if this message does not display correctly, click here | Table of Contents Rocco Ciciretti, Tor Vergata University of Rome - Department of Economics and Finance
Ambrogio Dalò, University of Gronigen - Faculty of Economics and Business
Giovanni Ferri, LUMSA University Gianluca Cubadda, University of Rome Tor Vergata - Department of Economics and Finance
Alain Hecq, Maastricht University - Department of Quantitative Economics Beniamino Pisicoli, University of Rome Tor Vergata - Department of Economics and Finance | |
CEIS: CENTRE FOR ECONOMIC & INTERNATIONAL STUDIES
Furio Camillo Rosati - Director "Herding and Anti-Herding Across ESG Funds" 
CEIS Working Paper No. 524 ROCCO CICIRETTI, Tor Vergata University of Rome - Department of Economics and Finance
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AMBROGIO DALÃ’, University of Gronigen - Faculty of Economics and Business
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GIOVANNI FERRI, LUMSA University
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We investigate to what extent ESG funds present an herding/anti-herding behavior, and the consequences of their investment strategies in terms of both systematic risk exposure and risk-adjusted returns. Our findings document that ESG funds pursue an anti-herding strategy that leads to higher risk-adjusted returns. Specifically, a one standard deviation increase in ESG score at the fund-level is associated with an increase in fund performance of about 3.74 basis points per year. Moreover, we document that such an enhanced performance does not come at the cost of higher systematic risk exposure but instead reduces it. A possible explanation behind our findings is that after the catching-up phase previously documented by the literature, ESG funds are now able to put to good use enhanced stock-picking skills built over the years. "Reduced Rank Regression Models in Economics and Finance"
CEIS Working Paper No. 525 GIANLUCA CUBADDA, University of Rome Tor Vergata - Department of Economics and Finance
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ALAIN HECQ, Maastricht University - Department of Quantitative Economics
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This chapter surveys the importance of reduced rank regression techniques (RRR) for modelling economic and financial time series. We mainly focus on models that are capable to reproduce the presence of common dynamics among variables such as the serial correlation common feature and the multivariate autoregressive index models. Cointegration analysis, for which RRR plays a central role, is not discussed in this chapter as it deserves a specific treatment on its own. Instead, we show how to detect and model comovements in time series that are stationary or that have been stationarized after proper transformations. The motivations for the use of RRR in time series econometrics include dimension reductions which simplify complex dynamics and thus making interpretations easier, as well as pursuing efficiency gains in both estimation and prediction. Via the final equation representation, RRR also makes the nexus between multivariate time series and parsimonious marginal ARIMA models. The drawback of RRR, which is common to all the dimension reduction techniques, is that the underlying restrictions may be present or not in the data. We provide in this chapter a couple of empirical applications to illustrate concepts and methods. "Banking Diversity, Financial Complexity and Resilience to Financial Shocks: Evidence from Italian Provinces"
CEIS Working Paper No. 526 BENIAMINO PISICOLI, University of Rome Tor Vergata - Department of Economics and Finance
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In this paper we investigate the influence of banking and financial diversity on stability. We compute an index of banking diversity for Italian provinces and, drawing from network theory, we propose a measure of the diversity and development of the overall provincial financial sector. Our results show that diversity in the banking and financial markets promotes greater stability. Such beneficial effects are particularly evident during periods of financial distress. We ascribe our findings to the better diversification achieved by more diverse financial systems, as documented by lower loans concentration and higher loans diversification in terms of economic destination and borrower category. | | ^top
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