Using high-frequency intraday data, we construct, test and model seven new realized volatility estimators for six international equity indices. We detect jumps in these estimators, construct the jump components of volatility and perform various tests on their properties. Then we use the class of...

This paper develops textual sentiment measures for China's stock market by extracting the textual tone of 60 million messages posted on a major online investor forum in China from 2008 to 2018. We conduct sentiment extraction by using both conventional dictionary methods based on customized word...

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...

We focus on the stock selection step of the index tracking problem in passive investment management and incorporate constant changes in the dynamics of markets into the decision. We propose an approach, using machine learning techniques, which analyzes the performance of the selection methods...

This articlemodels the dependence risk and resource allocation characteristics of two 20-stock coal–uranium and oil–gas sector portfolios fromthe Australian market in the context of the global financial crisis of 2008–2009. The modeling framework implemented consists of pair vine copulas...

The aim of this paper is to assess the effectiveness and risk in the stock exchange market in Central and Eastern Europe countries (CEE) in view of the largest stock exchanges: NYSE2‑LSE‑HKSE2. The implementation of this objective was based on an analysis of basic stock market indicators and...

This article empirically investigates the volatility spillover of stock returns from the market to disaggregated industry sectors. Seventeen sectors from the US and UK stock markets are estimated by the GARCH technique based on daily data from 1973 to 2008. The key findings are two-fold. In the...

A speculative bubble is usually defined as the difference between the market value of a security and its fundamental value. Although there are several important theoretical issues surrounding the topic of asset bubbles, the existence of bubbles is inherently an empirical issue that has not been...

Value-at-risk (VaR) is a useful risk measure broadly used by financial institutions all over the world. VaR has been extensively used to measure systematic risk exposure in developed markets like of the US, Europe and Asia. This paper analyzes the accuracy of VaR measure for Pakistan's emerging...