A Structural Model of Market Friction with Time-Varying Volatility

2021 ◽  
Author(s):  
Giuseppe Buccheri ◽  
Stefano Grassi ◽  
Giorgio Vocalelli
2019 ◽  
Vol 106 ◽  
pp. 103705 ◽  
Author(s):  
George Kapetanios ◽  
Riccardo M. Masolo ◽  
Katerina Petrova ◽  
Matthew Waldron

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Sheng-Lan Ma ◽  
Shao-Fei Jiang ◽  
Chen Wu ◽  
Si-Yao Wu

The integration of discrete wavelet transform and independent component analysis (DWT-ICA) method can directly identify time-varying changes in linear structures. However, better metrics of structural seismic damage and future performance after an event are related to structural permanent and total plastic deformations. This study proposes a two-stage technique based on DWT-FastICA and improved multiparticle swarm coevolution optimization (IMPSCO) using a baseline nonlinear Bouc–Wen structural model to directly identify changes in stiffness caused by damage as well as plastic or permanent deflections. In the first stage, the measured structural dynamic responses are preprocessed firstly by DWT, and then the Fast ICA is used to extract the feature components that contain the damage information for the purpose of initially locating damage. In the second stage, the structural responses are divided at the identified damage instant into segments that are used to identify the time-varying physical parameters by using the IMPSCO, and the location and extent of damage can accordingly be identified accurately. The efficiency of the proposed method in identifying stiffness changes is assessed under different ground motions using a suite of two different ground acceleration records. Meanwhile, the effect of noise level and damage extent on the proposed method is also analyzed. The results show that in a realistic scenario with fixed filter tuning parameters, the proposed approach identifies stiffness changes within 1.25% of true stiffness within 8.96 s; therefore, it can work in real time. Parameters are identified within 14% of the actual as-modeled value using noisy simulation-derived structural responses. This indicates that, in accordance with different demands, the proposed method can not only locate and quantify damage within a short time with a high precision but also has excellent noise tolerance, robustness, and practicality.


2019 ◽  
Vol 70 (9) ◽  
pp. 1837-1844 ◽  
Author(s):  
Yaseen M Arabi ◽  
Sarah Shalhoub ◽  
Yasser Mandourah ◽  
Fahad Al-Hameed ◽  
Awad Al-Omari ◽  
...  

Abstract Background The objective of this study was to evaluate the effect of ribavirin and recombinant interferon (RBV/rIFN) therapy on the outcomes of critically ill patients with Middle East respiratory syndrome (MERS), accounting for time-varying confounders. Methods This is a retrospective cohort study of critically ill patients with laboratory-confirmed MERS from 14 hospitals in Saudi Arabia diagnosed between September 2012 and January 2018. We evaluated the association of RBV/rIFN with 90-day mortality and MERS coronavirus (MERS-CoV) RNA clearance using marginal structural modeling to account for baseline and time-varying confounders. Results Of 349 MERS patients, 144 (41.3%) patients received RBV/rIFN (RBV and/or rIFN-α2a, rIFN-α2b, or rIFN-β1a; none received rIFN-β1b). RBV/rIFN was initiated at a median of 2 days (Q1, Q3: 1, 3 days) from intensive care unit admission. Crude 90-day mortality was higher in patients with RBV/rIFN compared to no RBV/rIFN (106/144 [73.6%] vs 126/205 [61.5%]; P = .02]. After adjusting for baseline and time-varying confounders using a marginal structural model, RBV/rIFN was not associated with changes in 90-day mortality (adjusted odds ratio, 1.03 [95% confidence interval {CI}, .73–1.44]; P = .87) or with more rapid MERS-CoV RNA clearance (adjusted hazard ratio, 0.65 [95% CI, .30–1.44]; P = .29). Conclusions In this observational study, RBV/rIFN (RBV and/or rIFN-α2a, rIFN-α2b, or rIFN-β1a) therapy was commonly used in critically ill MERS patients but was not associated with reduction in 90-day mortality or in faster MERS-CoV RNA clearance.


