if this message does not display correctly, click here | Table of Contents Federico Giorgi, University of Rome Tor Vergata - Department of Economics and Finance
Stefano Herzel, University of Rome Tor Vergata - Faculty of Economics
Paolo Pigato, University of Rome Tor Vergata - Department of Economics and Finance Andrea Fazio, Polytechnic University of Marche - Department of Economics and Social Sciences
Erminia Florio, University of Rome Tor Vergata, HEC Montréal
Gustavo Piga, University of Rome Chiara Puccioni, Confindustria
Daniela Vuri, University of Rome Tor Vergata, IZA Institute of Labor Economics, CESifo (Center for Economic Studies and Ifo Institute for Economic Research) Ranieri Dugo, University of Rome Tor Vergata - Department of Economics and Finance
Giacomo Giorgio, University of Tor Vergata
Paolo Pigato, University of Rome Tor Vergata - Department of Economics and Finance Marianna Brunetti, Dept. Economics and Finance, University of Rome Tor Vergata, CEFIN
Annalisa Fabretti, University Tor Vergata - Economia
Mariangela Zoli, University of Rome Tor Vergata | |
CEIS: CENTRE FOR ECONOMIC & INTERNATIONAL STUDIES
Furio Camillo Rosati - Director "A Reinforcement Learning Algorithm For Option Hedging" 
CEIS Working Paper No. 586 FEDERICO GIORGI, University of Rome Tor Vergata - Department of Economics and Finance
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STEFANO HERZEL, University of Rome Tor Vergata - Faculty of Economics
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PAOLO PIGATO, University of Rome Tor Vergata - Department of Economics and Finance We propose an algorithm, based on Reinforcement Learning, to hedge the payoff on a European call option. The algorithm is first tested in a model where the problem has a well known analytic solution, so that we can compare the strategy obtained by the algorithm to the theoretical optimal one. In a more realistic case, considering transaction costs, the algorithm outperforms the standard delta hedging strategy. "SMEs Performance in Public Procurement and the Italian Legality Rating "
CEIS Working Paper No. 587 ANDREA FAZIO, Polytechnic University of Marche - Department of Economics and Social Sciences
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ERMINIA FLORIO, University of Rome Tor Vergata, HEC Montréal
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GUSTAVO PIGA, University of Rome
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This study investigates the impact of the Italian Legality Rating (LR) on small and medium enterprises (SMEs) in public procurement. The LR, issued by the Italian Antitrust Authority, evaluates firms based on fiscal transparency, anti-corruption practices, corporate responsibility, and sustainability. While larger firms are more likely to obtain higher LR scores, SMEs benefit significantly from holding the certification. Using firm-level data and a Regression Discontinuity Design, we find that the LR increases SMEs' tender-winning probabilities by 12.9 percentage points, highlighting its role as a strong institutional signal. Our findings emphasize the LR's potential to enhance SME competitiveness in public procurement. "With a Little Help from Nurseries - Childcare Services and Mothers' Employment in Italy"
CEIS Working Paper No. 588 CHIARA PUCCIONI, Confindustria
DANIELA VURI, University of Rome Tor Vergata, IZA Institute of Labor Economics, CESifo (Center for Economic Studies and Ifo Institute for Economic Research)
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This study evaluates the impact of an Italian government initiative launched in 2007, which allocated e1 billion to regional governments to enhance early childhood care services for children aged 0-2, targeting both public and private childcare options. Exploiting variations in the timing of implementation across regions, we assess the program's effectiveness in increasing the public provision of early childcare services and maternal labor market participation. Results show a significant increase in both public childcare slots and labor market participation among mothers. However, the initiative had limited effects on less-educated women, likely due to the service's relatively high costs, which may hinder broader accessibility. "Multivariate Rough Volatility"
CEIS Working Paper No. 589 RANIERI DUGO, University of Rome Tor Vergata - Department of Economics and Finance
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GIACOMO GIORGIO, University of Tor Vergata
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PAOLO PIGATO, University of Rome Tor Vergata - Department of Economics and Finance Motivated by empirical evidence from the joint behavior of realized volatility time series, we propose to model the joint dynamics of log-volatilities using a multivariate fractional Ornstein-Uhlenbeck process. This model is a multivariate version of the Rough Fractional Stochastic Volatility model proposed in Gatheral, Jaisson, and Rosenbaum, Quant. Finance, 2018. It allows for different Hurst exponents in the different marginal components and non trivial interdependencies. We discuss the main features of the model and propose an estimator that jointly identifies its parameters. We derive the asymptotic theory of the estimator and perform a simulation study that confirms the asymptotic theory in finite sample. We carry out an extensive empirical investigation on all realized volatility time series covering the entire span of about two decades in the Oxford-Man realized library. Our analysis shows that these time series are strongly correlated and can exhibit asymmetries in their cross-covariance structure, accurately captured by our model. These asymmetries lead to spillover effects that we analyse theoretically within the model and then using our empirical estimates. Moreover, in accordance with the existing literature, we observe behaviors close to non-stationarity and rough trajectories. "Who Decides Matters: Female Representation and Academic Career Advancement "
CEIS Working Paper No. 590 MARIANNA BRUNETTI, Dept. Economics and Finance, University of Rome Tor Vergata, CEFIN
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ANNALISA FABRETTI, University Tor Vergata - Economia
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MARIANGELA ZOLI, University of Rome Tor Vergata
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This paper investigates the gender gap in academic promotions. The theoretical model proposed, in which men and women collectively negotiate their career upgrades but with different bargaining power, predicts that the likelihood of career progression for women depends negatively on the share of female scholars among the eligible candidates and positively on the available resources and women's bargaining power. We relate the latter to metrics of women's relative representation, such as the Glass-Ceiling Index, the Female Ratio, and the Share of Females in the boards in charge of deciding about those promotions. Leveraging a novel and suitably built dataset covering the universe of Italian Universities' Departments, we find robust evidence supporting these predictions. In particular, the probability of women being upgraded to associate and full professors is strongly and positively associated with the shares of women in the pool of professors in charge of deciding about those promotions. | | ^top
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