24th QFRG and DSLab seminar online [7.11.2022]
We kindly invite to join 24th seminar organised jointly by QFRG (Quantitative Finance Research Group) i DSLab (Data Science Lab).
During the meeting Illia Baranochnikov, student of the graduate program Quantitative Finance at the Faculty of Economic Sciences and prof. Robert Ślepaczuk, Head of the Department of Quantitative Finance of the Faculty will present the results of the research „A comparison of LSTM and GRU architectures with novel walk-forward approach to algorithmic investment strategy”.
Description:
The aim of this work is to build a profitable algorithmic investment strategy on various types of assets. The algorithm is built using recurrent neural networks (LSTM and GRU) as the primary source of signals to buy/sell financial instruments. LSTM and GRU architectures are compared in terms of obtaining the best results and beating the market. The algorithm is tested for four financial instruments (Bitcoin, Tesla, Brent Oil and Gold) on daily and hourly data frequencies. The out-of-sample period is from 1 January 2021 to 1 April 2022. A walk-forward process is responsible for training models and selecting the best model to forecast asset prices in the future. Ten model architectures with various hyperparameters are trained during each step of the walk-forward process. The model architecture with the highest Information Ratio (IR*) in the validation period is used for forecasting in the out-of-sample period. For each strategy, the performance metrics are calculated based on which the profitability of the algorithm is evaluated. At the end, a detailed sensitivity analysis with regards to the main hyperparameters is conducted. The results reveal that LSTM outperforms GRU in most of the cases and that investment strategy built based on LSTM/GRU architecture is able to beat the market only on 50% of tested cases.
The meeting will be held on November 7th at 6:30 p.m. via Zoom platform and will be held in English.
Link to the meeting: https://bit.ly/qfrg-dslab-seminar
Meeting ID: 982 2842 8808
Passcode: 636564
Please log in at the latest at 6:20 PM. The presentation is scheduled for about 45 minutes and after that we invite you to a discussion.
Joining a meeting implies consent to the recording. Please turn off cameras and microphones during the presentation and send the questions to the speaker in the chat.
