Manuela Pedio

Personal Details

First Name:	Manuela
Middle Name:
Last Name:	Pedio
Suffix:
RePEc Short-ID:	ppe941

Affiliation

(70%) School of Accounting and Finance
University of Bristol

Bristol, United Kingdom
http://www.bris.ac.uk/accounting-finance/
RePEc:edi:sabriuk (more details at EDIRC)

(30%) BAFFI Centre on Economics, Finance and Regulation
Università Commerciale Luigi Bocconi

Milano, Italy
http://www.bafficarefin.unibocconi.it/
RePEc:edi:cbbocit (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. Massimo Guidolin & Manuela Pedio, 2020. "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," BAFFI CAREFIN Working Papers 20145, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
   • Guidolin, Massimo & Pedio, Manuela, 2021. "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," Finance Research Letters, Elsevier, vol. 42(C).

   Cited by:

   1. Yue, Jun & Li, Yilin, 2023. "Media attention and corporate greenwashing behavior: Evidence from China," Finance Research Letters, Elsevier, vol. 55(PB).
   2. Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2024. "Google search trends and stock markets: Sentiment, attention or uncertainty?," International Review of Financial Analysis, Elsevier, vol. 91(C).
   3. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
   4. Hartvig, Áron Dénes & Pap, Áron & Pálos, Péter, 2023. "EU Climate Change News Index: Forecasting EU ETS prices with online news," Finance Research Letters, Elsevier, vol. 54(C).
   5. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).

2. Daniele Bianchi & Massimo Guidolin & Manuela Pedio, 2020. "Dissecting Time-Varying Risk Exposures in Cryptocurrency Markets," BAFFI CAREFIN Working Papers 20143, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

   Cited by:

   1. Victoria Dobrynskaya & Mikhail Dubrovskiy, 2022. "Cryptocurrencies Meet Equities: Risk Factors And Asset Pricing Relationships," HSE Working papers WP BRP 86/FE/2022, National Research University Higher School of Economics.
   2. Bianchi, Daniele & Babiak, Mykola, 2022. "On the performance of cryptocurrency funds," Journal of Banking & Finance, Elsevier, vol. 138(C).
      • Daniele Bianchi & Mykola Babiak, 2020. "On the Performance of Cryptocurrency Funds," CERGE-EI Working Papers wp672, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
      • Bianchi, Daniele & Babiak, Mykola, 2021. "On the Performance of Cryptocurrency Funds," Working Paper Series 408, Sveriges Riksbank (Central Bank of Sweden).
   3. Anyfantaki, Sofia & Arvanitis, Stelios & Topaloglou, Nikolas, 2021. "Diversification benefits in the cryptocurrency market under mild explosivity," European Journal of Operational Research, Elsevier, vol. 295(1), pages 378-393.
   4. Serdar Neslihanoglu, 2021. "Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the pre-COVID-19 and COVID-19 periods," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.

3. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Switching Nelson-Siegel Models," BAFFI CAREFIN Working Papers 19106, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

   Cited by:

   1. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
   2. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
      • Eo, Yunjong & Kang, Kyu Ho, 2019. "The Effects of Conventional and Unconventional Monetary Policy on Forecasting the Yield Curve," Working Papers 2019-08, University of Sydney, School of Economics, revised Nov 2019.
   3. 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.
   4. Zihao Wang & Kun Li & Steve Q. Xia & Hongfu Liu, 2021. "Economic Recession Prediction Using Deep Neural Network," Papers 2107.10980, arXiv.org.
   5. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.

4. Massimo Guidolin & Francesco Melloni & Manuela Pedio, 2019. "A Markov Switching Cointegration Analysis of the CDS-Bond Basis Puzzle," BAFFI CAREFIN Working Papers 19121, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

   Cited by:

   1. Giacomo Bulfone & Roberto Casarin & Francesco Ravazzolo, 2021. "Corporate CDS spreads from the Eurozone crisis to COVID-19 pandemic: A Bayesian Markov switching model," Working Paper series 21-09, Rimini Centre for Economic Analysis.
   2. Baltodano López Ovielt & Bulfone Giacomo & Casarin Roberto & Ravazzolo Francesco, 2024. "Modeling Corporate CDS Spreads Using Markov Switching Regressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 271-292, April.
   3. Kato, Kensuke & Nakamura, Nobuhiro, 2023. "Cointegration analysis of hazard rates and CDSs: Applications to pairs trading strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 612(C).

