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Alessandra Amendola

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.

    Cited by:

    1. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    2. Christian Conrad & Robert F. Engle, 2025. "Modelling Volatility Cycles: The MF2‐GARCH Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(4), pages 438-454, June.

  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. 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.
    2. Dina Chhorn, 2018. "Effect of Microfinance on Poverty and Welfare: New Evidence from 9 provinces in Cambodia," Post-Print hal-02147272, HAL.
    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. 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).

    Cited by:

    1. Salisu, Afees A. & Isah, Kazeem & Oloko, Tirimisiyu O., 2024. "Technology shocks and crude oil market connection: The role of climate change," Energy Economics, Elsevier, vol. 130(C).
    2. Bahram Adrangi & Arjun Chatrath & Saman Hatamerad & Kambiz Raffiee, 2025. "Equity Markets Volatility, Regime Dependence and Economic Uncertainty: The Case of Pacific Basin," Bulletin of Applied Economics, Risk Market Journals, vol. 12(1), pages 75-105.
    3. 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.
    4. 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.
    5. 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.
    6. Bahram Adrangi & Arjun Chatrath & Kambiz Raffiee, 2025. "Latin American Equities, Volatility Regimes, and the US Economic Policy Uncertainty," Bulletin of Applied Economics, Risk Market Journals, vol. 12(2), pages 15-44.
    7. Bahram Adrangi & Arjun Chatrath & Saman Hatamerad & Kambiz Raffiee, 2025. "Equity Markets Volatility, Regime Dependence and Economic Uncertainty: The Case of Pacific Basin," Papers 2507.05552, arXiv.org.
    8. Bahram Adrangi & Saman Hatamerad & Ales Kresta & Tomas Tichy, 2025. "Uncertainty and Volatility: Sectoral Equity Responses to Economic and Policy Shocks in the U.S," Bulletin of Applied Economics, Risk Market Journals, vol. 12(2), pages 77-110.
    9. 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 1-23, June.
    10. Tian, Yuan & Zhao, Junzhu & Zhen, Fang, 2025. "Monetary policy and oil volatility smirk," International Review of Financial Analysis, Elsevier, vol. 104(PB).
    11. 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).
    12. 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.
    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.
    14. 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.
    15. Bahram Adrangi & Ales Kresta & Kambiz Raffiee & Tomas Tichy, 2025. "Volatility in U.S. Natural Gas Prices: Exploring Market Dynamics and Economic Policy Uncertainties," Bulletin of Applied Economics, Risk Market Journals, vol. 12(2), pages 183-208.
    16. 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.
    17. 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.
    18. Priya, Pragati & Pal, Debdatta, 2024. "Does crude oil price volatility respond asymmetrically to financial shocks?," Resources Policy, Elsevier, vol. 92(C).
    19. 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.
    20. 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).
    21. 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.

  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. 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.
    2. 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.
    3. Aknouche, Abdelhakim, 2015. "Unified quasi-maximum likelihood estimation theory for stable and unstable Markov bilinear processes," MPRA Paper 69572, University Library of Munich, Germany.
    4. F. Blasques & Christian Francq & Sébastien Laurent, 2024. "Autoregressive conditional betas," Post-Print hal-04676069, HAL.
    5. 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.

  6. Amendola, Alessandra & Storti, Giuseppe, 2009. "Combination of multivariate volatility forecasts," SFB 649 Discussion Papers 2009-007, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Roland Strausz, 2010. "The Political Economy of Regulatory Risk," CESifo Working Paper Series 2953, CESifo.
    2. 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.
    3. Michael McAleer & Massimiliano Caporin, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," KIER Working Papers 815, Kyoto University, Institute of Economic Research.
    4. 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.
    5. A Clements & M Doolan, 2018. "Combining Multivariate Volatility Forecasts using Weighted Losses," NCER Working Paper Series 119, National Centre for Econometric Research.
    6. Grajek, Michał & Röller, Lars-Hendrik, 2009. "Regulation and investment in network industries: Evidence from European telecoms," SFB 649 Discussion Papers 2009-039, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Grith, Maria & Härdle, Wolfgang Karl & Park, Juhyun, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers 2009-041, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Choroś, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2009. "CDO and HAC," SFB 649 Discussion Papers 2009-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  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.

