Volatility Decomposition Research Articles

Sentiment and energy price volatility: A nonlinear high frequency analysis

This study investigates the volatility dynamics of oil and gas prices in an environment characterized by post-coronavirus disease 2019 recovery, uncertainty, high inflation, and geopolitical tensions. Unlike previous studies, we examine a long-run series of high-frequency data on gas and oil prices from July 2007 to May 2022, which provides more than one million observations with which to analyze volatility. We compute realized volatility (RV) and decompose it into continuous volatility and jumps. We then investigate the relationship between uncertainty, investor sentiment, and RV, as well as its main components. Econometrically, we extend the heterogeneous autoregressive model of Corsi (2009) while considering not only disaggregate proxies for volatility (jumps and continuous volatility) and introducing uncertainty and heterogeneous investor sentiment, but also by allowing the model to include asymmetry, nonlinearity, and time variation according to the regime under consideration. Our results present three main findings. First, we find significant evidence of volatility decomposition, suggesting that both markets are characterized by significant jumps. Second, we show that trading volume, extra-financial news (uncertainty, investor sentiment), and jumps appear to drive commodity price volatility. Third, we find evidence of nonlinearity and threshold effects on energy price volatility. These findings are relevant for policymakers, regulators, investors, and portfolio managers, as they enable them to better characterize and forecast changes in commodity prices.

Interconnectedness of cryptocurrency markets: an intraday analysis of volatility spillovers based on realized volatility decomposition

Interconnectedness of cryptocurrency markets: an intraday analysis of volatility spillovers based on realized volatility decomposition

The sources of portfolio volatility and mutual fund performance

We conduct a volatility decomposition to identify the source of performance differences between low volatility and high volatility mutual funds. Higher return covariances between fund holdings are associated with more fund-level exposure to the idiosyncratic volatility effect. The average security-level variance of fund holdings is only weakly associated with idiosyncratic volatility but is closely tied to a fund's exposure to the beta anomaly. We demonstrate that our measure of the within-portfolio covariance of fund holdings is useful in evaluating fund-level performance measures and exposure to volatility anomalies.

METHODOLOGY OF OBTAINING CHROMIUM CARBONYL COMPLEXES AND DEVICES USED IN OBTAINING THEM

The development of modern technology and the long-term processing of materials and constructions used in high temperature conditions make great demands. It is very important to obtain hard-melting metals that meet these requirements. In nature, the scarcity of hard-to-melt metals and their high cost force us to find other more efficient ways. One such solution is the application of hard- -melt metals in the form of thin layers or coatings on metals or structures. For to this purpose, carbonyl compounds of hard-to-melt metals are widely used in technology recently. Carbonyl compounds have important properties, one of which is that they act as raw materials for obtaining coatings and layers through thermal decomposition. However, some difficulties arise in obtaining chromium coatings based on chromium carbonyl complexes with organic ligands. In order to overcome such difficulties, the synthesis methodology of two chromium-based complex compounds with easy volatility and low decomposition temperature, which are used in the production of corrosion-resistant coatings, and the temperature range in their decomposition limits, physical chemical structure parameters have been determined. The research found that both chromium carbonyl complexes obtained by synthesis form chromium coatings with high adhesion on the metal carrier and increase their corrosion resistance. Chromium carbonyl complexes can serve as technologically favorable raw materials for obtaining the necessary chromium coating during the decomposition of groups at a very low temperature range (100-150 C) without creating additional pressure. Both synthesized complex compounds are raw materials for obtaining corrosion-resistant coatings on weld seams of 09Г2С steel. The use of these complexes as active fillers in abrasive metallurgy has also been determined. Keywords: Chromium, solvent, toluene, mesethylene, infrared spectrum, chromium carbonyl, complex, melting, decomposition, coating, heating, solution.

Systemic risk spillover of China’s energy industry based on the perspective of volatility decomposition

Systemic risk spillover of China’s energy industry based on the perspective of volatility decomposition

Co-volatility and asymmetric transmission of risks between the global oil and China's futures markets

We construct a multivariate heterogeneous autoregressive model specified with common stochastic volatility and the student-t distribution, the MHAR-CSV-t model, to investigate co-movements and high-frequency volatility transmissions between the WTI futures market and China's stock and commodity futures markets. Additionally, we analyse the time-varying volatility connectedness between these markets. We find that between these markets, the WTI futures market features the most episodes of volatility spikes, particularly since 2014. We find several structural breaks in realised volatility and its decomposition in positive and negative volatility. The results of the time-varying volatility connectedness identify corn, gold, and equity futures as persistent transmitters; the copper futures market as a net receiver; and oil futures as assuming both roles in the spillovers of volatility shocks across markets. We also find significant asymmetries in their volatility decomposition and their spillovers across these markets.

