1. School of Business and Economics Discussion on “Risk horizon Predictors of Euro Area Financial Stress” by Thomas Lejeune Stefan Straetmans Maastricht University (School of Business and Economics) Risk forum Paris, 30-31 March 2015

2. School of Business and Economics Discussion in a nutshell What is the paper about? Strengths Weaknesses

3. School of Business and Economics What is the paper about? Traditionally (e.g. CAPM, APT, FFC 4-factor model) “market” risk premium exogenously determined → sample average ≈ expected market return Here: asset pricing model for different risk premia Nonparametric (model free) approach: no utility function or distributional return assumptions, only knowledge of first 4 moments assumed New concept of risk related to “risk horizon” Identification of model parameters by use of term structure model of interest rates Use of risk premia as EWI in logit models for systemic stress

4. School of Business and Economics Strengths Dazzling analytic level Novel concept of individual asset risk (“risk horizon”) Take into account heavy tails via higher moments Nonparametric character of the approach → parsimony in terms of model assumptions reduces model risk as compared to previous approaches

5. School of Business and Economics Weaknesses (1) “Hermetic” write-up: paper should in principle be understandable for every financial economist (not necessarily a specialist in asset pricing) Journal you want to submit? → if it is for a specialized math journal, OK → if mainstream finance journal, more intuition explanation necessary → three more or less concentrically overlapping papers; fine for a phd thesis but what about a journal article? You refer a lot to previously unpublished research, make one master paper out of this?

6. School of Business and Economics Weaknesses (2) How accurate is the Chebyshev upper bound? Is extreme value analysis (EVT) more accurate alternative? Simplifying assumptions need more explanation - concept of risk horizon - knowledge of 2 nd -4 th moment also characterized by estimation risk - estimates of the tail index of financial returns suggest: - α is the number of bounded moments - in other words: the variance seems to exist but the kurtosis often does not!

7. School of Business and Economics Weaknesses (3) Accuracy of risk factors? Confidence bands? Tables 5-6: after adding controls, only credit trend stays significant as EWI, it seems Tables 5-6: why does the credit trend coefficient become so huge (in absolute value) after adding controls? Logit output - way too many tables! - discuss marginal logit effects - lots of controls, lack of parsimony - correlation, multicollinearity of control variables? - without control variables, pseudo-R2 low - static vs. dynamic logit (lagged dependent variable)

8. School of Business and Economics All in all High potential paper Should be readable for a wider audience than asset pricing except if you focus on very specialized journal