We explore the use of implied volatility indices as a tool for estimate changes in the synchronization of stock markets. Specifically, we assess the implied stock market’s volatility indices’ predictive power on synchronizing global equity indices returns. We built the correlation network of 26 stock indices and implemented in-sample and out-of-sample tests to evaluate the predictive power of VIX, VSTOXX, and VXJ implied volatility indices. To measure markets’ synchronization, we use the Minimum Spanning Tree length and the length of the Planar Maximally Filtered Graph. Our results indicate a high predictive power of all the volatility indices, both individually and together, though the VIX predominates over the evaluated options. We find that an increase in the markets’ volatility expectations, captured by the implied volatility indices, is a good Granger predictor of an increase in the synchronization of returns in the following month. Estimating, monitoring, and predicting returns’ synchronization is essential for investment decision-making, especially for diversification strategies and regulating financial systems.

This investigation connects two crucial economic and financial fields, financial networks, and forecasting. From the financial networks perspective, it is possible to enhance forecasting tools, since econometrics does not incorporate into standard economic models, second-order effects, nonlinearities, and systemic structural factors. Using daily returns from July 2001 to September 2019, we used minimum spanning tree and planar maximally filtered graph techniques to forecast the stock market realized volatility of 26 countries. We test the predictive power of our core models versus forecasting benchmarks models in and out of the sample. Our results show that the length of the minimum spanning tree is relevant to forecast volatility in European and Asian stock markets, improving forecasting models performance. As a new contribution, the evidence from this work establishes a road map to deepening the understanding of how financial networks can improve the quality of prediction of financial variables, being the latter, a crucial factor during financial shocks, where uncertainty and volatility skyrocket.

Purpose: The purpose of this paper is to provide evidence about the effects of the MILA agreement in terms of improving financial market efficiency. Design/methodology/approach: The authors measure efficiency by studying the stock reaction to earnings announcements using a conditional heteroscedasticity generalized autoregressive conditional heteroscedasticity-adjusted market model and the most commonly implemented event study tests for 3,399 events across four countries in the Latin American Integrated Market (MILA). Findings: Contrary to expectations, the results show that the MILA agreement has isolated gains in terms of reaction to corporate earnings announcements, which translates into partial improvements in market efficiency. However, the evidence indicates that the MILA agreement favored cointegration, which is in line with other studies. Practical implications: This paper provides evidence for policymakers and regulators that a stock market agreement is a condition that promotes market cointegration, but it is not an element that in itself ensures an improvement in market efficiency. To achieve greater MILA benefits, regulatory and market-level changes are required. Originality/value: This is the first study that analyses the effect of a stock market agreement on the efficiency of markets, expanding on what has been studied in the finance literature regarding the influence of these agreements on cointegration.

The synchronization in financial markets has increased during the rise of global markets. Nevertheless, global shocks provoke high levels of returns synchronization that jeopardize market stability. Using correlation‐based networks, regressions, and VAR models, we measure and estimate the effect of global synchronization on the world equity markets of North America, Latin America, Europe, Asia, and Oceania between July 2001 and April 2020. We find that our measure of global stock synchronization is dynamic over time, its minimums coincide with significant financial shocks, and it shrinks to its minimum levels, indicating that the returns of global markets are moving in a synchronized way. Also, it is a significant and positive factor of regional synchronization. Regional markets react heterogeneously to global synchronization shocks suggesting both local and global factors are sources of synchronization. Our work helps market participants who need to measure, monitor, and manage the synchronization of returns in a parsimonious, dynamic, and empirically tractable way. Our evidence highlights the necessity of including synchronization as a risk factor to assess the decision‐making criteria of a broad range of market participants ranging from regulators to investors. To policy‐makers, governments, and central banks, our work is a call to incorporate events of high global synchronization into the radar of hazards of the whole market stability.