Tid: 9 juni 2017 kl 10.50-11.25.Seminarierummet 3418, Institutionen för matematik, KTH, Lindstedtsvägen 25, plan 4. Karta!
Föredragshållare: Martina Bartold
Titel: Modelling of private infrastructure debt in a risk factor model
Abstract Allocation to private infrastructure debt investments has increased in the recent years. For managers of multi-asset portfolios, it is important to be able to assess the risk of the total portfolio and the contribution to risk of the various holdings in the portfolio. This includes being able to explain the risk of having private infrastructure debt investments in the portfolio. The modelling of private infrastructure debt face many challenges, such as the lack of private data and public indices for private infrastructure debt. In this thesis, two approaches for modelling private infrastructure debt in a parametric risk factor model are proposed. Both approaches aim to incorporate revenue risk, which is the risk occurring from the type of revenue model in the infrastructure project or company. Revenue risk is categorised into three revenue models; merchant, contracted and regulated, as spread level differences can be distinguished for private infrastructure debt investments using this categorisation. The difference in spread levels between the categories are used to estimate coefficients for the two modelling approaches. The spread levels are obtained from a data set and from a previous study. In the first modelling approach, the systematic risk factor approach, three systematic risk factors are introduced where each factor represent infrastructure debt investments with a certain revenue model. The risk or the volatility for each of these factors is the volatility of a general infrastructure debt index adjusted with one of the coefficients. In the second modelling approach, the idiosyncratic risk term approach, three constant risk terms for the revenue models are added in order to capture the revenue risk for private infrastructure debt investments. These constant risk terms are estimated with the coefficients and the historical volatility of a infrastructure debt index. For each modelling approach, the commonly used risk measures standalone risk and risk contribution are presented for the entire block of the infrastructure debt specific factors and for each of the individual factors within this block. Both modelling approaches should enable for better explanation of risk in private infrastructure debt investments by introducing revenue risk. However, the modelling approaches have not been backtested and therefore no conclusion can be made in regards to whether one of the proposed modelling approaches actually is better than current modelling approaches for private infrastructure debt.
|Sidansvarig: Henrik Hult