We develop a network-based vector autoregressive approach to uncover the interactions amongfinancial assets by integrating multiple realized measures based on high-frequency data. Undera restricted parameter structure, our approach allows the capture of cross-sectional and time ependencies...

Recent empirical studies show that ESG sentiment, the attitude of investors toward a company’s ESG performance, is a major factor that affects stock performance. While investing in ESG could bring potential risk deduction benefits, changing ESG sentiments in the market will lead to additional...

The financial economics literature proposes dozens of performance measures to be used, for instance, to compare, analyse, rank and select assets. There is thus a problem: which measures should be considered? We extend the current literature by comparing a large set of performance measures over...

This paper focuses on the relationship between the European Union Emission Trading System allowances' prices and the Italian electricity price, aiming at assessing whether such a mechanism has been a driver for the decarbonization of the power sector. To this aim, we calculate the long-run...

We present a generalisation of the double long memory ARFIMA-FIGARCH model introducing time-varying memory coefficients for both mean and variance. The model satisfies the empirical evidence of changing memory observed in average temperature series and can provide useful improvements in the...

This paper proposes structured parametrizations for multivariate volatility models, which use spatial weight matrices induced by economic proximity. These structured specifications aim at solving the curse of dimensionality problem, which limits feasibility of model-estimation to small...