Short-term wholesale funding and systemic risk: A global CoVaR approach

We use the CoVaR approach to identify the main factors behind systemic risk in a set of large international banks. We find that short-term wholesale funding is a key determinant in triggering systemic risk episodes. In contrast, we find weaker evidence that either size or leverage contributes to systemic risk within the class of large international banks. We also show that asymmetries based on the sign of bank returns play an important role in capturing the sensitivity of system-wide risk to individual bank returns. Since short-term wholesale funding emerges as the most relevant systemic factor, our results support the Basel Committee’s proposal to introduce a net stable funding ratio, penalizing excessive exposure to liquidity risk.     

Practical methods for measuring and managing operational risk in the financial sector: A clinical study

This paper analyzes the implications of the advanced measurement approach (AMA) for the assessment of operational risk. Through a clinical case study on a matrix of two selected business lines and two event types of a large financial institution, we develop a procedure that addresses the major issues faced by banks in the implementation of the AMA. For each cell, we calibrate two truncated distributions functions, one for “normal” losses and the other for the “extreme” losses. In addition, we propose a method to include external data in the framework. We then estimate the impact of operational risk management on bank profitability, through an adapted measure of RAROC. The results suggest that substantial savings can be achieved through active management techniques.     

Hedging the black swan: Conditional heteroskedasticity and tail dependence in S&P500 and VIX

The recent financial crisis has accentuated the fact that extreme outcomes have been overlooked and not dealt with adequately. While extreme value theories have existed for a long time, the multivariate variant is difficult to handle in the financial markets due to the prevalent heteroskedasticity embedded in most financial time series, and the complex extremal dependence that cannot be conveniently captured by a single structure. Moreover, most of the existing approaches are based on a limiting argument in which all variables become large at the same rate. In this paper, we show how the conditional approach of Heffernan and Tawn (2004) can be implemented to model extremal dependence between financial time series. We use a hedging example based on VIX futures to demonstrate the flexibility and superiority of the conditional approach against the conventional OLS regression approach.     

A simple continuous measure of credit risk

This paper introduces a simple parameterization for the risk-neutral default probability distributions for risky firms that are easily computed from quoted bond prices. The corresponding expected times to default have a particularly simple form and are proposed as a measure for credit risk. Being continuous in nature, times to default provide a much finer measure of risk than those provided by ratings agencies. Comparison with the ratings provided by Moody's and the distance to default measures calculated using the Merton [Merton, R. (1974). On the pricing of corporate debt: the risk structure of interest rates. Journal of Finance, 2(2), 449-470] model shows that the highest rank correlation is found between the proposed time to default measure and Moody's ratings.     

How important is asymmetric covariance for the risk premium of international assets?

This paper empirically investigates the importance of asymmetric conditional covariance when computing the risk premium of international assets. Conditional second moment asymmetry of equity indices is significant and varies over time. The risk premia estimated allowing for asymmetry are statistically and economically different from risk premia estimated without allowing for asymmetry. In particular, an international investor who ignores covariance asymmetry overestimates required returns for equities of the G4 countries and for the world market, on average.     

Bank CEO materialism: Risk controls,culture and tail risk

We investigate how the prevalence of materialistic bank CEOs has evolved over time, and how risk management policies, non-CEO executives’ behavior and tail risk vary with CEO materialism. We document that the proportion of banks run by materialistic CEOs increased significantly from 1994 to 2004, that the strength of risk management functions is significantly lower for banks with materialistic CEOs, and that non-CEO executives in banks with materialistic CEOs insider trade more aggressively around government intervention during the financial crisis. Finally, we find that banks with materialistic CEOs have significantly more downside tail risk relative to banks with non-materialistic CEOs.     

When more is less: Using multiple constraints to reduce tail risk

Financial institutions suffered large trading losses during the 2007–2009 global financial crisis. These losses cast doubt on the effectiveness of regulations and risk management systems based on a single Value-at-Risk (VaR) constraint. While some researchers have recommended using Conditional Value-at-Risk (CVaR) to control tail risk, VaR remains popular among practitioners and regulators. Accordingly, our paper examines the effectiveness of multiple VaR constraints in controlling CVaR. Under certain conditions, we theoretically show that they are more effective than a single VaR constraint. Furthermore, we numerically find that the maximum CVaR permitted by the constraints is notably smaller than with a single constraint. These results suggest that regulations and risk management systems based on multiple VaR constraints are more effective in reducing tail risk than those based on a single VaR constraint.     

