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The purpose of this paper is to investigate the sources of the apparent episodic stationarity of the P/E ratio.

The Stock–Watson procedure is used to decompose a VAR/VMA model into changes in structure and changes volatility. In theory, if the P/E ratio is properly anticipated and shocks are random, according to Samuelson's proof, it should exhibit the characteristics of a pure martingale and therefore it should not be possible to statistically reject trend nonstationary.

Using a rolling window, the P/E ratio is shown to have episodic periods when trend nonstationarity could be rejected and that the P/E ratio was not properly anticipated. However, if there were changes in the structure of the underlying P/E ratio model or changes in the volatility of the underlying model, it suggests that the shocks impacting the P/E ratio would not be random and it might be possible to reject nonstationarity. This is investigated further with the objective of determining whether there was underlying structural change or volatility changes that are associated with these periods when trend nonstationarity in the P/E ratio could be rejected. The results are tested and found to be robust to a number of different specifications examined, including different data periods and frequencies.

Results findings should be tested in other countries and in other periods.

The paper developed a methodology whereby it is possible to detect periods there the P/E ratio is not properly anticipated.

This study aims to investigate the existence of bubbles and their contagion effect in crude oil and stock markets of oil-exporting countries Gulf Cooperation Council (GCC) from 2016 to 2021.

The authors use Generalized Sup augmented Dickey–Fuller (GSADF) and Backward Sup augmented Dickey–Fuller (BSADF) to significantly identify multiple bubbles stock and oil markets with precise dates. Furthermore, the authors check the contagion effect of bubbles between crude oil and GCC stock markets based on the time-varying Granger causality test.

First, the authors find empirical evidence of downwards bubbles in crude oil prices and in all GCC stock indexes (except the Saudi stock index) during the corona virus disease 2019 (COVID-19) outbreak. Second, the authors do not detect empirical evidence of bubble transmission between crude oil markets and GCC stock markets (except with the Dubai Financial Market index).

The findings of this study would illuminate policymakers not to limit the factors of systematic financial crises in oil-exporting countries to crude oil and to consider factors such as monetary policy and economic diversification measures. This study has also crucial implications for investors. In fact, investors should not ignore the responses of the stock markets to oil price shocks that are heterogeneous across countries when looking for investment opportunities in the GCC region.

The study justifies the changing nature of the bubble contagion effect through the novel implementation of the time-varying Granger causality test to detect whether bubble contagion exists between oil and GCC stock markets and if that does, in which direction.

This study presents an investigation of the long and short‐term co‐movements between different hedge fund strategy indices and the stock markets of France, Germany, Japan, North America and the UK. To analyse relationships among these price indices, the EngleGranger methodology, based on bivariate testing for cointegration, and correlation analysis are conducted. The question of long‐term dependence instead of short‐term consideration is of particular interest, because portfolio optimization is based upon the cointegration of prices, rather than the correlation of returns. However, as is generally known, there is an information loss when returns are used instead of prices. Results indicate that there exists no station ary, long‐term relationship between the two as set groups. The overall suggestion is that opportunities exist to diversify an international portfolio by taking hedge funds into account. Moreover, this applies not only in terms of a limited time period, but also in the long‐run. Besides this main result, the augmented Dickey‐Fuller test statistics for cointegration residuals show quite different behaviour in comparison to the correlation co efficients. The values of the test statistics show that there seems to be a weaker tendency towards long‐term interrelation between hedge fund strategies and the US stock market. This applies even though average correlation co efficients among these assets exceed those of other combinations between stock and hedge fund indices.

The purpose of the paper is to examine the linkages between exchange rate and interest rate in India using quarterly data from Q1 of 1996 to Q4 of 2014.

Stationarity properties of data are checked using the Augmented Dickey–Fuller (ADF), Dickey–Fuller test with GLS de-trending (DF-GLS) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests and Perron’s unit root test with structural breaks. Johansen Juselius and Gregory Hansen tests are applied to assess cointegration, and block exogeneity test is used to detect causality among variables.

The study finds long-run relationship among interest rate, rupee–dollar exchange rate, capital flows, intervention, inflation differential, money supply differentials, output differentials and trade-balance differentials. However, the interest rate does not explain movements in the exchange rate, directly and indirectly, via capital flows. Intervention by the Central Banks to stabilize exchange rate does not have implications for movements in interest rate.

