scholarly journals Market risk stress testing for internationally active financial institutions

2011 ◽  
Vol 56 (188) ◽  
pp. 62-90 ◽  
Author(s):  
Petar Markovic ◽  
Branko Urosevic
Keyword(s):  
Financial Institutions ◽  
Stress Testing ◽  
Stress Test ◽  
Data Gathering ◽  
Market Risk ◽  
Case Scenario ◽  
Worst Case ◽  
Thomson Reuters ◽  
Comprehensive Framework

The paper develops a comprehensive framework for market risk stress testing in internationally active financial institutions. We begin by defining the scope and type of the stress test and explaining how to select risk factors and the stress time horizon. We then address challenges related to data gathering, followed by in-depth discussion of techniques for developing realistic shock scenarios. Next the process of shock application to a particular portfolio is described, followed by determination of portfolio profit and loss. We conclude by briefly discussing the issue of assigning probability to stress scenarios. We illustrate the framework by considering the development of a ?worst case? scenario using global financial market data from Thomson Reuters Datastream.

Detection and Determination of Minor Components in Nominally Pure Solids by Raman Spectroscopy

1987 ◽  
Vol 41 (8) ◽  
pp. 1324-1329 ◽  
Author(s):  
Charles K. Mann ◽  
Thomas J. Vickers ◽  
James D. Womack
Keyword(s):  
Raman Spectroscopy ◽  
Least Squares ◽  
Sulfanilic Acid ◽  
Qualitative And Quantitative Analysis ◽  
Case Scenario ◽  
Worst Case ◽  
Least Squares Fitting ◽  
Correlation Data ◽  
Treatment Procedures

The problems encountered in applying Raman spectroscopy to direct qualitative and quantitative analysis for minor impurities in nominally pure, colorless solids have been examined. Samples of sulfamethoxazole spiked with 0.5 to 5% of sulfanilamide and sulfanilic acid were used as test materials. A procedure is described which permits detection of spectral features of the specified impurities at the 0.5% level. Least-squares fitting and cross-correlation data treatment procedures for the determination of sulfanilamide in sulfamethoxazole, with limits of detection of about 0.1% for either approach, are described. Computer simulations have been used to examine detection of impurity peaks for a variety of conditions, including the worst-case scenario in which the impurity features coincide with the strongest features of the spectrum of the host material. A least-squares fitting approach is described which permits detection of the impurity peak at the 0.5% level, even under worst case conditions.

scholarly journals Stress testing as complement to climate scenarios: recharge scenarios to quantify streamflow drought sensitivity

2020 ◽  
Vol 383 ◽  
pp. 43-50
Author(s):  
Michael Stoelzle ◽  
Maria Staudinger ◽  
Kerstin Stahl ◽  
Markus Weiler
Keyword(s):  
Stress Testing ◽  
Stress Test ◽  
Ecological Integrity ◽  
Climate Scenarios ◽  
Stress Tests ◽  
Worst Case ◽  
Drought Sensitivity ◽  
Dry Spells ◽  
Reference Simulation ◽  
Recovery Times

Abstract. Precipitation deficits and temperature anomalies are often the main cause for low flows and summer streamflow droughts. However, where groundwater is the main contribution to sustain water availability and ecological integrity during dry spells, the role of recharge and catchment storage is crucial to understand streamflow drought sensitivity. Here we introduce recharge stress tests as complement to climate scenarios to characterize and quantify the streamflow drought sensitivities of catchments. The stress tests are presented by applying them to six headwater catchments in Switzerland with various catchment and streamflow characteristics. The stress tests drive the bucket-type hydrological model HBV in a framework, in which pre-drought recharge conditions can be decreased to test how catchments respond to and recover from drought. We identified an upper limit of stress test durations around 12 months as indicator of maximum recharge- and storage-memory for the study catchments. Varying response on stress testing across the catchments suggests different storage properties and thus different recovery times from drought. From the stress test simulations, we found up to 200 d longer summer streamflow droughts with additional streamflow deficits which account for up to 40 d of median flow. Using a worst-case pre-drought recharge in stress test simulation leads to minimum flow reductions of 50 %–80 % compared with the reference simulation. Based on the results we conclude with recommendations for further stress test research in drought hydrology.

Reducing Probabilistic Weather Forecasts to the Worst Case Scenario: Anchoring Effects

2008 ◽  
Author(s):  
Sonia Savelli ◽  
Susan Joslyn ◽  
Limor Nadav-Greenberg ◽  
Queena Chen
Keyword(s):  
Case Scenario ◽  
Worst Case ◽  
Weather Forecasts ◽  
Worst Case Scenario ◽  
Anchoring Effects

Stress-testing Russian Banking System: Will Banks Need Government Assistance Again?

