Talks in financial and insurance mathematics

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Spring Semester 2020

Date / Time

Speaker

Title

Location

20 February 2020
17:15-18:15

Martin Herdegen
University of Warwick

Event Details

Talks in Financial and Insurance Mathematics

Title	A Dual Characterisation of Regulatory Arbitrage for Coherent Risk Measure
Speaker, Affiliation	Martin Herdegen, University of Warwick
Date, Time	20 February 2020, 17:15-18:15
Location	HG G 43
Abstract	We revisit portfolio selection in a one-period financial market under a coherent risk measure constraint, the most prominent example being Expected Shortfall (ES). Unlike in the case of classical mean-variance portfolio selection, it can happen that no efficient portfolios exist. We call this situation regulatory arbitrage. We show that the presence or absence of regulatory arbitrage is intimately linked to the interplay between the set of equivalent martingale measures (EMMs) for the discounted risky assets and the set of absolutely continuous measures in the dual characterisation of the risk measure. In the special case of ES, our results show that the market does not admit regulatory arbitrage for ES at confidence level $\alpha$ if and only if there exists an EMM $Q \approx P$ such that $\Vert \frac{dQ}{dP} \Vert_\infty < \frac{1}{\alpha}$. The talk is based on joint work with my PhD student Nazem Khan.

A Dual Characterisation of Regulatory Arbitrage for Coherent Risk Measureread_more

HG G 43

27 February 2020
17:15-18:15

Alexander J. McNeil
The York Management School, University of York (UK)

Event Details

Talks in Financial and Insurance Mathematics

Title	Modelling Volatility with V-Transforms
Speaker, Affiliation	Alexander J. McNeil, The York Management School, University of York (UK)
Date, Time	27 February 2020, 17:15-18:15
Location	HG G 43
Abstract	An approach to the modelling of financial return series using a class of uniformity-preserving transforms for uniform random variables is proposed. V-transforms describe the relationship between quantiles of the return distribution and quantiles of the distribution of a predictable volatility proxy variable constructed as a function of the return. V-transforms can be represented as copulas and permit the construction and estimation of models that combine arbitrary marginal distributions with linear or non-linear time series models for the dynamics of the volatility proxy. The idea is illustrated using a transformed Gaussian ARMA process for volatility, yielding the class of VT-ARMA copula models. These can replicate many of the stylized facts of financial return series and facilitate the calculation of marginal and conditional characteristics of the model including quantile measures of risk. Estimation of models is carried out by adapting the exact maximum likelihood approach to the estimation of ARMA processes.

Modelling Volatility with V-Transformsread_more

HG G 43

19 March 2020
17:15-18:15

Agostino Capponi
Columbia University

Event Details

Talks in Financial and Insurance Mathematics

Title	Large Orders in Small Markets: On Optimal Execution with Endogenous Liquidity Supply
Speaker, Affiliation	Agostino Capponi, Columbia University
Date, Time	19 March 2020, 17:15-18:15
Location	HG G 43
Abstract	CANCELLED: We solve a continuous time dynamic Stackelberg game, where a large uninformed seller executes optimally, fully cognizant of the response of Cournot-competitive market makers. The game therefore endogenizes both demand and supply of liquidity. We provide closed form solutions for the value functions of market makers and large seller, the equilibrium bid/ask price, and the execution intensity. The closed-form solution yields several insights. First, stealth trading is both privately and socially costly because market makers incur additional costs not knowing when execution ends. Second, the presence of a large seller does not unambiguously benefit other participants. Market makers benefit only if there is enough risk-absorption capacity or if the execution period is short. Other investors benefit only when the seller sells at high enough intensity. The model explains quantitatively several empirical facts: order duration and participation rate correlate negatively, and price pressure subsides before execution ends. (based on joint work with Hongzhong Zhang and Albert Menkveld).

Large Orders in Small Markets: On Optimal Execution with Endogenous Liquidity Supplyread_more (CANCELLED)

HG G 43

25 March 2020
16:00-17:15

George Tzougas
London School of Economics

Event Details

Talks in Financial and Insurance Mathematics

Title	An EM Algorithm for Fitting Mixed Exponential Regression Models with Varying Dispersion
Speaker, Affiliation	George Tzougas, London School of Economics
Date, Time	25 March 2020, 16:00-17:15
Location	Zoom
Abstract	Regression modelling involving heavy-tailed response distributions, which have heavier tails than the exponential distribution, has become increasingly popular in many insurance settings including non-life insurance. Mixed Exponential models can be considered as a natural choice for the distribution of heavy-tailed claim sizes since their tails are not exponentially bounded. This paper is concerned with introducing a general family of mixed Exponential regression models with varying dispersion which can efficiently capture the tail behaviour of losses. Our main achievement is that we present an Expectation-Maximization (EM) type algorithm which can facilitate maximum likelihood (ML) estimation for our class of mixed Exponential models which allows for regression specifications for both the mean and dispersion parameters. Finally, a real data application based on motor insurance data is given to illustrate the versatility of the proposed EM type algorithm. Keywords:Mixed Exponential Distributions; EM Algorithm; Regression Models for the Mean and Dispersion parameters; Non-Life Insurance; Heavy-Tailed Losses

