Results 61 to 70 of about 113,493 (310)

Forecasting stock market volatility and the informational efficiency of the DAX-index options market [PDF]

, 2002
Alternative strategies for predicting stock market volatility are examined. In out-of-sample forecasting experiments implied-volatility information, derived from contemporaneously observed option prices or history-based volatility predictors, such as ...
Claessen, Holger, Mittnik, Stefan
core   +1 more source

Prospects of Electric Field Control in Perpendicular Magnetic Tunnel Junctions and Emerging 2D Spintronics for Ultralow Energy Memory and Logic Devices

Advanced Functional Materials, EarlyView.
Electric control of magnetic tunnel junctions offers a path to drastically reduce the energy requirements of the device. Electric field control of magnetization can be realized in a multitude of ways. These mechanisms can be integrated into existing spintronic devices to further reduce the operational energy.
Will Echtenkamp, Brahmdutta Dixit, Yifei Yang, Deyuan Lyu, Thomas Peterson, Qi Jia, Yu‐Chia Chen, Jian‐Ping Wang   +7 more
wiley   +1 more source

Coin impact on cross-crypto realized volatility and dynamic cryptocurrency volatility connectedness

Financial Innovation
This study evaluates the predictive accuracy of traditional time series (TS) models versus machine learning (ML) methods in forecasting realized volatility across major cryptocurrencies—Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), and Ripple (XRP ...
Burak Korkusuz, Mehmet Sahiner
doaj   +1 more source

Cryptocurrency price returns volatility modeling and forecasting with GARCH models [PDF]

RAUSP Management Journal
PurposeThe paper aims to identify suitable conditional variance models for the estimation and forecasting of cryptocurrency returns volatility.Design/methodology/approachThe methodology comprises the use of GARCH-family models estimated by maximum ...
Lukas Silva, Leandro Maciel
doaj   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Quantile forecasts of daily exchange rate returns from forecasts of realized volatility [PDF]

, 2008
Quantile forecasts are central to risk management decisions because of the widespread use of Value-at-Risk. A quantile forecast is the product of two factors: the model used to forecast volatility, and the method of computing quantiles from the ...
Ana Beatriz Galvão, Andersen, Andersen, Andersen, Andersen, Bandi, Barndorff-Nielsen, Barndorff-Nielsen, Barndorff-Nielsen, Barndorff-Nielsen, Blair, Bollerslev, Bollerslev, Christoffersen, Clements, Comte, Diebold, Engle, Ghysels, Ghysels, Giacomini, Giot, Granger, Hansen, Jae H. Kim, Koopman, Michael P. Clements, Poon, West, White, Zhang   +30 more
core   +1 more source

Complex Cryptographic and User‐Centric Physically Unclonable Functions Enabled by Strain‐Sensitive Nanocrystals via Selective Ligand Exchange

Advanced Functional Materials, EarlyView.
This study investigates electromechanical PUFs that improve on traditional electric PUFs. The electron transport materials are coated randomly through selective ligand exchange. It produces multiple keys and a key with motion dependent on percolation and strain, and approaches almost ideal inter‐ and intra‐hamming distances.
Seungshin Lim, Hanseok Seo, Taesung Park, Byung Ku Jung, Junhyeok Park, Young Kyun Choi, Dae Yang Oh, Soong Ju Oh   +7 more
wiley   +1 more source

Exploiting Two‐Photon Lithography, Deposition, and Processing to Realize Complex 3D Magnetic Nanostructures

Advanced Functional Materials, EarlyView.
Two‐photon lithography (TPL) enables 3D magnetic nanostructures with unmatched freedom in geometry and material choice. Advances in voxel control, deposition, and functionalization open pathways to artificial spin ices, racetracks, microrobots, and a number of additional technological applications.
Joseph Askey, Arjen van den Berg, Sandra Ruiz Gomez, Claire Donnelly, Dirk Grundler, Sam Ladak   +5 more
wiley   +1 more source

Advances in forecasting realized volatility: a review of methodologies

Financial Innovation
Over the past decade, volatility modeling has gained increasing importance in quantitative finance, significantly influencing risk management, investment strategies, and policymaking.
Radmir Mishelevich Leushuis, Nicolai Petkov   +1 more
doaj   +1 more source

The Implied-Realized Volatility Relation with Jumps in Underlying Asset Prices [PDF]

Recent developments allow a nonparametric separation of the continuous sample path component and the jump component of realized volatility. The jump component has very different time series properties than the continuous component, and accounting for ...
Bent Jesper Christensen, Morten Ørregaard Nielsen   +1 more
core