2010 ◽  
pp. 61-81 ◽  
Author(s):  
O. Solntsev ◽  
A. Pestova ◽  
M. Mamonov
Keyword(s):  
Stress Testing ◽  
Banking Sector ◽  
Stress Test ◽  
Banking System ◽  
Government Assistance ◽  
Methodological Issues ◽  
Loan Portfolio ◽  
Macroeconomic Indicators ◽  
Remote Stress ◽  
Capital Injections

The article analyzes factors that affect growth of the share of non-performing loans in the loan portfolio of Russian banks and proposes approaches for this share forecasting on the basis of dynamics of macroeconomic indicators. It also deals with methodological issues of remote stress-test of lending agencies. Using the results of conducted stress-test of Russian banks the authors assess their perspective capital needs in 2010 and estimate the share of government assistance in capital injections. Furthermore, the authors define the scale of vulnerable banks groups in the Russian banking sector.

EXPEDITION TO MALI, 2020

2020 ◽  
pp. 12-28
Author(s):  
D. V. Vaniukova ◽  
◽  
P. A. Kutsenkov ◽  
Keyword(s):  
Mass Murder ◽  
The State ◽  
Case Scenario ◽  
Worst Case ◽  
Traditional Art ◽  
Peter The Great ◽  
State Museum ◽  
Bobo Dioulasso ◽  
Oriental Studies ◽  
The Village

The research expedition of the Institute of Oriental studies of the Russian Academy of Sciences has been working in Mali since 2015. Since 2017, it has been attended by employees of the State Museum of the East. The task of the expedition is to study the transformation of traditional Dogon culture in the context of globalization, as well as to collect ethnographic information (life, customs, features of the traditional social and political structure); to collect oral historical legends; to study the history, existence, and transformation of artistic tradition in the villages of the Dogon Country in modern conditions; collecting items of Ethnography and art to add to the collection of the African collection of the. Peter the Great Museum (Kunstkamera, Saint Petersburg) and the State Museum of Oriental Arts (Moscow). The plan of the expedition in January 2020 included additional items, namely, the study of the functioning of the antique market in Mali (the “path” of things from villages to cities, which is important for attributing works of traditional art). The geography of our research was significantly expanded to the regions of Sikasso and Koulikoro in Mali, as well as to the city of Bobo-Dioulasso and its surroundings in Burkina Faso, which is related to the study of migrations to the Bandiagara Highlands. In addition, the plan of the expedition included organization of a photo exhibition in the Museum of the village of Endé and some educational projects. Unfortunately, after the mass murder in March 2019 in the village of Ogossogou-Pel, where more than one hundred and seventy people were killed, events in the Dogon Country began to develop in the worst-case scenario: The incessant provocations after that revived the old feud between the Pel (Fulbe) pastoralists and the Dogon farmers. So far, this hostility and mutual distrust has not yet developed into a full-scale ethnic conflict, but, unfortunately, such a development now seems quite likely.

Risk-Based Robust Bidding Strategies for EVs’ Aggregators in Day-ahead Markets with Uncertainty

2020 ◽  
Author(s):  
Ahmed Abdelmoaty ◽  
Wessam Mesbah ◽  
Mohammad A. M. Abdel-Aal ◽  
Ali T. Alawami
Keyword(s):  
Robust Optimization ◽  
Electricity Market ◽  
Real Life ◽  
Optimization Approach ◽  
Case Scenario ◽  
Worst Case ◽  
Bidding Strategies ◽  
Wind Generators ◽  
Proposed Model ◽  
Optimal Bidding

In the recent electricity market framework, the profit of the generation companies depends on the decision of the operator on the schedule of its units, the energy price, and the optimal bidding strategies. Due to the expanded integration of uncertain renewable generators which is highly intermittent such as wind plants, the coordination with other facilities to mitigate the risks of imbalances is mandatory. Accordingly, coordination of wind generators with the evolutionary Electric Vehicles (EVs) is expected to boost the performance of the grid. In this paper, we propose a robust optimization approach for the coordination between the wind-thermal generators and the EVs in a virtual<br>power plant (VPP) environment. The objective of maximizing the profit of the VPP Operator (VPPO) is studied. The optimal bidding strategy of the VPPO in the day-ahead market under uncertainties of wind power, energy<br>prices, imbalance prices, and demand is obtained for the worst case scenario. A case study is conducted to assess the e?effectiveness of the proposed model in terms of the VPPO's profit. A comparison between the proposed model and the scenario-based optimization was introduced. Our results confirmed that, although the conservative behavior of the worst-case robust optimization model, it helps the decision maker from the fluctuations of the uncertain parameters involved in the production and bidding processes. In addition, robust optimization is a more tractable problem and does not suffer from<br>the high computation burden associated with scenario-based stochastic programming. This makes it more practical for real-life scenarios.<br>

