Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by inflation and interest rate expectations as well...

Modelling and forecasting of asset volatility and covariance is of prime importance in the construction of portfolios. In this paper, we present a generalised multi-factor model that incorporates heteroskedasticity and dependence in the idiosyncratic error terms. We apply this model to...

We establish the out-of-sample predictability of monthly exchange rate changes via machine learning techniques based on 70 predictors capturing country characteristics, global variables, and their interactions. To guard against overfitting, we use the elastic net to estimate a high-dimensional...

The study examined high volatile assets, specifically the currency exchange rate of the open financial market. Takes into consideration the five most traded paired currencies of the global financial market. And observed, generally, the data set of the unit currency exchange rate exhibit...

This paper investigates the relationships among cross-sectional stock returns and analysts' forecast revisions, forecast dispersion and momentum. Market rewards the strategy in pursuit of revision up and away from revision down by 22.7% per annum over the 1983-2015 periods. I find that the...

Recent evidence indicates that market model alphas are stronger predictors of mutual fund flows than alphas with other models. Berk and van Binsbergen (2016) claim that this evidence indicates CAPM is the best asset pricing model but Barber, Huang and Odean (2016) (BHO) claim it is evidence...

You're probably familiar, at least in passing, with the 'convexity' of long-term bonds - i.e. that yields dropping 1% produce a bigger price move than yields rising 1%. A significant amount of brainpower has gone into understanding all the ramifications of this convexity in the fixed income...

Using trader-resolved data, we document lead-lag relationships between groups of investors in the foreign exchange market. Because these relationships are systematic and persistent, order flow is predictable from trader-resolved order flow. We thus propose a generic method to exploit trader...

Using a novel equity lending dataset, this paper is the first to show that expected returns strongly and negatively predict future equity lending fees. In comparing two expected return measures, I find that a rational expected return has stronger predictive power of future short selling activity...