“Supervised Autoencoder MLP in Financial Time Series Forecasting” - seminarium QFRG i DSLab [04.03.2024]
Serdecznie zapraszamy do wzięcia udziału w kolejnym seminarium organizowanym przez Quantitative Finance Research Group i Data Science Lab.
Podczas najbliższego spotkania wyniki swojego badania zaprezentują Bartosz Bieganowski – student anglojęzycznego programu WNE UW Quantitative Finance oraz dr hab. Robert Ślepaczuk, prof. ucz. – Kierownik Katedry Finansów Ilościowych i Uczenia Maszynowego WNE.
Spotkanie odbędzie się 4 marca 2024 r. od godz. 18:30 w formule hybrydowej: w sali B002 na WNE UW (ul. Długa 44/50) oraz za pośrednictwem platformy Zoom.
Meeting ID: 642 899 6565, hasło: xvx1Vh.
Link do spotkania:
https://uw-edu-pl.zoom.us/j/6428996565?pwd=cEcwemFXOVRLUDVLYU8xRVUwZDhEdz09
Spotkanie będzie prowadzone w języku angielskim.
Prosimy o zalogowanie najpóźniej o godz. 18:20.
Abstrakt:
This paper investigates the enhancement of financial time series forecasting with the use of neural networks through supervised autoencoders, aiming to improve investment strategy performance. It specifically examines the impact of noise augmentation and triple barrier labeling on risk-adjusted returns, using the Sharpe and Information Ratios. The study focuses on the S&P 500 index, EUR/USD, and BTC/USD as the traded assets from January 1, 2010, to April 30, 2022. Findings indicate that supervised autoencoders, with balanced noise augmentation and bottleneck size, significantly boost strategy effectiveness. However, excessive noise and large bottleneck sizes can impair performance, highlighting the importance of precise parameter tuning. This paper also presents a derivation of a novel optimization metric that can be used with triple barrier labeling. The results of this study have substantial policy implications, suggesting that financial institutions and regulators could leverage techniques presented to enhance market stability and investor protection, while also encouraging more informed and strategic investment approaches in various financial sectors.
