Naslov
Effect of labeling algorithms on financial performance metrics

Autori
Kovačević, Tomislav ; Goluža, Sven ; Merćep, Andro ; Kostanjčar, Zvonko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO) - proceedings / Skala, Karolj - Rijeka : Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2022, 980-984

ISBN
978-953-233-103-5

Skup
45th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2022)

Mjesto i datum
Opatija, Hrvatska, 23.05.2022. - 27.05.2022

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
financial time series ; stock prediction ; machine learning ; labeling algorithms

Sažetak
Machine learning models are increasingly common in predicting financial market movements. Unlike some other research areas, labels of financial time series are not unambiguously determined, which is why multiple labeling algorithms were proposed. The effect of a particular labeling algorithm on a trading strategy is often overlooked as most existing research uses only one type of labels to develop a machine learning model used for trading. However, different labeling algorithms lead to different generalization errors that may impede financial performance of a strategy. This paper examines the relationship between the classification performance of a model and the financial performance of a strategy based on the same model. The relationship is examined for two commonly used labeling algorithms: fixed-time horizon and triple-barrier method. Although the results for both labeling algorithms confirm a statistically significant correlation between classification and financial performance, the correlation coefficient itself has a low value.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA