Risk modeling comes in varying shapes and sizes throughout the financial world. Having previously worked as a derivatives trader on the Chicago Board Options Exchange and as a senior risk analyst, I ...

We propose a framework to link empirical models of systemic risk to theoretical network/ general equilibrium models used to understand the channels of transmission of systemic risk. The theoretical ...

Since 2008, over US$200 billion of operational risk losses have been incurred by large banks, mainly as a result of regulatory fines, lawsuits and demands for customer redress for various types of ...

In this paper we describe the use of hybrid dynamic Bayesian networks (HDBNs) to model the operational risk faced by financial institutions in terms of economic capital. We describe a methodology for ...

Factor modeling – the analysis of investment risks and the drivers of returns – has become increasingly sophisticated, thanks in large part to advanced technology and data science. Simply put, the ...

Powered by advanced factor research and daily refreshed data, Bloomberg’s MAC3 Risk Model transforms how investors see and manage risk in a multi-asset world. Bloomberg MAC3 gives investors a unified ...

As part of "shift left" to incorporate security discussions earlier in the software development life cycle, organizations are beginning to look at threat modeling to identify security flaws in ...

In the housing market, consumers need more tools to assess risks from climate change. As insurers improve their risk ...