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Davide Benedetti

Postdoctoral Teaching and Research Associate

Imperial College Business School
Finance Department

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Summary

I am a postdoctoral researcher in Finance at Imperial College Business School, currently involved in the WINnERS project. I received my PhD from Imperial College Business School joint with the Climate-KIC PhD programme of the European Institute of Innovation and Technology.

My research interests lie in the areas of economics of risk and insurance, actuarial science, applied statistics and econometrics. In particular, I have been working extensively on the statistical modelling of risk, as well as on the economic analysis of both the insurance and the banking sector.

Current research papers include:

  • Optimal investment decisions under climate change risks
  • Predictive analytics models for political violence and security posture assessment in conflict areas
  • Risk management and (re)insurance demand with financial constraints and counterparty risk
  • Pricing and testing dynamic adverse selection in life insurance contracts
  • Tail risk profiling of large commercial risks

At Imperial College Business School I have been module leader of Econometrics I & II at the PhD programme, and teaching assistant of Machine Learning, Applied Econometrics, Quantitative Methods and Life Insurance at MSc programs.

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Curriculum Vitae

Download CV
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Contacts

Imperial College Business School
South Kensington Campus
Exhibition Road
London, SW7 2AZ
United Kingdom

d.benedetti@imperial.ac.uk
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Research

Research Fields

Areas of Interest:
  • Economics of Risk and Insurance
  • Risk Analytics
  • Applied Statistics and Econometrics
  • Empirical Finance
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Working Papers

  • Climate Change Investment Risk: Optimal Portfolio Construction Ahead of the Transition to a Lower-carbon Economy
    with Enrico Biffis, Davide Benedetti, Fotis Chatzimichalakis, Luciano Fedele and Ian Simm
    Available at SSRN
    (Revise and Resubmit to Annals of Operations Research)
  • Security Posture Assessment in Conflict Areas: Evidence from Iraq
    with Enrico Biffis and Mehmet Shoukru
    We consider the problem of assessing the security posture of organizations operating in conflict areas. We show how spatio-temporal risk models can be used to understand the dynamics of attack occurrences and severities, providing insights into the design of the Close Protection security layer (i.e., the range of security measures under direct control of an organization). The research design is as follows: first, (i) we estimate spatio-temporal risk models on a granular dataset of attacks carried out in Iraq during the period 2007-15, to better understand the dynamics of attack occurrences and severities; then, (ii) we implement survey data from the top five security providers in Iraq to create Close Protection security benchmarks based on ‘unconditional’ (broad) information, as well as ‘conditional’ on the predictions from the risk models of point (i); finally, (iii) we quantify the economic gains of using predictive models by computing cost deviations of implementing the ‘unconditional’ security posture vs. the ‘conditional’ one vs. the observed one. As an application, we consider in detail four different areas presenting different socio-economic characteristics and patterns of attack occurrence. We then look at the oil and gas industry, and discuss a case study based on a medium sized oil field in the Basra province. We find that on average, firms design their Close Protection based on unconditional information, and sometimes overreacting to spikes in conflict activity that have limited bearing for the exposure at stake. Furthermore, in areas with extensive investments in counterinsurgency programs (e.g., Basra province), an appropriate use of spatio-temporal information can deliver average security cost savings of around 30% relative to the ‘unconditional’ benchmark, and of around 50% with respect to security postures driven by overreaction. Instead, areas featuring significant spatio-temporal clustering of events (e.g., Al-Anbar and Baghdad [Red Zone]) may require up to 50% more investment in mobile security.
  • Financial Constraints and Risk Management: Evidence from the US P&C Insurance Market
    with Enrico Biffis
    Using a large and granular panel dataset of reinsurance transactions by US Property & Casualty (P&C) insurers, we examine the determinants for both risk management demand (as measured by reinsurance coverage) and quality of hedging instruments (as proxied by reinsurer’s counterparty risk). The results show that more financially constrained insurers purchase less reinsurance. However, financial constraints are positively correlated with the demand for more credit worthy and hence expensive reinsurance. In terms of insurer’s credit rating, higher rated insurers tend to prefer higher rated reinsurance. Conversely, lower quality insurers seek (or can afford) lower rated reinsurance. The findings are in line with empirical predictions of corporate risk management models showing that the costs of risk management may outweigh its benefits in the presence of financial constraints.
  • Insurance contract design and endogenous frailty
    with Enrico Biffis
    We study how the design of options and guarantees can shape the exposure to mortality/longevity risk in life insurance contracts. We introduce a model of selective withdrawals, driven by exogenous and endogenous factors, offering insights into traditional approaches to the analysis of surrender guarantees and dynamic adverse selection. Via this model, the mortality risk profile of policyholders can be represented in terms of an endogenous frailty process shaped by the relative attractiveness of different contract benefits in different states of the world. This method does not require the knowledge of individual insureds’ health conditions, but only their exit times and reasons. This framework can be used, by both practitioners and researchers, for pricing, reserving and statistical testing of dynamic adverse selection in life insurance contracts.
  • Large Commercial Exposures and Tail Risk: Evidence from the Asia-Pacific P&C Insurance Market
    with Enrico Biffis and Andreas Milidonis
    Download link
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Publications

