36 results found
Biffis E, Goldys B, Prosdocimi C, et al., 2023, A pricing formula for delayed claims: appreciating the past to value the future, Mathematics and Financial Economics, ISSN: 1862-9679
<jats:title>Abstract</jats:title><jats:p>We consider the valuation of contingent claims with delayed dynamics in a Samuelson complete market model. We find a pricing formula that can be decomposed into terms reflecting the current market values of the past and the future, showing how the valuation of prospective cashflows cannot abstract away from the contribution of the past. As a practical application, we provide an explicit expression for the market value of human capital in a setting with wage rigidity. The formula we derive has successfully been used to explicitly solve the infinite dimensional stochastic control problems addressed in Biffis et al. (SIAM J Control Optim 58(4):1906–1938, 2020), Djeiche et al. (Stoch Process Appl 145:48–85, 2022) and Biagini et al. (SIAM J Financial Math 13(3):1004–1039, 2022).</jats:p>
Barucci E, Biffis E, Marazzina D, 2022, Health insurance, portfolio choice, and retirement incentives, European Journal of Operational Research, ISSN: 0377-2217
We study optimal portfolio choice and labor market participation in a continuous time setting in which agents face health shocks, medical expenses, and random lifetimes. We explore the implications of different forms of health coverage and study their impact on dynamic portfolios and labor supply decisions. We characterize these effects in semi-closed form, providing tools to measure retirement incentives as a function of relevant state variables and health cover arrangements. A calibration of the model matches empirically observed labor market participation patterns and portfolio decisions of US workers during the last phase of their working lives, while offering insights into the interlinkage between labor market participation, health insurance provision and portfolio choice.
Benedetti D, Biffis E, Chatzimichalakis F, et 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.
Biffis E, Chavez E, Louaas A, et al., 2021, Parametric insurance and technology adoption in developing countries, GENEVA RISK AND INSURANCE REVIEW, Vol: 47, Pages: 7-44, ISSN: 1554-964X
Biffis E, Gozzi F, Prosdocimi C, 2020, Optimal portfolio choice with path dependent labor income: the infinite horizon case, SIAM Journal on Control and Optimization, Vol: 58, Pages: 1906-1938, ISSN: 0363-0129
We consider an infinite horizon portfolio problem with borrowing constraints, in which an agentreceives labor income which adjusts to financial market shocks in a path dependent way. Thispath-dependency is the novelty of the model, and leads to an infinite dimensional stochasticoptimal control problem. We solve the problem completely, and find explicitly the optimalcontrols in feedback form. This is possible because we are able to find an explicit solutionto the associated infinite dimensional Hamilton-Jacobi-Bellman (HJB) equation, even if stateconstraints are present. To the best of our knowledge, this is the first infinite dimensionalgeneralization of Merton’s optimal portfolio problem for which explicit solutions can be found.The explicit solution allows us to study the properties of optimal strategies and discuss theirfinancial implications.
Benedetti D, Biffis E, Chatzimichalakis F, et 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.
Eastwood J, Hapgood MA, Biffis E, et 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.
Biffis E, Goldys B, Prosdocimi C, et al., 2019, A pricing formula for delayed claims: appreciating the past to value the future, Publisher: Elsevier BV
We consider the valuation of contingent claims with delayed dynamics in a Black and Scholes complete market model. We find a pricing formula that can be decomposed into terms reflecting the current market values of the past and the future, showing how the valuation of future cashflows cannot abstract away from the contribution of the past. As a practical application, we provide an explicit expression for the market value of human capital in a setting with wage rigidity.
