Volatility Process Research Articles

Charge transfer of cocrystal complex featuring efficient aggregation-induced emission and self-powered photo-electrochemical photodetector

A novel cocrystal complex CZIPA-AD assembled by twisting D-A molecule 5-(9H-carbazol-9-yl)isophthalic (CZIPA) and acridine (AD) through a facial solution volatilization process is reported. The combination of photophysical investigation and DFT analysis verify a reasonable cooperation of hybridized local and charge transfer (HLCT) and aggregation-induced emission (AIE) character. The orbital overlap on CZIPA (for local excited (LE) state) and orbital spatial separation between CZIPA and AD (for charge transfer (CT) state) satisfy the formation of HLCT character. The presence of AD molecules preclude the formation of π-stacking between the carbazole halves, preventing the quenching of PL emission in the aggregate state. It shows intense orange emission in aggregated solid state with high PLQY of 80% and prolonged PL lifetime of 38.57 ns. A self-powered photo-electrochemical photodetector fabricated from the cocrystal thin film exhibits a remarkable detectivity (4.78 × 1010 Jones) in neutral aqueous solution, which is at lest one order of magnitude higher than other reported inorganic materials measured in alkaline solution with additional bias potential.

EXPONENTIAL REALIZED GARCH-ITÔ VOLATILITY MODELS

This paper introduces a novel Itô diffusion process to model high-frequency financial data that can accommodate low-frequency volatility dynamics by embedding the discrete-time nonlinear exponential generalized autoregressive conditional heteroskedasticity (GARCH) structure with log-integrated volatility in a continuous instantaneous volatility process. The key feature of the proposed model is that, unlike existing GARCH-Itô models, the instantaneous volatility process has a nonlinear structure, which ensures that the log-integrated volatilities have the realized GARCH structure. We call this the exponential realized GARCH-Itô model. Given the autoregressive structure of the log-integrated volatility, we propose a quasi-likelihood estimation procedure for parameter estimation and establish its asymptotic properties. We conduct a simulation study to check the finite-sample performance of the proposed model and an empirical study with 50 assets among the S&P 500 compositions. Numerical studies show the advantages of the proposed model.

Combined bioreduction and volatilization of SeVI by Stenotrophomonas bentonitica: Formation of trigonal selenium nanorods and methylated species

Nowadays, metal pollution due to the huge release of toxic elements to the environment has become one of the world's biggest problems. Bioremediation is a promising tool for reducing the mobility and toxicity of these contaminants (e.g. selenium), being an efficient, environmentally friendly, and inexpensive strategy. The present study describes the capacity of Stenotrophomonas bentonitica to biotransform SeVI through enzymatic reduction and volatilization processes. HAADF-STEM analysis showed the bacterium to effectively reduce SeVI (200 mM) into intra- and extracellular crystalline Se0 nanorods, made mainly of two different Se allotropes: monoclinic (m-Se) and trigonal (t-Se). XAS analysis appears to indicate a Se crystallization process based on the biotransformation of amorphous Se0 into stable t-Se nanorods. In addition, results from headspace analysis by gas chromatography-mass spectometry (GC–MS) revealed the formation of methylated volatile Se species such as DMSe (dimethyl selenide), DMDSe (dimethyl diselenide), and DMSeS (dimethyl selenenyl sulphide). The biotransformation pathways and tolerance are remarkably different from those reported with this bacterium in the presence of SeIV. The formation of crystalline Se0 nanorods could have positive environmental implications (e.g. bioremediation) through the production of Se of lower toxicity and higher settleability with potential industrial applications.

