Dean Fantazzini : Citation Profile


Are you Dean Fantazzini?

M. V. Lomonosov Moscow State University

11

H index

11

i10 index

355

Citations

RESEARCH PRODUCTION:

41

Articles

29

Papers

2

Chapters

RESEARCH ACTIVITY:

   17 years (2006 - 2023). See details.
   Cites by year: 20
   Journals where Dean Fantazzini has often published
   Relations with other researchers
   Recent citing documents: 27.    Total self citations: 40 (10.13 %)

MORE DETAILS IN:
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   Permalink: http://citec.repec.org/pfa92
   Updated: 2024-01-16    RAS profile: 2023-10-19    
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Relations with other researchers


Works with:

Authors registered in RePEc who have co-authored more than one work in the last five years with Dean Fantazzini.

Is cited by:

Penikas, Henry (9)

Calabrese, Raffaella (5)

Fry, John (5)

Zhang, Yaojie (4)

Havranek, Tomas (4)

Pele, Daniel Traian (4)

Menkveld, Albert (3)

Leschinski, Christian (3)

BISIÈRE, Christophe (3)

Wang, Yudong (3)

Shi, Shuping (3)

Cites to:

Zhou, Wei-Xing (43)

Patton, Andrew (22)

Hansen, Peter (17)

Kilian, Lutz (15)

Phillips, Peter (15)

Lunde, Asger (14)

Bollerslev, Tim (13)

Askitas, Nikos (13)

Zimmermann, Klaus (12)

Fry, John (11)

Engle, Robert (10)

Main data


Where Dean Fantazzini has published?


Journals with more than one article published# docs
Applied Econometrics16
JRFM3
Energy Policy3
Computational Statistics & Data Analysis2
Economics Bulletin2

Working Papers Series with more than one paper published# docs
MPRA Paper / University Library of Munich, Germany23
DEM Working Papers Series / University of Pavia, Department of Economics and Management2
Quaderni di Dipartimento / University of Pavia, Department of Economics and Quantitative Methods2
Computing in Economics and Finance 2006 / Society for Computational Economics2

Recent works citing Dean Fantazzini (2024 and 2023)


YearTitle of citing document
2023Rational Bubbles: Too Many to be True?. (2023). Sola, Martin. In: Working Papers. RePEc:aoz:wpaper:240.

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2023Cryptocurrency Valuation: An Explainable AI Approach. (2022). Zhang, Luyao ; Liu, Yulin. In: Papers. RePEc:arx:papers:2201.12893.

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2023Risks and opportunities in arbitrage and market-making in blockchain-based currency markets. Part 1 : Risks. (2023). Astarita, Vittorio. In: Papers. RePEc:arx:papers:2304.08590.

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2023Americas decoupling from China: A perspective from stock markets. (2023). Liu, Kerry. In: Economic Affairs. RePEc:bla:ecaffa:v:43:y:2023:i:1:p:32-52.

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2023Seemingly Unrelated Regression Estimation for VAR Models with Explosive Roots. (2023). Li, Qiyuan ; Chen, YE. In: Oxford Bulletin of Economics and Statistics. RePEc:bla:obuest:v:85:y:2023:i:4:p:910-937.

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2023Rational bubbles: Too many to be true?. (2023). Sola, Martin ; Psaradakis, Zacharias ; Caravello, Tomas E. In: Journal of Economic Dynamics and Control. RePEc:eee:dyncon:v:151:y:2023:i:c:s0165188923000726.

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2023Accelerated economic recovery in countries powered by renewables. (2023). McCann, Kevin S ; Costanza, Robert ; Kubiszewski, Ida ; Jackson, Andrew L ; Yang, Qiang ; Gellner, Gabriel ; Coscieme, Luca ; Donohue, Ian. In: Ecological Economics. RePEc:eee:ecolec:v:212:y:2023:i:c:s0921800923001799.

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2023An optimized nonlinear time-varying grey Bernoulli model and its application in forecasting the stock and sales of electric vehicles. (2023). Wang, Junjie ; Yang, Yingjie ; Dang, Yaoguo ; Zhou, Huimin. In: Energy. RePEc:eee:energy:v:263:y:2023:i:pc:s0360544222027578.

