#9 Spotkanie Entuzjastów R w Krakowie

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We are happy to announce ninth eRka meetup. This time we will focus on financial modelling.

18:30 – 18:40 – Welcome

18:40 – 19:15 – “Modelling death probability in R” – Adam Wróbel

19:25 – 20:00 – "Monte Carlo simulation of a correlated credit counterparty risk in R" – Grzegorz Goryl

If there will be interest from non-polish speakers then presentations will be delivered in English.

BIOs and presentations abstracts

Adam Wróbel

Graduated from Warsaw School of Economics (SGH) in quantitative methods. Definitely R and data science enthusiast. Currently working as quant in model validation team for UBS. Before that he worked as an actuary for Nationale Nederlanden (life insurance).

Presentation: Modelling death probability in R

Presentation will provide overview of stochastic mortality models (Lee Carter is one of them) as a way to project future death probability. Such projections are needed to price and valuate an life insurance and pension products. It is also used for demographic projections. It is intended that presentation will be focused on: intuition, code and math behind models. Presentation will be narrowed to Polish mortality tables.

Grzegorz Goryl

Received PhD in physics at Jagiellonian University. Since 2011 he has been working as a quant, first in a hedge fund and then in an investment bank. Currently he is working on a quant position in the Risk Methodology team in the UBS. He is interested in the applying and implementing mathematical, esp. statistical, models into real life problems. His field of expertise covers mainly credit counterparty risk, credit derivatives and algorithmic trading.

Monte Carlo simulation of a correlated credit counterparty risk in R

Recently values of financial instruments have started to be adjusted according to risk related to a probability that a counterparty will default. The simplest instrument is a bond, where issuer default probability impacts yield to maturity. Another, very common instrument is credit default swap (CDS) used to hedge against default event of the bond issuer, for example. However, CDS issuer is also not default risk free. In this presentation it is shown how to simulate in R value of a portfolio consisting of a bond issued by counterparty A, and CDS referenced to A issued by counterparty B. However, there is another assumption, that counterparties A and B are correlated, and the correlation is defined on a default times level.