Details about Daniele Bianchi

Access statistics for papers by Daniele Bianchi.

Last updated 2023-12-06. Update your information in the RePEc Author Service.

Short-id: pbi325

Working Papers

2023

1. Variational inference for large Bayesian vector autoregressions
   Papers, arXiv.org View citations (1)

2022

2. Smoothing volatility targeting
   Papers, arXiv.org
3. Trading Volume and Liquidity Provision in Cryptocurrency Markets
   CERGE-EI Working Papers, The Center for Economic Research and Graduate Education - Economics Institute, Prague View citations (8)
   Also in Working Paper Series, Sveriges Riksbank (Central Bank of Sweden) (2022) View citations (2)
   See also Journal Article Trading volume and liquidity provision in cryptocurrency markets, Journal of Banking & Finance, Elsevier (2022) View citations (2) (2022)

2021

4. A Factor Model for Cryptocurrency Returns
   CERGE-EI Working Papers, The Center for Economic Research and Graduate Education - Economics Institute, Prague View citations (3)
5. On the Performance of Cryptocurrency Funds
   Working Paper Series, Sveriges Riksbank (Central Bank of Sweden) View citations (2)
   Also in CERGE-EI Working Papers, The Center for Economic Research and Graduate Education - Economics Institute, Prague (2020) View citations (4)
   See also Journal Article On the performance of cryptocurrency funds, Journal of Banking & Finance, Elsevier (2022) View citations (10) (2022)

2020

6. Dissecting Time-Varying Risk Exposures in Cryptocurrency Markets
   BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy View citations (6)

2018

7. Large-Scale Dynamic Predictive Regressions
   Papers, arXiv.org View citations (4)
8. Modeling Systemic Risk with Markov Switching Graphical SUR Models
   Working Papers, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University View citations (4)
   See also Journal Article Modeling systemic risk with Markov Switching Graphical SUR models, Journal of Econometrics, Elsevier (2019) View citations (31) (2019)

2016

9. The dynamics of expected returns: evidence from multi-scale time series modelling
   LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library

2015

10. Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section
    Working Papers, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University View citations (2)
    Also in Working Paper, Norges Bank (2013) View citations (1)
    See also Journal Article Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section, Journal of Business & Economic Statistics, Taylor & Francis Journals (2017) View citations (12) (2017)

2013

11. Dissecting the 2007-2009 real estate market bust: systematic pricing correction or just a housing fad?
    Working Paper, Norges Bank View citations (1)
    See also Journal Article Dissecting the 2007–2009 Real Estate Market Bust: Systematic Pricing Correction or Just a Housing Fad?, Journal of Financial Econometrics, Oxford University Press (2018) View citations (3) (2018)

Journal Articles

2023

1. The dynamics of returns predictability in cryptocurrency markets
   The European Journal of Finance, 2023, 29, (6), 583-611 View citations (3)

2022

2. On the performance of cryptocurrency funds
   Journal of Banking & Finance, 2022, 138, (C) View citations (10)
   See also Working Paper On the Performance of Cryptocurrency Funds, Working Paper Series (2021) View citations (2) (2021)
3. Trading volume and liquidity provision in cryptocurrency markets
   Journal of Banking & Finance, 2022, 142, (C) View citations (2)
   See also Working Paper Trading Volume and Liquidity Provision in Cryptocurrency Markets, CERGE-EI Working Papers (2022) View citations (8) (2022)

2021

4. Adaptive expectations and commodity risk premiums
   Journal of Economic Dynamics and Control, 2021, 124, (C) View citations (4)
5. Bond Risk Premiums with Machine Learning
   (Quadratic term structure models: Theory and evidence)
   The Review of Financial Studies, 2021, 34, (2), 1046-1089 View citations (71)
6. Corrigendum: Bond Risk Premiums with Machine Learning
   (Bond risk premiums with machine learning)
   The Review of Financial Studies, 2021, 34, (2), 1090-1103 View citations (63)

2019

7. Modeling systemic risk with Markov Switching Graphical SUR models
   Journal of Econometrics, 2019, 210, (1), 58-74 View citations (31)
   See also Working Paper Modeling Systemic Risk with Markov Switching Graphical SUR Models, Working Papers (2018) View citations (4) (2018)

2018

8. Dissecting the 2007–2009 Real Estate Market Bust: Systematic Pricing Correction or Just a Housing Fad?
   Journal of Financial Econometrics, 2018, 16, (1), 34-62 View citations (3)
   See also Working Paper Dissecting the 2007-2009 real estate market bust: systematic pricing correction or just a housing fad?, Working Paper (2013) View citations (1) (2013)

2017

9. Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section
   Journal of Business & Economic Statistics, 2017, 35, (1), 110-129 View citations (12)
   See also Working Paper Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section, Working Papers (2015) View citations (2) (2015)

2016

10. Global pulses of organic carbon burial in deep-sea sediments during glacial maxima
    Nature Communications, 2016, 7, (1), 1-7 View citations (4)

2014

11. Can Linear Predictability Models Time Bull and Bear Real Estate Markets? Out-of-Sample Evidence from REIT Portfolios
    The Journal of Real Estate Finance and Economics, 2014, 49, (1), 116-164 View citations (7)
12. Can long-run dynamic optimal strategies outperform fixed-mix portfolios? Evidence from multiple data sets
    European Journal of Operational Research, 2014, 236, (1), 160-176 View citations (7)