AIMC Topic: Models, Economic

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Explainable post hoc portfolio management financial policy of a Deep Reinforcement Learning agent.

PloS one
Financial portfolio management investment policies computed quantitatively by modern portfolio theory techniques like the Markowitz model rely on a set of assumptions that are not supported by data in high volatility markets such as the technological...

Enhancing stock index prediction: A hybrid LSTM-PSO model for improved forecasting accuracy.

PloS one
Stock price prediction is a challenging research domain. The long short-term memory neural network (LSTM) widely employed in stock price prediction due to its ability to address long-term dependence and transmission of historical time signals in time...

Unraveling asymmetrical spillover effects originating from China's green finance markets: Insights from asymmetric TVP-VAR and interpretable machine learning.

Journal of environmental management
This study combines an asymmetric TVP-VAR model with interpretable machine learning algorithms to confirm the presence of asymmetries in spillover effects within China's green finance market and to identify the macroeconomic drivers behind these effe...

Comprehensive financial health assessment using Advanced machine learning techniques: Evidence based on private companies listed on ChiNext.

PloS one
This study develops a specific and measurable framework for assessing the financial health (FH) of privately-owned companies listed on ChiNext, aimed at identifying financially sound enterprises and helping investors avoid losses caused by financial ...

Enhanced forecasting of rice price and production in Malaysia using novel multivariate fuzzy time series models.

Scientific reports
A significant portion of the world's population relies on rice as a primary source of nutrition. In Malaysia, rice production began in the early 1960s, which led to the cultivation of the country's most significant food crop up till the present day. ...

Generative Artificial Intelligence for Health Technology Assessment: Opportunities, Challenges, and Policy Considerations: An ISPOR Working Group Report.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: To provide an introduction to the uses of generative artificial intelligence (AI) and foundation models, including large language models, in the field of health technology assessment (HTA).

Predicting the volatility of Chinese stock indices based on realized recurrent conditional heteroskedasticity.

PloS one
The realized recurrent conditional heteroscedasticity (RealRECH) model improves volatility prediction by integrating long short-term memory (LSTM), a recurrent neural network unit, into the realized generalized autoregressive conditional heteroskedas...

Period-aggregated transformer for learning latent seasonalities in long-horizon financial time series.

PloS one
Fluctuations in the financial market are influenced by various driving forces and numerous factors. Traditional financial research aims to identify the factors influencing stock prices, and existing works construct a common neural network learning fr...

Factor-GAN: Enhancing stock price prediction and factor investment with Generative Adversarial Networks.

PloS one
Deep learning, a pivotal branch of artificial intelligence, has increasingly influenced the financial domain with its advanced data processing capabilities. This paper introduces Factor-GAN, an innovative framework that utilizes Generative Adversaria...

Heteroscedasticity effects as component to future stock market predictions using RNN-based models.

PloS one
Heteroscedasticity effects are useful for forecasting future stock return volatility. Stock volatility forecasting provides business insight into the stock market, making it valuable information for investors and traders. Predicting stock volatility ...