8 research outputs found
Estimation and allocation of insurance risk capital
Estimating tail risk measures such as Value at Risk (VaR) and Conditional Tail Expectation
(CTE) is a vital component in financial and actuarial risk management.
The CTE is a preferred risk measure, due to coherence and a widespread acceptance
in actuarial community. In particular we focus on the estimation of the CTE using
both parametric and nonparametric approaches.
In parametric case the conditional tail expectation and variance are analytically
derived for the exponential distribution family and its transformed distributions.
For small i.i.d. samples the exact bootstrap (EB) and the influence function are
used as nonparametric methods in estimating the bias and the the variance of the empirical
CTE. In particular, it is shown that the bias is corrected using the bootstrap
for the CTE case. In variance estimation the influence function of the bootstrapped
quantile is derived, and can be used to estimate the variance of any bootstrapped
L-estimator without simulations, including the VaR and the CTE, via the nonparametric
delta method. An industry model are provided by applying theoretical findings
on the bias and the variance of the estimated CTE.
Finally a new capital allocation method is proposed. Inspired by the allocation
of the solvency exchange option by Sherris (2006), this method resembles the CTE
allocation in its form and properties, but has its own unique features, such as managerbased
decomposition. Through a numerical example the proposed allocation is shown
to fail the no undercut axiom, but we argue that this axiom may not be aligned with
the economic reality
Essays in Quantitative Risk Management for Financial Regulation of Operational Risk Models
An extensive amount of evolving guidance and rules are provided to banks by financial regulators. A particular set of instructions outline requirements to calculate and set aside loss-absorbing regulatory capital to ensure the solvency of a bank. Mathematical models are typically used by banks to quantify sufficient amounts of capital. In this thesis, we explore areas that advance our knowledge in regulatory risk management.
In the first essay, we explore an aspect of operational risk loss modeling using scenario analysis. An actuarial modeling method is typically used to quantify a baseline capital value which is then layered with a judgemental component in order to account for and integrate what-if future potential losses into the model. We propose a method from digital signal processing using the convolution operator that views the problem of the blending of two signals. That is, a baseline loss distribution obtained from the modeling of frequency and severity of internal losses is combined with a probability distribution obtained from scenario responses to yield a final output that integrates both sets of information.
In the second essay, we revisit scenario analysis and the potential impact of catastrophic events to that of the enterprise level of a bank. We generalize an algorithm to account for multiple level of intensities of events together with unique loss profiles depending on the business units effected.
In the third essay, we investigate the problem of allocating aggregate capital across sub-portfolios in a fair manner when there are various forms of interdependencies. Relevant to areas of market, credit and operational risk, the multivariate shortfall allocation problem quantifies the optimal amount of capital needed to ensure that the expected loss under a convex loss penalty function remains bounded by a threshold. We first provide an application of the existing methodology to a subset of high frequency loss cells. Lastly, we provide an extension using copula models which allows for the modeling of joint fat-tailed events or asymmetries in the underlying process
Innovations in Quantitative Risk Management
Quantitative Finance; Game Theory, Economics, Social and Behav. Sciences; Finance/Investment/Banking; Actuarial Science
A development model for the internationalization of SME agro-food of Puglia: the ISCI project
The project targets the Axis 1 of the European territorial cooperation INTERREG program
Greece-Italy 2007-2013. The project was born with the aim of strengthen the presence of the local agri-food
SMEs on the foreign markets, enhancing innovation processes through an economic and coordinated
cooperation so to ease the internationalization processes of the two targeted areas. After a literature review,
we analyzed the economic context of Apulia Region; then we proceed to the definition of a model for the
internationalization of SMEs Agro-food of Puglia through the constitution of scientific and technological
incubators that will network to deliver innovative services for the internationalization of the agri-food
system. The final aim is to develop innovative services of marketing intelligence (MI) to spread knowledge
and information about the international markets and the creation and implementation of databases for the
search and classification of informative sources
Current Topics on Risk Analysis: ICRA6 and RISK2015 Conference
Peer ReviewedPostprint (published version
Current Topics on Risk Analysis: ICRA6 and RISK2015 Conference
Artículos presentados en la International Conference on Risk Analysis ICRA 6/RISK
2015, celebrada en Barcelona del 26 al 29 de mayo de 2015.Peer ReviewedPostprint (published version