In many settings of empirical interest, time variation in the distribution parameters is important for capturing the dynamic behaviour of time series processes. Although the fitting of heavy tail distributions has become easier due to computational advances, the joint and explicit modelling of...

Sentiment analysis is applied to the Federal Reserve's documents relating to the Federal Open Market Committee (FOMC). A new method of rating the sentiment of texts is developed through the creation of a 100 000 word sentiment dictionary, and is used to estimate the sentiment of the Beige Book...

We argue that the practise of valuing the portfolio is important for the calculation of the VaR. In particular, the seller (buyer) of an asset does not face horizontal demand (supply) curves. We propose a partially new approach for incorporating this fact in the VaR and in an empirical...

How do conditions in the financial sector affect the macroeconomy? We summarise the common variation in a large array of financial variables into a small set of statistical factors and examine the information content of these factors when forecasting GDP and inflation in four economies. We find...

Systematic trading is a method that is currently extremely popular in the investment world. The testing of systematic trading rules is usually done through backtesting and is at high risk of spurious accuracy as a result of the data-mining bias (DMB) present from testing multiple rules...

I present evidence of systematically heterogeneous expectations, a violation of the Rational Expectations Hypothesis. I demonstrate that the expectations of different gender and wealth cohorts have different relative abilities to predict inflation, interest rates, unemployment, income, stock...

Option pricing and allocation tools in portfolio construction should be prospective - based on assumptions about how prices will change in the future. Most capital market assumptions used in portfolio construction are based on retrospective analysis, boiling down to simple calculations of...

The article investigates the use of adaptive learning algorithms in constructing dynamic portfolios replicating the return characteristics of a given hedge fund. The emphasis is on out of sample conditional predictive capabilites as necessary to serve as a valuable risk management tool, rather...

This survey reviews a number of different fundamentals-based models for estimating default probabilities for firms and/or industries, and illustrates them with real applications by practitioners and policy making institutions. The models are especially useful when the firms analyzed do not have...

The Hierarchical risk parity (HRP) approach of portfolio allocation, introduced by [Lopez de Prado, 2016], applies graph theory and machine learning to build a diversified portfolio. Like the traditional risk based allocation methods, HRP is also a function of the estimate of the covariance...