Author(s):  
Katerina Petrova ◽  
George Kapetanios ◽  
Riccardo Masolo ◽  
Matthew Waldron

2018 ◽  
Vol 49 (4) ◽  
pp. 906-946 ◽  
Author(s):  
Geoffrey T. Wodtke

Social scientists are often interested in estimating the marginal effects of a time-varying treatment on an end-of-study continuous outcome. With observational data, estimating these effects is complicated by the presence of time-varying confounders affected by prior treatments, which may lead to bias in conventional regression and matching estimators. In this situation, inverse-probability-of-treatment-weighted (IPTW) estimation of a marginal structural model remains unbiased if treatment assignment is sequentially ignorable and the conditional probability of treatment is correctly modeled, but this method is not without limitations. In particular, it is difficult to use with continuous treatments, and it is relatively inefficient. This article explores using an alternative regression-based method—regression-with-residuals (RWR) estimation of a constrained structural nested mean model—that may overcome some of these limitations in practice. It is unbiased for the marginal effects of a time-varying treatment if treatment assignment is sequentially ignorable, the treatment effects of interest are invariant across levels of the confounders, and a model for the conditional mean of the outcome is correctly specified. The performance of RWR estimation relative to IPTW estimation is evaluated with a series of simulation experiments and with an empirical example based on longitudinal data from the Panel Study of Income Dynamics. Results indicate that it may outperform IPTW estimation in certain situations.


2019 ◽  
Vol 26 (3) ◽  
pp. 248-253
Author(s):  
Navneet Kaur Baidwan ◽  
Susan Goodwin Gerberich ◽  
Hyun Kim ◽  
Andrew D Ryan ◽  
Timothy Church ◽  
...  

BackgroundBiases may exist in the limited longitudinal data focusing on work-related injuries among the ageing workforce. Standard statistical techniques may not provide valid estimates when the data are time-varying and when prior exposures and outcomes may influence future outcomes. This research effort uses marginal structural models (MSMs), a class of causal models rarely applied for injury epidemiology research to analyse work-related injuries.Methods7212 working US adults aged ≥50 years, obtained from the Health and Retirement Study sample in the year 2004 formed the study cohort that was followed until 2014. The analyses compared estimates measuring the associations between physical work requirements and work-related injuries using MSMs and a traditional regression model. The weights used in the MSMs, besides accounting for time-varying exposures, also accounted for the recurrent nature of injuries.ResultsThe results were consistent with regard to directionality between the two models. However, the effect estimate was greater when the same data were analysed using MSMs, built without the restriction for complete case analyses.ConclusionsMSMs can be particularly useful for observational data, especially with the inclusion of recurrent outcomes as these can be incorporated in the weights themselves.


2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Elani Streja ◽  
Jongha Park ◽  
Ting-Yan Chan ◽  
Janet Lee ◽  
Melissa Soohoo ◽  
...  

It has been previously reported that a higher erythropoiesis stimulating agent (ESA) dose in hemodialysis patients is associated with adverse outcomes including mortality; however the causal relationship between ESA and mortality is still hotly debated. We hypothesize ESA dose indeed exhibits a direct linear relationship with mortality in models of association implementing the use of a marginal structural model (MSM), which controls for time-varying confounding and examines causality in the ESA dose-mortality relationship. We conducted a retrospective cohort study of 128 598 adult hemodialysis patients over a 5-year follow-up period to evaluate the association between weekly ESA (epoetin-α) dose and mortality risk. A MSM was used to account for baseline and time-varying covariates especially laboratory measures including hemoglobin level and markers of malnutrition-inflammation status. There was a dose-dependent positive association between weekly epoetin-αdoses ≥18 000 U/week and mortality risk. Compared to ESA dose of <6 000 U/week, adjusted odds ratios (95% confidence interval) were 1.02 (0.94–1.10), 1.08 (1.00–1.18), 1.17 (1.06–1.28), 1.27 (1.15–1.41), and 1.52 (1.37–1.69) for ESA dose of 6 000 to <12 000, 12 000 to <18 000, 18 000 to <24 000, 24 000 to <30 000, and ≥30 000 U/week, respectively. High ESA dose may be causally associated with excessive mortality, which is supportive of guidelines which advocate for conservative management of ESA dosing regimen in hemodialysis patients.


Sign in / Sign up

Export Citation Format

Share Document