This paper develops a copula-GARCH-MIDAS model to estimate the joint probability distribution of multivariate variables, and then derives CoVaR-type risk
Risk measures: a generalization from the univariate to the matrix-variate
This paper proposes a method to calculate matrix-variate value-at-risk.
This paper develops a method for estimating the value-at-risk and the conditional value-at-risk when the underlying risk factors follow a beta distribution in a univariate and matrix-variate setting.
Analytical expressions of the risk measures are developed.
A numerical solution for the risk measures for any parameterization of beta distributed loss variables is presented.
Of fundamental importance is the application of computer-based algorithms for solving classically analytic problems in financial risk management. The data we acquired from Colombian financial institutions are considered using both algorithmic and analytic methods. Our results demonstrate a correspondence between the two. Although our results are motivated by problems in finance, we believe that our methods may well more general applications as well.
Risk.net
Barclays quant proposes methodology for factoring hedging costs into derivatives valuations
Dealers make various adjustments to the fair value of derivatives contracts to account for the credit risk, funding costs and capital requirements associated with these transactions. But, somehow, the cost of hedging has so far escaped the attention of XVA desks.
While it is standard practice to set aside
ad hoc reserves to cover the cost of hedging, a formal mathematical formula for calculating these has been lacking. “Banks typically take transaction costs into account, but normally using just a heuristic approach,” says an XVA quant at a global bank.
Risk.net The slow corporate embrace of CSAs
Risk.net research finds 28 of 50 large companies now have CSAs – but has the trend run its course? Print this page
When Vodafone published its annual report in March last year, sharp-eyed investors may have spotted what looked like a red flag – a ballooning of the company’s short-term borrowing from €4.2 billion ($5.1 billion) in 2019 to €11.8 billion in 2020. Why had the telecoms giant loaded up on debt? And did it have anything to do with the Covid-19 lockdown that hit Europe just weeks before the report was filed?
In fact, it wasn’t a red flag at all – but there was a hidden connection to the pandemic.