5. Massimo Guidolin & Manuela Pedio & Alessandra tosi, 2019. "Time-Varying Price Discovery in Sovereign Credit Markets," BAFFI CAREFIN Working Papers 19120, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
   • Guidolin, Massimo & Pedio, Manuela & Tosi, Alessandra, 2021. "Time-varying price discovery in sovereign credit markets," Finance Research Letters, Elsevier, vol. 38(C).

   Cited by:

   1. Sebastiano Michele Zema & Francesco Cordoni, 2023. "A non-Normal framework for price discovery: The independent component based information shares measure," LEM Papers Series 2023/03, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
   2. Zubair Ali Raja & William J. Procasky & Renee Oyotode-Adebile, 2020. "The Relative Role of Sovereign CDS and Bond Markets in Efficiently Pricing Emerging Market Sovereign Credit Risk," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 19(3), pages 296-325, December.
   3. Zema, Sebastiano Michele, 2022. "Directed acyclic graph based information shares for price discovery," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
   4. Papavassiliou, Vassilios G. & Kinateder, Harald, 2021. "Information shares and market quality before and during the European sovereign debt crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).

6. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Effects on the Riskless Yield Curve with Regime Switching Nelson†Siegel Models," Working Papers 639, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.

   Cited by:

   1. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
   2. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
      • Eo, Yunjong & Kang, Kyu Ho, 2019. "The Effects of Conventional and Unconventional Monetary Policy on Forecasting the Yield Curve," Working Papers 2019-08, University of Sydney, School of Economics, revised Nov 2019.
   3. 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.
   4. Shang, Fei, 2022. "The effect of uncertainty on the sensitivity of the yield curve to monetary policy surprises," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
   5. Zihao Wang & Kun Li & Steve Q. Xia & Hongfu Liu, 2021. "Economic Recession Prediction Using Deep Neural Network," Papers 2107.10980, arXiv.org.
   6. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.

7. Alexander Berglund & Massimo Guidolin & Manuela Pedio, 2018. "Monetary Policy after the Crisis: Threat or Opportunity to Hedge Funds' Alphas?," BAFFI CAREFIN Working Papers 1884, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

   Cited by:

   1. Massimo Guidolin & Alexei Orlov, 2020. "Are Unconventional Monetary Policies a Priced Risk Factor for Hedge Fund Strategies?," BAFFI CAREFIN Working Papers 20146, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

8. Massimo Guidolin & Manuela Pedio, 2018. "Forecasting Commodity Futures Returns: An Economic Value Analysis of Macroeconomic vs. Specific Factors," BAFFI CAREFIN Working Papers 1886, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

   Cited by:

   1. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2020. "Forecasting commodity prices out-of-sample: Can technical indicators help?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 666-683.
   2. Massimo Guidolin & Manuela Pedio, 2020. "Distilling Large Information Sets to Forecast Commodity Returns: Automatic Variable Selection or HiddenMarkov Models?," BAFFI CAREFIN Working Papers 20140, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

9. Marta Giampietro & Massimo Guidolin & Manuela Pedio, 2017. "Estimating Stochastic Discount Factor Models with Hidden Regimes: Applications to Commodity Pricing," Working Papers 614, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
   • Giampietro, Marta & Guidolin, Massimo & Pedio, Manuela, 2018. "Estimating stochastic discount factor models with hidden regimes: Applications to commodity pricing," European Journal of Operational Research, Elsevier, vol. 265(2), pages 685-702.

   Cited by:

