To avert the impending global Cyber-Finance Insurance Crisis based upon large-scale commercial reliance upon quantitative models with inherent model risks, tail risks, and systemic risks in current form, this post-doctoral thesis makes the following key contributions: Develops the first known...

The amount of credit in the economy is a heterogeneous aggregate that can be analyzed across different dimensions. Considering such dimensions provides insights into the effect of monetary policy interventions because the credit components are observed to respond differently. Several possible...

The rapid spread of COVID-19 across the globe primed a variety of non-pharmaceutical interventions (NPIs). Given these NPIs, whether the SIR parameters followed a Bayesian learning, a random walk pattern or other type of learning with evolving epidemiological data over time has implications for...

Why should risk management systems account for parameter uncertainty? In order to answer this question, this paper lets an investor in a credit portfolio face non-diversifiable estimation-driven uncertainty about two parameters: probability of default and asset-return correlation. Bayesian...

In the Canadian large value payment system an important goal is to understand how liquidity is transferred through the system and hence how efficient the system is in settling payments. Understanding the structure of the underlying network of relationships between participants in the payment...

Recently, economists have argued that a bank’s importance within the financial system depends not only on its individual characteristics but also on its position within the banking network. A bank is deemed to be “central” if, based on our network analysis, it is predicted to hold the most...

We use a method similar to Google’s PageRank procedure to rank banks in the Canadian Large Value Transfer System (LVTS). Along the way we obtain estimates of the payment processing speeds for the individual banks. These differences in processing speeds are essential for explaining why observed...

We describe a method to improve credit portfolio models based on the Merton model by adding to the underlying distributions forward-looking tails deducted through the Bayesian Networks technology. Given the forward-looking stance of the approach, its results give a better quanti ed picture of...

We present and estimate a Bayesian Hierarchical model of mutual fund returns. In our model, a fund's alpha reflects not only that fund's return history, but also information from other fund returns. Because parameters are estimated simultaneously for all funds, we can identify common residual...

This paper utilizes a Bayesian hierarchical model to study the distribution of skill (alphas) among mutual funds. The hierarchical model specifies a probability distribution over all parameters and funds, making it possible to formally analyze the variability of alphas across funds. In addition,...