Biffis E, Chavez E, 2017, Satellite data and machine learning for weather risk management and food security, Risk Analysis, Vol: 37, Pages: 1508-1521, ISSN: 1539-6924
The increase in frequency and severity of extreme weather events poses challenges for the agricultural sector in developing economies and for food security globally. In this article, we demonstrate how machine learning can be used to mine satellite data and identify pixel-level optimal weather indices that can be used to inform the design of risk transfers and the quantification of the benefits of resilient production technology adoption. We implement the model to study maize production in Mozambique, and show how the approach can be used to produce countrywide risk profiles resulting from the aggregation of local, heterogeneous exposures to rainfall precipitation and excess temperature. We then develop a framework to quantify the economic gains from technology adoption by using insurance costs as the relevant metric, where insurance is broadly understood as the transfer of weather-driven crop losses to a dedicated facility. We consider the case of irrigation in detail, estimating a reduction in insurance costs of at least 30%, which is robust to different configurations of the model. The approach offers a robust framework to understand the costs versus benefits of investment in irrigation infrastructure, but could clearly be used to explore in detail the benefits of more advanced input packages, allowing, for example, for different crop varieties, sowing dates, or fertilizers.
Biffis E, Chavez E, 2017, On-line Appendix to "Satellite Data and Machine Learning for Weather Risk Management and Food Security", Risk Analysis, ISSN: 1539-6924
This Appendix provides additional technical details for the analysis contained in Biffis and Chavez (2017).
Eastwood J, Biffis E, Hapgood MA, et al., 2017, The economic impact of space weather: where do we stand?, Risk Analysis, Vol: 37, Pages: 206-218, ISSN: 0272-4332
Space weather describes the way in which the Sun, and conditions in space more generally, impact human activity and technology both in space and on the ground. It is now well understood that space weather represents a significant threat to infrastructure resilience, and is a source of risk that is wide‐ranging in its impact and the pathways by which this impact may occur. Although space weather is growing rapidly as a field, work rigorously assessing the overall economic cost of space weather appears to be in its infancy. Here, we provide an initial literature review to gather and assess the quality of any published assessments of space weather impacts and socioeconomic studies. Generally speaking, there is a good volume of scientific peer‐reviewed literature detailing the likelihood and statistics of different types of space weather phenomena. These phenomena all typically exhibit “power‐law” behavior in their severity. The literature on documented impacts is not as extensive, with many case studies, but few statistical studies. The literature on the economic impacts of space weather is rather sparse and not as well developed when compared to the other sections, most probably due to the somewhat limited data that are available from end‐users. The major risk is attached to power distribution systems and there is disagreement as to the severity of the technological footprint. This strongly controls the economic impact. Consequently, urgent work is required to better quantify the risk of future space weather events.
Biffis E, Lin Y, Milidonis A, 2017, On-line appendix to "The Cross-Section of Asia-Pacific Mortality Dynamics:Implications for Longevity Risk Sharing", Journal of Risk and Insurance, ISSN: 1539-6975
Biffis E, Lin Y, Milidonis A, 2017, The cross-section of Asia-Pacific mortality dynamics: Implications for longevity risk sharing, Journal of Risk and Insurance, Vol: 84, Pages: 515-532, ISSN: 1539-6975
We study the dynamics of longevity risk across a subset of countries in the Asia-Pacific (APAC)region. We use hand-collected and existing data on age-specific mortality rates from emergingand developed economies, to understand how secular changesin mortality vary within and acrossAPAC countries. We use our results to identify cross-hedgingopportunities among longevity riskexposures in the APAC region. We also introducek-forward contracts, which offer natural risksharing opportunities to hedgers in different countries. Weconsider the example of Korea andJapan as a case study
Biffis E, Blake D, Pitotti L, et al., 2016, The cost of counterparty risk and collateralization in longevity swaps, Journal of Risk and Insurance, Vol: 83, Pages: 387-419, ISSN: 1539-6975
Derivative longevity risk solutions, such as bespoke and indexed longevity swaps, allow pension schemes, and annuity providers to swap out longevity risk, but introduce counterparty credit risk, which can be mitigated if not fully eliminated by collateralization. We examine the impact of bilateral default risk and collateral rules on the marking to market of longevity swaps, and show how longevity swap rates must be determined endogenously from the collateral flows associated with the marking-to-market procedure. For typical interest rate and mortality parameters, we find that the impact of collateralization is modest in the presence of symmetric default risk, but more pronounced when default risk and/or collateral rules are asymmetric. Our results suggest that the overall cost of collateralization is comparable with, and often much smaller than, that found in the interest rate swaps market, which may then provide the appropriate reference framework for the credit enhancement of both indemnity-based and indexed longevity risk solutions.