  • Benedetti D., and Molnar R., (2020), Stress Testing Corporate Earnings of US Companies, In Data-Centric Business and Applications, Publisher: Springer, Cham, Pages: 347-370.
    Link
  • Eastwood J., Hapgood M. A., Biffis E., Benedetti D., Bisi M. M., Green L., Bentley R. D., and Burnett C. (2018). Quantifying the economic value of space weather forecasting for power grids: an exploratory study, Space Weather: The International Journal of Research and Applications, , 16(12), pp.2052-2067.
    Link
  • Benedetti D., Biffis E., and Milidonis A. (2015). Large Commercial Risks (LCR) in Insurance: Focus on Asia-Pacific, Insurance Risk and Finance Research Centre Technical report, Retrieved from www.irfrc.com.
    Download link
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Thesis Title

Essays in Corporate Risk Management and Insurance, 2018
Supervisor: Dr Enrico Biffis
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Teaching

Machine & Deep Learning with Finance Applications

MSc Risk Management and Financial Engineering - Imperial College Business School

Role: Teaching Assistant
Period: Summer 2019
(Course held by Prof. Guillaume Coqueret)
Topics covered in the tutorials:
  • Data Management (Cleaning and Pre-Processing) in R
  • Portfolio Performance Metrics in R
  • Factor Investing with Machine and Deep Learning
  • Lasso, Ridge and Elastic-Net
  • Trees, Random Forests and Gradient Boosting
  • Artificial Neural Networks
  • Extensions: Ensemble Learning, Interpretability and Backtesting
  • Validation and Tuning
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Applied Econometrics

MSc Finance & Accounting - Imperial College Business School

Role: Teaching Assistant
Period: Fall 2018
(Course held by Prof. Walter Distaso)
Topics covered in the tutorials:
  • Applications of R for Econometrics and Finance
  • Momentum Strategies and Portfolio Performance Metrics in R
  • Linear Models in R
  • Instrumental Variables and SEM in R
  • Time Series Analysis and Dynamic Linear Models in R
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Quantitative Methods

MSc Climate Change Management & Finance - Imperial College Business School

Role: Teaching Assistant
Period: Fall 2016; Fall 2017; Fall 2018
(Course held by Dr. Ralf Martin)
Topics covered in the tutorials:
  • Introduction to R
  • Linear Models in R
  • Instrumental Variables Regression in R
  • Fixed-Effects Panel Model in R
  • Time Series Analysis in R
  • Geographic Information System in R
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Econometrics I

MRes/PhD Programme - Imperial College Business School

Role: Course Leader
Period: Fall 2016
Topics covered in the lectures:
  • Introduction to Econometrics
  • Fundamentals of regression analysis I: Multivariate Regression Models
  • Fundamentals of regression analysis II: Non-linear Regression Models
  • Regression with binary dependent variable: Probit and Logit models
  • Endogeneity: Instrumental Variables Regression
  • Panel Data I: Fixed Effects, Clustered Covariance Matrix, Fixed Effects Vector Decomposition and its critique
  • Panel Data II: Anderson-Hsiao's, Arellano-Bond's, Hausman-Taylor's estimators and Hausman's specification test
  • Panel Data III: Incidental Parameters Problem, Concentrated estimators, Conditional Log-Likelihood, Mundlack's Approach to Probit model and Simulated Maximum Likelihood (SML)
  • Time Series I: Stationarity, Ergodicity, Wold Decomposition Theoreom, Autoregressive Processes and ADL models
  • Time Series II: Newey-West Robust SD, Non-Stationarity, Structural Breaks
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Econometrics II

MRes/PhD Programme - Imperial College Business School

Role: Course Leader
Period: Spring 2015; Spring 2016
Topics covered in the lectures:
  • Cross section analysis and introduction to panel: OLS, GLS, IV and GMM estimators
  • Fixed Effects model (FE), Fixed Effects Vector Decomposition (FEVD) and its critique
  • Robust covariance matrix for the FE model
  • Random Effects model (RE) and mixed RE-FE models: Mundlak's and Chamberlain's approach
  • Parameter Heterogeneity: Swamy's Random Coefficients model
  • Endogeneity in panel data: Anderson-Hsiao's, Arellano-Bond's and Hausman-Taylor's estimators
  • Specification tests in econometrics: Hausman's specification test
  • Non-linear panel data models: Incidental Parameters Problem, Concentrated estimators, Conditional Log-Likelihood, Random Effects Probit model and Simulated Maximum Likelihood (SML)
  • Truncation and sample selection bias: Heckman correction and extensions
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Life Insurance