Predicting anomaly performance with politics,the weather,global warming,sunspots, and the stars

Predictive regressions find that the party of the US president, the weather in Manhattan, global warming, the El Niño phenomenon, sunspots, and the conjunctions of the planets all have significant power predicting the performance of popular anomalies. The interpretation of these results has important implications for the asset pricing literature.     

Cyclicality in catastrophic and operational risk measurements

Using equity returns for financial institutions we estimate both catastrophic and operational risk measures over the period 1973–2003. We find evidence of cyclical components in both the catastrophic and operational risk measures obtained from the generalized Pareto distribution and the skewed generalized error distribution. Our new, comprehensive approach to measuring operational risk shows that approximately 18% of financial institutions’ returns represent compensation for operational risk. However, depository institutions are exposed to operational risk levels that average 39% of the overall equity risk premium. Moreover, operational risk events are more likely to be the cause of large unexpected catastrophic losses, although when they occur, the losses are smaller than those resulting from a combination of market risk, credit risk or other risk events.     

Measuring portfolio credit risk correctly: Why parameter uncertainty matters

Why should risk management systems account for parameter uncertainty? In addressing this question, the paper lets an investor in a credit portfolio face non-diversifiable uncertainty about two risk parameters – probability of default and asset-return correlation – and calibrates this uncertainty to a lower bound on estimation noise. In this context, a Bayesian inference procedure is essential for deriving and analyzing the main result, i.e. that parameter uncertainty raises substantially the tail risk perceived by the investor. Since a measure of tail risk that incorporates parameter uncertainty is computationally demanding, the paper also derives a closed-form approximation to such a measure.     

A systematic approach to multi-period stress testing of portfolio credit risk

We propose a new method for analysing multi-period stress scenarios for portfolio credit risk more systematically than in current macro stress tests. The plausibility of a scenario is quantified by its distance from an average scenario. For a given level of plausibility, we search systematically for the most adverse scenario. This ensures that no plausible scenario will be missed. We show how this method can be applied to some models already in use by practitioners. While worst case search requires numerical optimisation we show that we can work with reasonably good linear approximations to the portfolio loss function. This makes systematic multi-period stress testing computationally efficient and easy to implement. Applying our approach to data from the Spanish loan register we show that, compared to standard stress test procedures, our method identifies more harmful scenarios that are equally plausible.     

Stock market development under globalization: Whither the gains from reforms?

Over the past decades, many countries have implemented significant reforms (including financial liberalization, privatization, and regulatory and supervisory improvements) to foster domestic capital market development. Despite these policies, the performance of capital markets in several countries has been disappointing. To understand the effects of reforms, we study the impact of six capital market reforms on domestic stock market development and internationalization. We find that reforms tend to be followed by increases in domestic market capitalization and trading. But reforms are also followed by an increase in the share of activity in international equity markets, with potential negative spillover effects.     

Asset financing with credit risk

This paper develops a model for the unified valuation of all forms of real asset financing, such as bank loans, leases, securitization vehicles, and credit guarantees, secured by assets that generate a stochastic service flow to the operator, or a rental stream to the lessor, and depreciate over a finite economic life to their scrap value. Examples include mobile equipment, such as aircraft, railroad equipment, ships, trucks and trailers, as well as energy generation assets, heavy factory equipment and construction equipment. In the event of obligor default, after a repossession delay and incurring costs of repossession, maintenance, re-marketing and re-deployment, the lender repossesses the asset and sells it on the secondary market and is, thus, subject to the risk of decline in the market value of the asset. The model we develop in this paper treats all forms of asset financing in a unified fashion as contingent claims on the collateral asset and the credit of the borrower. As an application, we estimate the collateral asset model on historical secondary market data for aircraft values and calibrate the financing model to the Enhanced Equipment Trust Certificates (EETCs) issued in 2007 by Continental Airlines and secured by a fleet of new aircraft. We then apply the calibrated model to value private market financing, including bank loans, leases, and credit guarantees, consistently with the capital market financing, and assess the impact of repossession delays on credit spreads. This analysis leads to a policy insight suggesting that bankruptcy laws limiting asset repossession delays lead to lower costs of asset financing.     

Mapping global money laundering trends: Lessons from the pace setters

This paper uses an exploratory data analysis tool to map countries according to key factors—internet penetration rates, brain drain, efficiency of legal system, and effective tax and financial systems on the incidence of money laundering. Pace setters and laggards in the pervasiveness of money laundering for 88 countries will be identified. The results indicate that pace setters have high development of internet adoption, low incidence of brain drain, sound legal, tax and financial systems, and low incidence of money laundering. From the study, key policy initiatives adopted by pace-setter countries to reduce money laundering activities were examined.     

