Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
A framework for intraday ensemble trading on the foreign exchange market
Thesis (PhD)--Stellenbosch University, 2024.
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Stellenbosch University
2025
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613741660504064 |
|---|---|
| access_status_str | Open Access |
| author | Koegelenberg, Dirk Johan Coetzee |
| author2 | Van Vuuren, J. H. |
| author_browse | Koegelenberg, Dirk Johan Coetzee Van Vuuren, J. H. |
| author_facet | Van Vuuren, J. H. Koegelenberg, Dirk Johan Coetzee |
| author_sort | Koegelenberg, Dirk Johan Coetzee |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description |
Thesis (PhD)--Stellenbosch University, 2024. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/131719 |
| institution | Stellenbosch University (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:40:58.109Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Stellenbosch University |
| publisherStr | Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/131719 A framework for intraday ensemble trading on the foreign exchange market Koegelenberg, Dirk Johan Coetzee Van Vuuren, J. H. Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering. Foreign exchange -- Mathematical models Finance -- Mathematical models Investment analysis -- Data processing UCTD Thesis (PhD)--Stellenbosch University, 2024. ENGLISH BREAKFAST: Financial trading consists of traders buying and selling financial assets in the hope of generating profit over time. These assets are traded in financial markets, an example of which is the liquid and volatile Foreign exchange (Forex) market. Generating profit when trading on the Forex market is not a trivial task. Many traders are, in fact, unsuccessful due to a variety of complicating factors such as the stochastic nature of the Forex market, market information inefficiencies, and trader cognitive biases. One might think that these problems can be conquered with enough trading experience, but research on the topic has shown that even highly skilled investment managers struggle with trading performance consistency in the long term. Modelling the behaviour of the Forex market in the light of this market complexity might, therefore, seem daunting to any novice trader. In an attempt to overcome the inefficiencies inherent to human traders, however, trading algorithms have been proposed as an alternative for automating parts of the trading process. Substantial amounts of time and resources have been committed by researchers to the design of new and innovative trading algorithms tailored to the pursuit of trading profitably and the establishment of a competitive edge over human and other algorithmic contenders. As a result, various frameworks for developing trading algorithms have been proposed in the literature, each enabling the establishment of new approaches toward the development of such a trading algorithm. These frameworks, however, typically conform to one of two extremes: They are either problem-specific (focusing on a particular portion of the trading pipeline) or lack enough depth to facilitate the inner workings of, and communication between, different framework constituent components adequately. Moreover, few frameworks emphasise the potential benefits of employing ensembling approaches during the trading process in the context of intraday trading, especially in respect of trading strategy ensembling. An intraday ensemble-based trading framework is proposed in this dissertation with the objective of addressing the shortcomings of current frameworks for this purpose in the literature. More specifically, the framework is tailored to provide a detailed (albeit holistic) road map for its users which may be used to design an ensemble-based Forex trading algorithm. Apart from the pre-processing of input data, the framework also facilitates processes such as forecasting future market behaviour and trading strategy development. Forecasting is conducted by invoking various time series forecasting methods from the realm of machine learning which are ultimately ensembled into a single forecast. This ensemble forecast is then incorporated into the trading strategies developed which are, in turn, also ensembled so as to strike a balance between risk mitigation and returns maximisation when executing Forex trades in real time. The practicality of the proposed framework is demonstrated via a computerised instantiation thereof. This framework instantiation is verified, after which it is validated by conducting two simulated real-world trading case studies. AFRIKAANSE OPSOMMING: Finansi¨ele handel bestaan daaruit dat handelaars finansi¨ele bates koop en verkoop in die hoop om mettertyd wins te