MSc Risk Management and Financial Engineering - Imperial College Business School

Role: Teaching Assistant
Period: Spring 2014; Spring 2015
(Course held by Dr. Enrico Biffis)
Topics covered in the tutorials:
  • Mortality Protection Gap: definition and estimation
  • Valuation of Life Insurance Contracts: profit testing
  • Longevity Risk and Stochastic Mortality: Lee-Carter and extensions, continuous time models
  • Risk Quantification and Management: application of copulae and extreme value theory in Life Insurance
  • Simulation Methods for Life Insurance: Monte Carlo applications
  • Surrender Risk and Policyholder's Behaviour: generalized linear models for surrender risk, optimal policyholder's behaviour
  • Advanced Simulation Methods: Nested Monte Carlo and Least Squares Monte Carlo
  • Variable Annuity: pricing, management and product design
  • Solvency II
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Projects

WINnERS

PI: Dr. Erik Chavez (Imperial), CI: Dr. Enrico Biffis (Imperial)
Climate KIC, European Institute of Innovation and Technology
May 2016 - actual

WINnERS is a research project which aims to design an insurance product to protect the agricultural supply chain against climate and weather risks. The project is funded by Climate-KIC and actively supported by several organizations among which: the World Food Program and the World Bank. It has also partners from both the insurance sector and global food buyers.

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Space Weather Economic Costs

PI: Dr. Jonathan Eastwood (Imperial), CI: Dr. Enrico Biffis (Imperial)
Met Office, Airbus, UCL-MSSL and RAL
April 2016 - November 2016

Aim of the project was to estimate the direct impact of solar storms, solar flares and geomagnetic storms on energy and airline industries, as well as their indirect impact on the rest of the economy through those sectors.

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Urban Climate Change Resilience

PI: Dr. Enrico Biffis (Imperial)
Grantham Insitute and Commonwealth Scientific and Industrial Research Organisation
November 2015 - April 2016

The project consisted in a research study between the Grantham Institute and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) to identify the key research priorities in urban climate change resilience and scoping out potential areas for collaboration between Imperial and CSIRO including a joint PhD to start in 2016.

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Risk Appetite

PI: Dr. Enrico Biffis (Imperial), CI: Davide Benedetti
FINMAR, Willis Group
September 2015 - June 2016

The aim of the project was to gauge the risk appetite of corporates and financial institutions by analysing their insurance purchases. The objective was to pinpoint the true relation between insurance buyers' and sellers' characteristics, as well as its dependence on wider market conditions and sector characteristics.

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Large Commercial Risks (LCR)

PI: Dr. Andreas Milidonis (University of Cyprus), CI: Dr. Enrico Biffis (Imperial)
Insurance Intellectual Capital Initiative Consortium, SCOR, Hiscox, Liberty
June 2015 - August 2015

The Large Commercial Risks (LCR) project was directed by the Insurance Risk and Finance Research Centre in collaboration with Imperial College London Business School. The aims of the project are to provide: (i) a dataset of LCR, for the Asia-Pacific Region (APAC) region; (ii) a modelling framework for LCR in APAC; (iii) pricing implications and comparisons between the APAC region and other parts of the world, in particular North America and Europe.

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Oasis Loss Modelling Framework

PI: Prof. Ralf Toumi (Imperial)
Climate-KIC, European Institute of Innovation and Technology
July 2012 - June 2015

Oasis LMF is a non-for-profit organization with the aim to provide an open source catastrophe modelling service for (re)insurance companies, public bodies and financial institutions. The project was funded by Climate-KIC and supported by a large group of insurance companies and insurance brokers.

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Visiting

Visiting Positions

  • CRDB Bank plc
    Dar es Salaam, Tanzania, 10-21 December 2018, and 27 Jan - 8 Feb 2019
  • Department of Risk Management and Insurance, Georgia State University
    Atlanta (GA), USA, 16-31 May 2016
  • Private Agricultural Sector Support
    Dar es Salaam, Tanzania, 2-10 May 2016
  • Commonwealth and Scientific Research Organization
    Melbourne and Brisbane, Australia, January 2016
  • Insurance Risk and Finance Research Centre, Nanyang Business School
    Singapore, June 2015
  • Department of Risk Management and Insurance, Georgia State University
    Atlanta (GA), USA, April-May 2015
  • Department of Finance, Imperial College Business School
    London, UK, February-June 2012
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Summer Schools

  • PhD Summer School
    Design for Adaptation: Resilient Urban Communities
    Climate-KIC, European Institute of Innovation and Technology
    Bologna, 7-18 September 2015
  • Summer School (the Journey)
    Entrepreneurship and Climate Change
    Climate-KIC, European Institute of Innovation and Technology
    Wageningen-Budapest-Valencia, 4 August - 6 September 2013
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