A Comprehensive Framework for Quantitative Stress Tests in Financial Institutions

2013 ◽  
Author(s):  
Yasushi Takano ◽  
Jiro Hashiba ◽  
Rintaro Anraku ◽  
Ryuichi Sato ◽  
Sakae Mizuki ◽  
...  
Keyword(s):  
Financial Institutions ◽  
Stress Tests ◽  
Comprehensive Framework ◽  
Quantitative Stress

scholarly journals A Thermally Conductive Pt/AAO Catalyst for Hydrogen Passive Autocatalytic Recombination

Catalysts ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 491
Author(s):  
Alina E. Kozhukhova ◽  
Stephanus P. du Preez ◽  
Aleksander A. Malakhov ◽  
Dmitri G. Bessarabov
Keyword(s):  
Electron Microscopy ◽  
Particle Size ◽  
Combustion Temperature ◽  
Volume Fraction ◽  
Morphological Characteristics ◽  
Al Alloy ◽  
Impregnation Method ◽  
Case Scenario ◽  
Worst Case ◽  
Thermal Distribution

In this study, a Pt/anodized aluminum oxide (AAO) catalyst was prepared by the anodization of an Al alloy (Al6082, 97.5% Al), followed by the incorporation of Pt via an incipient wet impregnation method. Then, the Pt/AAO catalyst was evaluated for autocatalytic hydrogen recombination. The Pt/AAO catalyst’s morphological characteristics were determined by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The average Pt particle size was determined to be 3.0 ± 0.6 nm. This Pt/AAO catalyst was tested for the combustion of lean hydrogen (0.5–4 vol% H2 in the air) in a recombiner section testing station. The thermal distribution throughout the catalytic surface was investigated at 3 vol% hydrogen (H2) using an infrared camera. The Al/AAO system had a high thermal conductivity, which prevents the formation of hotspots (areas where localized surface temperature is higher than an average temperature across the entire catalyst surface). In turn, the Pt stability was enhanced during catalytic hydrogen combustion (CHC). A temperature gradient over 70 mm of the Pt/AAO catalyst was 23 °C and 42 °C for catalysts with uniform and nonuniform (worst-case scenario) Pt distributions. The commercial computational fluid dynamics (CFD) code STAR-CCM+ was used to compare the experimentally observed and numerically simulated thermal distribution of the Pt/AAO catalyst. The effect of the initial H2 volume fraction on the combustion temperature and conversion of H2 was investigated. The activation energy for CHC on the Pt/AAO catalyst was 19.2 kJ/mol. Prolonged CHC was performed to assess the durability (reactive metal stability and catalytic activity) of the Pt/AAO catalyst. A stable combustion temperature of 162.8 ± 8.0 °C was maintained over 530 h of CHC. To confirm that Pt aggregation was avoided, the Pt particle size and distribution were determined by TEM before and after prolonged CHC.

scholarly journals Quality control stress test for deep learning-based diagnostic model in digital pathology

2021 ◽  
Author(s):  
Birgid Schömig-Markiefka ◽  
Alexey Pryalukhin ◽  
Wolfgang Hulla ◽  
Andrey Bychkov ◽  
Junya Fukuoka ◽  
...  
Keyword(s):  
Deep Learning ◽  
Cancer Detection ◽  
Stress Testing ◽  
Computational Analysis ◽  
Stress Test ◽  
Digital Pathology ◽  
Model Performance ◽  
Diagnostic Model ◽  
Model Accuracy ◽  
Diagnostic Models

AbstractDigital pathology provides a possibility for computational analysis of histological slides and automatization of routine pathological tasks. Histological slides are very heterogeneous concerning staining, sections’ thickness, and artifacts arising during tissue processing, cutting, staining, and digitization. In this study, we digitally reproduce major types of artifacts. Using six datasets from four different institutions digitized by different scanner systems, we systematically explore artifacts’ influence on the accuracy of the pre-trained, validated, deep learning-based model for prostate cancer detection in histological slides. We provide evidence that any histological artifact dependent on severity can lead to a substantial loss in model performance. Strategies for the prevention of diagnostic model accuracy losses in the context of artifacts are warranted. Stress-testing of diagnostic models using synthetically generated artifacts might be an essential step during clinical validation of deep learning-based algorithms.

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