IteraLabs / atelier

A Computational Framework/Engine for Market Microstructure High Frequency Modeling, Synthetic Simulation and Historical Market Reconstruction/Replay
https://www.iteralabs.ai
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Implement Quant Metrics from TradFi Book #46

Open IFFranciscoME opened 1 day ago

IFFranciscoME commented 1 day ago

In order to provide a bridge to the Traditional Quantitative Finance literature, the project needs to support some calculations done within seminal works, research papers and books.

Problem

There is no direct reference of an academic, research content into the projects capacity

Solution

Take a seminal reference in Market Microstructure and chose an objective to reproduce.

Success Criteria

The table 4.1, on page 60, in [1] can be fully* produced for any given struct created from a synthetic progression of the order book struct

// -- Intra-day Patterns : Table 4.1

 1 Average share price (dollars)
 2 Average quoted spread†(dollars)
 3 Average spread before transactions (dollars)
 4 Fraction of MO that match at worse prices than the best quote
 5 Fraction of MO that match a hidden order inside the spread
 6 Mean total volume at best quotes (dollars ×10^3)
 7 Mean daily traded volume on NASDAQ†(dollars ×10^6)
 8 Mean fraction of daily traded volume that is hidden
 9 Mean total volume of active orders within 1% of mid-price (dollars ×10^6)
10 Average stock-specific market share of NASDAQ
11 Average total market capitalisation (dollars ×10^9)
12 Average daily number (Best Quote Orders ×10^3)
13 Mean Inter-Arrival Time of Best Quote Orders (seconds)
14 Median Inter-Arrival Time of Best Quote Orders (seconds)
15 Mean Size of Best Quote Orders (dollars ×10^3)

[1] J.-P. Bouchaud, J. Bonart, J. Donier, and M. Gould, Trades, Quotes and Prices: Financial Markets Under the Microscope. Cambridge, UK: Cambridge University Press, Mar. 2018.