Smart optical measurement probe for autonomously detecting nano-defects on bare semiconductor wafer surface: highly sensitive observation system using phase-contrast microscopy with a spatial light modulator

Nowadays, the yield rate of semiconductor process is strongly affected even by nanoscale defects on bare Si wafer surfaces. Therefore, a non-destructive and high-speed method for detection of nanoparticle contamination is highly demanded. In this research, a nanoparticle detection method is proposed based on the fact that the volatilization process of the volatile inert liquid behaves as an autonomous nanoparticle search probe. Dynamic phase contrast microscopy (Dynamic PCM) is proposed to detect small thickness changes of a thin liquid film with high sensitivity. The dynamic PCM is expected to have double sensitivity compared to normal PCM and it is experimentally verified. Based on previous results, 4% intensity change is expected for 10 nm particles and even over 1.5% intensity change is expected for 5 nm particles by using this proposed dynamic PCM.

Performance optimization of epoxy resin-based modified liquid asphalt mixtures

This study proposes a performance optimization scheme of liquid asphalt mixtures (LAMs) based on epoxy resin-based material modification and investigates its various performances. First, thermogravimetric analysis and headspace gas chromatography–mass spectrometry were used to analyze the differences between liquid asphalt before and after curing to clarify the formation mechanism of its adhesive force. Second, a molecular model was established. The best epoxy resin and curing agent types were evaluated using an improved Flory–Huggins model and the quantum computing method. Finally, two performance optimization schemes were established to reinforce the performance defects of the mixture caused by residual diluents. Results show that liquid asphalt solidification is a physical process of volatilization of diluents. Bisphenol A epoxy resin and a polyether amine curing agent are compatible with liquid asphalt and prone to curing reactions; thus, they are most suitable as epoxy resin-based modifiers. A solution obtained by adding 2% waterborne epoxy resin and 30% mineral powder replaced with cement can significantly improve the initial strength, strength generation rate, and low-temperature crack resistance of the LAM while optimizing high-temperature performance. This LAM modification can ensure that roads repaired using the modified LAM in a low-temperature environment can be quickly opened to use and improve the durability of the road surface.

A panel threshold VAR with stochastic volatility-in-mean model: an application to the effects of financial and uncertainty shocks in emerging economies

ABSTRACT This article proposes a panel threshold VAR with stochastic volatility-in-mean model. The volatility process is given by the average volatility of the structural shocks affecting some selected variables and is interpreted as a measure of macroeconomic uncertainty. The posterior is approximated using an adaptive Metropolis-Within-Gibbs algorithm. We apply the method by analysing the effects of uncertainty and financial shocks in good times and financial distress in emerging economies. In our sample, we find that, under normal financial conditions, financial shocks play a slightly more pervasive role than uncertainty shocks. However, under financial stress periods, uncertainty shocks become more important than financial shocks.

Overnight GARCH-Itô Volatility Models

Various parametric volatility models for financial data have been developed to incorporate high-frequency realized volatilities and better capture market dynamics. However, because high-frequency trading data are not available during the close-to-open period, the volatility models often ignore volatility information over the close-to-open period and thus may suffer from loss of important information relevant to market dynamics. In this article, to account for whole-day market dynamics, we propose an overnight volatility model based on Itô diffusions to accommodate two different instantaneous volatility processes for the open-to-close and close-to-open periods. We develop a weighted least squares method to estimate model parameters for two different periods and investigate its asymptotic properties.

An Ornstein–Uhlenbeck Model with the Stochastic Volatility Process and Tempered Stable Process for VIX Option Pricing

To effectively fit the dynamics and structure of frequent small jumps and sparse large jumps in the VIX time series, we introduce the tempered stable process (the CTS process and CGMY process) into the Ornstein–Uhlenbeck (OU) stochastic volatility model to build an OU model with the stochastic volatility process and tempered stable process. Based on two different assumptions for the underlying assets, we derive the formula of pricing models via two methods. Empirical studies are conducted to prove that our pricing models have a better performance in matching the VIX options. Furthermore, we find that the pricing model via the infinitesimal value method yields better results than pricing models with a measure of change. Overall, our proposed models enrich the derivative pricing theory and help investors understand and hedge risks.

