Risk metrics users assume that the moments of asset returns exist, irrespectively of the trading frequency, hence the observed values of these moments are used to capture the potential losses from asset trading (e.g. with Value-at-Risk (VaR) or Expected Shortfall (ES) calculations). Despite the...

Very little is known on how traditional risk metrics behave under intraday trading. We fill this void by examining the finiteness of the returns' moments and assessing the impact of their infinity in a risk management framework. We show that when intraday trading is considered, assuming finite...

Very little is known on how traditional risk metrics behave in ultra high frequency trading (UHFT). We fi�ll this void �firstly by examining the existence of the intraday returns moments, and secondly by assessing the impact of their (non)existence in a risk management framework. We show...

Risk metrics users assume that the moments of asset returns exist, irrespectively of the trading frequency, hence the observed values of these moments are used to capture the potential losses from asset trading (e.g. with Value-at-Risk (VaR) or Expected Shortfall (ES) calculations). Despite the...

Risk metrics users assume that the moments of asset returns exist, irrespectively of the trading frequency, hence the observed values of these moments are used to capture the potential losses from asset trading (e.g. with Value-at-Risk (VaR) or Expected Shortfall (ES) calculations). Despite the...

Based on Godambe's theory of estimating functions, we propose a class of cumulative sum (CUSUM) statistics to detect breaks in the dynamics of time series under weak assumptions. First, we assume a parametric form for the conditional mean, but make no specific assumption about the...

This paper considers multiple changes in the factor loadings of a high dimensional factor model occurring at dates that are unknown but common to all subjects. Since the factors are unobservable, the problem is converted to estimating and testing structural changes in the second moments of the...

We propose a portfolio construction method that accounts for the regime-dependent behavior of stocks, thereby impacting their expected returns. Using a hidden Markov model (HMM) and a regime-weighted least-squares approach, we estimate forward-looking regime-conditional factors. These factors...

This paper proposes maximum (quasi)likelihood estimation for high dimensional factor models with regime switching in the loadings. The model parameters are estimated jointly by EM algorithm, which in the current context only requires iteratively calculating regime probabilities and principal...

This paper proposes maximum (quasi)likelihood estimation for high dimensional factor models with regime switching in the loadings. The model para- meters are estimated jointly by the EM (expectation maximization) algorithm, which in the current context only requires iteratively calculating...