By assuming that short-run returns are independent and identically distributed, it is straightforward to extrapolate short-run risks to longer horizons. However, by generalizing the variance-ratio test to include higher co-moments, we establish a significant and sizable intertemporal dependency...

Market efficiency has been analyzed through many studies using different linear methods. However, studies on financial econometrics reveal that financial time series exhibit nonlinear patterns because of various reasons. This paper examines market efficiency at Borsa Istanbul using a smooth...

We propose how to quantify high-frequency market sentiment using high-frequency news from NASDAQ news platform and support vector machine classifiers. News arrive at markets randomly and the resulting news sentiment behaves like a stochastic process. To characterize the joint evolution of...

The COAALA copula allows to analyse financial market stability by studying co-movement between stocks and government bonds using information on both the global and the four local tail dependence measures (i.e. dependence between severe movements). Such encompassing view on stock-bond co-movement...

Under the APT framework and the assumption that the market portfolio is well-diversified, if not mean-variance efficient, the common factors in raw-returns are the market return plus the common factors in the space of excess-returns over the market return. This explains why the market betas fail...

This paper exploits the term structures of treasury yields to extract information about macroeconomic dynamics during the effective lower bound period (ELB). I introduce a new no-arbitrage macro-finance affine model jointly representing stochastic inflation trend and volatilitywith a short-term...

Based on a novel high-frequency data set for a large number of firms, I estimate the time-varying latent continuous and jump factors that explain individual stock returns. The factors are estimated using principal component analysis applied to a local volatility and jump covariance matrix. I...

We propose a new method, VASA, based on variable subsample aggregation of model predictions for equity returns using a large-dimensional set of factors. To demonstrate the effectiveness, robustness, and dimension reduction power of VASA, we perform a comparative analysis between state-of-the-art...

Technical trading rules are widely used by practitioners to forecast the U.S. equity premium. I decompose technical indicators into components with frequency-specific information, showing that the predictive power comes from medium-frequency variation in buy and sell signals, without much...

We analyze the effect of skewness in a simple two-asset framework. Returns follow the split bivariate normal distribution, which is a combination of bivariate normal distributions with different standard deviations. We show that expected returns deviate from the CAPM in equilibrium if assets...