Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison
The prediction of global solar radiation for the regions is of great importance in terms of
giving directions of solar energy conversion systems (design, modeling, and operation) …
giving directions of solar energy conversion systems (design, modeling, and operation) …
Neural networks for option pricing and hedging: a literature review
Neural networks have been used as a nonparametric method for option pricing and hedging
since the early 1990s. Far over a hundred papers have been published on this topic. This …
since the early 1990s. Far over a hundred papers have been published on this topic. This …
Electricity production based forecasting of greenhouse gas emissions in Turkey with deep learning, support vector machine and artificial neural network algorithms
MS Bakay, Ü Ağbulut - Journal of Cleaner Production, 2021 - Elsevier
Today, the world's primary energy demand has been met by the burning of fossil-based fuels
at a rate of 85%. This dominant use of fossil-based fuels has led to an accelerating increase …
at a rate of 85%. This dominant use of fossil-based fuels has led to an accelerating increase …
Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models
HY Kim, CH Won - Expert Systems with Applications, 2018 - Elsevier
Volatility plays crucial roles in financial markets, such as in derivative pricing, portfolio risk
management, and hedging strategies. Therefore, accurate prediction of volatility is critical …
management, and hedging strategies. Therefore, accurate prediction of volatility is critical …
Machine learning models and bankruptcy prediction
There has been intensive research from academics and practitioners regarding models for
predicting bankruptcy and default events, for credit risk management. Seminal academic …
predicting bankruptcy and default events, for credit risk management. Seminal academic …
Machine learning for financial risk management: a survey
Financial risk management avoids losses and maximizes profits, and hence is vital to most
businesses. As the task relies heavily on information-driven decision making, machine …
businesses. As the task relies heavily on information-driven decision making, machine …
Predicting volatility index according to technical index and economic indicators on the basis of deep learning algorithm
SM Daniali, SE Barykin, IV Kapustina… - Sustainability, 2021 - mdpi.com
The Volatility Index (VIX) is a real-time index that has been used as the first measure to
quantify market expectations for volatility, which affects the financial market as a main actor …
quantify market expectations for volatility, which affects the financial market as a main actor …
Option pricing using machine learning
CF Ivașcu - Expert Systems with Applications, 2021 - Elsevier
This paper examines the option pricing performance of the most popular Machine Learning
algorithms. The classic parametrical models suffer from several limitations in term of …
algorithms. The classic parametrical models suffer from several limitations in term of …
Wildland fire susceptibility mapping using support vector regression and adaptive neuro-fuzzy inference system-based whale optimization algorithm and simulated …
Fires are one of the most destructive forces in natural ecosystems. This study aims to
develop and compare four hybrid models using two well-known machine learning models …
develop and compare four hybrid models using two well-known machine learning models …
Conformal prediction of option prices
JA Bastos - Expert Systems with Applications, 2024 - Elsevier
The uncertainty associated with option price predictions has largely been overlooked in the
literature. This paper aims to fill this gap by quantifying such uncertainty using conformal …
literature. This paper aims to fill this gap by quantifying such uncertainty using conformal …