This study attempts to quantify the shocks to a banking network and analyze the transfer of shocks through the network. We consider two sources of shocks: external shocks due to market and macroeconomic factors which impact the entire banking system, and idiosyncratic shocks due to failure of a single bank. The external shocks will be estimated by using two methods: (i) non-parametric simulation of the time series of shocks that occurred to the banking system in the past, and (ii) using the extreme value theory (EVT) to model the tail part of the shocks. The external shocks we considered in this study are due to exchange rate and treasury bill rate volatility. Also, an ARMA/GARCH model is used to extract iid residuals for this purpose. In the next step, the probability of the failure of banks in the system is studied by using Monte Carlo simulation. We calibrate the model such that the network resembles the Canadian banking system.

This study attempts to quantify the shocks to a banking network and analyze the transfer of shocks through the network. We consider two sources of shocks: external shocks due to market and macroeconomic factors which impact the entire banking system, and idiosyncratic shocks due to failure of a single bank. The external shocks will be estimated by using two methods: (i) non-parametric simulation of the time series of shocks that occurred to the banking system in the past, and (ii) using the extreme value theory (EVT) to model the tail part of the shocks. The external shocks we considered in this study are due to exchange rate and treasury bill rate volatility. Also, an ARMA/GARCH model is used to extract iid residuals for this purpose. In the next step, the probability of the failure of banks in the system is studied by using Monte Carlo simulation. We calibrate the model such that the network resembles the Canadian banking system.

This study attempts to quantify the shocks to a banking network and analyze the transfer of shocks through the network. We consider two sources of shocks: external shocks due to market and macroeconomic factors which impact the entire banking system, and idiosyncratic shocks due to failure of a single bank. The external shocks will be estimated by using two methods: (i) non-parametric simulation of the time series of shocks that occurred to the banking system in the past, and (ii) using the extreme value theory (EVT) to model the tail part of the shocks. The external shocks we considered in this study are due to exchange rate and treasury bill rate volatility. Also, an ARMA/GARCH model is used to extract iid residuals for this purpose. In the next step, the probability of the failure of banks in the system is studied by using Monte Carlo simulation. We calibrate the model such that the network resembles the Canadian banking system.

This study attempts to quantify the shocks to a banking network and analyze the transfer of shocks through the network. We consider two sources of shocks: external shocks due to market and macroeconomic factors which impact the entire banking system, and idiosyncratic shocks due to failure of a single bank. The external shocks will be estimated by using two methods: (i) non-parametric simulation of the time series of shocks that occurred to the banking system in the past, and (ii) using the extreme value theory (EVT) to model the tail part of the shocks. The external shocks we considered in this study are due to exchange rate and treasury bill rate volatility. Also, an ARMA/GARCH model is used to extract iid residuals for this purpose. In the next step, the probability of the failure of banks in the system is studied by using Monte Carlo simulation. We calibrate the model such that the network resembles the Canadian banking system.

Systemic risk is a complex topic, with a large number of variables and constraints. In this thesis we introduce an agent-based network to study the effects of financial shocks on the financial network. The model takes into consideration the repurchase agreement (repo) market and rehypothecation. We introduce a financial network consisting of financial agents who are connected through direct channels (bilateral contracts) and indirect channels (markets). Each fi- nancial agent has a balance sheet with liquid assets (cash), collateral (bonds, shares), reverse repo assets, fixed assets (loans and mortgages) on the asset side and repo loans, deposits and equities on the liability side. Agents (i.e., banks) need to satisfy constraints on (i) liquidity, which deals with financial shocks, (ii) collateral, related to repo liabil- ities, rehypothecation, and (iii) solvency constraints, ensuring that equity is positive. Liquidity constrain can be broken by a financial shock (e.g., a bank run), while the collateral constraint can be broken by hoarding credit and collateral price reduction. When liquidity and collateral constraints are broken the financial agent will try to fix them through recalling reverse repos and firesale of fixed assets. Banks that fail to fix their constraints by the end of the day will be considered defaulted. We introduce netting and novation techniques to deal with defaulted banks and lower the stress on the financial markets. In the netting step we lower the exposure of financial agents by removing cycles in the repo liabilities between banks, while in the novation we redistribute the ownership of bilateral contracts and settle any residuals that are left. We also establish that, under certain conditions on the set of defaulted banks, that the novation step is order indifferent. Different network topologies and balance sheet compositions are tested under several financial shocks to check the robustness of the financial network under our framework. / Thesis / Doctor of Philosophy (PhD)