China and Countries along the “Belt and Road”: Agricultural Trade Volatility Decomposition and Food Security

Agricultural products are essential for human survival, and strengthening agricultural trade cooperation between China and countries along the “Belt and Road” (B&R) can promote food security, but there are few studies on bilateral trade fluctuation factors in the literature. This paper uses the modified multi-country multi-product CMS (constant market share) model and the two-country multi-product CMS model to decompose the fluctuation of agricultural trade between China and B&R countries by stage, region, and agricultural product type. The results show that in recent years, in the fluctuation of China’s exports to B&R countries, in overall agricultural products, the demand effect plays a major hindering role, accounting for −9.2%; in the region, Southeast Asia has the largest share of trade, which is mainly pulled by the joint demand effect, structural effect and competitiveness effect; in specific agricultural products, animal, fruit and vegetable, and food processing products are mainly pulled by competitiveness. In the fluctuation of B&R countries’ export to China, in overall agricultural products, the demand effect pulls the largest share, accounting for 72.55%; in the region, Southeast Asia is mainly driven by the joint pull of demand effect, structural effect. and competitiveness effect; in specific agricultural products, animal, fruit and vegetable, and food processing products are mainly driven by the pull of demand effect. The findings of this paper can provide a basis for making decisions on food security cooperation between China and B&R countries.

A versatile Fe(II) diketonate diamine adduct: Preparation, characterization and validation in the chemical vapor deposition of iron oxide nanomaterials

Iron(III) oxide nanomaterials are extremely promising for the development of magnetic devices, gas sensors, photocatalysts, and photoelectrodes for solar water splitting. The fabrication of such systems by chemical vapor deposition (CVD) relies on the use of molecular sources joining shelf-stability, high volatility, and clean decomposition. Herein, we report for the first time on a versatile iron(II) precursor, namely Fe(tfa)2TMEDA (tfa = 1,1,1-trifluoro-2,4-pentanedionate; TMEDA = N,N,N′,N′-tetramethylethylenediamine), combining the above features with a simple molecular concept. A theoretical-experimental characterization confirmed the compound spectroscopic purity and monomeric nature, and enabled to elucidate its structural, vibrational and electronic properties, along with its fragmentation pathway and thermal behavior. The ideal Fe(tfa)2TMEDA characteristics for CVD applications were finally validated through the fabrication of high purity iron oxide nanomaterials. The latter, comprising the sole metastable β-Fe2O3 polymorph rather than the most stable rust (α-Fe2O3), were characterized by the occurrence of oxygen defects and a nano-organization tunable as a function of growth temperature and reaction atmosphere.

Piezo-enhanced activation of dinitrogen for room temperature production of ammonia

The catalytic conversion of nitrogen to ammonia remains an energy-intensive process, demanding advanced concepts for nitrogen fixation. The major obstacle of nitrogen fixation lies in the intrinsically high bond energy (941 kJ mol−1) of the N≡N molecule and the absence of a permanent dipole in N2. This kinetic barrier is addressed in this study by an efficient piezo-enhanced gold catalysis as demonstrated by the room temperature reduction of dinitrogen into ammonia. Au nanostructures were immobilized on thin film piezoelectric support of potassium sodium niobate (K0.5Na0.5NbO3, KNN) by chemical vapor deposition of a new Au(III) precursor [Me2Au(PyTFP)(H2O)] 1 (PyTFP = (Z)-3,3,3-trifluoro-1-(pyridin-2-yl)-prop-1-en-2-olate) that exhibited high volatility (60 °C, 10–3 mbar) and clean decomposition mechanism to produce well adherent elemental gold films on KNN and Ti substrates. The gold-functionalized KNN films served as an efficient catalytic system for ammonia production with a Faradaic efficiency of 18.9% achieved upon ultrasonic actuation. Our results show that the spontaneous polarization of piezoelectric materials under external electrical fields augments the sluggish electron transfer kinetics by creating instant dipoles in adsorbed N2 molecules to deliver a piezo-enhanced catalytic system promising for sustained activation of dinitrogen molecules.

Mean-Reverting 4/2 Principal Components Model. Financial Applications

In this paper, we propose a new multivariate mean-reverting model incorporating state-of-the art 4/2 stochastic volatility and a convenient principal component stochastic volatility (PCSV) decomposition for the stochastic covariance. We find a quasi closed-form characteristic function and propose analytic approximations, which aid in the pricing of derivatives and calculation of risk measures. Parameters are estimated on three bivariate series, using a two-stage methodology involving method of moments and least squares. Moreover, a scaling factor is added for extra degrees of freedom to match data features. As an application, we consider investment strategies for a portfolio with two risky assets and a risk-free cash account. We calculate value-at-risk (VaR) values at a 95% risk level using both simulation-based and distribution-based methods. A comparison of these VaR values supports the effectiveness of our approximations and the potential for higher dimensions.

