Alessandra Amendola

Personal Details

First Name:	Alessandra
Middle Name:
Last Name:	Amendola
Suffix:
RePEc Short-ID:	pam108
	[This author has chosen not to make the email address public]
	https://docenti.unisa.it/003219/home

Affiliation

Dipartimento di Scienze Economiche e Statistiche (DISES)
Università degli Studi di Salerno

Fisciano, Italy
http://www.dises.unisa.it/
RePEc:edi:dssalit (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
   • Amendola, A. & Candila, V. & Cipollini, F. & Gallo, G.M., 2024. "Doubly multiplicative error models with long- and short-run components," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).

   Cited by:

   1. Christian Conrad & Robert F. Engle, 2021. "Modelling Volatility Cycles: The (MF)2 GARCH Model," Working Paper series 21-05, Rimini Centre for Economic Analysis.

2. Amendola,Alessandra & Boccia,Marinella & Mele,Gianluca & Sensini,Luca, 2018. "Fiscal incentives and firm performance : evidence from the Dominican Republic," Policy Research Working Paper Series 8382, The World Bank.

   Cited by:

   1. Alessandra Amendola & Marinella Boccia & Gianluca Mele & Luca Sensini, 2020. "Tax Policy and Firms' Financial Choices: Empirical Evidence from the Dominican Republic," MIC 2020: The 20th Management International Conference,, University of Primorska Press.

3. Amendola,Alessandra & Boccia,Marinella & Mele,Gianluca & Sensini,Luca, 2016. "Financial access and household welfare : evidence from Mauritania," Policy Research Working Paper Series 7533, The World Bank.

   Cited by:

   1. Djoufouet WULLI FAUSTIN, 2022. "Offre des services de microfinance en Afrique subsaharienne," Journal of Academic Finance, RED research unit, university of Gabes, Tunisia, vol. 13(1), pages 31-42, June.
   2. Dina Chhorn, 2018. "Effect of Microfinance on Poverty and Welfare: New Evidence from 9 provinces in Cambodia," Post-Print hal-02147272, HAL.
      • Dina Chhorn, 2018. "Effect of Microfinance on Poverty and Welfare: New Evidence from 9 provinces in Cambodia," Cahiers du GREThA (2007-2019) 2018-12, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
   3. Nordjo, R. & Adjasi, C., 2018. "The Impact of Finance on Welfare of Smallholder Farm Household in Ghana," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277142, International Association of Agricultural Economists.
   4. Koloma, Yaya, 2019. "Microfinance et réduction de la pauvreté selon le genre au Mali : un réexamen des données de 2007-2008 [Microfinance and Poverty Reduction by Gender in Mali: A Review of 2007-2008 data]," MPRA Paper 94745, University Library of Munich, Germany.

4. Amendola, Alessandra & Candila, Vincenzo & Scognamillo, Antonio, 2015. "On the influence of the U.S. monetary policy on the crude oil price volatility," 2015 Fourth Congress, June 11-12, 2015, Ancona, Italy 207860, Italian Association of Agricultural and Applied Economics (AIEAA).
   • Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.

   Cited by:

