| Working Paper |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Linear-Rational Multi-Curve Term Structure Model with Stochastic Spread |
0 |
0 |
0 |
0 |
1 |
1 |
9 |
18 |
| A linear-rational multi-curve term structure model with stochastic spread |
0 |
0 |
0 |
0 |
0 |
0 |
8 |
9 |
| A model of financial bubbles and drawdowns with non-local behavioral self-referencing |
0 |
0 |
0 |
12 |
0 |
0 |
17 |
48 |
| A model of financial bubbles and drawdowns with non-local behavioral self-referencing |
0 |
0 |
0 |
1 |
0 |
0 |
8 |
12 |
| A simple microstructure model based on the Cox-BESQ process with application to optimal execution policy |
0 |
0 |
0 |
7 |
0 |
0 |
4 |
14 |
| A two-Factor Asset Pricing Model and the Fat Tail Distribution of Firm Sizes |
0 |
0 |
0 |
38 |
1 |
1 |
13 |
226 |
| Alternative Risk Measures for Alternative Investments |
0 |
0 |
0 |
0 |
0 |
0 |
8 |
22 |
| Book review: "Financial Risk Management with Bayesian Estimation of GARCH Models: Theory and Applications" by D. Ardia (Springer) |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
5 |
| Book review: "Why Stock Market Crash?" by D. Sornette (Princeton University Press) |
0 |
0 |
0 |
0 |
0 |
1 |
9 |
17 |
| Collective Origin of the Coexistence of Apparent RMT Noise and Factors in Large Sample Correlation Matrices |
0 |
0 |
0 |
15 |
1 |
1 |
4 |
55 |
| Collective origin of the coexistence of apparent random matrix theory noise and of factors in large sample correlation matrices |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
| Comprendre et Gérer les Risques Grands et Extrêmes |
0 |
0 |
0 |
48 |
0 |
1 |
6 |
131 |
| Covariance Versus Precision Matrix Estimation for Efficient Asset Allocation |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
7 |
| Empirical Distributions of Log-Returns: between the Stretched Exponential and the Power Law? |
0 |
0 |
2 |
83 |
1 |
1 |
13 |
299 |
| Empirical Distributions of Stock Returns: Between the Stretched Exponential and the Power Law? |
0 |
0 |
0 |
0 |
0 |
1 |
13 |
27 |
| Extreme Financial Risks: From Dependence to Risk Management |
0 |
0 |
0 |
0 |
0 |
0 |
11 |
39 |
| Foreign Exchange Multivariate Multifractal Analysis |
0 |
0 |
0 |
31 |
0 |
2 |
6 |
21 |
| From Rational Bubbles to Crashes |
0 |
0 |
0 |
43 |
2 |
2 |
8 |
128 |
| From rational bubbles to crashes |
0 |
0 |
0 |
0 |
0 |
0 |
11 |
17 |
| General framework for a portfolio theory with non-Gaussian risks and non-linear correlations |
0 |
0 |
0 |
20 |
0 |
0 |
9 |
72 |
| Gibrat’s law for cities: uniformly most powerful unbiased test of the Pareto against the lognormal |
0 |
0 |
0 |
26 |
0 |
0 |
13 |
300 |
| Hedging Extreme Co-Movements |
0 |
0 |
0 |
20 |
0 |
0 |
9 |
66 |
| Heterogeneous expectations and long range correlation of the volatility of asset returns |
0 |
0 |
0 |
12 |
1 |
2 |
11 |
98 |
| Heterogeneous expectations and long range correlation of the volatility of asset returns |
0 |
0 |
0 |
9 |
0 |
0 |
6 |
72 |
| How Analystss Ability Affects Forecast Timing Under Bias and Uncertainty? |
0 |
0 |
0 |
0 |
1 |
1 |
11 |
14 |
| How to account for extreme co-movements between individual stocks and the market |
0 |
0 |
0 |
0 |
0 |
1 |
4 |
20 |
| Imitation and contrarian behavior: hyperbolic bubbles, crashes and chaos |
0 |
0 |
0 |
49 |
1 |
2 |
12 |
169 |
| Imitation and contrarian behavior: hyperbolic bubbles, crashes and chaos |
0 |
0 |
0 |
0 |
1 |
1 |
7 |
10 |
| Imitation and contrarian behavior: hyperbolic bubbles, crashes and chaos |
0 |
0 |
0 |
0 |
1 |
1 |
6 |
15 |
| Investigating Extreme Dependences: Concepts and Tools |
0 |
0 |
0 |
35 |
2 |
2 |
11 |
118 |
| Investors' expectations, management fees and the underperformance of mutual funds |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
9 |
| Investors’ Expectations, Management Fees and the Underperformance of Mutual Funds |
0 |
0 |
0 |
18 |
1 |
1 |
9 |
38 |
