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19 Results

A Calibrated Model of Intraday Settlement

Staff Discussion Paper 2018-3 Héctor Pérez Saiz, Siddharth Untawala, Gabriel Xerri
This paper estimates potential exposures, netting benefits and settlement gains by merging retail and wholesale payments into batches and conducting multiple intraday settlements in this hypothetical model of a single "calibrated payments system." The results demonstrate that credit risk exposures faced by participants in the system are largely dependent on their relative activity in the retail and wholesale payments systems.

Tail Risk in a Retail Payment System: An Extreme-Value Approach

Staff Discussion Paper 2018-2 Héctor Pérez Saiz, Blair Williams, Gabriel Xerri
The increasing importance of risk management in payment systems has led to the development of an array of sophisticated tools designed to mitigate tail risk in these systems. In this paper, we use extreme value theory methods to quantify the level of tail risk in the Canadian retail payment system (ACSS) for the period from 2002 to 2015.

On the Tail Risk Premium in the Oil Market

Staff Working Paper 2017-46 Reinhard Ellwanger
This paper shows that changes in market participants’ fear of rare events implied by crude oil options contribute to oil price volatility and oil return predictability. Using 25 years of historical data, we document economically large tail risk premia that vary substantially over time and significantly forecast crude oil futures and spot returns.

Credit Risk and Collateral Demand in a Retail Payment System

Staff Discussion Paper 2016-16 Héctor Pérez Saiz, Gabriel Xerri
The recent financial crisis has led to the development of new regulations to control risk in designated payment systems, and the implementation of new credit risk management standards is one of the key issues. In this paper, we study various credit risk management schemes for the Canadian retail payment system (ACSS) that are designed to cover the exposure of a defaulting member.

Measuring Systemic Risk Across Financial Market Infrastructures

Staff Working Paper 2016-10 Fuchun Li, Héctor Pérez Saiz
We measure systemic risk in the network of financial market infrastructures (FMIs) as the probability that two or more FMIs have a large credit risk exposure to the same FMI participant.

Volatility Forecasting when the Noise Variance Is Time-Varying

Staff Working Paper 2013-48 Selma Chaker, Nour Meddahi
This paper explores the volatility forecasting implications of a model in which the friction in high-frequency prices is related to the true underlying volatility. The contribution of this paper is to propose a framework under which the realized variance may improve volatility forecasting if the noise variance is related to the true return volatility.

Volatility and Liquidity Costs

Staff Working Paper 2013-29 Selma Chaker
Observed high-frequency prices are contaminated with liquidity costs or market microstructure noise. Using such data, we derive a new asset return variance estimator inspired by the market microstructure literature to explicitly model the noise and remove it from observed returns before estimating their variance.

Measuring Systemic Importance of Financial Institutions: An Extreme Value Theory Approach

Staff Working Paper 2011-19 Toni Gravelle, Fuchun Li
In this paper, we define a financial institution’s contribution to financial systemic risk as the increase in financial systemic risk conditional on the crash of the financial institution. The higher the contribution is, the more systemically important is the institution for the system.
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