**Eric
Jondeau **

**Finance**

**A General Equilibrium Appraisal of Capital Shortfall** (with J.-G. Sahuc) (2018) Swiss Finance Institute Research Paper No. 18-12.

We quantify the capital shortfall that results from a global financial crisis by using a macro-finance dynamic stochastic general equilibrium model that captures the interactions between the financial and real sectors of the economy. We show that a crisis similar to that observed in 2008 generates a capital shortfall (or stressed expected loss, SEL) equal to 2.8% of euro-area GDP, which corresponds to approximately 250 billion euros. We also find that using a cycle-dependent capital ratio that combines concern for both credit growth and SEL has a positive effect on output growth while mitigating the excessive risk taking of the banking system. Finally, our estimates confirm that most of the variability of the macroeconomic and financial variables at business cycle frequencies is due to investment and risk shocks.

**Measuring the Capital Shortfall of Large U.S. Banks** (with A. Khalilzadeh) (2018) Swiss Finance Institute Research Paper No. 18-11.

We develop a new methodology to measure the capital shortfall of commercial banks during a market downturn. The measure, which we call stressed expected loss (SEL), adopts the structure of the individual bank's balance sheet. SEL is defined as the difference between the market value of assets in the stress scenario and the book value of the deposits and short-term debt of the bank. We estimate the probability of default and the SEL of the 31 largest commercial banks in the U.S. between 1996 and 2016. The probability of default in a market downturn was as high as 25%, on average, between 2008 and 2012. It is now much lower and close to 5%, on average. SEL was very high (between $250 and $350 billion) during the subprime crisis. In 2016, it is close to $200 billion.

**When are Stocks Less Volatile in the Long Run?** (with Q. Zhang and X. Zhu) (2017) Swiss Finance Institute Research Paper No. 18-07.

Pastor and Stambaugh (2012) demonstrate that from a forward-looking perspective, stocks are more volatile in the long run than they are in the short run. We investigate how the economic constraint of non-negative equity premia aspects predictive variance. When investors expect non-negative returns in the market and thus impose the constraint on predictive regressions, they find that stocks are less volatile in the long run, even after taking account of estimation risk and uncertainties on current and future expected stock returns because the constraint provides additional parameter identification condition and prior information for future returns. Thus, it substantially reduces uncertainty on future stock returns. This fact, combined with the mean reversion property of stock return dynamics, leads to lower predictive variance in the long run.

**Periodic or Generational Actuarial Tables: Which One to Choose**? (with S. Arnold-Gaille, A. Jijie, and M. Rockinger) (December 2017) Swiss Finance Institute Research Paper No. 17-71.

The increase in life expectancy over the past several decades has been impressive and represents a key challenge for institutions that provide life insurance products. Indeed, when a new actuarial table is released with updated survival and death rates, such institutions need to update the amount of mathematical reserve that they need to set aside to guarantee the future payments of their annuities. As mortality forecasting techniques are currently well developed, it is relatively easy to forecast mortality over several decades and to directly use these forecast rates in the determination of the mathematical reserve needed to guarantee annuity payments. Future mortality evolution is then directly incorporated into the liabilities valuation of an institution, and it is thus commonly believed that such liabilities should not require much updating when a new actuarial table is released. In this paper, we demonstrate that contrary to this common belief, institutions that use generational tables (namely, tables including future mortality evolution) will most likely need to make more important adjustments (positive or negative) to their liabilities than will institutions using periodic (static) tables whenever a new table is released. By using three very different models to project mortality, we demonstrate that our findings are inherent in the required long horizons of the forecasts needed in the generational approach, with the uncertainty surrounding the forecast values increasing with the horizon. Therefore, generational tables may introduce more instability in a pension institution’s accounts than periodic tables.

**Optimal Long-Term Allocation with Pension Fund Liabilities** (with M. Rockinger) (October 2014) - Swiss Finance Institute Research Paper No. 14-58.

We build a macroeconomic model for Switzerland, the Euro Area, and the USA that drives the dynamics of several asset classes and the liabilities of a representative Swiss (defined-contribution) pension fund. This encompassing approach allows us to generate correlations between returns on assets and liabilities. We calibrate the economy using quarterly data between 1985:Q1 and 2013:Q2. Using a certainty equivalent approach, we demonstrate that a liabilities hedging portfolio outperforms an assets-only strategy by between 5% and 15% per year. The main reason for such a large improvement is that the optimal assets-only portfolio is typically long in cash, whereas hedging liabilities require the pension fund to be short in cash. It follows that imposing positivity restrictions in the construction of the portfolio also results in a large cost, between 4% and 8% per year. This estimate suggests that allowing pension funds to hedge their liabilities through borrowing cash and investing in a diversified bond portfolio helps to enhance the global portfolio return.

