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This study examined the factors affecting university students' financial decisions in Pakistan.

Structural equation models were used to analyze data from 300 university students using a questionnaire. Students' financial decisions were used as the dependent variable, while financial literacy, money ethics, money attitude, time preference, financial experience, and financial specialization agents were the independent variables.

Resultantly, power, personal financial literacy, achievement, financial behavior, avoidance, reward for efforts, financial experience, financial attitude, financial socialization agents, and time preference influence the students' financial decisions.

The findings are useful for financial and educational institutions and policymakers who design academic courses.

This study measured the effects of several critical contextual areas regarding financial literacy and students' decisions in Pakistani universities.

This study aims to examine the volatility spillover effects between oil and stock returns in the emerging seven economies.

In this study, the Granger causality test and vector autoregression-generalized autoregressive conditional heteroskedasticity approach to analyze the volatility spillover from 1995 to 2019 were used. The findings provide evidence of significant volatility spillover between oil and Brazil, China, India, Indonesia, Mexico, Russia and Turkey (E7) stock markets.

All emerging seven stock markets exhibit positive and low constant conditional correlations with oil assets. The magnitude of the correlation changes in respond to the country’s net position in the crude oil market. While a relatively high level of correlation exists between oil and the stock markets of net oil-exporting countries, a relatively low level of correlation exists between oil and the stock markets of net oil-importing countries.

The findings suggest that oil asset improves the risk-adjusted performance of a well-diversified portfolio of stocks. However, investors should invest a larger portion of their portfolios in E7 stock markets than in oil.

The purpose of this paper is to examine volatility spillover from the Chinese stock market to E7 and G7 stock markets. Using the estimated results, the authors also analyze the optimal weights and optimal hedge ratios for the portfolios including stocks from E7 and G7 countries.

The authors employed generalized vector autoregressive-generalized autoregressive conditional heteroskedasticity approach, developed by Ling and McAleer (2003), in order to analyze daily data on the national stock indices. Considering the late establishment of some E7 stock markets, the sampling covers the period from 1995 through 2015.

The findings indicate significant volatility spillover from the Chinese stock market to E7 and G7 stock markets. In particular, the Chinese stocks highly co-move with the stocks of countries within a same geographical region. While the highest volatility spillover occurs between China and India among E7 countries, the highest volatility spillover occurs between China and Japan among G7 countries. Furthermore, the examination of optimal weights and hedge ratios suggest that investors should hold more stocks from G7 countries than E7 countries for their portfolios.

To the best of the authors’ knowledge, this is the first study which investigates the volatility spillover in the stock markets of G7 and E7 countries. Moreover, the current study contributes particularly to the existing limited literature on the Chinese stock market. Since the Chinese stock market is not fully integrated to other markets and it is subject to intense government interventions, there is a widely accepted belief that the contagion effects from the Chinese stock market to other stock markets are not influential. This view discourages and limits the prospect studies. However, the findings of this paper refute this view and indicate significant interaction among the Chinese stock market and E7 and G7 stock markets.