21 papers · ranked by Valyu relevance
Axel Hutt, Scott Rich, Taufik A Valiante, Jérémie Lefebvre
Heterogeneity is the norm in biology. The brain is no different: neuronal cell-types are myriad, reflected through their cellular morphology, type, excitability, connectivity motifs and ion channel distributions. While this biophysical diversity enriches neural systems’ dynamical repertoire, it remains challenging to…
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…
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…
Ayumu Nono, Yusuke Uchiyama, Kei Nakagawa, Christian H. Weiss
Volatility, which represents the magnitude of fluctuating asset prices or returns, is used in the problems of finance to design optimal asset allocations and to calculate the price of derivatives. Since volatility is unobservable, it is identified and estimated by latent variable models known as volatility fluctuation…
Gabriele Casto
Volatility plays a central role in modern portfolio theory, as it is the dominant measure for quantifying financial risk. Since Markowitz's initial work in 1952 (Markowitz, 1952), portfolio optimization has been based on the assumption that asset returns belong to the family of elliptical distributions, so that the…
Oleh Danyliv, Bruce Bland
Working on different aspects of algorithmic trading we empirically discovered a new market invariant. It links together the volatility of the instrument with its traded volume, the average spread and the volume in the order book. The invariant has been tested on different markets and different asset classes. In all…
Payam Piray, Nathaniel D. Daw
Sound principles of statistical inference dictate that uncertainty shapes learning. In this work, we revisit the question of learning in volatile environments, in which both the first and second-order statistics of environments dynamically evolve over time. We propose a new model, the volatile Kalman filter (VKF)…
Zeyu Zheng, Zhi Qiao, Joel Tenenbaum, H. Eugene Stanley + 1 more
Econophysics and econometrics agree that there is a correlation between volume and volatility in a time series. Using empirical data and their distributions, we further investigate this correlation and discover new ways that volatility and volume interact, particularly when the levels of both are high. We find that the…
Jie Xu, Nicholas T. Van Dam, Yuejia Luo, André Aleman + 2 more
Humans adapt their learning strategies to changing environments by estimating the volatility of the reinforcement conditions. Here, we examine how volatility affects learning and the underlying functional brain organizations using a probabilistic reward reversal learning task. We found that the order of conditions was…
Gargi Majumdar, Fahd Yazin, Arpan Banerjee, Dipanjan Roy
Understanding the mechanisms behind the variability of neural signals holds the key to the characterization of developmental and lifespan aging trajectories. Here we propose that tracking temporally structured neural fluctuations or volatility in brain areas during naturalistic tasks provides a more salient…
Tim Leung, Brian Ward
We study a series of static and dynamic portfolios of VIX futures and their effectiveness to track the VIX index. We derive each portfolio using optimization methods, and evaluate its tracking performance from both empirical and theoretical perspectives. Among our results, we show that static portfolios of different…
D. Tuzsus, I. Pappas, J. Peters
Natural environments often exhibit various degrees of volatility, ranging from slowly changing to rapidly changing contingencies. How learners adapt to changing environments is a central issue in both reinforcement learning theory and psychology. For example, learners may adapt to changes in volatility by increasing…
Nicolás Magner, Jaime F. Lavin, Mauricio Valle, Nicolás Hardy + 1 more
'J E. Trinidad Segovia'] We explore the use of implied volatility indices as a tool for estimate changes in the synchronization of stock markets. Specifically, we assess the implied stock market’s volatility indices’ predictive power on synchronizing global equity indices returns. We built the correlation network of 26…
Claudiu Vințe, Marcel Ausloos, Titus Felix Furtună, Angeliki Papana
Grasping the historical volatility of stock market indices and accurately estimating are two of the major focuses of those involved in the financial securities industry and derivative instruments pricing. This paper presents the results of employing the intrinsic entropy model as a substitute for estimating the…
Alexander Badran, Beniamin Gołdys
A new modelling approach that directly prescribes dynamics to the term structure of VIX futures is proposed in this paper. The approach is motivated by the tractability enjoyed by models that directly prescribe dynamics to the VIX, practices observed in interest-rate modelling, and the desire to develop a platform to…
Gábor Petneházi, József Gáll
We investigate the predictability of several range-based stock volatility estimators, and compare them to the standard close-to-close estimator which is most commonly acknowledged as the volatility. The patterns of volatility changes are analyzed using LSTM recurrent neural networks, which are a state of the art method…
Fabian Woebbeking
By computing a volatility index (CVX) from cryptocurrency option prices, we analyze this market’s expectation of future volatility. Our method addresses the challenging liquidity environment of this young asset class and allows us to extract stable market implied volatilities. Two alternative methods are considered to…
Jung-Bin Su, Jaan Kalda
This study uses the fourteen stock indices as the sample and then utilizes eight parametric volatility forecasting models and eight composed volatility forecasting models to explore whether the neural network approach and the settings of leverage effect and non-normal return distribution can promote the performance of…
Anton Koshelev
| Abstract | . | . | | . | . | | . | . | | . | . | | . | | . | . | . | 4 4 7 8 18 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Introduction | . | . | | . | . | | . | . | | . | . | | . | | . | . | . | | | 1. Literature Review | . | . | | . | . |…
Gabriel Braun, Itamar Borges Jr., Adelia A. J. Aquino, Hans Lischka + 5 more
Pyrene fluorescence after a high-energy electronic excitation exhibits a prominent band shoulder not present after excitation at low energies. The standard assignment of this shoulder as a non-Kasha emission from the second-excited state (S2) has been recently questioned. To elucidate this issue, we simulated the…
M. Alexander Ardagh, Turan Birol, Qi Zhang, Omar Abdelrahman + 1 more
Catalytic reactions on surfaces with forced oscillations in physical or electronic properties undergo controlled acceleration consistent with the selected parameters of frequency, amplitude, and external stimulus waveform. In this work, the general reaction of reversible A-to-B chemistry is simulated by varying the…