genereer. Hierdie bates word in finansi¨ele markte soos die likiede en wisselvallige buitelandse valutamark verhandel. Om wins op die buitelandse valutamark te genereer is nie ’n maklike taak nie. Baie handelaars is, in werklikheid, onsuksesvol as gevolg van ’n verskeidenheid kompliserende faktore soos die stogastiese aard van die buitelandse valutamark, ondoeltreffendhede van mark inligting, en kognitiewe vooroordele van handelaars. ’n Mens sou dink dat hierdie probleme met genoeg handelservaring oorkom kan word, maar navorsing oor die onderwerp het getoon dat selfs hoogs-geskoolde beleggingsbestuurders sukkel om konsekwent handelsprestasie oor die langtermyn te behaal. Om in die lig van hierdie markkompleksiteit te poog om die gedrag van die buitelandse valutamark te modelleer, kan dus vir enige handelaarsnuweling skrikwekkend voorkom. In ’n poging om die ondoeltreffendheid inherent aan menslike handelaars te oorkom, is handelsalgoritmes egter as ’n alternatief vir die outomatisering van dele van die handelsproses voorgestel. Aansienlike hoeveelhede tyd en hulpbronne is deur navorsers aan die ontwerp van nuwe en innoverende handelsalgoritmes toegewy wat toegespits is op die strewe na winsgewende handel en die vestiging van ’n mededingende voordeel bo menslike en ander algoritmiese mededingers. As gevolg hiervan is verskeie raamwerke vir die ontwikkeling van handelsalgoritmes in die literatuur voorgestel, wat elkeen die ontwerp van nuwe benaderings tot die ontwikkeling van s´o ’n handelsalgoritme moontlik maak. Hierdie raamwerke neem egter tipies die vorm van een van twee uiterstes aan: Hulle is ´of probleemspesifiek (met ander woorde gefokus op ’n spesifieke gedeelte van die handelspyplyn) ´of nie diepgaande genoeg om die binnewerking van, en kommunikasie tussen, verskillende raamwerk-komponente voldoende te bewerkstellig nie. Boonop beklemtoon min raamwerke die potensi¨ele voordele van die gebruik van samevoegingsbenaderings tydens die verhandelingsproses met betrekking tot intradag-handel, veral in die konteks van handelstrategiesamevoeging. ’n Intradag-samevoegingsgebaseerde handelsraamwerk word in hierdie proefskrif voorgestel om die tekortkominge van huidige raamwerke vir hierdie doel in die literatuur aan te spreek. Meer spesifiek, die raamwerk is ontwikkel om ’n gedetailleerde (alhoewel holistiese) roetekaart vir gebruikers daar te stel wat gebruik kan word om ’n samevoegingsgebaseerde buitelandse valutahandelsalgoritme te ontwerp. Afgesien van die vooraf-verwerking van toevoerdata, fasiliteer die raamwerk ook prosesse soos die voorspelling van toekomstige markgedrag en handelstrategieontwikkeling. Vooruitskatting word uitgevoer deur gebruik te maak van verskeie tydreeksvoorspellingsmetodes uit die gebied van masjienleer wat uiteindelik tot ’n enkele vooruitskatting saamgevoeg word. Hierdie saamgevoegde voorspelling word dan in die ontwikkelde handelstrategie¨e ge¨ınkorporeer wat op hul beurt ook saamgestel word om ’n balans te vind tussen risikobestuur en opbrengsmaksimering wanneer daar intyds op die valutamark verhandel word. v https://scholar.sun.ac.za vi Opsomming Die uitvoerbaarheid van die voorgestelde raamwerk word via ’n gerekenariseerde instansiasie daarvan gedemonstreer. Hierdie raamwerk instansiasie word geverifieer, waarna dit bekragtig word deur twee gesimuleerde, realistiese handelsgevallestudies uit te voer. Doctoral 2025-02-20T09:02:57Z 2025-02-20T09:02:57Z 2024-12 Thesis https://scholar.sun.ac.za/handle/10019.1/131719 en Stellenbosch University xxvi, 327 pages : illustrations application/pdf Stellenbosch University |
| spellingShingle | Foreign exchange -- Mathematical models Finance -- Mathematical models Investment analysis -- Data processing UCTD Koegelenberg, Dirk Johan Coetzee A framework for intraday ensemble trading on the foreign exchange market |
| title | A framework for intraday ensemble trading on the foreign exchange market |
| title_full | A framework for intraday ensemble trading on the foreign exchange market |
| title_fullStr | A framework for intraday ensemble trading on the foreign exchange market |
| title_full_unstemmed | A framework for intraday ensemble trading on the foreign exchange market |
| title_short | A framework for intraday ensemble trading on the foreign exchange market |
| title_sort | framework for intraday ensemble trading on the foreign exchange market |
| topic | Foreign exchange -- Mathematical models Finance -- Mathematical models Investment analysis -- Data processing UCTD |
| url | https://scholar.sun.ac.za/handle/10019.1/131719 |
| work_keys_str_mv | AT koegelenbergdirkjohancoetzee aframeworkforintradayensembletradingontheforeignexchangemarket AT koegelenbergdirkjohancoetzee frameworkforintradayensembletradingontheforeignexchangemarket |