scholarly journals Sample Out-of-Sample Inference Based on Wasserstein Distance

2021 ◽  
Author(s):  
Jose Blanchet ◽  
Yang Kang
Keyword(s):  
Financial Institution ◽  
Wasserstein Distance ◽  
Data Driven ◽  
Risk Exposure ◽  
Perfect Information Games ◽  
Out Of Sample ◽  
Distributionally Robust ◽  
The One ◽  
Estimated Error ◽  
The Impact

Financial institutions make decisions according to a model of uncertainty. At the same time, regulators often evaluate the risk exposure of these institutions using a model of uncertainty, which is often different from the one used by the institutions. How can one incorporate both views into a single framework? This paper provides such a framework. It quantifies the impact of the misspecification inherent to the financial institution data-driven model via the introduction of an adversarial player. The adversary replaces the institution's generated scenarios by the regulator's scenarios subject to a budget constraint and a cost that measures the distance between the two sets of scenarios (using what in statistics is known as the Wasserstein distance). This paper also harnesses statistical theory to make inference about the size of the estimated error when the sample sizes (both of the institution and the regulator) are large. The framework is explained more broadly in the context of distributionally robust optimization (a class of perfect information games, in which decisions are taken against an adversary that perturbs a baseline distribution).

scholarly journals The Impact of Advertising and R&D on Bankruptcy Survival: A Double-Edged Sword

2020 ◽  
Vol 84 (5) ◽  
pp. 22-40
Author(s):  
Niket Jindal
Keyword(s):  
Machine Learning ◽  
Research And Development ◽  
Cash Flow ◽  
The Other ◽  
Cumulative Effects ◽  
Future Cash Flow ◽  
Low Level ◽  
Out Of Sample ◽  
The One ◽  
The Impact

Advertising and research and development (R&D) benefit firms by increasing sales and shareholder value. However, when a firm is in bankruptcy, the cumulative effects of its past advertising and R&D can be a double-edged sword. On the one hand, they increase the firm’s expected future cash flow, which increases the likelihood that the bankruptcy court will decide the firm can survive. On the other hand, they increase the liquidation value of the firm’s assets, which decreases the likelihood that the bankruptcy court will decide that the firm can survive. The author argues that the ability of advertising and R&D to either increase or decrease bankruptcy survival is contingent on the influence that the firm’s suppliers have, relative to other creditors, on the bankruptcy court’s decision. Advertising and R&D increase (decrease) bankruptcy survival when suppliers have a high (low) level of influence. Empirical analyses, conducted on 1,504 bankruptcies, show that advertising (R&D) increases bankruptcy survival when at least 35%−38% (18%−21%) of the bankrupt firm’s debt has been borrowed from suppliers, whereas it decreases bankruptcy survival below this point. Out-of-sample machine learning validation shows that the ability to predict whether a bankrupt customer will survive is substantially improved by considering the firm’s advertising and R&D.

scholarly journals Performance evaluation for distributionally robust optimization with binary entries

2020 ◽  
Vol 11 (1) ◽  
pp. 1-9
Author(s):  
Shunichi Ohmori ◽  
Kazuho Yoshimoto
Keyword(s):  
Performance Evaluation ◽  
Robust Optimization ◽  
Optimization Technique ◽  
Data Driven ◽  
Optimal Decision ◽  
Distributionally Robust Optimization ◽  
Worst Case ◽  
Leibler Divergence ◽  
Out Of Sample ◽  
Distributionally Robust

We consider the data-driven stochastic programming problem with binary entries where the probability of existence of each entry is not known, instead realization of data is provided. We applied the distributionally robust optimization technique to minimize the worst-case expected cost taken over the ambiguity set based on the Kullback-Leibler divergence. We investigate the out-of-sample performance of the resulting optimal decision and analyze its dependence on the sparsity of the problem.

