A survey of forex and stock price prediction using deep learning
Predictions of stock and foreign exchange (Forex) have always been a hot and profitable
area of study. Deep learning applications have been proven to yield better accuracy and …
area of study. Deep learning applications have been proven to yield better accuracy and …
Trends and applications of machine learning in quantitative finance
S Emerson, R Kennedy, L O'Shea… - … conference on economics …, 2019 - papers.ssrn.com
Recent advances in machine learning are finding commercial applications across many
industries, not least the finance industry. This paper focuses on applications in one of the …
industries, not least the finance industry. This paper focuses on applications in one of the …
Multimodal deep learning for finance: integrating and forecasting international stock markets
SI Lee, SJ Yoo - The Journal of Supercomputing, 2020 - Springer
In today's increasingly international economy, return and volatility spillover effects across
international equity markets are major macroeconomic drivers of stock dynamics. Thus …
international equity markets are major macroeconomic drivers of stock dynamics. Thus …
Deep portfolio optimization via distributional prediction of residual factors
Recent developments in deep learning techniques have motivated intensive research in
machine learning-aided stock trading strategies. However, since the financial market has a …
machine learning-aided stock trading strategies. However, since the financial market has a …
Forecasting the market with machine learning algorithms: An application of NMC-BERT-LSTM-DQN-X algorithm in quantitative trading
C Liu, J Yan, F Guo, M Guo - … on Knowledge Discovery from Data (TKDD …, 2022 - dl.acm.org
Although machine learning (ML) algorithms have been widely used in forecasting the trend
of stock market indices, they failed to consider the following crucial aspects for market …
of stock market indices, they failed to consider the following crucial aspects for market …
An enhanced wasserstein generative adversarial network with gramian angular fields for efficient stock market prediction during market crash periods
A Ghasemieh, R Kashef - Applied Intelligence, 2023 - Springer
At the beginning of 2020, the COVID-19 pandemic caused a sharp decline in equity market
indices, which remained stagnant for a considerable period. This resulted in significant …
indices, which remained stagnant for a considerable period. This resulted in significant …
Prediction of stock performance using deep neural networks
Stock performance prediction is one of the most challenging issues in time series data
analysis. Machine learning models have been widely used to predict financial time series …
analysis. Machine learning models have been widely used to predict financial time series …
Deep recurrent factor model: interpretable non-linear and time-varying multi-factor model
A linear multi-factor model is one of the most important tools in equity portfolio management.
The linear multi-factor models are widely used because they can be easily interpreted …
The linear multi-factor models are widely used because they can be easily interpreted …
Cross-sectional stock price prediction using deep learning for actual investment management
M Abe, K Nakagawa - Proceedings of the 2020 Asia Service Sciences …, 2020 - dl.acm.org
Stock price prediction has been an important research theme both academically and
practically. Various methods to predict stock prices have been studied until now. The feature …
practically. Various methods to predict stock prices have been studied until now. The feature …
Ric-nn: A robust transferable deep learning framework for cross-sectional investment strategy
K Nakagawa, M Abe… - 2020 IEEE 7th International …, 2020 - ieeexplore.ieee.org
Stock return predictability is an important research theme as it reflects our economic and
social organization, and significant efforts are made to explain the dynamism therein …
social organization, and significant efforts are made to explain the dynamism therein …