Volatility models for stylized facts of high‐frequency financial data

This article introduces novel volatility diffusion models to account for the stylized facts of high‐frequency financial data such as volatility clustering, intraday U‐shape, and leverage effect. For example, the daily integrated volatility of the proposed volatility process has a realized GARCH structure with an asymmetric effect on log returns. To further explain the heavy‐tailedness of the financial data, we assume that the log returns have a finite th moment for . Then, we propose a Huber regression estimator that has an optimal convergence rate of . We also discuss how to adjust bias coming from Huber loss and show its asymptotic properties.

Are News Effects Necessarily Asymmetric? Evidence from Bangladesh Stock Market

The primary objective of this paper is to empirically examine the nature and statistical significance of the news effect on conditional volatility of unpredictable components of stock returns. Daily stock return data of 12 local and multinational companies on Dhaka Stock Exchange Ltd., Bangladesh, for the period 1990 to 2011 were used in this study. The likelihood of asymmetric effects of news on conditional volatility was tested using a set of diagnostics under the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) framework. The results fail to reject the null hypothesis of symmetric effects, thereby suggesting that the conditional volatility of unpredictable components of stock returns is affected equally by positive and negative news. The robustness of the results was further checked by using three widely used asymmetric models, namely exponential GARCH (EGARCH), Glosten, Jagannathan & Runkle (GJR)-GARCH, and a partially non-parametric Autoregressive Conditional Heteroscedastic (PNP-ARCH) models. Yet again, the results do not provide any evidence of significant asymmetric effects in the volatility process. In addition, the descriptive results confirm the stylized facts of unpredictable return series such as non-normal distribution, time variant conditional volatility, and persistence in return volatility. Collectively these findings, perhaps, indicate the adequacy of the GARCH (1,1) model in representing the data generating process. A number of regulatory and behavioral factors that are anticipated to be accountable for the absence of asymmetric news effects are underlined. Finally, some policy implications of the results and possible extensions of the present paper are also conveyed. JEL codes: G10, G12, G14

Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data

This paper introduces a model that can accommodate both the continuous-time-diffusion and discrete-time mixed-GARCH–Jump models by embedding the discrete mixed-GARCH-Jump structure in the continuous volatility process. The key feature of the proposed model is that the corresponding conditional integrated volatility adopts the mixed-GARCH-Jump structure that accounts for the effect of jumps on future volatility. A Griddy–Gibbs sampler approach is proposed to estimate parameters, and volatility forecasting and value-at-risk forecasting based on the peaks-over-threshold method are developed. Simulations are carried out to check the finite sample performance of the proposed methodology, and empirical studies show that, in general, volatility is heavily influenced by the continuous innovations, rather than the extreme reactions. We find that both the simulation and empirical results in most cases support the proposed model.

A class of portfolio optimization solvable problems

This short paper reveals the largest class of stochastic volatility processes solvable in closed form within expected utility theory for a hyperbolic absolute risk aversion investor. The risky-asset setting considers a framework outside the seminal work of Liu (2007), and highlights applications not yet studied in the literature. The work also demonstrates that analytical solutions for ambiguity-aversion analyses within the framework of Maenhout (2004) are feasible.

15N Natural Abundance Characteristics of Ammonia Volatilization from Soils Applied by Different Types of Fertilizer

