Event Details
Forecasting Royal Bank of Canada’s Stock Market Performance with LSTM and Markov Chain modeling
Presenter: Amer Kumar
Supervisor:
Date: Wed, July 26, 2023
Time: 11:00:00 - 00:00:00
Place: via Zoom - please see link below
ABSTRACT
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https://uvic.zoom.us/j/88142751628
Meeting ID: 881 4275 1628
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Abstract:
Stock price prediction is one of the most important aspects of financial investment. This research aims to provide insights into the dynamics of stock prices, enabling more informed decision-making in financial investments by combining these two modeling approaches. Using a four-layer long short-term memory (LSTM) architecture and the Root Mean Square Error (RMSE) as the loss function, we aim to capture temporal dependencies and patterns to predict closing prices. Furthermore, we employ a three-state Markov chain to estimate the transition matrix, and metrics like steady-state distribution and mean hitting times have been used to calculate the matrix. The preliminary results indicate that this approach shows promising results for stock market prediction as LSTM has predictive power that caters more to long-term temporal trends while Markov Chain provides probabilistic values for staying and transitioning to states. The findings of the study highlight the effectiveness of combining LSTM and Markov Chain in capturing the intricate dynamics of the stock market data and predicting stock market prices.