Bilateral counterparty risk valuation adjustment with wrong way risk on collateralized commodity counterparty

2015 ◽  
Vol 02 (01) ◽  
pp. 1550001
Author(s):  
Yifan Yang ◽  
Frank J. Fabozzi ◽  
Michele Leonardo Bianchi
Keyword(s):  
Financial Institution ◽  
Stress Test ◽  
Gaussian Copula ◽  
Risk Exposure ◽  
Counterparty Risk ◽  
Regulatory Requirement ◽  
Risk Valuation ◽  
Exposure Factor ◽  
The Impact

Basel III requires banks to include a credit value adjustment (CVA) into capital charges. Both CVA and debt value adjustment (DVA) must be included for derivatives using mark-to-market accounting. An effective method to calculate bilateral-CVA (BR-CVA) by incorporating wrong-way risk (WWR) for a collateralized counterparty is proposed which handles WWR — defined as when counterparty credit exposure increases as default probability increases — by building a trivariate Gaussian copula between the aggregate market risk exposure factor and default quality of the financial institution and counterparty. This paper extends the ordered-scenario copula model proposed in the literature. It links BR-CVA pricing and WWR, which is close to the current regulatory requirement and useful for managing a financial institution's risk. A practical example is provided. Numerical results suggest that the proposed method is efficient and robust and can easily stress test the impact of WWR in BR-CVA pricing.

scholarly journals Impact of spatially constrained sampling of temporal contact networks on the evaluation of the epidemic risk

2016 ◽  
Vol 27 (6) ◽  
pp. 941-957 ◽  
Author(s):  
CHRISTIAN L. VESTERGAARD ◽  
EUGENIO VALDANO ◽  
MATHIEU GÉNOIS ◽  
CHIARA POLETTO ◽  
VITTORIA COLIZZA ◽  
...  
Keyword(s):  
Data Driven ◽  
Data Sets ◽  
Detailed Data ◽  
Epidemic Threshold ◽  
Limited Participation ◽  
Spatial Coverage ◽  
Sirs Model ◽  
The One ◽  
The Impact ◽  
Epidemic Risk

The ability to directly record human face-to-face interactions increasingly enables the development of detailed data-driven models for the spread of directly transmitted infectious diseases at the scale of individuals. Complete coverage of the contacts occurring in a population is however generally unattainable, due for instance to limited participation rates or experimental constraints in spatial coverage. Here, we study the impact of spatially constrained sampling on our ability to estimate the epidemic risk in a population using such detailed data-driven models. The epidemic risk is quantified by the epidemic threshold of the SIRS model for the propagation of communicable diseases, i.e. the critical value of disease transmissibility above which the disease turns endemic. We verify for both synthetic and empirical data of human interactions that the use of incomplete data sets due to spatial sampling leads to the underestimation of the epidemic risk. The bias is however smaller than the one obtained by uniformly sampling the same fraction of contacts: it depends non-linearly on the fraction of contacts that are recorded, and becomes negligible if this fraction is large enough. Moreover, it depends on the interplay between the timescales of population and spreading dynamics.

Static and Dynamic Studies of Gasoline in View of its Octane Number and its Toxic Effect

2013 ◽  
Vol 12 (7) ◽  
pp. 451-459
Author(s):  
Ashraf Yehia El-Naggar ◽  
Mohamed A. Ebiad
Keyword(s):  
Toxic Effect ◽  
Aromatic Hydrocarbons ◽  
Octane Number ◽  
Liquid Fuel ◽  
Positive Impact ◽  
Hydrocarbon Composition ◽  
Different Temperatures ◽  
Different Seasons ◽  
The One ◽  
The Impact

Gasoline come primarily from petroleum cuts, it is the preferred liquid fuel in our lives. Two gasoline samples of octane numbers 91 and 95 from Saudi Arabia petrol stations were studied. This study was achieved at three different temperatures 20oC, 30oC and 50oC representing the change in temperatures of the different seasons of the year. Both the evaporated gases of light aromatic hydrocarbons (BTEX) of gasoline samples inside the tank were subjected to analyze qualitatively and quantitatively via capillary gas chromatography. The detailed hydrocarbon composition and the octane number of the studied gasoline samples were determined using detailed hydrocarbon analyzer. The idea of research is indicating the impact of light aromatic compounds in gasoline on the toxic effect of human and environment on the one hand, and on octane number of gasoline on the other hand. Although the value of octane number will be reduced but this will have a positive impact on the environment as a way to produce clean fuel.