   1. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & José Álvarez-García, 2020. "Markov-Switching Stochastic Processes in an Active Trading Algorithm in the Main Latin-American Stock Markets," Mathematics, MDPI, vol. 8(6), pages 1-22, June.
   2. Seyedeh Fatemeh Razmi & Bahareh Ramezanian Bajgiran & Seyed Mohammad Javad Razmi & Kiana Baensaf Oroumieh, 2020. "The Effects of External Uncertainties against Monetary Policy Uncertainty on IRANIAN Stock Return Volatility Using GARCH-MIDAS Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 278-281.
   3. Fehmi Özsoy & Nükhet Doðan, 2022. "Deterministic Effects of Volatility on Mixed Frequency GARCH in Means MIDAS Model: Evidence from Turkey," International Econometric Review (IER), Econometric Research Association, vol. 14(1), pages 1-20, March.
   4. Oscar V. De la Torre-Torres & Francisco Venegas-Martínez & Mᵃ Isabel Martínez-Torre-Enciso, 2021. "Enhancing Portfolio Performance and VIX Futures Trading Timing with Markov-Switching GARCH Models," Mathematics, MDPI, vol. 9(2), pages 1-22, January.
   5. Alessandra Amendola & Marinella Boccia & Vincenzo Candila & Giampiero M. Gallo, 2020. "Energy and non–energy Commodities: Spillover Effects on African Stock Markets," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(4), pages 1-7.
   6. Vincenzo Candila & Salvatore Farace, 2018. "On the Volatility Spillover between Agricultural Commodities and Latin American Stock Markets," Risks, MDPI, vol. 6(4), pages 1-16, October.
   7. T.-H. Le & Sabri Boubaker & M.T. Bui & D. Park, 2023. "On the Volatility of WTI Crude Oil Prices: A Time-Varying Approach with Stochastic Volatility," Post-Print hal-04433059, HAL.
      • Le, Thai-Ha & Boubaker, Sabri & Bui, Manh Tien & Park, Donghyun, 2023. "On the volatility of WTI crude oil prices: A time-varying approach with stochastic volatility," Energy Economics, Elsevier, vol. 117(C).
   8. Lin, Boqiang & Su, Tong, 2021. "Do China's macro-financial factors determine the Shanghai crude oil futures market?," International Review of Financial Analysis, Elsevier, vol. 78(C).
   9. Bahram Adrangi & Arjun Chatrath & Kambiz Raffiee, 2023. "S&P 500 volatility, volatility regimes, and economic uncertainty," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1362-1387, October.
   10. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
   11. Xu Gong & Mingchao Wang & Liuguo Shao, 2022. "The impact of macro economy on the oil price volatility from the perspective of mixing frequency," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4487-4514, October.
   12. Krzysztof Echaust & Małgorzata Just, 2021. "Tail Dependence between Crude Oil Volatility Index and WTI Oil Price Movements during the COVID-19 Pandemic," Energies, MDPI, vol. 14(14), pages 1-21, July.
   13. Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.

5. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.

   Cited by:

   1. Yacouba Boubacar Maïnassara & Landy Rabehasaina, 2020. "Estimation of weak ARMA models with regime changes," Statistical Inference for Stochastic Processes, Springer, vol. 23(1), pages 1-52, April.
   2. B. Lafuente-Rego & P. D’Urso & J. A. Vilar, 2020. "Robust fuzzy clustering based on quantile autocovariances," Statistical Papers, Springer, vol. 61(6), pages 2393-2448, December.
   3. Boubacar Maïnassara, Yacouba & Raïssi, Hamdi, 2015. "Semi-strong linearity testing in linear models with dependent but uncorrelated errors," Statistics & Probability Letters, Elsevier, vol. 103(C), pages 110-115.
   4. Aknouche, Abdelhakim, 2015. "Unified quasi-maximum likelihood estimation theory for stable and unstable Markov bilinear processes," MPRA Paper 69572, University Library of Munich, Germany.

6. Alessandra Amendola & Giuseppe Storti, 2009. "Combination of multivariate volatility forecasts," SFB 649 Discussion Papers SFB649DP2009-007, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

   Cited by:

   1. Roland Strausz, 2010. "The Political Economy of Regulatory Risk," CESifo Working Paper Series 2953, CESifo.
      • Roland Strausz, 2009. "The Political Economy of Regulatory Risk," SFB 649 Discussion Papers SFB649DP2009-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
   2. Michael McAleer & Massimiliano Caporin, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," KIER Working Papers 815, Kyoto University, Institute of Economic Research.
      • Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Working Papers in Economics 12/06, University of Canterbury, Department of Economics and Finance.
      • Caporin, Massimiliano & McAleer, Michael, 2014. "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
      • Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Documentos de Trabajo del ICAE 2012-06, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Apr 2012.
      • Caporin, M. & McAleer, M.J., 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Econometric Institute Research Papers EI2012-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
   3. Michał Grajek & Lars-Hendrik Röller, 2009. "Regulation and Investment in Network Industries: Evidence from European Telecoms," SFB 649 Discussion Papers SFB649DP2009-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
      • Michal Grajek & Lars-Hendrik Röller, 2009. "Regulation and investment in network industries: Evidence from European telecoms," ESMT Research Working Papers ESMT-09-004, ESMT European School of Management and Technology.
      • Michał Grajek & Lars-Hendrik Röller, 2012. "Regulation and Investment in Network Industries: Evidence from European Telecoms," Journal of Law and Economics, University of Chicago Press, vol. 55(1), pages 189-216.
   4. Caporin, M. & McAleer, M.J., 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Econometric Institute Research Papers EI 2011-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
      • Massimiliano Caporin & Michael McAleer, 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Documentos de Trabajo del ICAE 2011-20, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
      • Michael McAleer & Massimiliano Caporin, 2011. "Ranking Multivariate GARCH Models by Problem Dimension:An Empirical Evaluation," KIER Working Papers 778, Kyoto University, Institute of Economic Research.
      • Massimiliano Caporin & Michael McAleer, 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Working Papers in Economics 11/23, University of Canterbury, Department of Economics and Finance.
   5. Barbara Choroś & Wolfgang Härdle & Ostap Okhrin, 2009. "CDO and HAC," SFB 649 Discussion Papers SFB649DP2009-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
   6. Moawia Alghalith & Christos Floros & Konstantinos Gkillas, 2020. "Estimating Stochastic Volatility under the Assumption of Stochastic Volatility of Volatility," Risks, MDPI, vol. 8(2), pages 1-15, April.
   7. A Clements & M Doolan, 2018. "Combining Multivariate Volatility Forecasts using Weighted Losses," NCER Working Paper Series 119, National Centre for Econometric Research.
      • Adam Clements & Mark Bernard Doolan, 2020. "Combining multivariate volatility forecasts using weighted losses," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 628-641, July.
   8. Maria Grith & Wolfgang Härdle & Juhyun Park, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers SFB649DP2009-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

