Incremental information of stock indicators

The present paper is the first to examine the incremental information of stock indicators in the spot and futures stock markets. The properties of volatility series of indicators in relation to spot and futures stock indices are examined. Correlations between either the spot or futures stock indices and the corresponding indicators are examined for their properties. The asymmetry, heterogeneity and jump properties of volatilities and correlations are studied. Indicators offer information not captured in the corresponding futures and spot stock indices. Volatility and correlation in the stock market are accurately in-sample predicted via asymmetric and HAR models. The inclusion of indicators improves the in-sample modeling of volatility and correlation in the stock market

Uncertainty and realized jumps in the pound-dollar exchange rate : evidence from over one century of data

We study the importance of economic uncertainty so as to predict realized jumps (hereafter jumps) in the pound-dollar exchange rate. The empirical analysis covers the time period from February 1900 to May 2018 on amonthly basis, incorporating several market states, including various booms and crashes. First, we apply a standard linear Granger causality test in order to identify causal effects fromeconomic uncertainty to jumps.We show that the standard linear Granger causality test fails to capture such casual effects. Providing the misspecification of the linear model, we next make use of a nonparametric causality-in-quantiles test. This test allows us to take into account the substantial evidence of nonlinearity along with the structural breaks between economic uncertainty and jumps. In applying this data-driven robust procedure, we find strong evidence of uncertainty causing jumps of the dollar-pound exchange rate. These results are robust over the entire conditional distribution of jumps, exhibiting the strongest impact at the lowest conditional quantiles considered. In addition, our results are generally found to be robust to alternative measures of uncertainty, jumps generated at a daily frequency based on shorter samples of intraday data, and across three other dollar-based exchange rates.https://www.degruyter.com/journal/key/snde/htmlam2024EconomicsSDG-08:Decent work and economic growt

The impact of political risk on return, volatility and discontinuity: evidence from the international stock and foreign exchange markets

The paper examines the impact of political risk on stock and foreign exchange markets in a comprehensive sample of sixty-six countries and twenty political risk indicators mostly covering the financial crisis and recovery periods from May 2001 to April 2014. The impact is assessed on return, volatility and jumps series of monthly frequency. Evidence reveals that Europe is mostly at higher risks generated from economic crisis; whereas, political risks explain the high volatility and discontinuity in international stock and foreign exchange markets in other regions

Market risk of BRIC Eurobonds in the financial crisis period

The market risk of returns for BRIC Eurobonds has not been thoroughly analyzed via nonparametric estimation methods. The significance of risk and jumps is examined in a monthly sampling frequency. A detailed comparison upon significance of risk and jumps between BRIC Eurobonds is provided. Comparison concerns risk and jumps during the international financial crisis period: February 2007 up to February 2010. Among the BRIC countries, Chinese Eurobonds are the most significant in terms of both risk and jumps. The most significant estimator is the monthly Yang & Zhang range across the set of BRIC Eurobonds. The shorter the expiry period, the higher is the significance of risk and jumps. This is evident in all BRIC Eurobonds. Risk and jumps estimates are higher for theoretical prices rather than for actual prices according to all risk and jump significance measures

The properties of realized volatility and realized correlation: evidence from the Indian stock market

This paper investigates the properties of realized volatility and correlation series in the Indian stock market by employing daily data converting to monthly frequency of five different stock indices from January 2, 2006 to November 30, 2014. Using non-parametric estimation technique the properties examined include normality, long-memory, asymmetries, jumps, and heterogeneity. The realized volatility is a useful technique which provides a relatively accurate measure of volatility based on the actual variance which is beneficial for asset management in particular for non-speculative funds. The results show that realized volatility and correlation series are not normally distributed, with some evidence of persistence. Asymmetries are also evident in both volatilities and correlations. Both jumps and heterogeneity properties are significant; whereas, the former is more significant than the latter. The findings show that properties of volatilities and correlations in Indian stock market have similarities as that show in the stock markets in developed countries such as the stock market in the United States which is more prevalent for speculative business traders

Optimally sampled realized range-based volatility estimators

Range-based volatility estimators are analyzed in both daily and intraday sampling frequency and are also compared to the realized volatility estimator. The family of realized range-based estimators is extended as three range-based estimators are introduced. These three realized Parkinson range-based estimators are estimated in an optimal sampling frequency. Empirical analysis concerns three major US spot equity indices. The descriptive statistics and the long-memory estimations are compared between the daily and realized range-based estimators, and across each group as well. The realized range-based estimators are also compared in terms of the properties of the jump components of volatility. Moreover, the relevant effects of jumps on volatility are assessed by the use of the class of Heterogeneous Autoregressive (HAR) models. © 2013 Elsevier B.V

Evaluation of the Federal Reserve’s financial-crisis timeline

The present paper evaluates the effect that the events and policy actions important for the Federal Reserve had in five US financial markets. Analysis concentrates on events starting from February 2007 up to August 2009, as dictated by the financial-crisis timeline of the Federal Reserve Bank of St. Louis. Evaluation is indicated via an economic and statistical significance criterion. The former is based on Sharpe-ratio and the latter on Welch's t-test. Robustness of the latter criterion as appropriate for event evaluation is provided via a Kolmogorov–Smirnov test. An overall comparative analysis across the board of categories of the financial events is provided as well. Are there categories of events more significant than others? Is it fiscal decisions or policy actions that more significantly affect US financial markets? Results suggest that academics, economists and financiers re-think the significance of some of the events and policy decisions. Analysis is implemented in the following US financial markets: stock spot indices, stock index futures, Exchange Traded Funds, US Treasury bond futures and spot exchange rates

Realized correlation analysis of contagion

This paper investigates the cross-market contagion between spot and futures US stock markets by examining the significance and properties (textbook and lead-lag asymmetries) of realized correlation, testing the assumptions of the cost-of-carry model, as well as testing the in-sample predictive significance of heterogeneity and jumps to realized correlation. Evidence from the US stock market suggests realized correlation can be very helpful analyzing contagion. There is strong evidence of statistically significant cross-market contagion in the US stock markets, when realized correlation is used as conditional correlation, across all methods employed. To the best of my knowledge, this paper is the first to nonparametrically analyze contagion based on realized correlation

The properties of realized correlation: Evidence from the French, German and Greek equity markets

In this paper I examine the properties of four realized correlation estimators and model their jumps. The correlations are between the French, German and Greek equity markets. Using intraday data I first construct four state-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. Then the realized correlation is modeled with the simple Heterogeneous Autoregressive (HAR) model and the Heterogeneous Autoregressive model with Jumps (HAR-J).DAX CAC40 Athens Stock Exchange Realized correlation Bipower variation Range Optimal sampling Long memory Asymmetry Jumps Heterogeneous autoregressive models

Nonparametric realized volatility estimation in the international equity markets

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 heterogeneous autoregressive (HAR) models for assessing the relevant effects of jumps on volatility. Our results expand and complement the previous literature on the nonparametric realized volatility estimation in terms of volatility jumps being examined and modeled for the international equity market, using such a variety of new realized volatility estimators. The selection of realized volatility estimator greatly affects jump detection, magnitude and modeling. The properties each volatility estimator tries to incorporate affect the detection, magnitude and properties of jumps. These volatility-estimation and jump properties are also evident in jump modeling based on statistical and economic terms