Ammonia (NH3) volatilized from cropland significantly impacts the ecological environment and human health. The identification and quantification of atmospheric sources of NH3 from cropland are therefore important for NH3 emission reduction and air pollution control. Choosing appropriate nitrogen (N) fertilizer types is one of the key ways to reduce NH3 emissions from agricultural systems due to different N fertilizers with different emission factors. The natural abundance isotope of N (δ15N) values can well identify the source of NH3 volatilization, although there is rare research on δ15N-NH3 values volatilized when applying different types of N fertilizers. Here, we conducted an incubation experiment to study the characteristics of δ15N-NH3 values during the whole volatilization process after different N fertilizers were applied to the soil. The results show that the cumulative NH3 volatilization from urea (U), urease inhibitor fertilizer (UI), compound fertilizer (CF) and ammonium nitrate phosphate fertilizer (AP) treatment was 5.25 ± 0.00, 3.11 ± 0.00, 3.22 ± 0.19 and 1.38 ± 0.12 kg N ha−1 at the end of the 15-day incubation period, respectively. The average δ15N value of NH3 volatilized from the U, UI, CF and AP treatments was −36.02 ± 4.95, −29.08 ± 9.70, −35.18 ± 4.98 and −29.42 ± 4.33‰, respectively. Generally, the δ15N-NH3 values ranged from −41.33 to −6.30‰ during the NH3 volatilization process. The δ15N-NH3 value was lower in the U treatment than in the UI and AP treatments (p < 0.05), which suggests that N forms and the slow-release additions of different fertilizers, such as NO3−-N and urease inhibitors, can delay or slow down NH3 volatilization, resulting in relative isotopic enrichment. Therefore, the basic properties of different N fertilizers, the changes in soil NH4+-N and cumulative NH3 during the volatilization process significantly impacted the δ15N-NH3 values.

Process and mechanism of strengthening chlorination cascade recovery of valuable metals from electroplating sludge

Electroplating sludge (ES) is a kind of man-made ore-rich hazardous waste with dual characteristics of resource and hazard. In this paper, through thermodynamic calculation and comparison of the chlorine supply capacity of different chlorinating agents, NH4Cl and CaCl2 are selected as the best synergistic chlorine donors, and FeSO4•7H2O is introduced as the green strengthening agent. The results show that the decomposition products SO2 and O2 of FeSO4•7H2O at approximately 700 °C can promote the decomposition of CaCl2 to Cl2 and transform sulfur into CaSO4. The enhanced chlorination system can prolong chlorination, and realize the efficient stepwise chlorination volatilization of Ni, Cu and Cr in ES by adjusting the temperature field. The mass ratios are controlled of M(ES): M(NH4Cl): M(CaCl2) = 10:12:3, M(CaCl2): M(FeSO4•7H2O) = 1:2, and roast at 1100 °C for 90 min, Cr, Ni and Cu recovery rates reach 31.23%, 93.86% and 98.75%, respectively. The content of metals such as nickel and copper in the roasted product is significantly reduced, and the leaching toxicity reaches the standard, which can be used as a secondary resource. The stepwise separation mechanism of Cr, Ni and Cu is further explored through XRD, thermodynamic analysis, XPS, etc. The Me–O and Me–S (Me = Ni, Cu, Cr, etc.) bonds in NiO, CuO and Cr2S3 are easily destroyed by active-[Cl] in HCl and Cl2 to combine to form CrCl3, NiCl2 and CuCl3, which are gradually volatilized in steps at 500 °C, 800 °C and 900 °C, respectively. This study proposed a new chlorination system and explored the stepwise chlorination volatilization process of multi-metal, which provided a new method for metal recovery from ES and polymetallic solid waste.

Asymptotics for multifactor Volterra type stochastic volatility models

We study multidimensional stochastic volatility models in which the volatility process is a positive continuous function of a continuous multidimensional Volterra process that can be not self-similar. The main results obtained in this paper are a generalization of the results due, in the one-dimensional case, to Cellupica and Pacchiarotti (J. Theor. Probab. 34(2):682–727). We state some (pathwise and finite-dimensional) large deviation principles for the scaled log-price and as a consequence some (pathwise and finite-dimensional) short-time large deviation principles.

In-Situ and Real-Time 3D Pyrometry for Thermal History Diagnosis in Laser Fusion Process

Laser-based powder bed fusion (PBF) involves complex thermal cycles including rapid heating, fast solidification, and melt-back effect. The dynamic behavior of the melt pool may cause various quality issues. However, laser-based PBF (e.g., selective laser melting) is a volatile process, which makes in-situ process monitoring very difficult. This study uses in-situ high-speed coaxial pyrometry to real-time capture emission of the dynamic melt pool at the track, layer, and part levels in SLM of SS 316L powders. Emission readings have been characterized and correlated with thermal histories at different levels. The results have shown that the relationship between emissions and temperature can be used to establish pyrometry as a process signature for overheating in an SLM process.