7. Giuseppe Storti & Alessandra Amendola, 2000. "A Non Linear Time Series Approach To Modelling Asymmetry In Stock Market Indexes," Computing in Economics and Finance 2000 97, Society for Computational Economics.
   • Alessandra Amendola & Giuseppe Storti, 2002. "A non-linear time series approach to modelling asymmetry in stock market indexes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(2), pages 201-216, June.

   Cited by:

   1. Mohamed Boutahar & Gilles Dufrénot & Anne Péguin-Feissolle, 2008. "A Simple Fractionally Integrated Model with a Time-varying Long Memory Parameter d t," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 225-241, April.
      • Mohamed Boutahar & Gilles Dufrénot & Anne Peguin-Feissolle, 2008. "A simple fractionally integrated model with a time-varying long memory parameter dt," Post-Print halshs-00390136, HAL.
   2. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.
   3. Giuseppe Storti & Cosimo Vitale, 2003. "BL-GARCH models and asymmetries in volatility," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 12(1), pages 19-39, February.
   4. Giuseppe Storti & Cosimo Vitale, 2003. "Likelihood inference in BL-GARCH models," Computational Statistics, Springer, vol. 18(3), pages 387-400, September.

Articles

1. Amendola, A. & Candila, V. & Cipollini, F. & Gallo, G.M., 2024. "Doubly multiplicative error models with long- and short-run components," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
   • Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
   See citations under working paper version above.
2. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2021. "Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model," Econometrics and Statistics, Elsevier, vol. 20(C), pages 12-28.

   Cited by:

   1. José Antonio Núñez-Mora & Roberto Joaquín Santillán-Salgado & Mario Iván Contreras-Valdez, 2022. "COVID Asymmetric Impact on the Risk Premium of Developed and Emerging Countries’ Stock Markets," Mathematics, MDPI, vol. 10(9), pages 1-36, April.
   2. Afees A. Salisu & Wenting Liao & Rangan Gupta & Oguzhan Cepni, 2023. "Economic Conditions and Predictability of US Stock Returns Volatility: Local Factor versus National Factor in a GARCH-MIDAS Model," Working Papers 202323, University of Pretoria, Department of Economics.
   3. Weiß, Christian H. & Ruiz Marín, Manuel & Keller, Karsten & Matilla-García, Mariano, 2022. "Non-parametric analysis of serial dependence in time series using ordinal patterns," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
   4. Haohua Li & Elie Bouri & Rangan Gupta & Libing Fang, 2023. "Return Volatility, Correlation, and Hedging of Green and Brown Stocks: Is there a Role for Climate Risk Factors?," Working Papers 202301, University of Pretoria, Department of Economics.

3. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.

   Cited by:

   1. Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2021. "Optimal and robust combination of forecasts via constrained optimization and shrinkage," LIDAM Reprints LFIN 2021014, Université catholique de Louvain, Louvain Finance (LFIN).
      • Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2022. "Optimal and robust combination of forecasts via constrained optimization and shrinkage," International Journal of Forecasting, Elsevier, vol. 38(1), pages 97-116.
      • Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2020. "Optimal and robust combination of forecasts via constrained optimization and shrinkage," LIDAM Discussion Papers LFIN 2020006, Université catholique de Louvain, Louvain Finance (LFIN).
   2. Mila Andreani & Vincenzo Candila & Giacomo Morelli & Lea Petrella, 2021. "Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach," Risks, MDPI, vol. 9(8), pages 1-20, August.
   3. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
   4. Xin Jin & Jia Liu & Qiao Yang, 2021. "Does the Choice of Realized Covariance Measures Empirically Matter? A Bayesian Density Prediction Approach," Econometrics, MDPI, vol. 9(4), pages 1-22, December.
   5. Robiyanto Robiyanto & Bayu Adi Nugroho & Andrian Dolfriandra Huruta & Budi Frensidy & Suyanto Suyanto, 2021. "Identifying the Role of Gold on Sustainable Investment in Indonesia: The DCC-GARCH Approach," Economies, MDPI, vol. 9(3), pages 1-14, August.
   6. Moawia Alghalith & Christos Floros & Konstantinos Gkillas, 2020. "Estimating Stochastic Volatility under the Assumption of Stochastic Volatility of Volatility," Risks, MDPI, vol. 8(2), pages 1-15, April.
   7. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.

4. Alessandra Amendola & Vincenzo Candila & Luca Sensini & Giuseppe Storti, 2020. "Corporate Governance, Investment, Profitability and Insolvency Risk: Evidence from Italy," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 10(4), pages 1-10.

   Cited by:

   1. Luca Sensini & Maria Vazquez, 2023. "Effects of Working Capital Management on SME Profitability: Evidence from an Emerging Economy," International Journal of Business and Management, Canadian Center of Science and Education, vol. 16(4), pages 1-85, February.
   2. Enrique Diaz & Luca Sensini, 2020. "Entrepreneurial Orientation and Firm Performance: Evidence from Argentina," International Business Research, Canadian Center of Science and Education, vol. 13(8), pages 1-47, August.
   3. Yarong Chen & Luca Sensini & Maria Vazquez, 2021. "Determinants of Leverage in Emerging Markets: Empirical Evidence," International Journal of Economics and Financial Issues, Econjournals, vol. 11(2), pages 40-46.

5. Alessandra Amendola & Marinella Boccia & Vincenzo Candila & Giampiero M. Gallo, 2020. "Energy and non–energy Commodities: Spillover Effects on African Stock Markets," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(4), pages 1-7.

   Cited by:

   1. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2021. "Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model," Econometrics and Statistics, Elsevier, vol. 20(C), pages 12-28.

6. Alessandra Amendola & Marinella Boccia & Gianluca Mele & Luca Sensini, 2020. "Fiscal Policies and Performance: Evidence from Dominican Republic firms," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(5), pages 1-16.

   Cited by:

   1. Alessandra Amendola & Marinella Boccia & Gianluca Mele & Luca Sensini, 2020. "Tax Policy and Firms' Financial Choices: Empirical Evidence from the Dominican Republic," MIC 2020: The 20th Management International Conference,, University of Primorska Press.

7. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.

   Cited by:

   1. Han, Yingwei & Li, Jie, 2023. "The impact of global economic policy uncertainty on portfolio optimization: A Black–Litterman approach," International Review of Financial Analysis, Elsevier, vol. 86(C).
   2. Xiafei Li & Dongxin Li & Xuhui Zhang & Guiwu Wei & Lan Bai & Yu Wei, 2021. "Forecasting regular and extreme gold price volatility: The roles of asymmetry, extreme event, and jump," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1501-1523, December.
   3. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & José Álvarez-García, 2020. "Markov-Switching Stochastic Processes in an Active Trading Algorithm in the Main Latin-American Stock Markets," Mathematics, MDPI, vol. 8(6), pages 1-22, June.
   4. Yu Wei & Lan Bai & Kun Yang & Guiwu Wei, 2021. "Are industry‐level indicators more helpful to forecast industrial stock volatility? Evidence from Chinese manufacturing purchasing managers index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 17-39, January.
   5. Oscar V. De la Torre-Torres & Francisco Venegas-Martínez & Mᵃ Isabel Martínez-Torre-Enciso, 2021. "Enhancing Portfolio Performance and VIX Futures Trading Timing with Markov-Switching GARCH Models," Mathematics, MDPI, vol. 9(2), pages 1-22, January.
   6. Mila Andreani & Vincenzo Candila & Giacomo Morelli & Lea Petrella, 2021. "Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach," Risks, MDPI, vol. 9(8), pages 1-20, August.
   7. Yu-Hui Liao & Yeong-Jia Goo, 2019. "Do Higher Asymmetry Threshold Effects Exist on the Gold Return Volatility during Highly Fluctuating Periods?," Sustainability, MDPI, vol. 11(18), pages 1-14, September.
   8. Amendola, A. & Candila, V. & Cipollini, F. & Gallo, G.M., 2024. "Doubly multiplicative error models with long- and short-run components," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
      • Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
   9. Alessandra Amendola & Marinella Boccia & Vincenzo Candila & Giampiero M. Gallo, 2020. "Energy and non–energy Commodities: Spillover Effects on African Stock Markets," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(4), pages 1-7.
   10. Vincenzo Candila & Salvatore Farace, 2018. "On the Volatility Spillover between Agricultural Commodities and Latin American Stock Markets," Risks, MDPI, vol. 6(4), pages 1-16, October.
   11. Marco Tronzano, 2021. "Financial Crises, Macroeconomic Variables, and Long-Run Risk: An Econometric Analysis of Stock Returns Correlations (2000 to 2019)," JRFM, MDPI, vol. 14(3), pages 1-25, March.
   12. Pan, Beier, 2023. "The asymmetric dynamics of stock–bond liquidity correlation in China: The role of macro-financial determinants," Economic Modelling, Elsevier, vol. 124(C).
   13. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.

8. Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
   • Amendola, Alessandra & Candila, Vincenzo & Scognamillo, Antonio, 2015. "On the influence of the U.S. monetary policy on the crude oil price volatility," 2015 Fourth Congress, June 11-12, 2015, Ancona, Italy 207860, Italian Association of Agricultural and Applied Economics (AIEAA).
   See citations under working paper version above.
9. Alessandra Amendola & Marinella Boccia & Gianluca Mele & Luca Sensini, 2017. "An Assessment of the Access to Credit-Welfare Nexus: Evidence from Mauritania," International Journal of Business and Management, Canadian Center of Science and Education, vol. 12(9), pages 1-77, August.

   Cited by:

   1. Mohamedou Bouasria & Arvind Ashta & Zaka Ratsimalahelo, 2020. "Bottlenecks to Financial Development, Financial Inclusion, and Microfinance: A Case Study of Mauritania," JRFM, MDPI, vol. 13(10), pages 1-28, October.

10. Alessandra Amendola & Francesco Giordano & Maria Lucia Parrella & Marialuisa Restaino, 2017. "Variable selection in high‐dimensional regression: a nonparametric procedure for business failure prediction," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(4), pages 355-368, August.

    Cited by:

    1. Maria Elisabete Neves & Carla Henriques & João Vilas, 2021. "Financial performance assessment of electricity companies: evidence from Portugal," Operational Research, Springer, vol. 21(4), pages 2809-2857, December.
    2. Fernando Zambrano Farias & María del Carmen Valls Martínez & Pedro Antonio Martín-Cervantes, 2021. "Explanatory Factors of Business Failure: Literature Review and Global Trends," Sustainability, MDPI, vol. 13(18), pages 1-26, September.
    3. Bertrand, Jean-Louis & Parnaudeau, Miia, 2019. "Understanding the economic effects of abnormal weather to mitigate the risk of business failures," Journal of Business Research, Elsevier, vol. 98(C), pages 391-402.
    4. Bertrand, Jean-Louis & Brusset, Xavier & Chabot, Miia, 2021. "Protecting franchise chains against weather risk: A design science approach," Journal of Business Research, Elsevier, vol. 125(C), pages 187-200.
    5. Juan-Pierrà Bruwer, 2018. "Do Internal Control Activities Adversely Influence the Profitability and Solvency of South African SMMEs?," Journal of Economics and Behavioral Studies, AMH International, vol. 10(1), pages 49-58.
    6. Xinyue Gu & Bo Li, 2020. "Cross‐estimation for decision selection," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(5), pages 932-958, September.

11. Alessandra Amendola & Marialuisa Restaino, 2017. "An evaluation study on students’ international mobility experience," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 525-544, March.

    Cited by:

    1. Marialuisa Restaino & Maria Prosperina Vitale & Ilaria Primerano, 2020. "Analysing International Student Mobility Flows in Higher Education: A Comparative Study on European Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(3), pages 947-965, June.

12. Alessandra Amendola & Alfonso Pellecchia & Luca Sensini, 2016. "Factors Driving the Credit Card Ownership in Italy," International Business Research, Canadian Center of Science and Education, vol. 9(6), pages 131-142, June.

    Cited by:

    1. Henriques, David, 2018. "Cards on the table: efficiency and welfare effects of the no-surcharge rule," LSE Research Online Documents on Economics 90664, London School of Economics and Political Science, LSE Library.

13. A. Amendola & V. Candila, 2016. "Evaluation of volatility predictions in a VaR framework," Quantitative Finance, Taylor & Francis Journals, vol. 16(5), pages 695-709, May.