Systemic risk contributions: A credit portfolio approach

We put forward a framework for measuring systemic risk and attributing it to individual banks. Systemic risk is coherently measured as the expected loss to depositors and investors when a systemic event occurs. The risk contributions are calculated so as to ensure a full risk allocation among institutions. Applying our methodology to a panel of 54–86 of the world’s major commercial banks for a 13-year time span with monthly frequency not only allows us to closely match the list of G-SIBs; we can also use individual risk contributions to compute bank-specific surcharges: systemic capital charges as well as countercyclical buffers. We therefore address both dimensions of systemic risk – cross-sectional and time-series – in a single integrated approach. As the analysis of risk drivers confirms, the main focus of macroprudential supervision should be on a solid capital base throughout the financial cycle and de-correlation of banks’ asset values.     

The term structure of banking crisis risk in the United States: A market data based compound option approach

We use a compound option-based structural credit risk model to estimate banking crisis risk for the United States based on market data on bank stocks on a daily frequency. We contribute to the literature by providing separate information on short-term, long-term and total crisis risk instead of a single-maturity risk measure usually inferred by Merton-type models or barrier models. We estimate the model by applying the Duan (1994) maximum-likelihood approach. A strongly increasing total crisis risk estimated from early July 2007 onwards is driven mainly by short-term crisis risk. Banks that defaulted or were overtaken during the crisis have a considerably higher crisis risk (especially higher long-term risk) than banks that survived the crisis.     

Point and Figure charting: A computational methodology and trading rule performance in the S&P 500 futures market

This paper empirically contributes to the existing trading rule literature by providing a methodology for the calculation of Point and Figure charts using ultra-high-frequency data and tests trading rules using eight objective, pre-defined trading rules on S&P 500 futures contracts traded between 1990 and 1998. To assess the robustness of reported profits, a bootstrapping adjustment was conducted to determine the forecasting power of the PF trading rules. The results producing mixed statistical significance with some rules proving significant while many others were not.     

THE CHOICE OF TRADING VENUE AND RELATIVE PRICE IMPACT OF INSTITUTIONAL TRADING: ADRs VERSUS THE UNDERLYING SECURITIES IN THEIR LOCAL MARKETS

We address two important themes associated with institutions’ trading in foreign markets: (1) the choice of trading venues (between a company's listing in its home market and that in the United States as an American Depositary Receipt [ADR]) and (2) the comparison of trading costs across the two venues. We identify institutional trading in both venues using proprietary institutional trading data. Overall, our research underscores the intuition that the choice of institutional trading in a stock's local market or as an ADR is a complex process that embodies variables that measure the relative adverse selection and liquidity at order, stock, and country levels. Institutions route a higher percentage of trades to more liquid markets, and these trades are associated with higher cumulative abnormal returns. We also find that institutional trading costs are generally lower for trading cross‐listed stocks on home exchanges even after controlling for selection bias.     

How do policy and information shocks impact co-movements of China’s T-bond and stock markets?

We investigate the impacts of policy and information shocks on the correlation of China’s T-bond and stock returns, using originally the asymmetric dynamic conditional correlation (DCC) model that allows for the coexistence of opposite-signed asymmetries. The co-movements of China’s capital markets react to large macroeconomic policy shocks as evidenced by structural breaks in the correlation following the drastic 2004 macroeconomic austerity. We show that the T-bond market and the bond–stock correlations bear more of the brunt of the macroeconomic contractions. We also find that the bond–stock correlations respond more strongly to joint negative than joint positive shocks, implying that investors tend to move both the T-bond and stock prices in the same direction when the two asset classes have been hit concurrently by bad news, but tend to shift funds from one asset class to the other when hit concurrently by good news. However, the stock–stock correlation is found to increase for joint positive shocks, indicating that investors tend to herd more for joint bullish than joint bearish stock markets in Shanghai and Shenzhen.     

A simple model of credit contagion

We propose a simple model of credit contagion in which we include macro- and microstructural interdependencies among the debtors within a credit portfolio. The microstructure captures interdependencies between debtors that go beyond their exposure to common factors, e.g., business or legal interdependencies. We show that even for diversified portfolios, moderate microstructural interdependencies have a significant impact on the tails of the loss distribution. This impact increases dramatically for less diversified microstructures.