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2023Investing in wine, precious metals and G-7 stock markets – A co-occurrence analysis for price bubbles. (2023). Potrykus, Marcin. In: International Review of Financial Analysis. RePEc:eee:finana:v:87:y:2023:i:c:s1057521923001539.

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2023Price bubbles in the European natural gas market between 2011 and 2020. (2023). Kocaaslan, Ozge Kandemir ; Akcora, Begum. In: Resources Policy. RePEc:eee:jrpoli:v:80:y:2023:i:c:s0301420722006298.

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2023Co-explosivity versus leading effects: Evidence from crude oil and agricultural commodities. (2023). Charfeddine, Lanouar ; Belhoula, Mohamed Malek ; el Montasser, Ghassen. In: Resources Policy. RePEc:eee:jrpoli:v:81:y:2023:i:c:s0301420723000399.

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2023Price bubbles in commodity market – A single time series and panel data analysis. (2023). Potrykus, Marcin. In: The Quarterly Review of Economics and Finance. RePEc:eee:quaeco:v:87:y:2023:i:c:p:110-117.

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2023.

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2023.

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2023Rough-Set-Based Rule Induction with the Elimination of Outdated Big Data: Case of Renewable Energy Equipment Promotion. (2023). Wang, Pei-An ; Gung, Roger R ; Liang, Wen-Yau ; Huang, Chun-Che. In: Sustainability. RePEc:gam:jsusta:v:15:y:2023:i:20:p:14984-:d:1261771.

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2023Rockets and Feathers in the Gasoline Market: Evidence from South Korea. (2023). Lee, Chul-Yong ; Cha, Kyung Soo . In: Sustainability. RePEc:gam:jsusta:v:15:y:2023:i:4:p:3815-:d:1074031.

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2023A theory of predictive sales analytics adoption. (2023). Heinitz, Nicolas ; Alavi, Sascha ; Habel, Johannes. In: AMS Review. RePEc:spr:amsrev:v:13:y:2023:i:1:d:10.1007_s13162-022-00252-0.

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2023The transaction behavior of cryptocurrency and electricity consumption. (2023). Chang, Chun-Ping ; Zhao, Xinxin ; Feng, Gen-Fu ; Zheng, Mingbo. In: Financial Innovation. RePEc:spr:fininn:v:9:y:2023:i:1:d:10.1186_s40854-023-00449-7.

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2023Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms. (2023). Shaikh, Parvez Ahmed ; Khan, Faridoon. In: Future Business Journal. RePEc:spr:futbus:v:9:y:2023:i:1:d:10.1186_s43093-023-00200-9.

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2023Searching for migration: estimating Japanese migration to Europe with Google Trends data. (2023). Verhaeghe, Pieter-Paul ; Leysen, Bert. In: Quality & Quantity: International Journal of Methodology. RePEc:spr:qualqt:v:57:y:2023:i:5:d:10.1007_s11135-022-01560-0.

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2023Testing for explosive bubbles: a review. (2023). Anton, Skrobotov. In: Dependence Modeling. RePEc:vrs:demode:v:11:y:2023:i:1:p:26:n:1.

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2023Forecasting Chinas stock market volatility with shrinkage method: Can Adaptive Lasso select stronger predictors from numerous predictors?. (2023). Xu, Yongan ; Liang, Chao ; Chen, Zhonglu. In: International Journal of Finance & Economics. RePEc:wly:ijfiec:v:28:y:2023:i:4:p:3689-3699.

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2023Forecasting realized volatility of Bitcoin: The informative role of price duration. (2023). Tabche, Ibrahim ; Slim, Skander ; Karathanasopoulos, Andreas ; Osman, Mohamed ; Koubaa, Yosra. In: Journal of Forecasting. RePEc:wly:jforec:v:42:y:2023:i:7:p:1909-1929.

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2023.

