We study the rank of the instantaneous or spot covariance matrix Σ(t) of a multidimensional continuous semi-martingale X(t). Given highfrequency observations X(i=n), i = 0; : : : ;n, we test the null hypothesis rank (Σ(t)) ≤ r for all t against local alternatives where the average (r + 1)st...

Purpose - It is crucial to find a better portfolio optimization strategy, considering the cryptocurrencies' asymmetric volatilities. Hence, this research aimed to present dynamic optimization on minimum variance (MVP), equal risk contribution (ERC) and most diversified portfolio (MDP)....

In this paper, we develop a penalized realized variance (PRV) estimator of the quadratic variation (QV) of a high-dimensional continuous Itô semimartingale. We adapt the principle idea of regularization from linear regression to covariance estimation in a continuous-time high-frequency setting....

I study time-variation in variance discount rates, defined as the expected returns for investing in variance risk. I show that variance discount rates drive a significant fraction of the variation in prices of S&P 500 variance swaps. This analysis offers important insights into preferences of...

In this paper we propose a new pricing methodology for European multi-asset options based on the family of normal mean-variance mixture copulas. The goal is to develop a copula-based method with the flexibility to reproduce the correlation skew, and at the same time efficient enough to be used...

We introduce a novel covariance estimator that exploits the heteroskedastic nature of financial time series by employing exponential weighted moving averages and shrinking the in-sample eigenvalues through cross-validation. Our estimator is model-agnostic in that we make no assumptions on the...