We develop a new method that detects jumps nonparametrically in financial time series and significantly outperforms the current benchmark on simulated data. We use a long short- term memory (LSTM) neural network that is trained on labelled data generated by a process that experiences both jumps...

We evaluate how non-normality of asset returns and the temporal evolution of volatility and higher moments affects the conditional allocation of wealth. We show that if one neglects these aspects, as would be the case in a mean-variance allocation, a sighifiant cost would arise. The performance...

The failure of uncovered interest rate parity to explain short-term interest rate movements is well documented. We show that short-term changes in long-term interest rates do help to explain short-term exchange rate movements. The relationship gets stronger over our sample period, as the...

DeMiguel, Garlappi, and Uppal (Review of Financial Studies, 22 (2009), 1915-1953) showed that in the stock market, it is difficult for an optimized portfolio constructed using mean-variance analysis to outperform a simple equally-weighted portfolio because of estimation error. In this paper, we...

The authors assess the performance of the real-time diagnostic, openly presented to the public on the website of the Financial Crisis Observatory (FCO) at ETH Zurich, of the bubble regime that developed in Chinese stock markets since mid-2014 and that started to burst in June 2015. The analysis...

We propose a technique to avoid spurious detections of jumps in high-frequency data via an explicit thresholding on available test statistics. We prove that it eliminates asymptotically all spurious detections. Monte Carlo results show that it performs also well in finite samples. In Dow Jones...

This paper shows that the VIX market contains information on the variance of the S&P 500 returns, which is not already spanned by the S&P 500 market. We estimate a flexible affine model based on a joint time series of underlying indexes and option prices on both markets. We find that including...

This paper analyzes brief episodes of high-intensity quotes turnover and revision-"bursts" in quotes-in the U.S. equity market. Such events occur very frequently, several hundred times a day for actively traded stocks. We find significant price impact associated with these market makers...

We build a simple diagnostic criterion for approximate factor structure in large panel datasets. Given observable factors, the criterion checks whether the errors are weakly cross-sectionally correlated or share at least one unobservable common factor (interactive effects). A general version...

We propose a novel methodology that jointly estimates the proportions of skilled/unskilled funds and the cross-sectional distribution of skill in the mutual fund industry. We model this distribution as a three-component mixture of a point mass at zero and two components — one negative, one...