High-frequency volatility modeling: A Markov-Switching Autoregressive Conditional Intensity model

We develop a Markov-Switching Autoregressive Conditional Intensity (MS-ACI) model with time-varying transitional probability, and show that it can be reliably estimated via the Stochastic Approximation Expectation–Maximization algorithm. Applying our model to high-frequency transaction data, we detect two distinct regimes in the intraday volatility process: a dominant volatility regime that is observable throughout the trading day representing the risk-transferring trading activity of investors, and a minor volatility regime that concentrates around market liquidity shocks which mainly capture impacts of firm-specific news arrivals. We propose a novel daily volatility decomposition based on the two detected volatility regimes.

Forecasting realized volatility of agricultural commodities

We forecast the realized and median realized volatility of agricultural commodities using variants of the heterogeneous autoregressive (HAR) model. We obtain tick-by-tick data on five widely-traded agricultural commodities (corn, rough rice, soybeans, sugar, and wheat) from the CME/ICE. Real out-of-sample forecasts are produced for between 1 and 66 days ahead. Our in-sample analysis shows that the variants of the HAR model which decompose volatility measures into their continuous path and jump components and incorporate leverage effects offer better fitting in the predictive regressions. However, we demonstrate convincingly that such HAR extensions do not offer any superior predictive ability in their out-of-sample results, since none of these extensions produce significantly better forecasts than the simple HAR model. Our results remain robust even when we evaluate them in a Value-at-Risk framework. Thus, there is no benefit from including more complexity, related to the volatility decomposition or relative transformations of the volatility, in the forecasting models.

Structure-Decomposition relationships of homoleptic and heteroleptic vanadium(IV) alkoxides for defined gas phase depositions of VO2 and V2O3 thin films

A facile high yield synthesis of a novel non-oxo heteroleptic vanadium(IV) alkoxide with chelating asymmetric fluorinated ß-heteroarylacetamides (2,2,2-trifluoro-N-(pyridine-2-yl)acetamide (H-PyTFA) (1)) with the general formula [V(OtBu)2(PyTFA)2] (4) as precursor for nanostructured vanadium oxides films deposited by chemical vapor deposition (CVD) is presented here. Single crystal X-ray analysis, electron paramagnetic resonance (EPR) spectroscopy and mass spectrometry (EI-MS) revealed the unambiguous structural and electronic features of the monomeric octahedral complex 4. Comparative thermogravimetric studies with homoleptic monomeric vanadium(IV) tert–butoxide [V(OtBu)4] (2) and trimeric [V3(μ-OEt)4(OEt)8] (3) displayed the strong influence of the alkyl function in vanadium(IV) alkoxides and chelating ligands on volatility, stability and thermal decomposition pathways to different oxide phases and morphologies. We demonstrated a controlled two-step thermal decomposition of heteroleptic vanadium(IV) alkoxide (4) which offer new opportunities for a versatile growth by the enlarged ‘CVD window’ between sublimation temperature and decomposition temperature and selective self-limited growth originated from the ‘Energy trap’ between the first and second decomposition steps. Preliminary CVD experiments proofed the successful conversion of the heteroleptic precursor 4 into vanadium dioxide with ribbon-like morphology on silicon, which revealed the impact of molecular precursor engineering on crystal growth kinetics.

Controlling the Thermal Stability and Volatility of Organogold(I) Compounds for Vapor Deposition with Complementary Ligand Design

Atomic layer deposition (ALD) of gold is being studied by multiple research groups, but to date no process using non‐energetic co‐reactants has been demonstrated. In order to access milder co‐reactants, precursors with higher thermal stability are required. We set out to uncover how structure and bonding affect the stability and volatility of a family of twelve organogold(I) compounds using a combination of techniques: X‐ray diffraction (XRD), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and density functional theory (DFT). Small, unsubstituted phosphonium ylide ligands bind more strongly to Au(I) than their silyl‐substituted analogues, but the utility of both these ligands suffers due to their poor volatility and substantial thermal decomposition. Pentafluorophenyl (C6F5) is introduced as a new, very electronegative ligand for gold vapor deposition precursors, and it was found that the disadvantage to volatility due to π‐stacking and other intermolecular interactions in the solid state was overshadowed by dramatic improvements to kinetic and thermodynamic stability. We introduce a new figure of merit to compare and rank the suitability of these and other complexes as precursors for vapor deposition. Finally, DFT calculations on four compounds that have high figures of merit show a linear correlation between the gold‐coordinative ligand bond dissociation energies and the observed decomposition temperatures, highlighting and justifying this design strategy.