    Cited by:

    1. Mateusz Buczyński & Marcin Chlebus, 2019. "Old-fashioned parametric models are still the best. A comparison of Value-at-Risk approaches in several volatility states," Working Papers 2019-12, Faculty of Economic Sciences, University of Warsaw.
    2. Kejin Wu & Sayar Karmakar, 2023. "A model-free approach to do long-term volatility forecasting and its variants," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-38, December.
    3. Michele Leonardo Bianchi & Giovanni De Luca & Giorgia Rivieccio, 2020. "CoVaR with volatility clustering, heavy tails and non-linear dependence," Papers 2009.10764, arXiv.org.
    4. Vincenzo Candila & Giampiero M. Gallo & Lea Petrella, 2020. "Mixed--frequency quantile regressions to forecast Value--at--Risk and Expected Shortfall," Papers 2011.00552, arXiv.org, revised Mar 2023.
    5. Georges Tsafack & James Cataldo, 2021. "Backtesting and estimation error: value-at-risk overviolation rate," Empirical Economics, Springer, vol. 61(3), pages 1351-1396, September.
    6. María de la O González & Francisco Jareño & Camalea El Haddouti, 2019. "Sector Portfolio Performance Comparison between Islamic and Conventional Stock Markets," Sustainability, MDPI, vol. 11(17), pages 1-23, August.
    7. Marchese, Malvina & Kyriakou, Ioannis & Tamvakis, Michael & Di Iorio, Francesca, 2020. "Forecasting crude oil and refined products volatilities and correlations: New evidence from fractionally integrated multivariate GARCH models," Energy Economics, Elsevier, vol. 88(C).
    8. Bianchi, Michele Leonardo & De Luca, Giovanni & Rivieccio, Giorgia, 2023. "Non-Gaussian models for CoVaR estimation," International Journal of Forecasting, Elsevier, vol. 39(1), pages 391-404.

14. Amendola, Alessandra & Restaino, Marialuisa & Sensini, Luca, 2015. "An analysis of the determinants of financial distress in Italy: A competing risks approach," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 33-41.

    Cited by:

    1. Ben Jabeur, Sami, 2017. "Bankruptcy prediction using Partial Least Squares Logistic Regression," Journal of Retailing and Consumer Services, Elsevier, vol. 36(C), pages 197-202.
    2. Marialuisa Restaino & Marco Bisogno, 2019. "A Business Failure Index Using Rank Transformation," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(1), pages 56-65, January.
    3. Mateusz Heba & Marcin Chlebus, 2020. "Impact of using industry benchmark financial ratios on performance of bankruptcy prediction logistic regression model," Working Papers 2020-30, Faculty of Economic Sciences, University of Warsaw.
    4. Şaban Çelik & Bora Aktan & Bruce Burton, 2022. "Firm dynamics and bankruptcy processes: A new theoretical model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 567-591, April.
    5. Tian, Shaonan & Yu, Yan, 2017. "Financial ratios and bankruptcy predictions: An international evidence," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 510-526.
    6. Mselmi, Nada & Lahiani, Amine & Hamza, Taher, 2017. "Financial distress prediction: The case of French small and medium-sized firms," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 67-80.
    7. Fedorova, Elena & Ledyaeva, Svetlana & Drogovoz, Pavel & Nevredinov, Alexandr, 2022. "Economic policy uncertainty and bankruptcy filings," International Review of Financial Analysis, Elsevier, vol. 82(C).
    8. A. N. Adi & Z. Baridwan & E. Mardiati, 2018. "Profitability, Liquidity, Leverage and Corporate Governance Impact on Financial Statement Fraud and Financial Distress as Intervening Variable," Вестник Киевского национального университета имени Тараса Шевченко. Экономика., Socionet;Киевский национальный университет имени Тараса Шевченко, vol. 5(200), pages 66-74.
    9. Nurul Izzaty Hasanah Azhar & Norziana Lokman & Md. Mahmudul Alam & Jamaliah Said, 2021. "Factors determining Z-score and corporate failure in Malaysian companies," Post-Print hal-03520192, HAL.
       • Nurul Izzaty Hasanah Azhar & Norziana Lokman & Md. Mahmudul Alam & Jamaliah Said, 2021. "Factors determining Z-score and corporate failure in Malaysian companies," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 21(3), pages 370-386.
       • Azhar, Nurul Izzaty Hasanah & Lokman, Norziana & Alam, Md. Mahmudul & Said, Jamaliah, 2021. "Factors Determining Z-score and Corporate Failure in Malaysian Companies," OSF Preprints ke8ab, Center for Open Science.
    10. Pham, Tho & Talavera, Oleksandr & Wood, Geoffrey & Yin, Shuxing, 2022. "Quality of working environment and corporate financial distress," Finance Research Letters, Elsevier, vol. 46(PB).
        • Tho Pham & Oleksandr Talavera & Geoffrey Wood & Shuxing Yin, 2021. "Quality of working environment and corporate financial distress," Discussion Papers 21-04, Department of Economics, University of Birmingham.
    11. Ayoola Tajudeen John & Obokoh Lawrence Ogechukwu, 2018. "Corporate Governance and Financial Distress in the Banking Industry: Nigerian Experience," Journal of Economics and Behavioral Studies, AMH International, vol. 10(1), pages 182-193.
    12. Rémi Stellian & Jenny Paola Danna-Buitrago & David Andrés Londoño Bedoya, 2018. "Fragilidad financiera empresarial y expectativas de ingresos: evidencias de un modelo multi-agentes," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 37(73), February.
    13. Maria-Lenuţa Ciupac-Ulici & Daniela-Georgeta Beju & Ioan-Alin Nistor & Flaviu Pișcoran, 2023. "The impact of the Altman score on the energy sector companies," Journal of Financial Studies, Institute of Financial Studies, vol. 8(Special-J), pages 45-56, June.
    14. Rémi Stellian & Jenny P. Danna‐Buitrago, 2020. "Financial distress, free cash flow, and interfirm payment network: Evidence from an agent‐based model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(4), pages 598-616, October.