**Asymmetric Beta Comovement and Systematic Downside Risk** (with Q. Zhang) (October 2014) - Swiss Finance Institute Research Paper No. 14-59.

In this paper, we document evidence that downside betas tend to comove more than upside betas during a financial crisis, but upside betas tend to comove more than the downside betas during financial booms. We find that the asymmetry between Downside-Beta Comovement and Upside-Beta Comovement is the main driving force for market level skewness. An indicator called "Systematic Downside Risk" (SDR) is defined to characterize this asymmetry in the comovement of betas. This indicator negatively predicts future market returns. The SDR effectively forecasts future monthly stock market movements with an out-of-sample R-square above 2.27% relative to a strategy based on historical mean. An investor who timed the market using SDR would have obtained a Sharpe ratio gain of 0.206.

**Portfolio
Allocation for European Markets with Predictability and Parameter Uncertainty** (with M. Rockinger) (August 2010) - NCCR Working Paper No. 660

We implement a long-horizon static and dynamic portfolio allocation involving
a risk-free and a risky asset. This model is calibrated at a quarterly frequency
for ten European countries. We also use maximum-likelihood estimates and Bayesian
estimates to account for parameter uncertainty. We find that for most European
countries the dividend-price ratio and inflation have predictive power. For
countries where returns are predictable, we demonstrate out-of-sample economic
signicance for the long-horizon allocation. Parameter uncertainty plays a second-order
role, dominated by strong variation in the dynamic allocation itself induced
by large variations in the state variables. The market timing appears economically
relevant for many countries.

**Optimal
Liquidation Strategies in Illiquid Markets** (with A. Perilla and M. Rockinger)
(July 2007) - Swiss Finance Institute Research Paper No. 09-24.

An institutional trader who wishes to trade a large position in the Paris stock
market faces the choice between a block trade or several small trades. Actual
data reveals that block trades increase subsequent to agitated markets. For
an investor who wishes to trade through the electronic market, we extend the
optimal trading algorithm of Almgren and Chriss (2001) to allow for volume impact.
To do so, we extend Sadka's (2006) microstructure model to allow for differential
price impact of buys and sells. Estimations for a large set of companies reject
restrictions that would discard volume impact and the buy/sell distinction.
A comparative static exercise reveals the importance of the general order arrival
rate for the optimal trading speed. Priors concerning the general order arrival
rate are more important than priors concerning price variations or changes in
the microstructure parameters to capture market crashes.

**The
Bank Bias: Segmentation of French Fund Families** (with M. Rockinger)
- Banque de France Working Paper, 2004, n°107.

In this paper, we investigate the performance-growth relation of French mutual
funds. Using panel techniques, we find that capital inflows to French past top
performing funds are not as strong as expected. This result suggests that there
exist barriers to investment, that may come from the fact that funds are mostly
managed by banks and insurance companies and that there are high switching costs
for an investor to transfer cash from one financial institution to another.
We call this phenomenon "bank bias", because investors do not diversify
enough across banks' funds. Furthermore, we provide a test of our conjecture
and cannot reject it.

**Econometrics
of Rational Expectations Models **

**Aggregating
Rational Expectations Models In the Presence of Unobserved Micro Heterogeneity**
(with F. Pelgrin) (August 2009) - Swiss Finance Institute Research Paper No.
09-30.

Our paper addresses the correction of the aggregation bias in linear rational
expectations models when there is some unobserved micro-parameter heterogeneity
and only macro data are available. Starting from Lewbel (1994), we propose two
new consistent estimators, which rely on a flexible parametric specification
of the cross-sectional parameter distributions and account for the dependence
across coefficients inherent in such models. A Monte-Carlo study reveals that
the finite-sample and asymptotic properties of the proposed estimators outperform
the Lewbel approach and correct the aggregation bias found with the maximum-likelihood
and generalized-method-of-moments approaches. As a by-product, we also infer
the cross-sectional distribution of the parameters. Finally, we re-assess the
empirical evidence about the New Keynesian Phillips curve and explain the apparent
discrepancy between micro- and macro-based estimates of the average persistence
of inflation.

Technical
Appendix