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Multivariate Hawkes Process Modeled News Flow: Forecasting Financial Markets
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
2018 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesisAlternative title
Multivariat Hawkes-process-modellerat nyhetsflöde: prognosticering av finansiella marknader (Swedish)
Abstract [en]

Within the quantitative financial community there are a lot of different approaches in forming profitable trading strategies. This is frequently performed by analyzing historical prices from different perspectives. Some have analyzed other factors than price that might provide insight in which way the market is heading, which in some cases have been successful. This thesis investigates if a news flow model based on a multivariate Hawkes process could give a peek into the future news flow, and if it can be used to successfully predict financial market movements in terms of logarithmic returns by utilizing regression and classification models such as support vector machines. The results show that the trained models perform poorly in general in terms of common regression and classification metrics. Applying the trained models in simple trading strategies show that in some cases they perform better than a buy-and-hold strategy. The ambiguous results indicate that the models might be profitable in trading strategies, but that the predictions might not be very reliable. The trained models cannot seem to find important structures in the predicted news flow relating to market returns, but before dismissing the news flow model entirely it might altered in some sense by, e.g., expanding the dataset with more observations and by looking at other granularities of time.

Abstract [sv]

Kvantitativa analytiker inom finansvärlden försöker med olika tillvägagångssätt utforma vinnande trading-strategier. Oftast görs detta genom att analysera historiska priser från olika perspektiv. Vissa har analyserat andra faktorer än prisrelaterade sådana, i hopp om att dessa ska ge insikt om vart marknaden är på väg, som i vissa fall har lyckats. Det här arbetet undersöker om en nyhetsflödesmodell baserad på en multivariat Hawkes-process kan ge en inblick i det framtida nyhetsflödet, och om det kan användas för att lyckosamt prediktera finansiella marknaders rörelser i termer av logaritmisk avkastning genom att nyttja regressions- och klassificeringsmodeller. Resultaten visar att de tränade modellerna generellt sett presterar dåligt i termer av vanliga regressions- och klassificeringsmått. Genom att applicera de tränade modellerna till enkelt utformade trading-strategier visas att i vissa fall kan dessa prestera bättre än en buy-and-hold-strategi. De tvetydiga resultaten indikerar att modellerna kan vara lönsamma, men att prediktionerna inte är särskilt pålitliga. De tränade modellerna verkar inte kunna finna viktiga strukturer i data från nyhetsflödesmodellen som relaterar till marknadsavkastningar, men innan nyhetflödesmodellen avfärdas skulle den kunna modifieras genom att, t. ex., utöka antalet observationer, och genom att undersöka andra tidsgranulariteter.

Place, publisher, year, edition, pages
2018. , p. 56
Keywords [en]
hawkes, hawkes process, finance, financial application, news flow, news, trading, futures, prediction, forecast
National Category
Mathematics
Identifiers
URN: urn:nbn:se:umu:diva-157671OAI: oai:DiVA.org:umu-157671DiVA, id: diva2:1300563
External cooperation
Lynx Asset Management AB
Educational program
Master of Science in Engineering and Management
Supervisors
Examiners
Available from: 2019-04-01 Created: 2019-03-28 Last updated: 2019-04-01Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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