Alfred Lehar

Using Market Information for Banking System Risk Assessment

We propose a new method for the analysis of systemic stability of a banking system relying mostly on market data. We model both asset correlations and interlinkages from interbank borrowing so that our analysis gauges two major sources of systemic risk: correlated exposures and mutual credit relations that may cause domino effects of insolvencies. We apply our method to a data set of the ten major UK banks and analyze insolvency risk over a one-year horizon. We also suggest a stress-testing procedure by analyzing the conditional asset return distribution that results from the hypothetical failure of individual institutions in this system. Rather than looking at individual bank defaults ceteris paribus, we take the change in the asset return distribution and the resulting change in the risk of all other banks into account. This takes previous stress tests of interlinkages a substantial step further.

Macroprudential Capital Requirements and Systemic Risk

When setting banks’ regulatory capital requirement based on their contribution to the overall risk of the banking system we have to consider that the risk of the banking system as well as each bank’s risk contribution changes once bank equity capital gets reallocated. We define macroprudential capital requirements as the fixed point at which each bank’s capital requirement equals its contribution to the risk of the system under the proposed capital requirements. We use a network based structural model to measure systemic risk and how it changes with bank capital and allocate risk to individual banks based on five risk allocation mechanisms used in the literature. Using a sample of Canadian banks we find that macroprudential capital allocations can differ by as much as 25% from observed capital levels, are not trivially related to bank size or individual bank default probability, increase in interbank assets, and differ substantially from a simple risk attribution analysis. We further find that across all risk allocation mechanisms macroprudential capital requirements reduce the default probabilities of individual banks as well as the probability of a systemic crisis by about 25%. Macroprudential capital requirements are robust to model risk and are positively correlated to future capital raised by banks as well as future losses in equity value. Our results suggest that financial stability can be substantially enhanced by implementing a systemic perspective on bank regulation.

GARCH vs. stochastic volatility: Option pricing and risk management

This paper examines the out-of-sample performance of two common extensions of the Black-Scholes framework, namely a GARCH and a stochastic volatility option pricing model. The models are calibrated to intraday FTSE 100 option prices. We apply two sets of performance criteria, namely out-of-sample valuation errors and Value-at-Risk oriented measures. When we analyze the fit to observed prices, GARCH clearly dominates both stochastic volatility and the benchmark Black Scholes model. However, the predictions of the market risk from hypothetical derivative positions show sizable errors. The fit to the realized profits and losses is poor and there are no notable differences between the models. Overall we therefore observe that the more complex option pricing models can improve on the Black Scholes methodology only for the purpose of pricing, but not for the Value-at-Risk forecasts. (authors abstract)

Handbook on Systemic Risk: Network Models and Systemic Risk Assessment

Abstract Over recent years a number of network models of interbank markets have been developed and applied to the analysis of insolvency contagion and systemic risk. In this chapter we survey the concepts used in these models and discuss their main findings as well as their applications in systemic risk analysis. Network models are designed to address potential domino effects resulting from the failure of financial institutions. Specifically they attempt to answer the question of whether the failure of one institution will result in the subsequent failure of others. Since in a banking crisis authorities usually intervene to stabilize the banking system, failures and contagious failures by domino effects are very rarely observed in practice. Empirical analysis is thus difficult and as a consequence most studies of insolvency contagion are built on simulation models. In this chapter we describe in some detail how such simulations are designed and discuss the main insights that have so far been obtained by applications to the complex network of real world exposure data of banking systems. Keywords Contagion, Interbank Market, Systemic Risk, Financial Stability. JEL-Classification Numbers: G21, C15, C81, E44 Introduction Will the failure of a financial institution be a threat to the stability of the banking system? This is a key question for authorities in the management of a financial crisis. At the height of a crisis the general level of uncertainty and the panic among market participants usually lead to stabilization policies and interventions of the public sector.

Industry Structure and the Strategic Provision of Trade Credit by Upstream Firms

Trade credit can serve as a strategic tool for a supplier to influence retailer behavior in the product market. The unique structure of trade credit, a period of free financing followed by a high interest rate increases the cost of rolling over unsold goods making retailers more aggressive when demand is low. Ex-ante retailers optimally hold smaller inventories which softens competition when demand is high. The modified product market behavior induced by trade credit financing increases the producer surplus at the expense of consumers and reduces welfare in oligopoly markets.

Imperfect Renegotiations in Interbank Financial Networks

Interbank financial networks enable banks to share the risks in their assets but potentially also increase systemic spillovers of insolvency from one bank to others in the network. We model a renegotiation game to explicitly examine the forgiveness of commitments of insolvent banks by solvent banks to limit the systemic transmission of financial distress. The assets of the insolvent bank can be appropriated by the forgiving bank in the two-bank network, but not the three-bank network, where they may be appropriated by the third bank, leading to a renegotiation breakdown. We also show how banks can ex ante optimally construct networks from interbank loans and derivatives to minimize the costs of such inefficient financial distress. This paper was accepted by Itay Goldstein, finance.

Bitcoin Microstructure and the Kimchi Premium

Between January 2016 and February 2018, Bitcoin were in Korea on average 4.73% more expensive than in the United States, a fact commonly referred to as the Kimchi premium. We argue that capital controls create frictions as well as amplify existing frictions from the microstructure of the Bitcoin network that limit the ability of arbitrageurs to take advantage of persistent price differences. We find that the Bitcoin premia are positively related to transaction costs, confirmation time in the blockchain, and to Bitcoin price volatility in line with the idea that the delay and the associated price risk during the transaction period make trades less attractive for risk averse arbitrageurs and hence allow prices to diverge. A cross country comparison shows that Bitcoin tend to trade at higher prices in countries with lower financial freedom. Finally unlike the prediction from the stock bubble literature, the Kimchi premium is negatively related to the trading volume, which also suggests that the Bitcoin microstructure is important to understand the Kimchi premium.