Economy or Climate? Impact of Policy Uncertainty on Price Volatility of China’s Carbon Emission Trading Markets DOI Creative Commons
Zhuoer Chen, Xiaohui Gao, Nan Chen

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(10), P. 2448 - 2448

Published: May 10, 2025

Based on the economic and climate policy uncertainty index price data of major carbon emission trading markets from May 2014 to August 2023, this paper uses generalized autoregressive conditional heteroskedasticity mixing sampling (GARCH-MIDAS) model analyze impact market volatility. The results indicate following: (1) volatility in Hubei is influenced by both uncertainties, while Guangdong only affected uncertainty, Shenzhen uncertainty. (2) Before establishment national market, prices were impacted uncertainties. (3) On contrary, after was not above research conclusions are helpful for regulatory agencies policymakers assess future direction pilot provide an empirical basis preventing resolving risks. At same time, proposed GARCH-MIDAS effectively solves inconsistent frequency problem volatility, providing a new perspective study factors affecting

Language: Английский

Monte Carlo Simulations for Resolving Verifiability Paradoxes in Forecast Risk Management and Corporate Treasury Applications DOI Creative Commons
Martin Pavlík, Grzegorz Michalski

International Journal of Financial Studies, Journal Year: 2025, Volume and Issue: 13(2), P. 49 - 49

Published: April 1, 2025

Forecast risk management is central to the financial process. This study aims apply Monte Carlo simulation solve three classic probabilistic paradoxes and discuss their implementation in corporate management. The article presents as an advanced tool for processes. method allows a comprehensive analysis of forecasts, making it possible assess potential errors cash flow forecasts predict value treasury growth under various future scenarios. In investment decision-making process, supports evaluation effectiveness projects by calculating expected net identifying risks associated with investments, allowing more informed decisions be made project implementation. used reducing volatility, which contributes lowering cost capital increasing company. Simulation also enables accurate liquidity planning, including forecasting availability determining appropriate reserves based on probability distributions. credit interest rate risk, enabling impact economic scenarios company’s obligations. context strategic extension decision tree analysis, where subsequent are results earlier ones. Creating models simulations makes take into account random variables key indicators, such free (FCF). Compared traditional methods, offers detailed precise approach decision-making, providing companies vital information uncertainty. emphasizes that use not only enhances management, but long-term value. entire process able move predicting flows discounted at capital. We both numerical analytical methods veridical paradoxes. Veridical type paradox result counterintuitive, turns out true after careful examination. means although initial reasoning may lead wrong conclusion, correct mathematical or logical confirms correctness results. An example Monty Hall’s problem, intuitive answer suggests equal success, while shows changing increases chances winning. method. following were used: conditional probability, Bayes’ rule multiple conditions. solved truth-type discovered why Hall problem was so widely discussed 1990s. differentiated problems using different numbers doors prizes.

Language: Английский

Citations

0

Can Inclusive Finance Curb Sustainability Regulatory Risk for Corporations? DOI
Xiaoyu Zhu, Chao Zhou, Hanzhe Zeng

et al.

Research in International Business and Finance, Journal Year: 2025, Volume and Issue: unknown, P. 102901 - 102901

Published: April 1, 2025

Language: Английский

Citations

0

Economy or Climate? Impact of Policy Uncertainty on Price Volatility of China’s Carbon Emission Trading Markets DOI Creative Commons
Zhuoer Chen, Xiaohui Gao, Nan Chen

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(10), P. 2448 - 2448

Published: May 10, 2025

Based on the economic and climate policy uncertainty index price data of major carbon emission trading markets from May 2014 to August 2023, this paper uses generalized autoregressive conditional heteroskedasticity mixing sampling (GARCH-MIDAS) model analyze impact market volatility. The results indicate following: (1) volatility in Hubei is influenced by both uncertainties, while Guangdong only affected uncertainty, Shenzhen uncertainty. (2) Before establishment national market, prices were impacted uncertainties. (3) On contrary, after was not above research conclusions are helpful for regulatory agencies policymakers assess future direction pilot provide an empirical basis preventing resolving risks. At same time, proposed GARCH-MIDAS effectively solves inconsistent frequency problem volatility, providing a new perspective study factors affecting

Language: Английский

Citations

0