Data science in economics: comprehensive review of advanced machine learning and deep learning methods
This paper provides a comprehensive state-of-the-art investigation of the recent advances in
data science in emerging economic applications. The analysis is performed on the novel …
data science in emerging economic applications. The analysis is performed on the novel …
Artificial intelligence in accounting and finance: Challenges and opportunities
Z Yi, X Cao, Z Chen, S Li - IEEE Access, 2023 - ieeexplore.ieee.org
The rapid expansion of artificial intelligence (AI) technologies presents novel technical
solutions to traditional accounting and finance problems. Despite this, scholars in …
solutions to traditional accounting and finance problems. Despite this, scholars in …
[HTML][HTML] Blockchain metrics and indicators in cryptocurrency trading
JC King, R Dale, JM Amigó - Chaos, Solitons & Fractals, 2024 - Elsevier
The objective of this paper is the construction of new indicators that can be useful to operate
in the cryptocurrency market. These indicators are based on public data obtained from the …
in the cryptocurrency market. These indicators are based on public data obtained from the …
Two robust long short-term memory frameworks for trading stocks
This paper aims to find a superior strategy for the daily trading on a portfolio of stocks for
which traditional trading strategies perform poorly due to the low frequency of new …
which traditional trading strategies perform poorly due to the low frequency of new …
Multi model-based hybrid prediction algorithm (MM-HPA) for stock market prices prediction framework (SMPPF)
SR Polamuri, K Srinivas, AK Mohan - Arabian Journal for Science and …, 2020 - Springer
In financial arena, stock markets have influence on the performance of organizations and
investors. Stock markets are highly dynamic in nature, and predicting the stock prices is a …
investors. Stock markets are highly dynamic in nature, and predicting the stock prices is a …
A Comparative Study of Deep Learning Algorithms in Univariate and Multivariate Forecasting of the Malaysian Stock Market (Kajian Perbandingan Algoritma …
MRAB KHALIL, AABU BAKAR - Sains Malaysiana, 2023 - ukm.edu.my
As part of a financial institution, the stock market has been an essential factor in the growth
and stability of the national economy. Investment in the stock market is risky because of its …
and stability of the national economy. Investment in the stock market is risky because of its …
Stochastic neural networks-based algorithmic trading for the cryptocurrency market
Throughout the history of modern finance, very few financial instruments have been as
strikingly volatile as cryptocurrencies. The long-term prospects of cryptocurrencies remain …
strikingly volatile as cryptocurrencies. The long-term prospects of cryptocurrencies remain …
Can Long-short Term Memory Neural Network With Symbolic Genetic Algorithm Predict Stock Price Change Basing on Fundamental Indicators
Q Li, N Kamaruddin, HA Al-Jaifi - 2023 - researchsquare.com
This paper presents an enhanced framework that combines Symbolic Genetic Algorithm
(SGA) with Long-Short Term Memory Neural Network (LSTM) for predicting cross-sectional …
(SGA) with Long-Short Term Memory Neural Network (LSTM) for predicting cross-sectional …
Data science in economics
This paper provides the state of the art of data science in economics. Through a novel
taxonomy of applications and methods advances in data science are investigated. The data …
taxonomy of applications and methods advances in data science are investigated. The data …
Forecasting ETF Performance: A Comparative Study of Deep Learning Models and the Fama-French Three-Factor Model.
The global financial landscape has witnessed a significant shift towards Exchange-Traded
Funds (ETFs), with their market capitalization surpassing USD 10 trillion in 2023, due to …
Funds (ETFs), with their market capitalization surpassing USD 10 trillion in 2023, due to …