The study finds capital flows to be insensitive with respect to interest rates and hence thwarts International Monetary Fund ’s (IMF) claim of using interest rates as a tool to stabilize exchange rate. The much-debated conflict between exchange-rate stabilization and control over interest rates also does not hold up to the empirical reality of India.

The study augments the existing literature by taking into account the problem of structural break in the relationship between interest rate and exchange rate. Three measures of interest rate are used to assess the robustness of results adding to their credibility compared to previous studies.

A Monte Carlo experiment is used to examine the size and power properties of alternative Bayesian tests for unit roots. Four different prior distributions for the root that is potentially unity – a uniform prior and priors attributable to Jeffreys, Lubrano, and Berger and Yang – are used in conjunction with two testing procedures: a credible interval test and a Bayes factor test. Two extensions are also considered: a test based on model averaging with different priors and a test with a hierarchical prior for a hyperparameter. The tests are applied to both trending and non-trending series. Our results favor the use of a prior suggested by Lubrano. Outcomes from applying the tests to some Australian macroeconomic time series are presented.

The present study investigates the dynamic effects of domestic credit measured by claims on non financial public enterprises and claims on private sector on the real GDP in Jordan for the period 1970‐2002. The stationarity properties and the order of integration of the data employed were empirically examined using the Augmented Dickey‐Fuller test. The cointegration test proposed by Johansen was also employed to test for the existence of longrun relationship among the non stationary time series data. The result of the cointegration test suggests that there exists a cointegrating relationship between real GDP and claims on private sector. The short‐run and long‐run relationships between real GDP and claims on private sector were examined using the VEC technique. In the short run, real GDP turns out to have an impact which is statistically significant on the claims on private sector, while in the long run, the claims on private sector turn out to affect real GDP at the 1% significance level.

To examine the existence of underwriting cycles for the property‐liability insurance industry as a whole, and by line of business. Specifically to consider whether the combined ratio is stationary and stable.

The augmented Dickey‐Fuller (ADF) test is employed for unit roots, while dummy variable methods, the Chow test, and switching regression are used for stability.

Underwriting profits of most lines of business and all lines combined are not stationary and have structural changes. For the whole property‐liability industry, a structural change occurred in 1981. Before the change, underwriting cycles existed since combined ratios followed an AR(2) process. After the change, combined ratios are non‐stationary.

Without clear underwriting cycles, there is more difficulty for the insurance industry in pricing and reserving, for regulators in monitoring the financial strength of insurers, and for customers in terms of the affordability and availability of insurance.

The paper recognizes the non‐stationarity of combined‐ratio series, years of structural changes in the insurance industry and specific lines of business, and the possibility that underwriting profit is cointegrated with investment income.

Internationalization of capital markets gives opportunities to investors to invest their money in the country of their choice, not just in their own country. The relationships between international stock markets have become increasingly important in recent times. The purpose of this paper is to study the inter‐linkages between stock markets of India, Pakistan and Sri Lanka.

This paper studies the inter‐linkages between stock markets of India, Pakistan and Sri Lanka. Daily closing levels of the benchmark indices in the three countries are taken for a period of January 2003‐June 2010. While line charts, correlogram and unit‐root test are applied to check the stationary nature of the series; Granger's causality model, vector auto regression (VAR) model and variance decomposition analysis are performed to find out the linkages between the markets under study.

The paper concludes that while the National Stock Exchange (India) Granger causes Karachi Stock Exchange (Pakistan) and Colombo Stock Exchange (Sri Lanka), the vice versa is not true. These results of Granger's causality model are also confirmed by the VAR models.

Studies have been conducted in large numbers to test the linkages and integration between stock exchanges of the developed nations, namely the USA, Canada, Europe and Japan. Even the studies that have focused on the developing and under‐developed nations have studied the linkages of those with the developed nations. Little research has been conducted about the inter‐linkages between the nations from Asia. Even fewer studies have focused on stock exchanges in the South‐Asian region. This research paper focuses on the return from the benchmark stock exchanges from these three countries and also on the linkages between India, Pakistan and Sri Lanka.