   1. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2020. "Forecasting commodity prices out-of-sample: Can technical indicators help?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 666-683.
   2. Massimo Guidolin & Manuela Pedio, 2021. "Forecasting commodity futures returns with stepwise regressions: Do commodity-specific factors help?," Annals of Operations Research, Springer, vol. 299(1), pages 1317-1356, April.
   3. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
   4. Nguyen, Quynh Nga & Aboura, Sofiane & Chevallier, Julien & Zhang, Lyuyuan & Zhu, Bangzhu, 2020. "Local Gaussian correlations in financial and commodity markets," European Journal of Operational Research, Elsevier, vol. 285(1), pages 306-323.
   5. Shirui Wang & Tianyang Zhang, 2024. "Predictability of commodity futures returns with machine learning models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 302-322, February.
   6. Massimo Guidolin & Manuela Pedio, 2020. "Distilling Large Information Sets to Forecast Commodity Returns: Automatic Variable Selection or HiddenMarkov Models?," BAFFI CAREFIN Working Papers 20140, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
   7. Massimo Guidolin & Manuela Pedio, 2018. "Forecasting Commodity Futures Returns: An Economic Value Analysis of Macroeconomic vs. Specific Factors," BAFFI CAREFIN Working Papers 1886, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
   8. P. Zhukov E. & П. Жуков Е., 2019. "Новые модели анализа изменений стоимости компании, основанные на стохастических ставках дисконтирования // New Models for Analyzing Changes in Company Value Based on Stochastic Discount Rates," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 23(3), pages 35-48.
   9. Schücking, Maximilian & Jochem, Patrick, 2020. "Two-stage stochastic program optimizing the total cost of ownership of electric vehicles in commercial fleets," Working Paper Series in Production and Energy 50, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
   10. Schücking, Maximilian & Jochem, Patrick, 2021. "Two-stage stochastic program optimizing the cost of electric vehicles in commercial fleets," Applied Energy, Elsevier, vol. 293(C).
   11. Liu, Chunbo & Zhang, Xuan & Zhou, Zhiping, 2023. "Are commodity futures a hedge against inflation? A Markov-switching approach," International Review of Financial Analysis, Elsevier, vol. 86(C).

10. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2015. "The Impact of Monetary Policy on Corporate Bonds under Regime Shifts," Working Papers 562, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    • Guidolin, Massimo & Orlov, Alexei G. & Pedio, Manuela, 2017. "The impact of monetary policy on corporate bonds under regime shifts," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 176-202.

    Cited by:

    1. Wang, Cindy S.H. & Fan, Rui & Xie, Yiqiang, 2023. "Market systemic risk, predictability and macroeconomics news," Finance Research Letters, Elsevier, vol. 56(C).
    2. Massimo Guidolin & Manuela Pedio, 2019. "Does the Cost of Private Debt Respond to Monetary Policy? Heteroskedasticity-Based Identification in a Model with Regimes," BAFFI CAREFIN Working Papers 19118, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
       • Massimo Guidolin & Valentina Massagli & Manuela Pedio, 2021. "Does the cost of private debt respond to monetary policy? Heteroskedasticity-based identification in a model with regimes," The European Journal of Finance, Taylor & Francis Journals, vol. 27(18), pages 1804-1833, December.
       • Massimo Guidolin & Valentina Massagli & Manuela Pedio, 2021. "Does the Cost of Private Debt Respond to Monetary Policy? Heteroskedasticity-Based Identification in a Model with Regimes," Working Papers 676, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    3. Chen, Louisa & Verousis, Thanos & Wang, Kai & Zhou, Zhiping, 2023. "Financial stress and commodity price volatility," Energy Economics, Elsevier, vol. 125(C).
    4. Lin, Saiyan & Chen, Rongda & Lv, Zhihong & Zhou, Tianqing & Jin, Chenglu, 2019. "Integrated measurement of liquidity risk and market risk of company bonds based on the optimal Copula model," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    5. Jonathan Fletcher & Elizabeth Littlejohn & Andrew Marshall, 2023. "Exploring the performance of US international bond mutual funds," The Financial Review, Eastern Finance Association, vol. 58(4), pages 765-782, November.
    6. Hristov, Nikolay & Hülsewig, Oliver, 2017. "Unexpected loan losses and bank capital in an estimated DSGE model of the euro area," Journal of Macroeconomics, Elsevier, vol. 54(PB), pages 161-186.
       • Nikolay Hristov & Oliver Hülsewig, 2016. "Unexpected Loan Losses and Bank Capital in an Estimated DSGE Model of the Euro Area," CESifo Working Paper Series 6160, CESifo.
    7. Hattori, Takahiro & Yoshida, Jiro, 2023. "The impact of Bank of Japan’s exchange-traded fund purchases," Journal of Financial Stability, Elsevier, vol. 65(C).
    8. Du, Ke & Fu, Yishu & Qin, Zhenjiang & Zhang, Shuoxun, 2020. "Regime shift, speculation, and stock price," Research in International Business and Finance, Elsevier, vol. 52(C).
    9. Nozawa, Yoshio & Qiu, Yancheng, 2021. "Corporate bond market reactions to quantitative easing during the COVID-19 pandemic," Journal of Banking & Finance, Elsevier, vol. 133(C).

11. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2014. "Understanding the Impact of Monetary Policy Shocks on the Corporate Bond Market in Good and Bad Times: A Markov Switching Model," BAFFI CAREFIN Working Papers 1623, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

    Cited by:

    1. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2015. "The Impact of Monetary Policy on Corporate Bonds under Regime Shifts," Working Papers 562, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
       • Guidolin, Massimo & Orlov, Alexei G. & Pedio, Manuela, 2017. "The impact of monetary policy on corporate bonds under regime shifts," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 176-202.
    2. Rhea Choudhary, 2022. "Analysing the spillover effects of the South African Reserve Banks bond purchase programme," Working Papers 11025, South African Reserve Bank.
    3. Sensarma, Rudra & Bhattacharyya, Indranil, 2016. "The impact of monetary policy on corporate bonds in India," Journal of Policy Modeling, Elsevier, vol. 38(3), pages 587-602.
    4. Rhea Choudhary, 2022. "AnalysingthespillovereffectsoftheSouthAfricanReserveBanksbondpurchaseprogramme," Working Papers 11039, South African Reserve Bank.

Articles

1. Guidolin, Massimo & Pedio, Manuela, 2021. "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," Finance Research Letters, Elsevier, vol. 42(C).
   • Massimo Guidolin & Manuela Pedio, 2020. "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," BAFFI CAREFIN Working Papers 20145, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
   See citations under working paper version above.
2. Massimo Guidolin & Manuela Pedio, 2021. "Forecasting commodity futures returns with stepwise regressions: Do commodity-specific factors help?," Annals of Operations Research, Springer, vol. 299(1), pages 1317-1356, April.

   Cited by:

   1. Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
      • Haase, Felix & Neuenkirch, Matthias, 2023. "Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US," International Journal of Forecasting, Elsevier, vol. 39(2), pages 587-605.
      • Felix Haase & Matthias Neuenkirch, 2021. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," CESifo Working Paper Series 8828, CESifo.
      • Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Working Paper Series 2020-03, University of Trier, Research Group Quantitative Finance and Risk Analysis.
   2. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
   3. Julia S. Mehlitz & Benjamin R. Auer, 2021. "Time‐varying dynamics of expected shortfall in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 895-925, June.
   4. Shirui Wang & Tianyang Zhang, 2024. "Predictability of commodity futures returns with machine learning models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 302-322, February.
   5. Zhang, Yue-Jun & Zhang, Han, 2023. "Volatility forecasting of crude oil futures market: Which structural change-based HAR models have better performance?," International Review of Financial Analysis, Elsevier, vol. 85(C).
   6. Yue-Jun Zhang & Han Zhang & Rangan Gupta, 2023. "A new hybrid method with data-characteristic-driven analysis for artificial intelligence and robotics index return forecasting," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
   7. Krzysztof Drachal, 2022. "Forecasting the Crude Oil Spot Price with Bayesian Symbolic Regression," Energies, MDPI, vol. 16(1), pages 1-29, December.
   8. Xiu Wu & Jinting Zhang & Daojun Zhang, 2021. "Explore Associations between Subjective Well-Being and Eco-Logical Footprints with Fixed Effects Panel Regressions," Land, MDPI, vol. 10(9), pages 1-15, September.

3. Guidolin, Massimo & Pedio, Manuela & Tosi, Alessandra, 2021. "Time-varying price discovery in sovereign credit markets," Finance Research Letters, Elsevier, vol. 38(C).
   • Massimo Guidolin & Manuela Pedio & Alessandra tosi, 2019. "Time-Varying Price Discovery in Sovereign Credit Markets," BAFFI CAREFIN Working Papers 19120, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
   See citations under working paper version above.
4. Alexander Berglund & Massimo Guidolin & Manuela Pedio, 2020. "Monetary policy after the crisis: A threat to hedge funds' alphas?," Journal of Asset Management, Palgrave Macmillan, vol. 21(3), pages 219-238, May.

   Cited by:

   1. Aiken, Adam L. & Kang, Minjeong, 2023. "Hedge fund manager timing and selectivity skill over time. A holdings-based estimate," Finance Research Letters, Elsevier, vol. 58(PB).

5. Guidolin, Massimo & Pedio, Manuela, 2019. "Forecasting and trading monetary policy effects on the riskless yield curve with regime switching Nelson–Siegel models," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.