The Development of Agritourism in the Podkarpackie Voivodeship in the Light of International and National Conditions

2017 ◽  
Vol 13 ◽  
pp. 244-261
Author(s):  
Mariola Tracz ◽  
Małgorzata Bajgier-Kowalska ◽  
Radosław Uliszak
Keyword(s):  
Development Strategy ◽  
Current State ◽  
Central Statistical ◽  
Central Statistical Office ◽  
Tourism Resources ◽  
The One ◽  
The Impact ◽  
District Offices ◽  
Socio Economic Factors

Podkarpackie Voivodeship is one of the regions of Poland in which the number of agritourism entities is very high. Therefore tourism plays a significant role in its development strategy. The aim of the paper is to identify the current state of agritourism and the changes that have occurred in the region in the years 2000–2016. Specific objectives are to determine the distribution of agritourism farms and their offer, together with a comprehensive analysis of the environmental and socio-economic factors, as well as the impact of the Slovak-Ukrainian border. The report was developed on the statistical materials from the Polish Central Statistical Office, Podkarpackie Agricultural Advisory Centre in Boguchwała and data collected from municipalities and district offices that is published on their websites, as well as through interviews with 100 owners of agritourism farms in the Podkarpackie Voivodeship. The research has shown, on the one hand, the decline in the number of farms in the region and, on the other hand, the increase in the diversity of the tourist offer of these entities. Distribution of agritourism farms is closely linked to the attractiveness of natural environment and quality of secondary tourism resources. Traditional agritourism has not yet fully used its countryside, as well as cross-border advantages of its location.

ANALISIS RISIKO OPERASIONAL MENGGUNAKAN PENDEKATAN DISTRIBUSI KERUGIAN DENGAN METODE AGREGAT

2011 ◽  
Vol 10 (2) ◽  
pp. 1
Author(s):  
Y. ARBI ◽  
R. BUDIARTI ◽  
I G. P. PURNABA
Keyword(s):  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Financial Institution ◽  
Expected Value ◽  
Insurance Companies ◽  
Limited Data ◽  
Loss Distribution Approach ◽  
Potential Loss ◽  
The Impact

Operational risk is defined as the risk of loss resulting from inadequate or failed internal processes or external problems. Insurance companies as financial institution that also faced at risk. Recording of operating losses in insurance companies, were not properly conducted so that the impact on the limited data for operational losses. In this work, the data of operational loss observed from the payment of the claim. In general, the number of insurance claims can be modelled using the Poisson distribution, where the expected value of the claims is similar with variance, while the negative binomial distribution, the expected value was bound to be less than the variance.Analysis tools are used in the measurement of the potential loss is the loss distribution approach with the aggregate method. In the aggregate method, loss data grouped in a frequency distribution and severity distribution. After doing 10.000 times simulation are resulted total loss of claim value, which is total from individual claim every simulation. Then from the result was set the value of potential loss (OpVar) at a certain level confidence.

Diversity and the Performance of Selected Financial Institutions of Asia

2018 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Shafaque Fatima ◽  
Saqib Sharif
Keyword(s):  
Financial Institutions ◽  
Positive Impact ◽  
Financial Institution ◽  
Gender Diversity ◽  
Business Case ◽  
Ordinary Least Squares ◽  
Cross Sectional ◽  
Age Diversity ◽  
The Impact ◽  
Nationality Diversity

Linking with the business case for diversity, this study examines whether the top management team (TMT) and the board of directors (BODs) diversity has a positive impact on financial institution (FI) performance in select countries of Asia least researched domain. We use data from 119 financial institutions across Asia for the year 2015, initially 1,447 institutions; however, incomplete data was excluded from final analysis. We use three proxies for diversity, that is, nationality diversity, gender diversity, and age diversity of TMT and BODs. To investigate the impact of TMT and BODs diversity, cross-sectional ordinary least-squares estimation is applied, using Return on Average Assets (ROAA%) as a measure of performance.  We find that nationality diversity and age diversity is positively and significantly related to FIs performance. Our evidence indicates that executives and board members with diverse exposure and younger age improve FIs profitability. However, there is no significant relationship between gender and FIs performance.

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