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Introduction: Studies on the insurance sector/companies have, in recent years, taken their place in literature at an increasing rate. Especially after the 2008 global financial crisis, the need for people to ensure their assets has structurally changed both the transaction volume and the yield structure of insurance sector. The increase in demand for insurance has also increased the appetite of investors to make an investment on this sector. The transaction volume of the insurance sector has increased year by year coupled with the number of insurance companies traded on the stock exchanges has started to increase in the same direction.

Aim: This chapter aims to determine the return structure of the Borsa Istanbul Insurance Index (XSGRT) based on daily closing values.

Method: Markedly with similar studies in the literature review, the authors determined that the Markov Regime Switching (MRS) model is the best-suited model for the current research. It was applied for the data set of XSGRT Index from 1997 to 2020.

Results: The result shows that XSGRT has three regimes named as expansion regime, normal regime and recession regime. Subsequently, it has been determined that the index generally attends to transition from the recession regime to the expansion regime and normal regime. This outcome is statistically significant at a 5% significance level and confirmed by backtesting results. Likewise, the duration of the recession regime is longer than the normal and expansion regime.

Conclusion: Despite the fact that the XSGRT has not yet completed its development compared to other main and sectoral indices, it is one of the indices that offer attractive earnings for investors. To put it differently, the desire of insurance companies to stay longer totally in the normal and expansion period and their immediate exit from the recession period provides them with a significant competitive advantage in contrast to other indices.

Originality/Value: This research contributes to the literature by providing additional evidence for existing studies using the longer duration of data set and applying the MRS model for Insurance Index. Best of our knowledge, it is the first study that examines the return structure of XSGRT based on its daily closing values from 1997 to 2020. In essence, investors can use the result of this study and compare it with other stock indices to make the accurate investment decision to maximise their welfare and return on their equity investments. The authors suggest that not only the return but also the regime structures of the invested shares (indices) should be taken into account for investment decisions.

Our study concentrates exclusively on the domestic effective tax rate (ETR), with the purpose of finding and characterizing their financial determinants. Using data on almost 5,000 US companies between fiscal years 2003 and 2010, we use regression analysis to find that the domestic ETR is affected by company size (as measured by sales), the extent to which the company is leveraged, level of fixed assets intensity, and the state of the economy. In addition, we find that domestic ETRs are also affected by the company’s level of internationality, which counterintuitively implies that the greater the company’s international activity, the less domestic taxes it pays for every dollar of US income. Both financial managers and policy makers can use our findings to reduce tax liabilities domestically, and to improve corporate tax regulations. While several attempts are made in the literature to compare ETRs of corporations that reside in different geographic locations, this is the first to characterize ETR determinants.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

This chapter sheds new light on the linkages between stock market fluctuations and business cycles in Asia. It shows that at cyclical frequencies stock markets lead business cycles by six months on average. China, Korea, and Taiwan constitute exceptions, as their real and stock market cycles are contemporaneously synchronized. The low level of maturity of these markets offers a potential explanation of this outcome. Furthermore, we find that the linkage also holds during phases of cyclical upswing and downturn, with the exception of China, where the financial market lags behind industrial production during expansions. Finally, for most of the countries (except Thailand and Malaysia), the linkage is also robust to the presence of financial crises.