| 1. |
- Menkveld, Albert J., et al.
(författare)
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Nonstandard Errors
- 2024
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Ingår i: JOURNAL OF FINANCE. - : Wiley-Blackwell. - 0022-1082 .- 1540-6261. ; 79:3, s. 2339-2390
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Tidskriftsartikel (refereegranskat)abstract
- In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty-nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
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| 2. |
- Bondarenko, Oleg, et al.
(författare)
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A General Framework for the Derivation of Asset Price Bounds : An Application to Stochastic Volatility Option Model
- 2009
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Ingår i: Review of Derivatives Research. - : Springer Science and Business Media LLC. - 1380-6645 .- 1573-7144. ; 12:2, s. 81-107
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Tidskriftsartikel (refereegranskat)abstract
- We present a generalization of Cochrane and Saá-Requejo’s good-deal bounds which allows to include in a flexible way the implications of a given stochas- tic discount factor model. Furthermore, a useful application to stochastic volatility models of option pricing is provided where closed-form solutions for the bounds are obtained. A calibration exercise demonstrates that our benchmark good-deal pricing results in much tighter bounds. Finally, a discussion of methodological and economic issues is also provided.
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| 3. |
- Kartsev, Alexey, et al.
(författare)
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Stability and magnetism of FeN high-pressure phases
- 2019
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Ingår i: Physical Chemistry, Chemical Physics - PCCP. - : Royal Society of Chemistry (RSC). - 1463-9076 .- 1463-9084. ; 21:9, s. 5262-5273
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Tidskriftsartikel (refereegranskat)abstract
- Most of the experimentally discovered compounds in the iron-nitrogen system belong to the low concentration part of the Fe-N phase diagram. In our paper, which is based on ab initio calculations, we have studied the formation and stability of high-pressure iron mono-nitride phases, and in particular a new magnetic phase with a NiAs-type structure. We have investigated the role of dynamic, thermodynamic and electronic properties, such as electronic correlations and pressure-induced phase stabilisation. Additionally, we have demonstrated that the new hexagonal FeN phase is stable over a wide range of external pressures and can persist at zero pressure as a metastable phase. Further, we have shown that this phase has a relatively low Curie temperature and may possess non-collinear magnetism.
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| 4. |
- Radivilova, Tamara, et al.
(författare)
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Statistical and Signature Analysis Methods of Intrusion Detection
- 2022
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Ingår i: Information Security Technologies in the Decentralized Distributed Networks. - Cham : Springer. - 9783030951610 ; , s. 115-131
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Bokkapitel (refereegranskat)abstract
- Existing models and methods of intrusion detection are mostly aimed at detecting intensive attacks, do not take into account the security of computer system resources and the properties of information flows. This limits the ability to detect anomalies in computer systems and information flows in a timely manner. The latest monitoring and intrusion detection solutions must take into account self-similar and statistical traffic characteristics, deep packet analysis, and the time it takes to process the information. An analysis of properties traffic and data collected at nodes and in the network was performed. Based on the analysis traffic parameters that will be used as indicators for intrusion detection were selected. A method of intrusion detection based on packet statistical analysis is described and simulated. A comparative analysis of binary classification of fractal time series by machine learning methods is performed. We consider classification by the example of different types of attack detection in traffic implementations. Random forest with regression trees and multilayer perceptron with periodic normalization were chosen as classification methods. The experimental results showed the effectiveness of the proposed methods in detecting attacks and identifying their type. All methods showed high attack detection accuracy values and low false positive values. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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