Similar Search Results

Bitcoin as an investment and hedge alternative : a DCC MGARCH model analysis

Rudolf, Karl Oton; El Zein, Samer Ajour; Jackman … - In: Risks : open access journal 9 (2021) 9, pp. 1-22

Volatility and investor sentiment have been factors for the slow adoption rate of Bitcoin (BTC) that was first recognized in 2008 as a potential store of value, investment vehicle and a hedge alternative to gold during a recession. The purpose of this applied mathematics study will use a...

Persistent link: https://www.econbiz.de/10012612471

The impact of blockchain on the quality of accounting information : an Iraqi case study

Alkafaji, Bashaer Khudhair Abbas; Dashtbayaz, Mahmoud Lari - In: Risks : open access journal 11 (2023) 3, pp. 1-22

This paper aims to investigate the impact of blockchain on the quality of the information in listed and non … parts: one part is related to the level of familiarity with blockchain technology of accountants, independent auditors …, managers, etc., and the other part is related to the effect of blockchain technology on the quality of accounting information …

Persistent link: https://www.econbiz.de/10014303635

Active management of pperational risk in the regimes of the "unknown" : what can machine learning or heuristics deliver?

Milkau, Udo; Bott, Jürgen - In: Risks : open access journal 6 (2018) 2, pp. 1-16

Advanced machine learning has achieved extraordinary success in recent years. “Active” operational risk beyond ex post analysis of measured-data machine learning could provide help beyond the regime of traditional statistical analysis when it comes to the “known unknown” or even the...

Persistent link: https://www.econbiz.de/10011866399

Evaluating the effectiveness of modern forecasting models in predicting commodity futures prices in volatile economic times

Vancsura, László; Tatay, Tibor; Bareith, Tibor - In: Risks : open access journal 11 (2023) 2, pp. 1-16

The paper seeks to answer the question of how price forecasting can contribute to which techniques gives the most accurate results in the futures commodity market. A total of two families of models (decision trees, artificial intelligence) were used to produce estimates for 2018 and 2022 for 21-...

Persistent link: https://www.econbiz.de/10014233184

Flared gas can reduce some risks in crypto mining as well as oil and gas operations

Vazquez, Jennifer; Crumbley, Donald Larry - In: Risks : open access journal 10 (2022) 6, pp. 1-12

There are numerous risks associated with mining and owning cryptocurrencies, and exploring and producing oil and natural gas are highly risky, costly, and controversial. A marriage of digital mining and exploring and producing oil and natural gas has reduced the major risks and costs for both...

Persistent link: https://www.econbiz.de/10013363009

Modeling the yield curve of BRICS countries : parametric vs. machine learning techniques

Castello, Oleksandr; Resta, Marina - In: Risks : open access journal 10 (2022) 2, pp. 1-18

We compare parametric and machine learning techniques (namely: Neural Networks) for in-sample modeling of the yield curve of the BRICS countries (Brazil, Russia, India, China, South Africa). To such aim, we applied the Dynamic De Rezende-Ferreira five-factor model with time-varying decay...

Persistent link: https://www.econbiz.de/10013093028

An approach for variable selection and prediction model for estimating the Risk-Based Capital (RBC) based on machine learning algorithms

Park, Jaewon; Shin, Minsoo - In: Risks : open access journal 10 (2022) 1, pp. 1-20

The risk-based capital (RBC) ratio, an insurance company's financial soundness system, evaluates the capital adequacy needed to withstand unexpected losses. Therefore, continuous institutional improvement has been made to monitor the financial solvency of companies and protect consumers' rights,...

Persistent link: https://www.econbiz.de/10012805414

Improving explainability of major risk factors in artificial neural networks for auto insurance rate regulation

Xie, Shengkun - In: Risks : open access journal 9 (2021) 7, pp. 1-21

In insurance rate-making, the use of statistical machine learning techniques such as artificial neural networks (ANN) is an emerging approach, and many insurance companies have been using them for pricing. However, due to the complexity of model specification and its implementation, model...

Persistent link: https://www.econbiz.de/10012598958

Mathematical model for choosing counterparty when assessing information security risks

Koltays, Andrey; Konev, Anton; Shelupanov, Alexander - In: Risks : open access journal 9 (2021) 7, pp. 1-13

The need to assess the risks of the trustworthiness of counterparties is increasing every year. The identification of increasing cases of unfair behavior among counterparties only confirms the relevance of this topic. The existing work in the field of information and economic security does not...

Persistent link: https://www.econbiz.de/10012599598

Quantum support vector regression for disability insurance

Djehiche, Boualem; Löfdahl, Björn - In: Risks : open access journal 9 (2021) 12, pp. 1-9

We propose a hybrid classical-quantum approach for modeling transition probabilities in health and disability insurance. The modeling of logistic disability inception probabilities is formulated as a support vector regression problem. Using a quantum feature map, the data are mapped to quantum...

Persistent link: https://www.econbiz.de/10012745406