In this paper, I show that the variance of Fama-French factors, the variance of the momentum factor, as well as the correlation between these factors, predict an important fraction of the time-series variation in post-1990 aggregate stock market returns. This predictability is particularly...

In this article, the Universal Approximation Theorem of Artificial Neural Networks (ANNs) is applied to the SABR stochastic volatility model in order to construct highly efficient representations. Initially, the SABR approximation of Hagan et al. [2002] is considered, then a more accurate...

The VIX index is not only a volatility index but also a polynomial combination of all possible higher moments in market return distribution under the risk-neutral measure. This paper formulates the VIX as a linear decomposition of four fundamentally different elements: the realized variance...

This paper outlines a method to forecast FX spot rates. The data set consists of the Bloomberg FX spot rates for emerging markets as defined by Bloomberg. The in-sample data set consisted of weekly FX spot rates for ten Emerging markets, from August 2013 to March 2019. The out sample spanned...

We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no arbitrage restrictions by regularizing appropriate groups of coefficients. The second...

This chapter surveys recent econometric methodologies for inference in large dimensional conditional factor models in finance. Changes in the business cycle and asset characteristics induce time variation in factor loadings and risk premia to be accounted for. The growing trend in the use of...

This paper details efforts at developing and estimating a Vector Autoregressive (VAR) econometric model representative of the financial statements of a firm. Although the model can be generalized to represent the financial statements of any firm, this work was carried out as a case study, where...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

Several approaches for subset recovery and improved forecasting accuracy have been proposed and studied. One way is to apply a regularization strategy and solve the model selection task as a continuous optimization problem. One of the most popular approaches in this research field is given by...