Margin Requirements and Systemic Liquidity Risk

Margin requirements and systemic liquidity risk

Liquidity risk and the performance of UK mutual funds

Systematic Liquidity Risk and Stock Price Reaction to Shocks: Evidence from London Stock Exchange

The information content of Basel III liquidity risk measures

I construct a systemic liquidity risk index (SLRI) from data on violations of arbitrage relationships across several asset classes between 2004 and 2010. Then I test whether the equity returns of 53 global banks were exposed to this liquidity risk factor. Results show that the level of bank returns is not directly affected by the SLRI, but their volatility increases when liquidity conditions deteriorate. I do not find a strong association between bank size and exposure to the SLRI - measured as the sensitivity of volatility to the index. Surprisingly, exposure to systemic liquidity risk is positively associated with the Net Stable Funding Ratio (NSFR). The link between equity volatility and the SLRI allows me to calculate the cost that would be borne by public authorities for providing liquidity support to the financial sector. I use this information to estimate a liquidity insurance premium that could be paid by individual banks in order to cover for that social cost.

This study examines the relationship between systematic liquidity risk and stock price reaction to large 1‐day price changes (or shocks). We base our analysis on a yearly updated constituents list of the FTSE All share index. Our overall results are consistent with the price continuation hypothesis, which suggests that positive (negative) shocks will be followed by positive (negative) abnormal returns. However, further analysis indicates that stocks with low systematic liquidity risk react efficiently to both positive and negative shocks, whereas stocks with high systematic liquidity risk underreact to both positive and negative shocks. Our results are valid irrespective of various robustness tests such as size of the shock, size of the firm, month‐of‐the‐year and day‐of‐the‐week effects. We conclude that trading on price patterns following shocks may not be profitable, as it involves taking substantial liquidity exposure.

Firm size, ownership structure, and systematic liquidity risk: The case of an emerging market

This study examines whether systematic liquidity risk is priced on the London Stock Exchange (LSE). We use the proportional quoted bid-ask spread, Amihud's (2002) market illiquidity ratio, and turnover rate as liquidity proxies. In contrast to the US studies, we do not find evidence that systematic liquidity risk is priced on the LSE.

The thesis is composed of three main chapters each with an independent objective. The first inspects the main funding risk drivers employing a multivariate copula estimation. The second looks at the systemic liquidity risk asking whether macroeconomic fluctuations can trigger and create simultaneous liquidity shortages in banks’ funding position using agent based model(ABM). The third examines the funding liquidity risk’s procyclical behaviour to macroeconomic changes using a feedback mechanism. The findings of the three chapters, are as follow: Chapter 2, detects and quantifies the main funding liquidity risk drivers and shows that commercial banks’ Net Stable Funding Ratio (NSFR) substantially decreases when macroeconomic adverse conditions are applied. In Chapter 3 the results suggest that banks face simultaneous liquidity shortages when the economy’s agents operate under economic recession. Chapter 4 indicates that funding risk is pro cyclical to the macroeconomic fluctuations while large banks’ responses assist on withstanding substantial liquidity shortages when macroeconomic shocks are applied. This study contributes to the literature in three folds: 1) Introduces a new stress test scope by assessing funding liquidity risk and its interrelations with the macroeconomic environment. 2) Provides evidence on prudential policies by incorporating systemic liquidity risk in macro prudential stress test framework. 3) Measures funding liquidity risk pro-cyclical, by developing a second round effects mechanism.

The Profitability of Risk Arbitrage in Mergers and Acquisitions

Systemic Funding Liquidity Risk and Bank Failures

By stepping between bilateral counterparties, a central counterparty (CCP) transforms credit exposure. CCPs generally improve financial stability. Nevertheless, large CCPs are by nature concentrated and interconnected with major global banks. Moreover, although they mitigate credit risk, CCPs create liquidity risks, because they rely on participants to provide cash. Such requirements increase with both market volatility and default; consequently, CCP liquidity needs are inherently procyclical. This procyclicality makes it more challenging to assess CCP resilience in the rare event that one or more large financial institutions default. Liquidity-focused macroprudential stress tests could help to assess and manage this systemic liquidity risk.

This article examines the influence of liquidity risk on the U.S. secondary corporate loan market (herein loan market). The authors empirically disentangle the impact of both loan-level liquidity shocks and systematic liquidity risk from default risk. Loans that experience shocks to either liquidity or default risk experience ongoing price declines, complementing evidence presented elsewhere of price momentum in loan markets. The prices of loans with high liquidity risk are significantly discounted when market liquidity is low, consistent with the time-varying funding liquidity constraints of financial intermediaries. In keeping with a close link between high risk debt markets and equity markets, there is evidence that equity market risk is priced in the loan market.

When a widespread funding shock hits the banking system, banks may engage in strategic behaviour to deal with funding shortages by a pre-emptive disposal of assets. Alternatively, they may adopt a more cautious strategy to mitigate price reactions, thereby distributing the assets sales into smaller portions over time. We model banks’ optimal behaviour using standard optimisation techniques and show that an equilibrium always exits in a stylised setting. A numerical analysis to approximate the equilibrium supplements the theoretical part. The implementation delivers two liquidity measures for the German banking system: the Systemic Liquidity Buffer and the Systemic Liquidity Shortfall. These measures are more informative about systemic liquidity risk than regulatory liquidity measures, such as the LCR, because they model adverse, nonlinear price dynamics in a more realistic way. Our approach is applied to different stress scenarios.

Implied Bond Liquidity