Systemic risk for financial institutions in UK

Marginal Expected Shortfall (MES) is an approach used to measure the systemic risk financial institutions face. It estimates how significantly systemic events (poor market performance, out of 1.6 times Standard Deviation borders) are expected to affect market capitalization of a particular firm. The concept was developed in the late 2000s and is widely used for cross-country comparisons of financial firms. For the purposes of generalization of this technique it is often used with market data containing non-domestic currencies for some financial firms. That may lead to results having currency noise in them as it is shown for 77 UK financial firms in our analysis between 2001 and 2014.

An agent-based simulator to estimate domestic energy use

Throughout recent years, there has been an increase in the population size, as well as a fast economic growth, which has led to an increase of the energy demand that comes mainly from fossil fuels. In order to reduce the ecological footprint, governments have implemented sustainable measures and it is expected that by 2035 the energy produced from renewable energy sources, such as wind and solar would be responsible for one-third of the energy produced globally. However, since the energy produced from renewable sources is governed by the availability of the respective primary energy source there is often a mismatch between production and demand, which could be solved by adding flexibility on the demand side through demand response (DR). DR programs influence the end-user electricity usage by changing its cost along the time. Under this scenario the user needs to estimate the energy demand and on-site production in advance to plan its energy demand according to the energy price. This work focuses on the development of an agent-based electrical simulator, capable of: (a) estimating the energy demand and on-site generation with a 1-min time resolution for a 24-h period, (b) calculating the energy price for a given scenario, (c) making suggestions on how to maximize the usage of renewable energy produced on-site and to lower the electricity costs by rescheduling the use of certain appliances. The results show that this simulator allows reducing the energy bill by 11% and almost doubling the use of renewable energy produced on-site.

Testing for tail breaks in currency returns

In this work project we study the tail properties of currency returns and analyze whether changes in the tail indices of these series have occurred over time as a consequence of turbulent periods. Our analysis is based on the methods introduced by Quintos, Fan and Phillips (2001), Candelon and Straetmans (2006, 2013), and their extensions. Specifically, considering a sample of daily data from December 31, 1993 to February 13, 2015 we apply the recursive test in calendar time (forward test) and in reverse calendar time (backward test) and indeed detect falls and rises in the tail indices, signifying increases and decreases in the probability of extreme events.