together, these components collaboratively construct a dynamic and realistic dataset, mirroring real-world financial systems.
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The datasets are all EXCEL files, and the datasets include daily stock price changes of three listed companies from 2021.1.4 to 2021.12.31 and Shanghai banking borrowing rates from 2021.2.2 to 2021.12.28. The three listed companies are Xiaomi Group, Zijin Mining and Fuwei Film and TV, which are representative in their respective fields. Since most of the numerical simulation parameters are directly given artificially in the existing studies, which is not convincing.
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The dataset is pre-processed from two datasets: UCI credit card dataset (https://archive.ics.uci.edu/ml/datasets/default+of+credit+card+clients) and ULB credit card dataset (https://www.kaggle.com/mlg-ulb/creditcardfraud).
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