Order-flow and long-memory in a simulated financial market
收藏DataCite Commons2025-10-27 更新2026-05-07 收录
下载链接:
https://zivahub.uct.ac.za/articles/dataset/Order-flow_and_long-memory_in_a_simulated_financial_market/30449312/1
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资源简介:
This is the dataset used in our Honours Project on "Order-flow and long-memory in a simulated financial market". It can be used hand-in-hand with our code to replicate our findings. The data consists of intraday quote and trade tick (trade-by-trade) data for the top 42 stocks listed on the JSE, from January to December 2015. This data does not contain Trader IDs (a way of knowing which trade is associated with which trader) and thus one needs to apply a method for generating synthetic trader IDs for these trades. We used the Maitrier-Loeper-Bouchaud (MLB) algorithm once we had processed this raw data. Trader IDs are required in order to calculate metaorder lengths, which is a key component needed when estimating the microscopic exponent 'alpha'.
提供机构:
University of Cape Town
创建时间:
2025-10-27