15. Alessandra Amendola & Giuseppe Storti, 2015. "Model Uncertainty and Forecast Combination in High‐Dimensional Multivariate Volatility Prediction," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(2), pages 83-91, March.

    Cited by:

    1. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    2. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
       • Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Papers No 01/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
       • Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
    3. Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
    4. Yaojie Zhang & Yu Wei & Li Liu, 2019. "Improving forecasting performance of realized covariance with extensions of HAR-RCOV model: statistical significance and economic value," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1425-1438, September.
    5. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    6. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
       • Almeida, Daniel de & Hotta, Luiz & Ruiz Ortega, Esther, 2015. "MGARCH models: tradeoff between feasibility and flexibility," DES - Working Papers. Statistics and Econometrics. WS ws1516, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Wei Kuang, 2021. "Conditional covariance matrix forecast using the hybrid exponentially weighted moving average approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1398-1419, December.
    8. Ma, Feng & Li, Yu & Liu, Li & Zhang, Yaojie, 2018. "Are low-frequency data really uninformative? A forecasting combination perspective," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 92-108.
    9. A Clements & M Doolan, 2018. "Combining Multivariate Volatility Forecasts using Weighted Losses," NCER Working Paper Series 119, National Centre for Econometric Research.
       • Adam Clements & Mark Bernard Doolan, 2020. "Combining multivariate volatility forecasts using weighted losses," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 628-641, July.

16. Alessandra Amendola & Marialuisa Restaino & Luca Sensini, 2013. "Corporate Financial Distress And Bankruptcy: A Comparative Analysis In France, Italy And Spain," Global Economic Observer, "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences;Institute for World Economy of the Romanian Academy, vol. 1(2), pages 131-142, November.

    Cited by:

    1. Misankova Maria & Zvarikova Katarina & Kliestikova Jana, 2017. "Bankruptcy Practice in Countries of Visegrad Four," Economics and Culture, Sciendo, vol. 14(1), pages 108-118, June.

17. Amendola, Alessandra & Storti, Giuseppe, 2008. "A GMM procedure for combining volatility forecasts," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3047-3060, February.

    Cited by:

    1. Foschi, Paolo & Pascucci, Andrea, 2009. "Calibration of a path-dependent volatility model: Empirical tests," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2219-2235, April.
    2. Alessandra Amendola & Giuseppe Storti, 2009. "Combination of multivariate volatility forecasts," SFB 649 Discussion Papers SFB649DP2009-007, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Ewa Ratuszny, 2015. "Risk Modeling of Commodities using CAViaR Models, the Encompassing Method and the Combined Forecasts," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 129-156.
    4. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    5. Degiannakis, Stavros, 2018. "Multiple Days Ahead Realized Volatility Forecasting: Single, Combined and Average Forecasts," MPRA Paper 96272, University Library of Munich, Germany.
       • Degiannakis, Stavros, 2018. "Multiple days ahead realized volatility forecasting: Single, combined and average forecasts," Global Finance Journal, Elsevier, vol. 36(C), pages 41-61.
    6. Borovkova, Svetlana & Permana, Ferry J., 2009. "Implied volatility in oil markets," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2022-2039, April.

