This paper proposes a methodology for default probability estimation for low default portfolios, where the statistical inference may become troublesome. The author suggests using logistic regression models with the Bayesian estimation of parameters. The piecewise logistic regression model and...

Much of the trading activity in Equity markets is directed to brokerage houses. In exchange they provide so-called quot;soft dollarsquot; which basically are amounts spent in quot;researchquot; for identifying profitable trading opportunities. Soft dollars represent about USD 1 out of every USD...

Hedge Fund returns are often highly serially correlated mainly due to illiquidity exposures given that investments in such securities tend to be inactively traded and associated market prices are not always readily available. Following that, observed returns of such alternative investments tend...

We explore properties of asymmetric generalized autoregressive conditional heteroscedasticity (GARCH) models in the threshold GARCH family and propose a more general Spline-GTARCH model, which captures high-frequency return volatility, low-frequency macroeconomic volatility as well as an...

Public interest, explosive returns, and diversification opportunities gave stimulus to the adoption of traditional financial tools to crypto-currencies. While the CRIX index offered the first scientifically-backed proxy to the cryptomarket (analogous to S&P 500), the introduction of Bitcoin...

We suggest a simple practical method to combine the human and artificial intelligence to both learn best investment practices of fund managers, and provide recommendations to improve them. Our approach is based on a combination of Inverse Reinforcement Learning (IRL) and RL. First, the IRL...

This paper presents a credit migration model that aims to consistently capture the point-in-time dynamics of the credit worthiness of debt issuers and their obligations, and a calibration routine that permits the model to effectively fit historical ratings data. Our approach is to view the...

We present a data-driven proof of concept model capable of reproducing expected counterparty credit exposures from market and trade data. The model has its greatest advantages in quick single-contract exposure evaluations that could be used in front office xVA solutions. The data was generated...

This paper provides practical insights into common statistical measures used to validate a model's discriminatory power for the probability of default (PD), loss liven default (LGD) and exposure at default (EAD). The study has more of an informative value without delivering empirical evidence....

This paper empirically analyzes in a time-varying context if the U.S. corporate Credit Default Swaps (CDS) and bond markets of 81 reference entities reflect the same information on their prices between October 2004 and December 2010, using OTC traded CDS. The analysis shows that frictions in the...