Imperial College London

Dr Davide Benedetti

Business School

Casual - Student demonstrator - lower rate
 
 
 
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Contact

 

d.benedetti Website

 
 
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Location

 

349ACE ExtensionSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

5 results found

Benedetti D, Biffis E, Chatzimichalakis F, Lilloy Fedele L, Simm Iet al., 2021, Climate change investment risk: optimal portfolio construction ahead of the transition to a lower-carbon economy, Annals of Operations Research, Vol: 299, Pages: 847-871, ISSN: 0254-5330

There is an increasing likelihood that governments of major economies will act within the next decade to reduce greenhouse gas emissions, probably by intervening in the fossil fuel markets through taxation or cap & trade mechanisms (collectively “carbon pricing”). We develop a model to capture the potential impact of carbon pricing on fossil fuel stocks, and use it to inform Bayesian portfolio construction methodologies, which are then used to create what we call Smart Carbon Portfolios. We find that investors could reduce ex-post risk by lowering the weightings of some fossil fuel stocks with corresponding higher weightings in lower-risk fossil fuel stocks and/or in the stocks of companies active in energy efficiency markets. The financial costs of such de-risking strategy are found to be statistically negligible in risk-return space. Robustness of the results is explored with alternative approaches.

Journal article

Benedetti D, Biffis E, Chatzimichalakis F, Lilloy Fedele LR, Simm Iet al., 2020, Climate change investment risk: optimal portfolio construction ahead of the transition to a lower-carbon economy

There is an increasing likelihood that governments of major economies will act within thenext decade to reduce greenhouse gas emissions, probably by intervening in the fossil fuelmarkets through taxation or cap & trade mechanisms (collectively “carbon pricing”). Wedevelop a model to capture the potential impact of carbon pricing on fossil fuel stocks,and use it to inform Bayesian portfolio construction methodologies, which are then used tocreate what we call Smart Carbon Portfolios. We find that investors could reduce ex-post riskby lowering the weightings of some fossil fuel stocks with corresponding higher weightingsin lower-risk fossil fuel stocks and/or in the stocks of companies active in energy efficiencymarkets. The financial costs of such de-risking strategy are found to be statistically negligiblein risk-return space. Robustness of the results is explored with alternative approaches.

Working paper

Benedetti D, Molnar R, 2020, Stress Testing Corporate Earnings of US Companies, Data-Centric Business and Applications, Publisher: Springer, Cham, Pages: 347-370

Book chapter

Eastwood J, Hapgood MA, Biffis E, Benedetti D, Bisi MM, Green L, Bentley RD, Burnett Cet al., 2019, Quantifying the economic value of space weather forecasting for power grids: An exploratory study, Space Weather, Vol: 16, Pages: 2052-2067, ISSN: 1539-4956

An accurate understanding of space weather socioeconomic impact is fundamental to the development of appropriate operational services, forecasting capabilities, and mitigation strategies. One way to approach this problem is by developing physics‐based models and frameworks that can lead to a bottom‐up estimate of risk and likely impact. Here we describe the development of a new framework to assess the economic impact of space weather on power distribution networks and the supply of electricity. In particular, we focus on the phenomenon of the geomagnetic substorm, which is relatively localized in time and space, and occurs multiple times with varying severity during a geomagnetic storm. The framework uses the AE index to characterize substorm severity, and the impact of the substorm is modulated by the resilience of the power grid and the nature of available forecast. Possible scenarios for substorm sequences during a 1‐in‐10‐, a 1‐in‐30‐, and a 1‐in‐100‐year geomagnetic storm events are generated based on the 2003, 1989, and 1859 geomagnetic storms. Economic impact, including international spill over, can then be calculated using standard techniques, based on the duration and the geographical footprint of the power outage. Illustrative calculations are made for the European sector, for a variety of forecast and resilience scenarios. However, currently available data are highly regionally inhomogeneous, frustrating attempts to define an overall global economic impact at the present time.

Journal article

Benedetti D, Biffis E, Milidonis A, 2015, Large Commercial Risks (LCR) in Insurance: Focus on Asia-Pacific, Insurance Risk and Finance Research Centre Technical report

Report

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