Neural network–based financial volatility forecasting: A systematic review

W Ge, P Lalbakhsh, L Isai, A Lenskiy… - ACM Computing Surveys …, 2022 - dl.acm.org
Volatility forecasting is an important aspect of finance as it dictates many decisions of market
players. A snapshot of state-of-the-art neural network–based financial volatility forecasting …

Novel stock crisis prediction technique—a study on indian stock market

N Naik, BR Mohan - IEEE Access, 2021 - ieeexplore.ieee.org
A stock market crash is a drop in stock prices more than 10% across the major indices. Stock
crisis prediction is a difficult task due to more volatility in the stock market. Stock price sell …

Oil price uncertainty and manufacturing production

GC Aye, V Dadam, R Gupta, B Mamba - Energy Economics, 2014 - Elsevier
Given the rapid rise and volatility of oil prices, the paper investigates the effect of oil price
uncertainty on the South African manufacturing production using monthly observations …

Carbon market risk estimation using quantum conditional generative adversarial network and amplitude estimation

X Zhou, H Zhao, Y Cao, X Fei… - Energy Conversion …, 2024 - Wiley Online Library
Accurately and efficiently estimating the carbon market risk is paramount for ensuring
financial stability, promoting environmental sustainability, and facilitating informed decision …

Study on the Pakistan stock market using a new stock crisis prediction method

I Javid, R Ghazali, I Syed, M Zulqarnain, NA Husaini - Plos one, 2022 - journals.plos.org
A Stock market collapse occurs when stock prices drop by more than 10% across all main
indexes. Predicting a stock market crisis is difficult because of the increased volatility in the …

[PDF][PDF] GARCH models in value at risk estimation: empirical evidence from the Montenegrin stock exchange

J Cerović Smolović, M Lipovina-Božović… - Economic research …, 2017 - hrcak.srce.hr
This article considers the adequacy of generalised autoregressive conditional
heteroskedasticity (GARCH) model use in measuring risk in the Montenegrin emerging …

[PDF][PDF] The role of the loss function in value-at-risk comparisons

P Abad, SB Muela, CL Martín - The Journal of Risk Model …, 2015 - researchgate.net
This paper examines whether the comparison of value-at-risk (VaR) models depends on the
loss function used for such a purpose. We show a detailed comparison for several VaR …

Modeling oil price uncertainty effects on economic growth in Mexico: a sector-level analysis

D Rodríguez-Benavides, R Andrés-Rosales… - … Science and Pollution …, 2022 - Springer
This paper analyzes the impact of international oil price uncertainty on the different
economic sectors (primary, secondary, and tertiary) in Mexico in the period 1993: 1–2020: 4 …

[图书][B] Discounting, Libor, CVA and Funding: Interest Rate and Credit Pricing

C Kenyon, R Stamm - 2012 - books.google.com
Providing the most up-to-date tools and techniques for pricing interest rate and credit
products for the new financial world, this book discusses pricing and hedging, funding and …

Volatility forecasts by clustering: Applications for VaR estimation

Z Wang, P Chen, P Liu, C Wu - International Review of Economics & …, 2024 - Elsevier
It is well known that volatility has time-varying and clustering characteristics. The information
content of volatility clustering is particularly important in turbulent periods, such as the stage …