Güntay, Levent

Profile URL
https://hdl.handle.net/20.500.11779/2798
Name Variants
Job Title
Email Address
guntayl@mef.edu.tr
Main Affiliation
04.03. Department of Business Administration
Status
Former Staff
Website
ORCID ID
0000-0002-5532-3101
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
AAD-7362-2019

Research Topics

Domains
Social Sciences
Fields
Economics, Econometrics and FinanceBusiness, Management and Accounting
Subfields
FinanceAccountingEconomics and Econometrics
Specific Research Areas
Credit Risk and Financial Regulations
Banking stability, regulation, efficiency
Corporate Finance and Governance
Insurance and Financial Risk Management
Financial Markets and Investment Strategies

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
0
Research Products
GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
0
Research Products
QUALITY EDUCATION4
QUALITY EDUCATION
0
Research Products
GENDER EQUALITY5
GENDER EQUALITY
0
Research Products
CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
Research Products
AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
0
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
1
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
CLIMATE ACTION13
CLIMATE ACTION
0
Research Products
LIFE BELOW WATER14
LIFE BELOW WATER
0
Research Products
LIFE ON LAND15
LIFE ON LAND
0
Research Products
PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
Research Products
This researcher does not have a Scopus ID.
Documents

6

Citations

237

Go to WoS profile

Publication Collaboration

Affiliation Name Count
Federal Deposit Insurance Corporation 14
European Corporate Governance Institute 5
Centre for Economic Policy Research 5
Boston University 4
American Enterprise Institute 4
1 / 3
Data obtained from OpenAlex
Scholarly Output

3

Articles

1

Views / Downloads

82/99

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

21

Scopus Citation Count

21

Patents

0

Projects

0

WoS Citations per Publication

7.00

Scopus Citations per Publication

7.00

Open Access Source

3

Supervised Theses

0

JournalCount
Journal Of Financial Services Research1
Current Page: 1 / 1

Scopus Quartile Distribution

Competency Cloud

GCRIS Competency Cloud

Filters

2016 - 20173

Settings

Author of Publication: search.filters.isAuthorOfPublication.0eafea47-f5f0-4e5c-ac30-3a639f689f0c

Scholarly Output Search Results

Now showing 1 - 3 of 3
  • Master Term Project
    Fraud Detection In the Bitcoin Exchange Market
    (MEF Üniversitesi, Fen Bilimleri Enstitüsü, 2017) Namlı, Hüseyin; Güntay, Levent
    The trading volume and financial assets of Bitcoin are growing up, while the popularity of Bitcoin world increasing continuously in recent years. In parallel, the market becomes an attraction center for malicious people.
  • Master Term Project
    Risk Parameter Calculation Using Princpal Component Analysis of Yield Curves: the Case of Borsa İstanbul Fixed Income Market
    (MEF Üniversitesi, Fen Bilimleri Enstitüsü, 2017) Konuk, Hayrettin; Güntay, Levent
    To enable a trustworthy clearing operation, clearinghouses require conservative margins to avoid the risk of incurring a loss in case one counterparty defaults. When margin requirements for fixed income instruments are calculated, yield curves of each instrument are stressed using their first three principal components. All instruments in an account are then evaluated against each stressed yield curve and the margin requirement is calculated as the difference of the combined value of these instruments calculated with the worst of the stressed yield curves between their combined values calculated with related unstressed curves. The aim of this project is to construct a tool for applying principle component analysis (PCA) on daily zero coupon yield curve of Turkish Treasury Securities. The analysis employs a yield curve panel data set obtained consisting historical zero coupon yield curves. The data set includes interest rates of 60 different maturities varying between overnight and 15 years and 1250 daily observations between December 2010 and December 2015. The result of this analysis provides a method that could be run at the end of each clearing day to determine the major components of the yield curve such as level/height, slope and curvature that describes at least 95% of the variation in interest changes and subject to stress shocks
  • Article
    Citation - WoS: 21
    Citation - Scopus: 21
    Testing for Systemic Risk Using Stock Returns
    (Springer, 2016-05-26) Kupiec, Paul; Güntay, Levent
    The literature proposes several stock return-based measures of systemic risk but does not include a classical hypothesis tests for detecting systemic risk. Using a joint null hypothesis of Gaussian returns and the absence of systemic risk, we develop a hypothesis test statistic to detect systemic risk in stock returns data. We apply our tests on conditional value-at-risk (CoVaR) and marginal expected shortfall (MES) estimates of the 50 largest US financial institutions using daily stock return data between 2006 and 2007. The CoVaR test identifies only one institution as systemically important while the MES test identifies 27 firms including some of the financial institutions that experienced distress in the past financial crisis. We perform a simulation analysis to assess the reliability of our proposed test statistics and find that our hypothesis tests have weak power, especially tests using CoVaR. We trace the power issue to the inherent variability of the nonparametric CoVaR and MES estimators that have been proposed in the literature. These estimators have large standard errors that increase as the tail dependence in stock returns strengthens.