    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.
    2. 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.
    3. Giuseppe Storti & Cosimo Vitale, 2003. "Likelihood inference in BL-GARCH models," Computational Statistics, Springer, vol. 18(3), pages 387-400, September.
    4. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.

Articles

  1. Md Samsul Alam & Alessandra Amendola & Vincenzo Candila & Shahram Dehghan Jabarabadi, 2024. "Is Monetary Policy a Driver of Cryptocurrencies? Evidence from a Structural Break GARCH-MIDAS Approach," Econometrics, MDPI, vol. 12(1), pages 1-20, January.

    Cited by:

    1. Tayfun Tuncay Tosun & Erginbay Uğurlu, 2025. "The Impact of the Fed’s Monetary Policy on Cryptocurrencies: Novel Policy Implications for Central Banks," JRFM, MDPI, vol. 18(7), pages 1-14, July.
    2. Jairo Andrés Rendón, 2024. "The Bitcoin yield gap in Colombia: unraveling the influence of FX and Bitcoin convenience yields," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.

  2. 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).
    See citations under working paper version above.
  3. Luigi Aldieri & Alessandra Amendola & Vincenzo Candila, 2023. "The Impact of ESG Scores on Risk Market Performance," Sustainability, MDPI, vol. 15(9), pages 1-16, April.

    Cited by:

    1. Amendola, Alessandra & Bernardelli, Adelaide Emma & Giudici, Paolo, 2025. "Measuring inequality in the adoption of ESG scores by small and medium enterprises," International Review of Economics & Finance, Elsevier, vol. 103(C).
    2. Manpreet Kaur Makkar & Basit Ali Bhat & Mohsin Showkat & Fatma Mabrouk, 2025. "The ESG Paradox: Risk, Sustainability, and the Smokescreen Effect," Sustainability, MDPI, vol. 17(16), pages 1-17, August.
    3. Luning Tong & Maowei Chen, 2024. "The Impact of Female Director Background on the ESG Performance of Chinese Technology Firms: A Moderating Effect Based on Risk Appetite," Sustainability, MDPI, vol. 16(23), pages 1-20, December.
    4. Luis Jacob Escobar-Saldívar & Dacio Villarreal-Samaniego & Roberto J. Santillán-Salgado, 2025. "The Effects of ESG Scores and ESG Momentum on Stock Returns and Volatility: Evidence from U.S. Markets," JRFM, MDPI, vol. 18(7), pages 1-21, July.
    5. Doğan, Murat & Sayılır, Özlem & Komath, Muhammed Aslam Chelery & Çimen, Emre, 2025. "Prediction of market value of firms with corporate sustainability performance data using machine learning models," Finance Research Letters, Elsevier, vol. 77(C).
    6. Prodosh Eugene Simlai, 2025. "Non-Pecuniary Risk, ESG Ratings, and Expected Stock Returns," Sustainability, MDPI, vol. 17(16), pages 1-24, August.
    7. Bamel, Nisha & Khatri, Komal & Bamel, Umesh & Kumar, Satish, 2025. "ESG disclosure and firm performance in global south economy: Does industry profile and board independence moderate the relationship," International Review of Economics & Finance, Elsevier, vol. 100(C).
    8. Lu, Xiaomeng & Zhang, Xianjun & Guo, Fusen & Li, Feng, 2024. "Evaluating ESG Investment Profitability: From the Perspective of Sophistication in Investment Decision-Making," Finance Research Letters, Elsevier, vol. 69(PA).

  4. Alessandra Amendola & Marinella Boccia & Gianluca Mele & Luca Sensini, 2023. "Do fiscal policies affect the firms’ growth and performance? Urban versus rural area," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(1), pages 1-33, March.

    Cited by:

    1. Li, Xitong & He, Peiming & Liao, Honglin & Liu, Jindan & Chen, Litai, 2024. "Does network infrastructure construction reduce urban–rural income inequality? Based on the “Broadband China” policy," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    2. Glenn P. Jenkins & Abdallah Othman & Edna Armendariz & Anastasiya Yarygina, 2025. "Systematic Review Of Evidence On The Impact Of Tax Incentives In Latin American And Caribbean Countries," Development Discussion Papers 2025-05, JDI Executive Programs.

