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Extreme Return-Volume Dependence in East-Asian Stock Markets : A Copula Approach

Ning, Cathy Q. - 2013

A copula approach is used to examine the extreme return-volume relationship in six emerging East-Asian equity markets. The empirical results indicate that there is significant and asymmetric return-volume dependence at extremes for these markets. In particular, extremely high returns (large...

Persistent link: https://www.econbiz.de/10013084099

Secular Mean Reversion and Long-Run Predictability of the Stock Market

Zakamulin, Valeriy - 2015

Empirical financial literature documents the evidence of mean reversion in stock prices and the absence of out-of-sample return predictability over periods shorter than 10 years. The goal of this paper is to test the random walk hypothesis in stock prices and return predictability over periods...

Persistent link: https://www.econbiz.de/10013036031

The forecasting performances of volatility models in emerging stock markets : is a generalization really possible?

Iltuzer, Zeynep; Tas, Oktay - In: Journal of applied finance & banking 3 (2013) 2, pp. 49-73

In almost all stages of forecasting volatility, certain subjective decisions need to be made. Despite of an enormous literature in the area, these subjectivities are hindrances to reaching an overall conclusion on the performances of the models. In order to find out outperforming model in...

Persistent link: https://www.econbiz.de/10009743532

Center of Volume Mass : Does Options Trading Predict Stock Returns?

Bernile, Gennaro (帅纳) - 2020

We examine whether the distribution of trades along the set of strike prices of option contracts on the same stock contains information about underlying price discovery. We show that option traders' demand for delta exposure drives the volume-weighted average strike-spot price ratio (VWKS). In...

Persistent link: https://www.econbiz.de/10012845908

PREDICTING STOCK RETURN AND VOLATILITY WITH MACHINE LEARNING AND ECONOMETRIC MODELS : A COMPARATIVE CASE STUDY OF THE BALTIC STOCK MARKET

Nõu, Anders; Lapitskaya, Darya; Eratalay, Mustafa Hakan; … - 2022

For stock market predictions, the essence of the problem is usually predicting the magnitude and direction of the stock price movement as accurately as possible. There are different approaches (e.g., econometrics and machine learning) for predicting stock returns. However, it is non-trivial to...

Persistent link: https://www.econbiz.de/10013305881

Estimating and Predicting Multivariate Volatility Thresholds in Global Stock Markets

Audrino, Francesco; Trojani, Fabio - 2003

This paper proposes a double tree structured AR-GARCH model for the analysis of stock index return series, which extends previous approaches to incorporate (i) an arbitrary number of multivariate thresholds in conditional means and volatilities of stock index returns and (ii) a richer...

Persistent link: https://www.econbiz.de/10014089647

Ultra-Simple Shiller's CAPE : How One Year's Data Can Predict Equity Market Returns Better Than Ten (Presentation Slides)

Philips, Thomas K. - 2019

as t-statistics, and instead evaluate models using the correlation between their out-of-sample predictions of the future …

Persistent link: https://www.econbiz.de/10012864087

The Properties of Realized Correlation : Evidence from the French, German and Greek Equity Markets

Vortelinos, Dimitrios I. - 2015

In this paper I examine the properties of four realized correlation estimators and model their jumps. The correlations …-of-the-art realized correlation estimators which I then use to testing for normality, long-memory, asymmetries and jumps and also to … modeling for jumps. Jumps are detected when the realized correlation is higher than 0.99 and lower than 0.01 in absolute values …

Persistent link: https://www.econbiz.de/10013029288

Can Volume Predict Bitcoin Returns and Volatility? A Quantiles-Based Approach

Balcilar, Mehmet - 2017

Prior studies on the price formation in the Bitcoin market consider the role of Bitcoin transactions at the conditional mean of the returns distribution. This study employs in contrast a non-parametric causality-in-quantiles test to analyse the causal relation between trading volume and Bitcoin...

Persistent link: https://www.econbiz.de/10012960531

Sector Level Equity Returns Predictability with Machine Learning and Market Contagion Measure

Peng, Weijia; Yao, Chun - 2023

In this paper, we develop new latent risk measures that are designed as a prior synthesis of key forecasting information associated with financial market contagion. These measures are based on the decomposition (using high-frequency financial data) of the quadratic covariation between two assets...

Persistent link: https://www.econbiz.de/10014256827