17 papers · ranked by Valyu relevance
Jiang-Cheng Li, Jin Guo, Rui Ma, Guangyan Zhong + 1 more
Synchronization, which has been a common natural phenomenon, occurs frequently in complex financial systems and is an important contagion mechanism for systemic financial risks and even financial crises. In view of this, we construct a coupled stochastic volatility model and its volatility synchronization analysis…
Ekleen Kaur
The application of the standard static Geometric Brownian Motion (GBM) model for cryptocurrency risk management resulted in a systemic failure, evidenced by a 80.67% chance of loss in the VaR0.05 benchmark. This study addresses a critical literature gap by comparatively testing three conditional volatility models the…
Patrick Woitschig, Mike West
We present a new class of Bayesian dynamic models for bivariate price-realized volatility time series in financial forecasting. A novel dynamic gamma process model adopted for realized volatility is integrated with traditional Bayesian dynamic linear models (DLMs) for asset price series. This represents reduced-form…
Mark Higgins
This model incorporates a key dynamic relevant for pricing barrier derivatives in the foreign exchange markets: a positive correlation between moves in implied volatility skew and moves in the spot price. We analyze that correlation and its impact on both barrier option pricing and volatility swap pricing. Those price…
Yang, Junlin
This paper investigates how institutional learning and regional spillovers shape volatility dynamics in ASEAN equity markets. Using daily data for Indonesia, Malaysia, the Philippines, and Thailand from 2010 to 2024, we construct a high-frequency institutional learning index via a MIDAS–EPU approach. Unlike existing…
Jin Zeng, Jingwen Wu, Alessandro Mazzoccoli
This study examines volatility spillovers between Chinese and U.S. equity markets by developing a comprehensive framework that captures asymmetric volatility, extreme co-movements, and dynamic correlations. We propose an integrated methodology combining EGARCH models with Student-t innovations, a Student-t copula, and…
Joanna Olbryś, Dawid Toczydłowski, Stanisław Drożdż
The aim of this study is to thoroughly assess the informational content of the CBOE Volatility Index® (VIX® Index) in the context of various turbulent periods. The VIX Index is especially important from an investor perspective. It is often referred to as the “investor fear gauge”, because its level tends to spike…
Fabrizio Cipollini, Giulia Cruciani, Giampiero M. Gallo, Alessandra Insana + 2 more
| 1 | | Introduction | 3 | |---|------------|------------------------------------------------------------------|-------------| | 2 | 2.1 2.2 | The Raw Data from Kibot Price Analysis Volume Analysis | 4 5 6 | | 3 | | Some Insights on Odd-Lot Trades | 7 | | 4 | 4.1 | The VOLARE Back-end: Data Preparation Asset Classes |…
Yan Li, Dezhi Liu, Ruobin Gao, Yang Yu + 1 more
Accurate forecasting of copper futures prices is crucial for risk management and investment decisions. However, existing approaches primarily rely on historical prices and incorporate behavioral signals without a unified modeling framework. To address this limitation, we propose MBTI-Net (Multi-source…
Jamie M. Waterman, Gareth J. Moore, Loren K. Amdahl-Culleton, Sara Hoefer + 1 more
Biological responses to environmental stimuli are inherently dynamic. Recent technological advances enable detailed time-resolved measurements of such responses. However, a unifying model for the quantitative characterisation of dynamic response curves is lacking, thus limiting biological insights and comparisons. We…
Nicholas Appiah, Ali Jaffri, Dilmi C. W. Hettiachchi-Halpe-Kankanamalage, Svetlozar T. Rachev
This paper examines portfolio optimization for commodity exchange-traded funds (ETFs) under heavy-tailed return behavior. Using daily Bloomberg data for 30 U.S.-listed commodity ETFs from 12 December 2018 to 16 December 2024, we study funds spanning agriculture, energy, metals, and broad commodity index exposure. We…
Taiji Yamada, Kazuyuki Samejima
Action selection involves two systems: a model-free reinforcement learning strategy, which relies on experience with action–outcome pairs, and a model-based reinforcement learning strategy, which enables more flexible behavior via inference using a model of the invariant environmental structure. Although environmental…
Brónagh McCoy, Rebecca P. Lawson, Varun Dutt
Anxiety is known to alter learning in uncertain environments. Experimental paradigms and computational models addressing these differences have mainly assessed the impact of volatility, with more highly anxious individuals showing a reduced adaptation of learning rate in volatile compared to stable environments.…
Wanjun Lin, Laurence T. Hunt, Erdem Pulcu, Michael Browning
The ability to seek reward and avoid punishment is a fundamental survival instinct. In natural environments, however, the statistics of rewards and punishments can change independently of one another. In addition, individuals experiencing anxiety and depression may be selectively biased to process rewards and…
Georgia Zournatzidou, Konstantinos Gkillas
The environmental impact of Bitcoin (BTC) has been a source of concern due to its substantial energy consumption, which is a result of its proof-of-work mining algorithm and transaction processes. The global usage levels of Bitcoin are comparable to those of some affluent nations. This study examines the nonlinear…
Xiaotong Fang, Payam Piray
Inferring the true cause of noise—distinguishing between volatility (environmental change) and stochasticity (outcome randomness)—is essential for learning in noisy environments. While most studies rely on binary outcomes, previous models are designed for continuous outcome and use ad hoc approximations to handle…
Authors not listed
The functionality of viral proteases, such as those from Dengue Virus (DENV) and SARS-CoV-2, is intrinsically linked to their conformational dynamics. While Molecular Dynamics (MD) is a powerful tool to study these motions, its computational cost limits large-scale screening. Here, we present a rapid analysis of the…