  5. 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. Li, Wei & Zhang, Junchao & Cao, Xiangye & Han, Wei, 2024. "Is the prediction of precious metal market volatility influenced by internet searches regarding uncertainty?," Finance Research Letters, Elsevier, vol. 62(PB).
    2. 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.
    3. Vincenzo Candila & Oguzhan Cepni & Giampiero M. Gallo & Rangan Gupta, 2024. "Influence of Local and Global Economic Policy Uncertainty on the Volatility of US State-Level Equity Returns: Evidence from a GARCH-MIDAS Approach with Shrinkage and Cluster Analysis," Working Papers 202437, University of Pretoria, Department of Economics.
    4. Jiawei Xu & Elie Bouri & Libing Fang & Rangan Gupta, 2025. "US-China Tensions and Stock Market Co-movement between the US and China: Insights from a DCC-DAGARCH-MIDAS Model," Working Papers 202522, University of Pretoria, Department of Economics.
    5. 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.
    6. 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).
    7. Marco Guerzoni & Luigi Riso & Maria Grazia Zoia, 2025. "Forecasting the Impact of Extreme Weather Events on Electricity Prices in Italy: A GARCH-MIDAS Approach with Enhanced Variable Selection," DISCE - Working Papers del Dipartimento di Politica Economica dipe0043, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    8. Zuo, Ziyue & Xiao, Xinping & Gao, Mingyun & Rao, Congjun, 2025. "Mixed-frequency fusion grey panel model for spatiotemporal prediction of photovoltaic power generation," Renewable Energy, Elsevier, vol. 248(C).
    9. 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.
    10. Liu, Liping & Lü, Zheng & Yoon, Seong-Min, 2025. "Impact of policy uncertainty on stock market volatility in the China’s low-carbon economy," Energy Economics, Elsevier, vol. 141(C).

  6. 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. Md Samsul Alam & Alessandra Amendola & Vincenzo Candila & Shahram Dehghan Jabarabadi, 2024. "Is Monetary Policy a Driver of Cryptocurrencies? Evidence from a Structural Break GARCH-MIDAS Approach," Econometrics, MDPI, vol. 12(1), pages 1-20, January.
    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.

  7. 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. Alessandra Amendola & Vincenzo Candila & Antonio Naimoli & Giuseppe Storti, 2024. "Adaptive combinations of tail-risk forecasts," Papers 2406.06235, arXiv.org.
    2. Alexandridis, Antonios K. & Panopoulou, Ekaterini & Souropanis, Ioannis, 2024. "Forecasting exchange rate volatility: An amalgamation approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 97(C).
    3. 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.
    4. 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.
    5. Hengzhen Lu & Qiujin Gao & Ling Xiao & Gurjeet Dhesi, 2024. "Forecasting EUA futures volatility with geopolitical risk: evidence from GARCH-MIDAS models," Review of Managerial Science, Springer, vol. 18(7), pages 1917-1943, July.
    6. Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2022. "Correction to: Optimal and robust combination of forecasts via constrained optimization and shrinkage," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1050-1050.
    7. Yuan Zhao & Xue Gong & Weiguo Zhang & Weijun Xu, 2025. "Stock return forecasting based on the proxy variables of category factors," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-48, December.
    8. 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.
    9. 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).
    10. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2025. "Volatility forecasting and volatility-timing strategies: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 75(C).
    11. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.
    12. 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.
    13. Yang Zhou & Chi Xie & Gang-Jin Wang & Jue Gong & You Zhu, 2025. "Forecasting cryptocurrency volatility: a novel framework based on the evolving multiscale graph neural network," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-52, December.
    14. Davide Ferrari & Alessandro Fulci & Sandra Paterlini, 2025. "Selection Confidence Sets for Equally Weighted Portfolios," Papers 2510.14988, arXiv.org.
    15. 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.

  8. 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.

  9. 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. 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.
    3. 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.

  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.

    Cited by:

    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.
    2. 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.
    3. 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.
    4. 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).
    5. 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.
    6. 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.
    7. 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 1-23, June.
    8. 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).
    9. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.
    10. Liu, Liping & Lü, Zheng & Yoon, Seong-Min, 2025. "Impact of policy uncertainty on stock market volatility in the China’s low-carbon economy," Energy Economics, Elsevier, vol. 141(C).
    11. 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.
    12. 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.
    13. 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.
    14. 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.

  11. 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. 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.
    2. 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.
    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. 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.
    5. 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.
    6. 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.

