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A machine learning approach in financial markets
Blekinge Tekniska Högskola, Institutionen för programvaruteknik och datavetenskap.
2003 (engelsk)Independent thesis Advanced level (degree of Master (One Year))Oppgave
Abstract [en]

In this work we compare the prediction performance of three optimized technical indicators with a Support Vector Machine Neural Network. For the indicator part we picked the common used indicators: Relative Strength Index, Moving Average Convergence Divergence and Stochastic Oscillator. For the Support Vector Machine we used a radial-basis kernel function and regression mode. The techniques were applied on financial time series brought from the Swedish stock market. The comparison and the promising results should be of interest for both finance people using the techniques in practice, as well as software companies and similar considering to implement the techniques in their products.

sted, utgiver, år, opplag, sider
2003. , s. 36
Emneord [en]
Financial time series, indicator optimization, support vector machines, prediction
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-5571Lokal ID: oai:bth.se:arkivex84B8AC103A83D1CCC1256D95002E28FEOAI: oai:DiVA.org:bth-5571DiVA, id: diva2:832956
Uppsök
Physics, Chemistry, Mathematics
Veileder
Tilgjengelig fra: 2015-04-22 Laget: 2003-09-02 Sist oppdatert: 2018-01-11bibliografisk kontrollert

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