An EM Algorithm for Fitting Mixed Exponential Regression Models with Varying Dispersionread_more

Zoom

2 April 2020
17:15-18:15

Antonis Papapantoleon
National Technical University of Athens

Event Details

Talks in Financial and Insurance Mathematics

Title	CANCELLED!! TBA
Speaker, Affiliation	Antonis Papapantoleon, National Technical University of Athens
Date, Time	2 April 2020, 17:15-18:15
Location	HG G 43

CANCELLED!! TBA

HG G 43

8 April 2020
16:00-17:15

TBA

Event Details

Talks in Financial and Insurance Mathematics

Title	Title T.B.A.
Speaker, Affiliation	TBA ,
Date, Time	8 April 2020, 16:00-17:15
Location	HG G 43

Title T.B.A.

HG G 43

23 April 2020
16:00-17:00

Corina Constantinescu

Event Details

Talks in Financial and Insurance Mathematics

Title	Stochastic Mortality Modelling for Dependent Coupled Lives
Speaker, Affiliation	Corina Constantinescu,
Date, Time	23 April 2020, 16:00-17:00
Location	HG G 43
Abstract	Broken-heart syndrome is the most common form of short-term dependence, inducing a temporary increase in an individual’s force of mortality upon the occurrence of extreme events, such as the loss of a spouse. Socioeconomic influences on bereavement processes allow for suggestion of variability in the significance of short-term dependence between couples in countries of differing levels of economic development. Motivated by analysis of a Ghanaian data set, we propose a stochastic mortality model of the joint mortality of paired lives and the causal relation between their death times, in a less economically developed country than those considered in existing studies. The paired mortality intensities are assumed to be non-mean-reverting Cox–Ingersoll–Ross processes, reflecting the reduced concentration of the initial loss impact apparent in the data set. The effect of the death on the mortality intensity of the surviving spouse is given by a mean-reverting Ornstein–Uhlenbeck process which captures the subsiding nature of the mortality increase characteristic of broken-heart syndrome. Inclusion of a population wide volatility parameter in the Ornstein–Uhlenbeck bereavement process gives rise to a significant non-diversifiable risk, heightening the importance of the dependence assumption in this case. Applying the model proposed to an insurance pricing problem, we obtain the appropriate premium under consideration of dependence between coupled lives through application of the indifference pricing principle. Joint presentation with Kira Henshaw and Olivier Menoukeu-Pamen

Stochastic Mortality Modelling for Dependent Coupled Livesread_more

HG G 43

30 April 2020
16:00-17:00

Michal Pesta
(Charles University Prague)

Event Details

Talks in Financial and Insurance Mathematics

Title	Infinitely Stochastic Micro Forecasting
Speaker, Affiliation	Michal Pesta, (Charles University Prague)
Date, Time	30 April 2020, 16:00-17:00
Location	HG G 43
Abstract	Forecasting costs is now a front burner in empirical economics. We propose an unconventional tool for stochastic prediction of future expenses based on the individual (micro) developments of recorded events. Consider a firm, enterprise, institution, or state, which possesses knowledge about particular historical events. For each event, there is a series of several related subevents: payments or losses spread over time, which all leads to an infinitely stochastic process at the end. Nevertheless, the issue is that some already occurred events do not have to be necessarily reported. The aim lies in forecasting future subevent flows coming from already reported, occurred but not reported, and yet not occurred events. Our methodology is illustrated on quantitative risk assessment, however, it can be applied to other areas such as startups, epidemics, war damages, advertising and commercials, digital payments, or drug prescription as manifested in the talk. As a theoretical contribution, inference for infinitely stochastic processes is developed. In particular, a non-homogeneous Poisson process with non-homogeneous Poisson processes as marks is used, which includes for instance the Cox process as a special case.

Infinitely Stochastic Micro Forecastingread_more

HG G 43

14 May 2020
16:15-17:15

Martin Bladt

Event Details

Talks in Financial and Insurance Mathematics

Title	Time series copula models with v-transforms: an alternative to GARCH modelling
Speaker, Affiliation	Martin Bladt,
Date, Time	14 May 2020, 16:15-17:15
Location	HG
Abstract	We propose a general class of time series models to model return volatility. The main idea is to use a V-transform to relate the original time series to a volatility proxy, which can be modelled using copula time series processes. Using a construction that we refer to as stochastic inversion of a V-transform, we develop processes that can model the dynamics of the conditional mean as well as the volatility of return data. We illustrate the class of models using ARMA and D-vine copula processes for the implied volatility proxies. Using real world data, we show that these models are competitive and can sometimes outperform popular models from the GARCH family.

Time series copula models with v-transforms: an alternative to GARCH modellingread_more

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