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Works by Dean Fantazzini:


YearTitleTypeCited
2019Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility In: Russian Journal of Industrial Economics.
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article1
2019Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility.(2019) In: MPRA Paper.
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This paper has nother version. Agregated cites: 1
paper
2010Modelling and forecasting the global financial crisis: Initial findings using heterosckedastic log-periodic models In: Economics Bulletin.
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article1
2011Forecasting the Global Financial Crisis in the Years 2009-2010: Ex-post Analysis In: Economics Bulletin.
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article0
2009The effects of misspecified marginals and copulas on computing the value at risk: A Monte Carlo study In: Computational Statistics & Data Analysis.
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article20
2010Three-stage semi-parametric estimation of T-copulas: Asymptotics, finite-sample properties and computational aspects In: Computational Statistics & Data Analysis.
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article4
2021Asymmetry and hysteresis in the Russian gasoline market: The rationale for green energy exports In: Energy Policy.
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article1
2021Asymmetry and hysteresis in the Russian gasoline market: the rationale for green energy exports.(2021) In: MPRA Paper.
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This paper has nother version. Agregated cites: 1
paper
2011Global oil risks in the early 21st century In: Energy Policy.
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article13
2011Global oil risks in the early 21st century.(2011) In: MPRA Paper.
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This paper has nother version. Agregated cites: 13
paper
2016The oil price crash in 2014/15: Was there a (negative) financial bubble? In: Energy Policy.
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article53
2016The Oil Price Crash in 2014/15: Was There a (Negative) Financial Bubble?.(2016) In: MPRA Paper.
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This paper has nother version. Agregated cites: 53
paper
2015Forecasting German car sales using Google data and multivariate models In: International Journal of Production Economics.
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article23
2015Forecasting German Car Sales Using Google Data and Multivariate Models.(2015) In: MPRA Paper.
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This paper has nother version. Agregated cites: 23
paper
2014Reviewing electricity production cost assessments In: Renewable and Sustainable Energy Reviews.
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article29
2013Reviewing electricity production cost assessments.(2013) In: MPRA Paper.
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This paper has nother version. Agregated cites: 29
paper
2023Detecting Pump-and-Dumps with Crypto-Assets: Dealing with Imbalanced Datasets and Insiders’ Anticipated Purchases In: Econometrics.
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article0
2023Detecting Pump-and-Dumps with Crypto-Assets: Dealing with Imbalanced Datasets and Insiders’ Anticipated Purchases.(2023) In: MPRA Paper.
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This paper has nother version. Agregated cites: 0
paper
2021Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg In: Forecasting.
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article2
2021Forecasting internal migration in Russia using Google Trends: Evidence from Moscow and Saint Petersburg.(2021) In: MPRA Paper.
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This paper has nother version. Agregated cites: 2
paper
2020Does the Hashrate Affect the Bitcoin Price? In: JRFM.
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article7
2020Does the hashrate affect the bitcoin price?.(2020) In: MPRA Paper.
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This paper has nother version. Agregated cites: 7
paper
2021Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure In: JRFM.
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article1
2021Crypto-exchanges and Credit Risk: Modelling and Forecasting the Probability of Closure.(2021) In: MPRA Paper.
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This paper has nother version. Agregated cites: 1
paper
2022Crypto-Coins and Credit Risk: Modelling and Forecasting Their Probability of Death In: JRFM.
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article0
2022Crypto Coins and Credit Risk: Modelling and Forecasting their Probability of Death.(2022) In: MPRA Paper.
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This paper has nother version. Agregated cites: 0
paper
2014Forecasting the real price of oil using online search data In: International Journal of Computational Economics and Econometrics.
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article12
2008A New Approach for Firm Value and Default Probability Estimation beyond Merton Models In: Computational Economics.
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article6
2015Long Memory and Periodicity in Intraday Volatility In: The Journal of Financial Econometrics.
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article26
2012Long memory and Periodicity in Intraday Volatility.(2012) In: DEM Working Papers Series.
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This paper has nother version. Agregated cites: 26
paper
2011Fractionally Integrated Models for Volatility: A Review In: Palgrave Macmillan Books.
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chapter3
2011The Intraday Analysis of Volatility, Volume and Spreads: A Review with Applications to Futures’ Markets In: Palgrave Macmillan Books.
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chapter0
2014Proposed Coal Power Plants and Coal-To-Liquids Plants: Which Ones Survive and Why? In: DEM Working Papers Series.
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paper0
2009Small Sample Properties of Copula-GARCH Modelling: A Monte Carlo Study In: Quaderni di Dipartimento.
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paper0
2009A Copula-VAR-X Approach for Industrial Production Modelling and Forecasting In: Quaderni di Dipartimento.
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paper3
2010A copula-VAR-X approach for industrial production modelling and forecasting.(2010) In: Applied Economics.
