We describe a general equilibrium model with a banking system in which the deposit bank collects deposits from households and the merchant bank provides funds to firms. The merchant bank borrows collateralized short-term funds from the deposit bank. In an economic downturn, as the value of collateral decreases, the merchant bank must sell assets on short notice, reinforcing the crisis, and defaults if its cash buffer is insufficient. The deposit bank suffers from losses because of the depreciated assets. If the value of the deposit bank's assets is insufficient to cover deposits, it also defaults. Deposits are insured by the government, with a premium paid by the deposit bank equal to its expected loss on the deposits. We define the bank's capital shortfall in the crisis as the expected loss on deposits under stress. We calibrate the model on the U.S. economy and show how this measure of stressed expected loss behaves for different calibrations of the model. A 40% decline of the securities market would induce a loss of 12.5% in the ex-ante value of deposits.

We develop a methodology to measure the expected loss of commercial banks in a market downturn, which we call stressed expected loss (SEL). We simulate a market downturn as a negative shock on interest rate and credit market risk factors that reflect the banks’ market-sensitive assets. We measure SEL as the difference between the mark-to-market value of the assets in the downturn and the book value of the liabilities. Based on large U.S. commercial banks, we empirically demonstrate that individual SEL predicts the loss of capital projected by banks in a severely adverse scenario and that aggregate SEL predicts macroeconomic variables.

Central banks are increasingly concerned about climate-related risks and want to ensure that the financial system is resilient to them. As they integrate these risks into financial stability monitoring, they also discuss how to apply environmental criteria to their own policy portfolio management, without compromising their policy mandate. We describe different strategies and assess their relevance for central banks, using the Swiss National Bank’s (SNB) equity portfolio as a laboratory. We develop a carbon-conscious screening approach that is likely consistent with its policy mandate. The approach reduces the portfolio’s carbon footprint by 20%, with little impact on diversification or performance.

We quantify the bank capital shortfall that results from a financial crisis by estimating a macro-finance dynamic stochastic general equilibrium model that captures the interactions between the financial and real sectors of the euro-area economy. The introduction of both deposit and shadow banks captures several characteristics of the banking system and reveals a financial amplification mechanism. By using a combination of a large positive risk shock and a large negative investment shock, we show that a crisis similar to that observed in 2008 would generate a bank capital shortfall between 2.2% and 3% of euro-area GDP, which corresponds to approximately 207–282 billion euros.

Average skewness, which is the average of monthly skewness values across firms, performs well at predicting future market returns. This prediction still holds after controlling for the size or liquidity of the firms or for current business cycle conditions. Also, average skewness compares favorably with other economic and financial predictors of subsequent market returns. The asset allocation exercise based on predictive regressions also shows that average skewness generates superior performance.

We estimate a general microstructure model of the transitory and permanent impact of order flow on stock prices. Jumps are detected in both the transaction price (observation equation) and fundamental value (state equation). The model’s parameters and variances are updated in real time. Prices can be altered by both the size and direction of trades, and the effects of buy-initiated and sell-initiated trades are different. We estimate this model using tick-by-tick data for 12 large-capitalization stocks traded on the Euronext-Paris Bourse. We find that, at tick frequency, the overnight return, the intraday jumps, and the continuous innovations represent approximately 7%,8.5%, and 36.7% of the total variation of stock returns. The microstructure model explains on average 47.7% of the total variation. Once jumps are filtered and parameters are estimated in real time, we also find that the price impact of trades is symmetric on average. However, the price of highly liquid stocks with a large proportion of sell-initiated orders tends to be more sensitive to buy trades, whereas the price of less liquid stocks with a large proportion of buy-initiated orders tends to be more sensitive to sell trades.

In this paper, we compare various methods that extract a Risk Neutral Density (RND) out of PIBOR interest-rate futures options and we investigate how traders react to a political event. Our benchmark model derives from A. Brace, D. Ga̧tarek, M. Musiela [Mathematical Finance 7 (1997) 127–155]. We also consider a mixture of log-normals (as in W.R. Melik, C.P. Thomas, Journal of Financial and Quantitative Analysis 32 (1997) 91–116), an Hermite expansion (as in P. Abken, D.B. Madan, S. Ramamurtie, Estimation of risk-neutral and statistical densities by Hermite polynomial approximation: with an application to Eurodollar Futures Options, Federal Reserve Bank of Atlanta, 1996), and a method based on Maximum Entropy (according to P. Buchen, M. Kelly, Journal of Financial and Quantitative Analysis 31 (1996) 143–159). We take care of the early exercise feature and we show how to approximate RNDs for a fixed time to maturity. The various methods generate similar RNDs. A daily panel of options running from February 1997 to July 1997 reveals that operators expected the snap election a few days before the official announcement was made and that a substantial amount of political uncertainty subsisted even a month after the elections. Uncertainty evolved with polls forecasts of the future government.

Systemic risk may be defined as the propensity of a financial institution to be undercapitalized when the financial system as a whole is undercapitalized. In this article, we investigate the case of non-US institutions, with several factors explaining the dynamics of financial firms returns and with asynchronicity of time zones. We apply this methodology to the 196 largest European financial firms and estimate their systemic risk over the 2000–12 period. We find that, for certain countries, the cost for the taxpayer to rescue the riskiest domestic banks is so high that some banks might be considered too big to be saved.

Pástor and Stambaugh (2012) find that from a forward-looking perspective, stocks are more volatile in the long run than they are in the short run. We demonstrate that when the nonnegative equity premium (NEP) condition is imposed on predictive regressions, stocks are in fact less volatile in the long run, even after taking estimation risk and uncertainties into account. The reason is that the NEP provides an additional parameter identification condition and prior information for future returns. Combined with the mean reversion of stock returns, this condition substantially reduces uncertainty on future returns and leads to lower long-run predictive variance.