Biffis E, Chavez E, 2014, Tail Risk in Commercial Property Insurance, Risks - Open Access Risk Management Journal, Vol: 2, Pages: 393-410
Biffis E, Kosowski R, 2014, Recreating Sustainable Retirement: Resilience, Solvency, and Tail Risk, Recreating Sustainable Retirement: Resilience, Solvency, and Tail Risk, Editors: Mitchell, Maurer, Hammond, Publisher: Oxford University Press, ISBN: 9780191029974
This book analyzes such challenges to retirement sustainability, and it explores ways to better manage and finance them. Insights provided help build retirement systems capable of withstanding what the future will bring.
Biffis E, Blake D, 2014, Keeping Some Skin in the Game: How to Start a Capital Market in Longevity Risk Transfers, North American Actuarial Journal, Vol: 18, Pages: 14-21
Biffis E, Kosowski R, 2014, Managing Capital Market Risk for Retirement, Recreating Sustainable Retirement: Extreme Risk and Pension Security, Editors: Maurer, Mitchell, Publisher: Oxford University Press
Biffis E, Blake D, 2013, Informed intermediation of longevity exposures, Journal of Risk and Insurance, Vol: 80, Pages: 559-584, ISSN: 0022-4367
Biffis E, Denuit M, Devolder P, 2010, Stochastic mortality under measure changes, Scandinavian Actuarial Journal, Vol: 2010, Pages: 284-311, ISSN: 0346-1238
Biffis E, Kyprianou AE, 2010, A note on scale functions and the time value of ruin for Levy risk processes, Insurance: Mathematics and Economics, Vol: 46, Pages: 85-91, ISSN: 0167-6687
Bacinello AR, Biffis E, Millossovich P, 2010, Regression-based algorithms for life insurance contracts with surrender guarantees, Quantitative Finance, Vol: 10, Pages: 1077-1090, ISSN: 1469-7696
Biffis E, Denuit M, Devolder P, 2010, Stochastic Mortality Under Measure Changes, Publisher: Pensions Institute, London, PI-0512
Biffis E, Blake D, 2010, Mortality-linked securities and derivatives, Optimizing the Aging, Retirement and Pensions Dilemma, Editors: Bertocchi, Schwartz, Ziemba, Publisher: John Wiley & Sons
Biffis E, Morales M, 2010, On an extension of the Gerber-Shiu function to path-dependent penalties, Insurance: Mathematics and Economics, Vol: 46, Pages: 92-97, ISSN: 0167-6687
Biffis E, Blake D, 2010, Securitizing and tranching longevity exposures, Insurance: Mathematics and Economics, Vol: 46, Pages: 186-197, ISSN: 0167-6687
Frankland R, Smith AD, Wilkins T, et al., 2009, Modelling extreme market events, British Actuarial Journal, Vol: 15, Pages: 99-217, ISSN: 1357-3217
Bacinello AR, Biffis E, Millossovich P, 2009, Pricing life insurance contracts with early exercise features, Journal of Computational and Applied Mathematics, Vol: 233, Pages: 27-35, ISSN: 0377-0427
Biffis E, Blake D, 2009, Mortality-linked securities and derivatives, Publisher: Pensions Institute, London, PI-0901
Biffis E, 2008, Pricing of life insurance liabilities, Encyclopedia of Quantitative Risk Assessment and Analysis, Editors: Melnick, Everitt, New York, Publisher: John Wiley & Sons
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