Explicit minimal representation of variance matrices, and its implication for dynamic volatility models

SummaryWe propose a minimal representation of variance matrices of dimension k, where parameterization and positive-definiteness conditions are both explicit. Then we apply it to the specification of dynamic multivariate volatility processes. Compared to the most parsimonious unrestricted formulation currently available, the required number of covariance parameters (hence processes) is reduced by about a half, which makes them estimable in full parametric generality if needed. Our conditions are easy to implement: there are only k of them, and they are explicit and univariate. To illustrate, we forecast minimum-variance portfolios and show that risk is always reduced (by a factor of 2 to 3 in spite of us using the simplest dynamics) compared to the standard benchmark used in finance, while also improving returns on the investment. Because of our representation, we do not get the usual dimensionality problems of existing unrestricted models, and the performance relative to the benchmark is actually improved substantially as k increases.

The valuation of barrier options under a threshold rough Heston model

In this paper, we propose a novel model for pricing double barrier options, where the asset price is modeled as a threshold geometric Brownian motion time changed by an integrated activity rate process, which is driven by the convolution of a fractional kernel with the CIR process. The new model both captures the leverage effect and produces rough paths for the volatility process. The model also nests the threshold diffusion, Heston and rough Heston models. We can derive analytical formulas for the double barrier option prices based on the eigenfunction expansion method. We also implement the model and numerically investigate the sensitivities of option prices with respect to the parameters of the model.

Corrosion behaviour characterisation of 316L stainless steel and Inconel 625 in supercritical water containing hydrochloric acid and high oxygen

ABSTRACT Corrosion was currently the most crucial factor hindering the commercial development of supercritical water oxidation (SCWO) technology. Stainless steel represented by 316L and Ni-based alloy represented by Inconel 625 were performed and compared with corrosion resistance in supercritical environment with high concentrations of oxygen and chlorides. The results shown that the duplex layer was formed on two samples. The surface of 316L SS was mainly composed of loose magnetite and haematite, resulted in pitting corrosion, microcracks, and the exfoliation of oxide. The inner layer were separately a small amount of Cr2O3 oxide and FeCr2O4 spinel, which were caused by the lower content of chromium. Compared with 316L SS, the oxide film structure of Inconel 625 was composed of the outer layer of spinel and the inner layer of Cr-rich oxide. Some nodular oxides were formed, and it can be explained by the volatilisation process of chromium.

A multi-omics framework reveals strawberry flavor genes and their regulatory elements.

Flavor is essential to consumer preference of foods and is an increasing focus of plant breeding programs. In fruit crops, identifying genes underlying volatile organic compounds has great promise to accelerate flavor improvement, but polyploidy and heterozygosity in many species have slowed progress. Here we use octoploid cultivated strawberry to demonstrate how genomic heterozygosity, transcriptomic intricacy and fruit metabolomic diversity can be treated as strengths and leveraged to uncover fruit flavor genes and their regulatory elements. Multi-omics datasets were generated including an expression quantitative trait loci map with 196 diverse breeding lines, haplotype-phased genomes of a highly-flavored breeding selection, a genome-wide structural variant map using five haplotypes, and volatile genome-wide association study (GWAS) with > 300 individuals. Overlaying regulatory elements, structural variants and GWAS-linked allele-specific expression of numerous genes to variation in volatile compounds important to flavor. In one example, the functional role of anthranilate synthase alpha subunit 1 in methyl anthranilate biosynthesis was supported via fruit transient gene expression assays. These results demonstrate a framework for flavor gene discovery in fruit crops and a pathway to molecular breeding of cultivars with complex and desirable flavor.