   Cited by:

   1. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
   2. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
      • Eo, Yunjong & Kang, Kyu Ho, 2019. "The Effects of Conventional and Unconventional Monetary Policy on Forecasting the Yield Curve," Working Papers 2019-08, University of Sydney, School of Economics, revised Nov 2019.
   3. 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.
   4. Shang, Fei, 2022. "The effect of uncertainty on the sensitivity of the yield curve to monetary policy surprises," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
   5. Zihao Wang & Kun Li & Steve Q. Xia & Hongfu Liu, 2021. "Economic Recession Prediction Using Deep Neural Network," Papers 2107.10980, arXiv.org.
   6. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.

6. Guidolin, Massimo & Hansen, Erwin & Pedio, Manuela, 2019. "Cross-asset contagion in the financial crisis: A Bayesian time-varying parameter approach," Journal of Financial Markets, Elsevier, vol. 45(C), pages 83-114.

   Cited by:

   1. Samitas, Aristeidis & Kampouris, Elias & Polyzos, Stathis, 2022. "Covid-19 pandemic and spillover effects in stock markets: A financial network approach," International Review of Financial Analysis, Elsevier, vol. 80(C).
   2. Si, Deng-Kui & Li, Xiao-Lin & Xu, XuChuan & Fang, Yi, 2021. "The risk spillover effect of the COVID-19 pandemic on energy sector: Evidence from China," Energy Economics, Elsevier, vol. 102(C).
   3. Li, Yueshan & Chen, Shoudong & Sensoy, Ahmet & Wang, Lu, 2024. "Over-expected shocks and financial market security: Evidence from China's markets," Research in International Business and Finance, Elsevier, vol. 68(C).
   4. Elżbieta Kacperska & Jakub Kraciuk, 2021. "Changes in the Stock Market of Food Industry Companies during the COVID-19 Pandemic—A Comparative Analysis of Poland and Germany," Energies, MDPI, vol. 14(23), pages 1-17, November.
   5. Agnello, Luca & Castro, Vítor & Sousa, Ricardo M., 2022. "On the international co-movement of natural interest rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
   6. Alexandr Patalaha & Maria A. Shchepeleva, 2023. "Bank Crisis Management Policies and the New Instability," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 43-60, December.
   7. Chibane, Messaoud & Gabriel, Amadeus & Giménez Roche, Gabriel A., 2022. "Credit booms and crisis-emergent asset comovement: The problem of latent correlation," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 270-279.
   8. Golitsis, Petros & Gkasis, Pavlos & Bellos, Sotirios K., 2022. "Dynamic spillovers and linkages between gold, crude oil, S&P 500, and other economic and financial variables. Evidence from the USA," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
   9. Hadhri, Sinda, 2023. "News-based economic policy uncertainty and financial contagion: An international evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 63-76.
   10. Imen Bedoui-Belghith & Slaheddine Hallara & Faouzi Jilani, 2023. "Crisis transmission degree measurement under crisis propagation model," SN Business & Economics, Springer, vol. 3(1), pages 1-27, January.
   11. Wan, Xiaoyuan & Zhang, Jiachen, 2024. "Systematic COVID risk, idiosyncratic COVID risk and stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
   12. Xiaoyang Chen & Liguo Zhou & Lin Wang & Yuelong Zheng, 2023. "Risk spillover in China’s real estate industry chain: a DCC-EGARCH-ΔCoVaR model," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
   13. Wang, Haiying & Yuan, Ying & Li, Yiou & Wang, Xunhong, 2021. "Financial contagion and contagion channels in the forex market: A new approach via the dynamic mixture copula-extreme value theory," Economic Modelling, Elsevier, vol. 94(C), pages 401-414.
   14. Shen, Junjie & Huang, Shupei, 2022. "Copper cross-market volatility transition based on a coupled hidden Markov model and the complex network method," Resources Policy, Elsevier, vol. 75(C).
   15. Polyzos, Stathis & Samitas, Aristeidis & Katsaiti, Marina-Selini, 2020. "Who is unhappy for Brexit? A machine-learning, agent-based study on financial instability," International Review of Financial Analysis, Elsevier, vol. 72(C).
   16. Bitetto, Alessandro & Cerchiello, Paola & Mertzanis, Charilaos, 2023. "Measuring financial soundness around the world: A machine learning approach," International Review of Financial Analysis, Elsevier, vol. 85(C).
   17. Daniele Bianchi & Massimo Guidolin & Manuela Pedio, 2020. "Dissecting Time-Varying Risk Exposures in Cryptocurrency Markets," BAFFI CAREFIN Working Papers 20143, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
   18. Ur Rehman, Mobeen & Al Rababa'a, Abdel Razzaq & El-Nader, Ghaith & Alkhataybeh, Ahmad & Vo, Xuan Vinh, 2022. "Modelling the quantile cross-coherence between exchange rates: Does the COVID-19 pandemic change the interlinkage structure?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
   19. Yuntong Liu & Yu Wei & Yi Liu & Wenjuan Li, 2020. "Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, December.

7. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2018. "How good can heuristic-based forecasts be? A comparative performance of econometric and heuristic models for UK and US asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 18(1), pages 139-169, January.

   Cited by:

   1. Lee, Chien-Chiang & Chen, Mei-Ping, 2021. "The effects of investor attention and policy uncertainties on cross-border country exchange-traded fund returns," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 830-852.
   2. Huthaifa Alqaralleh & Ahmad Al-Majali & Abeer Alsarayrh, 2021. "Analyzing the Dynamics Between Macroeconomic Variables and the Stock Indexes of Emerging Markets, Using Non-linear Methods," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(3), pages 193-204, May.
   3. Massimo Guidolin & Manuela Pedio, 2020. "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," BAFFI CAREFIN Working Papers 20145, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
      • Guidolin, Massimo & Pedio, Manuela, 2021. "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," Finance Research Letters, Elsevier, vol. 42(C).
   4. Hartvig, Áron Dénes & Pap, Áron & Pálos, Péter, 2023. "EU Climate Change News Index: Forecasting EU ETS prices with online news," Finance Research Letters, Elsevier, vol. 54(C).

8. Giampietro, Marta & Guidolin, Massimo & Pedio, Manuela, 2018. "Estimating stochastic discount factor models with hidden regimes: Applications to commodity pricing," European Journal of Operational Research, Elsevier, vol. 265(2), pages 685-702.
   • Marta Giampietro & Massimo Guidolin & Manuela Pedio, 2017. "Estimating Stochastic Discount Factor Models with Hidden Regimes: Applications to Commodity Pricing," Working Papers 614, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
   See citations under working paper version above.
9. Guidolin, Massimo & Pedio, Manuela, 2017. "Identifying and measuring the contagion channels at work in the European financial crises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 117-134.

   Cited by:

   1. Silvio Contessi & Pierangelo De Pace & Massimo Guidolin, 2020. "Mildly Explosive Dynamics in U.S. Fixed Income Markets," Working Papers 667, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
      • Contessi, Silvio & De Pace, Pierangelo & Guidolin, Massimo, "undated". "Mildly Explosive Dynamics in U.S. Fixed Income Markets," Economics Department, Working Paper Series 1001, Economics Department, Pomona College, revised 12 Feb 2020.
      • Contessi, Silvio & De Pace, Pierangelo & Guidolin, Massimo, 2020. "Mildly explosive dynamics in U.S. fixed income markets," European Journal of Operational Research, Elsevier, vol. 287(2), pages 712-724.
      • Silvio Contessi & Pierangelo De Pace & Massimo Guidolin, 2017. "Mildly Explosive Dynamics in U.S. Fixed Income Markets," Globalization Institute Working Papers 324, Federal Reserve Bank of Dallas.
   2. Starkey, Christopher Michael & Tsafack, Georges, 2023. "Measuring financial contagion: Dealing with the volatility Bias in the correlation dynamics," International Review of Financial Analysis, Elsevier, vol. 90(C).
   3. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," International Journal of Forecasting, Elsevier, vol. 35(1), pages 25-44.
      • Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," Working Paper Series in Economics 123, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
   4. Marina Yu. Malkina, 2024. "Financial Contagion of the Commodity Markets from the Stock Market during Pandemic and New Sanctions Shocks," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 23(2), pages 452-475.
   5. Marina Yu. Malkina & Anton O. Ovcharov, 2022. "Financial Contagion of Russian Companies from the Oil Market under the Influence of Sanctions and Pandemic Shock," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 4, pages 8-28, August.
   6. Chen, Louisa & Verousis, Thanos & Wang, Kai & Zhou, Zhiping, 2023. "Financial stress and commodity price volatility," Energy Economics, Elsevier, vol. 125(C).
   7. Alexakis, Christos & Pappas, Vasileios, 2018. "Sectoral dynamics of financial contagion in Europe - The cases of the recent crises episodes," Economic Modelling, Elsevier, vol. 73(C), pages 222-239.
   8. Guidolin, Massimo & Hansen, Erwin & Pedio, Manuela, 2019. "Cross-asset contagion in the financial crisis: A Bayesian time-varying parameter approach," Journal of Financial Markets, Elsevier, vol. 45(C), pages 83-114.
   9. Tihana Skrinjaric, 2022. "Macroeconomic effects of systemic stress: a rolling spillover index approach," Public Sector Economics, Institute of Public Finance, vol. 46(1), pages 109-140.
   10. Roman Garcia & Dimitri Lorenzani & Daniel Monteiro & Francesco Perticari & Bořek Vašíček & Lukas Vogel, 2021. "Financial Spillover and Contagion Risks in the Euro Area in 2007-2019," European Economy - Discussion Papers 137, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
   11. Jiang, Hai & Tang, Shenfeng & Li, Lifang & Xu, Fangming & Di, Qian, 2022. "Re-examining the Contagion Channels of Global Financial Crises: Evidence from the Twelve Years since the US Subprime Crisis," Research in International Business and Finance, Elsevier, vol. 60(C).
   12. Ahmed, Walid M.A., 2021. "Stock market reactions to upside and downside volatility of Bitcoin: A quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).