| Investors’ Misperception: A Hidden Source of High Markups in the Mutual Fund Industry |
0 |
0 |
0 |
35 |
0 |
0 |
8 |
187 |
| Macroeconomic Dynamics of Assets, Leverage and Trust |
0 |
0 |
0 |
0 |
0 |
0 |
5 |
8 |
| Macroeconomic Dynamics of Assets, Leverage and Trust |
0 |
0 |
0 |
28 |
0 |
0 |
8 |
54 |
| Minimizing extremes |
0 |
0 |
0 |
0 |
1 |
2 |
11 |
18 |
| Multi-Moments Method for Portfolio Management: Generalized Capital Asset Pricing Model in Homogeneous and Heterogeneous markets |
0 |
0 |
1 |
37 |
2 |
2 |
14 |
146 |
| Multi-dimensional Rational Bubbles and fat tails: application of stochastic regression equations to financial speculation |
0 |
0 |
0 |
27 |
1 |
2 |
13 |
91 |
| Multi-dimensional rational bubbles and fat tails |
0 |
0 |
0 |
0 |
0 |
1 |
13 |
17 |
| New Results for Additive and Multiplicative Risk Apportionment |
0 |
0 |
0 |
31 |
1 |
2 |
12 |
53 |
| New Results for Additive and Multiplicative Risk Apportionment |
0 |
0 |
0 |
4 |
0 |
0 |
9 |
31 |
| New Results for additive and multiplicative risk apportionment |
0 |
0 |
0 |
0 |
0 |
0 |
8 |
19 |
| On Cross-risk Vulnerability |
0 |
0 |
0 |
29 |
0 |
1 |
11 |
94 |
| On cross-risk vulnerability |
0 |
0 |
0 |
0 |
0 |
0 |
10 |
19 |
| On the Power of Generalized Extreme Value (GEV) and Generalized Pareto Distribution (GPD) Estimators for Empirical Distributions of Stock Returns |
0 |
0 |
0 |
0 |
2 |
2 |
9 |
24 |
| Preparing for the Worst: Incorporating Downside Risk in Stock Market Investments |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
7 |
| Preserving preference rankings under non-financial background risk |
0 |
0 |
0 |
17 |
0 |
0 |
11 |
77 |
| Preserving preference rankings under non-financial background risk |
0 |
0 |
0 |
0 |
0 |
0 |
8 |
14 |
| Professor Zipf goes to Wall Street |
0 |
0 |
0 |
80 |
0 |
1 |
18 |
246 |
| Robust reverse engineering of crosssectional returns and improved portfolio allocation performance using the CAPM |
0 |
0 |
1 |
8 |
0 |
0 |
9 |
62 |
| Self-Consistent Asset Pricing Models |
0 |
0 |
0 |
14 |
1 |
2 |
12 |
105 |
| Self-consistent asset pricing models |
0 |
0 |
0 |
0 |
0 |
0 |
7 |
20 |
| Shuffling for understanding multifractality, application to asset price time series |
0 |
0 |
0 |
1 |
0 |
0 |
15 |
21 |
| Tail Dependence of Factor Models |
0 |
0 |
0 |
19 |
1 |
2 |
12 |
74 |
| Testing the Gaussian Copula Hypothesis for Financial Assets Dependences |
0 |
0 |
0 |
42 |
0 |
0 |
14 |
198 |
| Testing the Gaussian Copula Hypothesis for Financial Assets Dependences |
0 |
0 |
0 |
1,388 |
0 |
0 |
12 |
3,399 |
| Testing the Gaussian copula hypothesis for financial assets dependence |
0 |
0 |
0 |
0 |
0 |
0 |
11 |
16 |
| Testing the Gaussian copula hypothesis for financial assets dependences |
0 |
0 |
0 |
25 |
1 |
1 |
14 |
138 |
| The modified weibull distribution for asset returns: reply |
0 |
0 |
0 |
0 |
0 |
1 |
7 |
15 |
| Theory of Zipf's Law and Beyond |
0 |
0 |
0 |
0 |
0 |
0 |
7 |
37 |
| Theory of Zipf's Law and of General Power Law Distributions with Gibrat's law of Proportional Growth |
0 |
0 |
0 |
46 |
0 |
0 |
13 |
187 |
| VaR-Efficient Portfolios for a Class of Super- and Sub-Exponentially Decaying Assets Return Distributions |
0 |
0 |
0 |
21 |
1 |
1 |
6 |
83 |
| Value-at-Risk-efficient portfolios for class of super- and sub-exponentially decaying assets return distributions |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
5 |
| Volatility fingerprints of large shocks: Endogeneous versus exogeneous |
0 |
0 |
0 |
22 |
2 |
2 |
7 |
77 |
| Wealth and Income Inequalities ← → r > g |
0 |
0 |
0 |
36 |
2 |
3 |
16 |
76 |
| Zipf's law and maximum sustainable growth |
0 |
0 |
0 |
54 |
1 |
1 |
16 |
168 |
| Zipf's law and maximum sustainable growth |
0 |
0 |
0 |
0 |
0 |
0 |
8 |
22 |
| Total Working Papers |
0 |
0 |
4 |
2,431 |
30 |
48 |
625 |
7,907 |
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