Similar Search Results

Exchange rate forecasting with advanced machine learning methods

Pfahler, Jonathan Felix - In: Journal of risk and financial management : JRFM 15 (2022) 1, pp. 1-17

Historically, exchange rate forecasting models have exhibited poor out-of-sample performances and were inferior to the random walk model. Monthly panel data from 1973 to 2014 for ten currency pairs of OECD countries are used to make out-of sample forecasts with artificial neural networks and...

Persistent link: https://www.econbiz.de/10012813245

The rich get richer and the poor get poorer : social media and the post-IPO behavior of investors in biotechnology firms : the relationship with twitter volume

Siev, Smadar - In: Journal of risk and financial management : JRFM 14 (2021) 10, pp. 1-17

of social media-specifically, Twitter-on these returns. The results indicate positive yet insignificant cumulative …-IPO years. An examination of Twitter activity and share returns demonstrates a robust correlation between the two, suggesting … that investors' attention to firms may be reflected in their Twitter usage. …

Persistent link: https://www.econbiz.de/10012628769

A gated recurrent unit approach to bitcoin price prediction

Dutta, Aniruddha; Kumar, Saket; Basu, Meheli - In: Journal of risk and financial management : JRFM 13 (2020) 2/23, pp. 1-16

In today's era of big data, deep learning and artificial intelligence have formed the backbone for cryptocurrency portfolio optimization. Researchers have investigated various state of the art machine learning models to predict Bitcoin price and volatility. Machine learning models like recurrent...

Persistent link: https://www.econbiz.de/10012173959

A novel model structured on predictive churn methods in a banking organization

Silveira, Leonardo José; Pinheiro, Plácido Rogério; … - In: Journal of risk and financial management : JRFM 14 (2021) 10, pp. 1-24

A constant in the business world is the frequent movement of customers joining or abandoning companies’ services and products. The customer is one of the company’s most important assets. Reducing the customer abandonment rate has become a matter of survival and, at the same time, the most...

Persistent link: https://www.econbiz.de/10012745384

Stochastic analysis and neural network-based yield prediction with precision agriculture

Shoshi, Humayra; Hanson, Erik; Nganje, William; … - In: Journal of risk and financial management : JRFM 14 (2021) 9, pp. 1-17

In this paper, we propose a general mathematical model for analyzing yield data. The data analyzed in this paper come from a characteristic corn field in the upper midwestern United States. We derive expressions for statistical moments from the underlying stochastic model. Consequently, we...

Persistent link: https://www.econbiz.de/10012627667

Machine learning the carbon footprint of Bitcoin mining

Calvo Pardo, Héctor F.; Mancini, Tullio; Olmo, Jose - In: Journal of risk and financial management : JRFM 15 (2022) 2, pp. 1-30

Building on an economic model of rational Bitcoin mining, we measured the carbon footprint of Bitcoin mining power consumption using feed-forward neural networks. We found associated carbon footprints of 2.77, 16.08 and 14.99 MtCO2e for 2017, 2018 and 2019 based on a novel bottom-up approach,...

Persistent link: https://www.econbiz.de/10012821293

Application of artificial intelligence in stock market forecasting : a critique, review, and research agenda

Chopra, Ritika; Sharma, Gagan Deep - In: Journal of risk and financial management : JRFM 14 (2021) 11, pp. 1-34

The stock market is characterized by extreme fluctuations, non-linearity, and shifts in internal and external environmental variables. Artificial intelligence (AI) techniques can detect such non-linearity, resulting in much-improved forecast results. This paper reviews 148 studies utilizing...

Persistent link: https://www.econbiz.de/10012795264

Neural network models for empirical finance

Calvo Pardo, Héctor F.; Mancini, Tullio; Olmo, Jose - In: Journal of risk and financial management : JRFM 13 (2020) 11/265, pp. 1-22

This paper presents an overview of the procedures that are involved in prediction with machine learning models with special emphasis on deep learning. We study suitable objective functions for prediction in high-dimensional settings and discuss the role of regularization methods in order to...

Persistent link: https://www.econbiz.de/10012389830

Latent segmentation of stock trading strategies using multi-modal imitation learning

Maeda, Iwao; DeGraw, David; Kitano, Michiharu; … - In: Journal of risk and financial management : JRFM 13 (2020) 11/250, pp. 1-12

While exchanges and regulators are able to observe and analyze the individual behavior of financial market participants through access to labeled data, this information is not accessible by other market participants nor by the general public. A key question, then, is whether it is possible to...

Persistent link: https://www.econbiz.de/10012389888

A neural network Monte Carlo approximation for expected utility theory

Zhu, Yichen; Escobar, Marcos - In: Journal of risk and financial management : JRFM 14 (2021) 7, pp. 1-18

This paper proposes an approximation method to create an optimal continuous-time portfolio strategy based on a combination of neural networks and Monte Carlo, named NNMC. This work is motivated by the increasing complexity of continuous-time models and stylized facts reported in the literature....

Persistent link: https://www.econbiz.de/10012626104