Market Simulations with a Matching Engine
| dc.contributor.advisor | Gebbie, Timothy | |
| dc.contributor.author | Jericevich, Ivan | |
| dc.date.accessioned | 2023-03-02T11:03:30Z | |
| dc.date.available | 2023-03-02T11:03:30Z | |
| dc.date.issued | 2022 | |
| dc.date.updated | 2023-02-20T12:58:21Z | |
| dc.description.abstract | We demonstrate the CoinTossX Java web-application as a low-latency, high-throughput, open-source matching engine/artificial exchange/simulation platform and deploy it to a cloud environment for asynchronous order matching and submission in a controlled framework via two seperate simulation techniques — Hawkes processes and agent-based modelling. A 10-variate Hawkes model stress tests the software whilst measuring the extent to which a matching engine can cloud the modelling of underlying order submission and management processes in a continuous-double auction. Estimation and calibration to the subsequent trade-and-quote data results in a model specification statistically different from the original — providing insight into the limits of the software, inference conducted on HFT models and future market microstructure modelling considerations. An asynchronous ABM with interacting low-frequency liquidity takers and high-frequency liquidity-providers is subsequently formulated with the aim of producing realistic trading scenarios/price action without relying on restrictive modelling assumptions or additional sources of noise. The resulting simulations are shown to replicate many stylized facts along with non-trivial price-impact curves and we use this to argue for future simple, reactive/actor-based financial model specifications that mimics real-world work-flow and system implementation. | |
| dc.identifier.apacitation | Jericevich, I. (2022). <i>Market Simulations with a Matching Engine</i>. (). ,Faculty of Science ,Department of Statistical Sciences. Retrieved from http://hdl.handle.net/11427/37141 | en_ZA |
| dc.identifier.chicagocitation | Jericevich, Ivan. <i>"Market Simulations with a Matching Engine."</i> ., ,Faculty of Science ,Department of Statistical Sciences, 2022. http://hdl.handle.net/11427/37141 | en_ZA |
| dc.identifier.citation | Jericevich, I. 2022. Market Simulations with a Matching Engine. . ,Faculty of Science ,Department of Statistical Sciences. http://hdl.handle.net/11427/37141 | en_ZA |
| dc.identifier.ris | TY - Master Thesis AU - Jericevich, Ivan AB - We demonstrate the CoinTossX Java web-application as a low-latency, high-throughput, open-source matching engine/artificial exchange/simulation platform and deploy it to a cloud environment for asynchronous order matching and submission in a controlled framework via two seperate simulation techniques — Hawkes processes and agent-based modelling. A 10-variate Hawkes model stress tests the software whilst measuring the extent to which a matching engine can cloud the modelling of underlying order submission and management processes in a continuous-double auction. Estimation and calibration to the subsequent trade-and-quote data results in a model specification statistically different from the original — providing insight into the limits of the software, inference conducted on HFT models and future market microstructure modelling considerations. An asynchronous ABM with interacting low-frequency liquidity takers and high-frequency liquidity-providers is subsequently formulated with the aim of producing realistic trading scenarios/price action without relying on restrictive modelling assumptions or additional sources of noise. The resulting simulations are shown to replicate many stylized facts along with non-trivial price-impact curves and we use this to argue for future simple, reactive/actor-based financial model specifications that mimics real-world work-flow and system implementation. DA - 2022_ DB - OpenUCT DP - University of Cape Town KW - Statistical Sciences LK - https://open.uct.ac.za PY - 2022 T1 - Market Simulations with a Matching Engine TI - Market Simulations with a Matching Engine UR - http://hdl.handle.net/11427/37141 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/37141 | |
| dc.identifier.vancouvercitation | Jericevich I. Market Simulations with a Matching Engine. []. ,Faculty of Science ,Department of Statistical Sciences, 2022 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/37141 | en_ZA |
| dc.language.rfc3066 | eng | |
| dc.publisher.department | Department of Statistical Sciences | |
| dc.publisher.faculty | Faculty of Science | |
| dc.subject | Statistical Sciences | |
| dc.title | Market Simulations with a Matching Engine | |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationlevel | MSc |