18. Amendola, Alessandra & Niglio, Marcella & Vitale, Cosimo, 2006. "The moments of SETARMA models," Statistics & Probability Letters, Elsevier, vol. 76(6), pages 625-633, March.

    Cited by:

    1. Milheiro-Oliveira, Paula, 2022. "An alternative sequential method for the state estimation of a partially observed SETAR(1) process," Statistics & Probability Letters, Elsevier, vol. 184(C).
    2. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
       • Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    3. Marian Vavra, 2012. "A Note on the Finite Sample Properties of the CLS Method of TAR Models," Birkbeck Working Papers in Economics and Finance 1206, Birkbeck, Department of Economics, Mathematics & Statistics.
    4. Chan, Wai-Sum, 2022. "On temporal aggregation of some nonlinear time-series models," Econometrics and Statistics, Elsevier, vol. 21(C), pages 38-49.
    5. Cathy Chen & Feng Liu & Richard Gerlach, 2011. "Bayesian subset selection for threshold autoregressive moving-average models," Computational Statistics, Springer, vol. 26(1), pages 1-30, March.
    6. Marcella Niglio, 2007. "Multi-step forecasts from threshold ARMA models using asymmetric loss functions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 16(3), pages 395-410, November.
    7. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.
    8. Xiaobing Zheng & Kun Liang & Qiang Xia & Dabin Zhang, 2022. "Best Subset Selection for Double-Threshold-Variable Autoregressive Moving-Average Models: The Bayesian Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1175-1201, March.

19. Amendola, Alessandra & Francq, Christian & Koopman, Siem Jan, 2006. "Special Issue on Nonlinear Modelling and Financial Econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2115-2117, December.

    Cited by:

    1. Belsley, David A. & Davidson, Russell & Kontoghiorghes, Erricos John & MacKinnon, James G. & van Dijk, Herman K., 2009. "The fourth special issue on Computational Econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1923-1924, April.
    2. Ruxandra Savonea & Mihaela Ştefănescu, 2009. "Econometric Modelling For Simulating The Economic Impact Of Structural Reforms In Romania: A Pilot Project," Romanian Economic Business Review, Romanian-American University, vol. 4(4), pages 103-110, Winter.
    3. Marcel Ausloos & Roy Cerqueti & Francesca Bartolacci & Nicola G. Castellano, 2018. "SME investment best strategies. Outliers for assessing how to optimize performance," Papers 1807.09583, arXiv.org.
       • Ausloos, Marcel & Cerqueti, Roy & Bartolacci, Francesca & Castellano, Nicola G., 2018. "SME investment best strategies. Outliers for assessing how to optimize performance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 754-765.

20. Alessandra Amendola & Marcella Niglio, 2004. "Predictor distribution and forecast accuracy of threshold models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 13(1), pages 3-14, April.

    Cited by:

    1. Błażej Mazur & Mateusz Pipień, 2012. "On the Empirical Importance of Periodicity in the Volatility of Financial Returns - Time Varying GARCH as a Second Order APC(2) Process," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(2), pages 95-116, June.
    2. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.

21. Alessandra Amendola & Giuseppe Storti, 2002. "A non-linear time series approach to modelling asymmetry in stock market indexes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(2), pages 201-216, June.
    • Giuseppe Storti & Alessandra Amendola, 2000. "A Non Linear Time Series Approach To Modelling Asymmetry In Stock Market Indexes," Computing in Economics and Finance 2000 97, Society for Computational Economics.
    See citations under working paper version above.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 6 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-ECM: Econometrics (3) 2009-04-18 2009-05-16 2020-06-22
2. NEP-ETS: Econometric Time Series (3) 2009-04-18 2009-05-16 2020-06-22
3. NEP-FOR: Forecasting (3) 2009-04-18 2009-05-16 2016-04-30
4. NEP-ORE: Operations Research (3) 2009-04-18 2009-05-16 2020-06-22
5. NEP-CBA: Central Banking (2) 2014-10-22 2016-04-30
6. NEP-ENE: Energy Economics (2) 2014-10-22 2016-04-30
7. NEP-MON: Monetary Economics (2) 2014-10-22 2016-04-30
8. NEP-DEV: Development (1) 2016-03-10
9. NEP-MAC: Macroeconomics (1) 2014-10-22

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