We propose a novel method of estimating default probabilities using equity option data. The resulting default probabilities are highly correlated with estimates of default probabilities extracted from CDS spreads, which assume constant recovery rates. Additionally, the option implied default...

Robust estimation techniques based on symmetric probability distributions are often substituted for OLS to obtain efficient regression parameters with thick-tail distributed data. The empirical, simulation and theoretical results in this paper show that with skewed distributed data, symmetric...

We investigate how individual equity prices respond to continuous and jumpy market price moves and how these different market price risks, or betas, are priced in the cross section of expected stock returns. Based on a novel high-frequency data set of almost one thousand stocks over two decades,...

A dynamic copula model is introduced, in which the copula structure is inferred from the realized covariance matrix estimated from within-day high-frequency data. The estimation is carried out in a method-of-moments fashion using Hoeffding's lemma. Applying this procedure day by day gives rise...

The constant-maturity zero-coupon Treasury yield curve is one of the most studied datasets. We reconstruct the yield curve using a non-parametric kernel-smoothing method with a novel adaptive bandwidth specifically designed to fit the Treasury yield curve. Our curve is globally smooth while...

Because of the heavy trading of the market and limitation of the recording mechanism, the multiple records of high-frequency data appear frequently. The lack of order information for local data makes it difficult to estimate integrated volatility. We propose a range-based estimator of integrated...

Tail risk refers to the possibility that a rare event would adversely affect the value of a portfolio in a significant manner. It became much more relevant due to recent periods of strong market turbulence.We describe how to quantify such risk, which tail risk protection strategies were...

A credit derivative is a path dependent contingent claim on the aggregate loss in a portfolio of credit sensitive securities. We estimate the value of a credit derivative by Monte Carlo simulation of the affine point process that models the loss. We consider two algorithms that exploit the...

Recent research has focused on modelling asset prices by Itocirc; semimartingales. In such a modelling framework, the quadratic variation consists of a continuous and a jump component. This paper is about inference on the jump part of the quadratic variation, which can be estimated by the...