Impact of Price–Quantity Uncertainties and Risk Aversion on Energy Retailer’s Pricing and Hedging Behaviors

The joint uncertainties of wholesale price and end-user demand quantity often poses huge pricing challenges to energy retailers. However, the literature lacks analysis of such uncertainties’ impacts on retailer pricing behaviors and possible hedging behaviors. To study these impacts, this paper proposes four models: a risk-averse or a risk-neutral retailer deciding retail price with or without forward contract. We present closed-form solutions for these four models on optimal retail price, as well as optimal forward position (if allowed). We propose a novel approach of volatility decomposition to describe the relationship between behaviors and different volatility sources. Comparative statics gives detailed analysis of the pricing and hedging behaviors in both uncertainties, as well as their correlation. We obtain profit distributions using Monte Carlo simulations in the context of the California Electricity Market. Results show that the price and quantity uncertainties and their correlation create significant differences in the retailer’s behaviors, and the determinants of these differences are different. In addition, forward contract increases expected profit and decreases profit volatility for risk-averse retailers simultaneously. These results could serve as a benchmark for analyses of deregulated, imperfect energy markets coupled with contingent financial markets under both price and quantity uncertainties.

Molecular Routes to Two-Dimensional Metal Dichalcogenides MX2 (M = Mo, W; X = S, Se).

New synthetic access to two-dimensional transition metal dichalcogenides (TMDCs) is highly desired to exploit their extraordinary semiconducting and optoelectronic properties for practical applications. We introduce here an entirely novel class of molecular precursors, [MIV(XEtN(Me)EtX)2] (MIV = MoIV, WIV, X = S, Se), enabling chemical vapor deposition of TMDC thin films. Molybdenum and tungsten complexes of dianionic tridentate pincer-type ligands (HXEt)2NR (R = methyl, tert-butyl, phenyl) produced air-stable monomeric dichalcogenide complexes, [W(SEtN(Me)EtS)2] and [Mo(SEtN(Me)EtS)2], displaying W and Mo centers in an octahedral environment of 4 S and 2 N donor atoms. Owing to their remarkable volatility and clean thermal decomposition, both Mo and W complexes, when used in the chemical vapor deposition (CVD) process, produced crystalline MoS2 and WS2 thin films. X-ray diffraction analysis and atomic-scale imaging confirmed the phase purity and 2D structural characteristics of MoS2 and WS2 films. The new set of ligands presented in this work open ups convenient access to a scalable and precursor-based synthesis of 2D transition metal dichalcogenides.

Discount Rates and Cash Flows: A Local Projection Approach

We develop a volatility decomposition derived from flexible local projections to quantify the relative contributions of expected discount rates and cash flows to the variation of dividend yields. Local projections enable the incorporation of large information sets, the use of monthly data along with annual data, and to consider time variation in the volatility decomposition. By expanding the set of state variables and allowing for time-varying parameters, we find that while the variation of expected discount rates remains generally the dominant contributor to market volatility, the contribution of expected cash flows is by no means negligible.

Elemental Software Architecture

This paper discusses a software architecture methodology, called Elemental Software Architecture, which is derived from two other existing methodologies: Juval Lowy’s Method and Robert Martin’s Clean Architecture. Juval Lowy’s Method decomposes requirements into core use case and further decomposes these use cases using volatility decomposition into layers that contain Clients, Managers, Engines, Resource Accessors and Resources. Robert Martin’s Clean Architecture decomposes requirements into use cases that are further decomposed into different parts using the SOLID principles to make system resilient against changes in requirements and scaling. Similarities exist between two methodologies, and both can be mapped to common elements. The methodology proposed in this paper uses these common elements and a decomposition method to decompose the requirements of a system into these common elements.

The Role of US Variables in Long-Run and Short-Run Taiwan Stock Volatility

ABSTRACTThis article uses the GARCH-MIDAS model to decompose Taiwan stock volatility and studies the role of US economic variables in each component. The full-sample results indicate that the additional explanatory information of US variables is contributed mostly by stock market measures, and the link between short-run Taiwan and US stock volatility is particularly evident. The out-of-sample results suggest that the in-sample significant US variables lead to slightly smaller forecast errors for both volatility components, but the improvements are very limited. The analysis also extends to Electronics and Non-Electronics subindices, a range-based volatility estimator and a different volatility decomposition method. Despite these alternatives, the main conclusions do not change.

The growth-volatility relationship redux: what does volatility decomposition tell?

Abstract This paper revisits the empirical relationship between volatility and long-run growth, but the key contribution lies in decomposing growth volatility into its business-cycle and trend components. This volatility decomposition also accounts for enormous heterogeneity among countries in terms of their long-run growth trajectories. We identify a negative effect of trend volatility, which we refer to as long-run volatility, on growth, but no effect of business-cycle volatility. However, if long-run volatility is omitted, there would be a spurious (negative) effect of business-cycle volatility. Our results draw attention to a crucial question about different volatility measures and their implications in macroeconomic analyses.