  12. 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. Kristijan Breznik & Marialuisa Restaino & Maria Prosperina Vitale & Giancarlo Ragozini, 2024. "Analyzing countries’ performances within the international student mobility program over time," Annals of Operations Research, Springer, vol. 342(3), pages 1925-1943, November.
    2. Cintia Denise Granja & Fabiana Visentin, 2024. "International Student Mobility and Academic Performance: Does Timing Matter?," Research in Higher Education, Springer;Association for Institutional Research, vol. 65(2), pages 322-353, March.
    3. Marco Ortu & Luca Frigau & Giulia Contu, 2024. "Topic based quality indexes assessment through sentiment," Computational Statistics, Springer, vol. 39(1), pages 289-311, February.
    4. 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.

  13. 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.
    See citations under working paper version above.
  14. 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.

  15. 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.
    2. Khan Jahirul Islam & Julien Picault, 2025. "One card fits all? Exploring the incidence, intensity, and extent of credit card use in Canada (1999–2019)," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 30(1), pages 1-28, March.

  16. 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. 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).
    2. Georges Tsafack & James Cataldo, 2021. "Backtesting and estimation error: value-at-risk overviolation rate," Empirical Economics, Springer, vol. 61(3), pages 1351-1396, September.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Michele Leonardo Bianchi & Giovanni De Luca & Giorgia Rivieccio, 2020. "CoVaR with volatility clustering, heavy tails and non-linear dependence," Papers 2009.10764, arXiv.org.

  17. 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. Pham, Tho & Talavera, Oleksandr & Wood, Geoffrey & Yin, Shuxing, 2022. "Quality of working environment and corporate financial distress," Finance Research Letters, Elsevier, vol. 46(PB).
    2. Fedorova, Elena & Ledyaeva, Svetlana & Drogovoz, Pavel & Nevredinov, Alexandr, 2022. "Economic policy uncertainty and bankruptcy filings," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. 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.
    4. Rémi Stellian & Jenny Paola Danna-Buitrago & David Andr�s Londo�o 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).
    5. 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.
    6. 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. 14(8), pages 45-56, June.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Simone Poli & Marco Gatti, 2024. "The relevance of cash flow information in predicting corporate bankruptcy in Italian private companies," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2024(1), pages 179-202.
    12. 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.
    13. 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.
    14. 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.
    15. 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.

  18. 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. Alessandra Amendola & Vincenzo Candila & Antonio Naimoli & Giuseppe Storti, 2024. "Adaptive combinations of tail-risk forecasts," Papers 2406.06235, arXiv.org.
    2. 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. 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.
    4. A Clements & M Doolan, 2018. "Combining Multivariate Volatility Forecasts using Weighted Losses," NCER Working Paper Series 119, National Centre for Econometric Research.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.

  19. 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.

  20. 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 & Vincenzo Candila & Antonio Naimoli & Giuseppe Storti, 2024. "Adaptive combinations of tail-risk forecasts," Papers 2406.06235, arXiv.org.
    3. Amendola, Alessandra & Storti, Giuseppe, 2009. "Combination of multivariate volatility forecasts," SFB 649 Discussion Papers 2009-007, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Vincenzo Candila & Oguzhan Cepni & Giampiero M. Gallo & Rangan Gupta, 2024. "Influence of Local and Global Economic Policy Uncertainty on the Volatility of US State-Level Equity Returns: Evidence from a GARCH-MIDAS Approach with Shrinkage and Cluster Analysis," Working Papers 202437, University of Pretoria, Department of Economics.
    5. Degiannakis, Stavros, 2018. "Multiple Days Ahead Realized Volatility Forecasting: Single, Combined and Average Forecasts," MPRA Paper 96272, University Library of Munich, Germany.
    6. Borovkova, Svetlana & Permana, Ferry J., 2009. "Implied volatility in oil markets," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2022-2039, April.
    7. 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.
    8. 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.

  21. 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. 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.
    2. 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.
    3. 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.

  22. 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.
    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. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.
    5. Chan, Wai-Sum, 2022. "On temporal aggregation of some nonlinear time-series models," Econometrics and Statistics, Elsevier, vol. 21(C), pages 38-49.
    6. 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.
    7. 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.
    8. 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.

  23. 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. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.
    2. 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.

  24. 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.
    See citations under working paper version above.

Chapters

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