10. Guidolin, Massimo & Orlov, Alexei G. & Pedio, Manuela, 2017. "The impact of monetary policy on corporate bonds under regime shifts," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 176-202.
    • Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2015. "The Impact of Monetary Policy on Corporate Bonds under Regime Shifts," Working Papers 562, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    See citations under working paper version above.
11. Guidolin, Massimo & Orlov, Alexei G. & Pedio, Manuela, 2014. "Unconventional monetary policies and the corporate bond market," Finance Research Letters, Elsevier, vol. 11(3), pages 203-212.

    Cited by:

    1. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2015. "The Impact of Monetary Policy on Corporate Bonds under Regime Shifts," Working Papers 562, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
       • Guidolin, Massimo & Orlov, Alexei G. & Pedio, Manuela, 2017. "The impact of monetary policy on corporate bonds under regime shifts," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 176-202.
    2. Österholm, Pär, 2018. "The relation between treasury yields and corporate bond yield spreads in Australia: Evidence from VARs," Finance Research Letters, Elsevier, vol. 24(C), pages 186-192.
    3. Jonathan Fletcher & Elizabeth Littlejohn & Andrew Marshall, 2023. "Exploring the performance of US international bond mutual funds," The Financial Review, Eastern Finance Association, vol. 58(4), pages 765-782, November.
    4. Díaz, Antonio & Escribano, Ana, 2022. "Liquidity dimensions in the U.S. corporate bond market," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 1163-1179.

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 14 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-FOR: Forecasting (6) 2017-01-08 2018-09-24 2019-01-21 2019-07-22 2019-11-11 2020-07-27. Author is listed
2. NEP-MON: Monetary Economics (6) 2015-11-15 2018-09-24 2019-01-21 2019-07-22 2019-09-30 2021-03-01. Author is listed
3. NEP-CBA: Central Banking (5) 2018-09-24 2019-01-21 2019-07-22 2019-09-30 2021-03-01. Author is listed
4. NEP-FMK: Financial Markets (4) 2017-01-08 2018-09-24 2019-11-11 2020-08-10
5. NEP-MAC: Macroeconomics (4) 2015-11-15 2019-07-22 2019-11-11 2020-08-10
6. NEP-ORE: Operations Research (4) 2019-09-30 2020-07-13 2020-07-27 2020-08-10
7. NEP-BIG: Big Data (2) 2020-07-13 2020-07-27
8. NEP-RMG: Risk Management (2) 2020-07-27 2020-08-10
9. NEP-UPT: Utility Models and Prospect Theory (2) 2019-11-11 2020-07-13
10. NEP-EEC: European Economics (1) 2019-11-11
11. NEP-PAY: Payment Systems and Financial Technology (1) 2020-08-10
12. NEP-URE: Urban and Real Estate Economics (1) 2019-09-30

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