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This paper has nother version. Agregated cites: 3
article
2014Nowcasting and Forecasting the Monthly Food Stamps Data in the US Using Online Search Data In: PLOS ONE.
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article6
2014Nowcasting and Forecasting the Monthly Food Stamps Data in the US using Online Search Data.(2014) In: MPRA Paper.
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This paper has nother version. Agregated cites: 6
paper
2020Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries In: MPRA Paper.
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paper4
2020Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries.(2020) In: Applied Econometrics.
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This paper has nother version. Agregated cites: 4
article
2020Discussing copulas with Sergey Aivazian: a memoir In: MPRA Paper.
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paper0
2022Using crypto assets pricing methods to build technical oscillators for short-term bitcoin trading In: MPRA Paper.
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paper0
2023Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models In: MPRA Paper.
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paper0
2022Forecasting oil prices with penalized regressions, variance risk premia and Google data In: MPRA Paper.
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2022Forecasting oil prices with penalized regressions, variance risk premia and Google data.(2022) In: Applied Econometrics.
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This paper has nother version. Agregated cites: 0
article
2013Hydrocarbon liquefaction: viability as a peak oil mitigation strategy In: MPRA Paper.
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paper3
2011Everything You Always Wanted to Know about Log Periodic Power Laws for Bubble Modelling but Were Afraid to Ask In: MPRA Paper.
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paper38
2013Everything you always wanted to know about log-periodic power laws for bubble modeling but were afraid to ask.(2013) In: The European Journal of Finance.
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This paper has nother version. Agregated cites: 38
article
2014Editorial for the Special Issue on Computational Methods for Russian Economic and Financial Modelling In: MPRA Paper.
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2016Everything you always wanted to know about bitcoin modelling but were afraid to ask In: MPRA Paper.
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2016Everything you always wanted to know about bitcoin modelling but were afraid to ask. I.(2016) In: Applied Econometrics.
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This paper has nother version. Agregated cites: 19
article
2019A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies In: MPRA Paper.
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2020A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies.(2020) In: Economia e Politica Industriale: Journal of Industrial and Business Economics.
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This paper has nother version. Agregated cites: 6
article
2019The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades In: MPRA Paper.
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paper2
2019The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades.(2019) In: Applied Econometrics.
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This paper has nother version. Agregated cites: 2
article
2008An Econometric Analysis of Financial Data in Risk Management In: Applied Econometrics.
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article3
2009Econometric Analysis of Financial Data in Risk Management.(2009) In: Applied Econometrics.
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This paper has nother version. Agregated cites: 3
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2008Econometric Analysis of Financial Data in Risk Management (continuation). Section III: Managing Operational Risk In: Applied Econometrics.
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article2
2008Credit Risk Management In: Applied Econometrics.
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article13
2009Credit Risk Management (Cont.) In: Applied Econometrics.
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article3
2011Analysis of multidimensional probability distributions with copula functions In: Applied Econometrics.
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article7
2011Analysis of multidimensional probability distributions with copula functions. II.(2011) In: Applied Econometrics.
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This paper has nother version. Agregated cites: 7
article
2011Analysis of multidimensional probability distributions with copula functions. III In: Applied Econometrics.
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article7
2009Economic Factors in a Model of Voting: The Case of The Netherlands, Great Britain, and Israel In: Applied Econometrics.
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article0
2012Credit default swaps and CDS-bond basis with Russian companies: a review and an analysis of the effects of the short selling ban during the second great contraction In: Applied Econometrics.
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article1
2017Everything you always wanted to know about bitcoin modelling but were afraid to ask. Part 2 In: Applied Econometrics.
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article4
2018Big Data for computing social well-being indices of the Russian population In: Applied Econometrics.
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article1
2009Enhanced credit default models for heterogeneous SME segments In: Journal of Financial Transformation.
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article3
2006A Unified Copula Framework for VaR forecasting In: Computing in Economics and Finance 2006.
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paper0
2006A new framework for firm value using copulas In: Computing in Economics and Finance 2006.
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paper0
2009Random Survival Forests Models for SME Credit Risk Measurement In: Methodology and Computing in Applied Probability.
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article28
2011Small sample properties of copula-GARCH modelling: a Monte Carlo study In: Applied Financial Economics.
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article0

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