تعامل پویا میان بازارهای سهام، اوراق قرضه و بیمه
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|15087||2013||25 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : The North American Journal of Economics and Finance, Volume 26, December 2013, Pages 28–52
This paper explores the lead–lag relationships and the dynamic linkages among stock, insurance and bond markets in the developed countries. This is the first empirical study which sheds light on the extent and magnitude of the association among these financial markets used by the Granger causality test of Toda and Yamamoto (1995), generalized impulse response approach, and generalized variance decomposition in a multivariate setting. Our empirical results illustrate that there are indeed various patterns of dynamic relationships. The direction of causality appears to differ across countries. While investigating these interactive relationships under unexpected shocks, there is a one-way significant influence between the life insurance premium and long-run interest rate. These empirical findings serve as valuable applications not only for investors to diversify their risk away as well as to earn the abnormal return, but also for policy-makers to allocate resources more efficiently.
In mid-September 2008, the Federal Reserve felt it necessary to lend not just once but twice to American International Group (AIG) to keep the world's largest property–casualty insurance conglomerate afloat (Harrington, 2009 and Litan, 2009). Why did the Federal Reserve want to assist AIG through the financial turmoil? Reports conjecture if AIG were bankrupted, it would result in a serious shock over the global financial sectors. A failed AIG gives U.S. economy big shock and starts the global financial crisis, and U.S. government is aware of that the insurance market wields greatly influence over the world economy or over the worldwide financial sectors. In addition, according to previous studies, the real impact of insurance market on economic performance has been proved empirically (Chang and Lee, 2012, Chen et al., 2012, Haiss and Sümegi, 2008, Han et al., 2010, Lee, 2013, Lee et al., 2013, Sümegi and Haiss, 2008 and Ward and Zurbruegg, 2000). However, to date, the literature on investigating these vital linkages between insurance and other financial markets is less developed. In the past few years, the role of insurance companies in financial markets has been transformed. The functions of insurance companies are turning to risk transfers (i.e., bearing risks as other economic agents who might stabilize their income streams, dampen volatility and enhance the performance of economic activity) and institutional investors in financial markets. Along with the financial innovation, the changes in the global financial environment have led to growing business opportunities for the insurance industry. Insurance companies have evolved new-style insurance contracts to enable investors to generate capital profits and meet their financial requirements for life. U.K.-style contracts, U.S. universal life contracts, Norwegian-style contracts and so on, as well as with-profit life insurance policies, which contain guarantees and embedded options, have recently raised considerable concerns in many countries (Kassberger, Kiesel, & Liebmann, 2008). Therefore, a well-developed insurance market will broaden the investment spectrum and extend investment maturities. Haiss and Sümegi (2008) demonstrate that the importance of the insurance-growth linkage was growing due to the increasing share of the insurance sector in the aggregate financial sector of a mature market-driven economy. Insurance companies are one of the biggest institutional investors in the stock, bond and real estate markets. When a government implements economic or financial policies, they must think of the influence of the insurance market to provide more social benefit in stable society. In practice, few studies explore the dynamic interrelationships among the stock, bond and insurance markets and investigate the impact of unexpected shocks based on a developed multi-country comparison. The theoretical literature has mostly emphasized the potential complementarity or substitutability between stock and bond markets (Barsky, 1989, Campbell and Ammer, 1993 and Shiller and Beltratti, 1992). Moreover, insurers differ in the amount of excess capacity that they hold and they face different state-level regulatory constraint (Jawadi, Bruneau, & Sghaier, 2009). But, the insurance market has hardly been investigated for its role in comparison with other financial markets. Nevertheless, total insurance premiums have been rapidly growing, even though previous studies do not focus on the insurance market,1 from 1979 to 2007 in the U.S. and U.K. as shown in Fig. 1. The motivation is to discern whether there are directional dynamic relationships among those financial markets. More interestingly, by applying multi-country analysis, we not only observe some common phenomenon and special outcomes in the world, but also it offers us useful information – long-term domestic and international investors who diversify their portfolio risk away as well as speculative in regard to abnormal returns. Full-size image (39 K) Fig. 1. Varying insurance premiums in dollars for the U.S. and U.K. Figure options The purposes of this article are, first, to examine the causal relationships that potentially exist related to growth in the insurance industry, the stock returns, and long-term interest rate, and to discuss the complementary, substitutive or independent effects among these financial markets for developed countries. Besides, we attempt to provide meaningful information for domestic or international investors to construct their trading strategies for arbitrage, hedging or diversifying their risk away. Second, by describing the dynamic reactions among these markets under unexpected shocks we can provide some implications to policy-makers as well, such as those resulting from monetary or fiscal policies or the current financial crisis (domestic or international events). To accomplish these tasks, we first focus on time-series econometric framework within six developed countries (Canada, France, Japan, the United Kingdom and the United States) from 1979 to 2007, as well as provide detailed insurance data to separate the total insurance premiums from life and non-life business. Moreover, the Toda and Yamamoto (1995; TY hereafter) approach is also used to examine the dynamic movement among the stock, insurance and bond markets. The TY approach allows us to study the causal relationship without performing pre-tests to avoid our data loss. Broadly speaking, our insurance data cover 29-year long period and are more completed and reliable than those in previous related studies. Regarding Granger causality tests are sensitive to omitted variables bias, we follow Ward and Zurbruegg (2000) and Lee (2013) to employ multivariate framework instead of using bivariate framework to begin with. In addition, a fundamental issue in finance is concerned that partial analysis of dynamic causal relations is employed in the paper because a rigorous time-series analysis is infeasible to practice. Last, we employ advanced generalized forecast error variance decomposition (GVDC) as well as the generalized impulse response functions (GIRF) as described by Pesaran and Shin (1998) to examine the dynamic effect among the stock, insurance and bond markets. The GVDC can provide the proportion of the movements in the dependent variables that are due to their own shock, versus shocks to the other variables (Chen et al., 2011, Hammoudeh and Sari, 2011 and Sousa, 2010). Therefore, GVDC provides information regarding the relative importance of each random innovation in affecting the variables in the VAR system. Those methodologies provide meaningful interpretations of the initial impact of shocks – a feature that is missing in the traditional approach but it might be important in the analysis of the insurance market where information is transmitted together with different market states. The main findings in our papers are various patterns of dynamic relationships across those developed countries. The stock markets in U.K. and U.S. are the leading indexes of the insurance market, and bond market is also affected by the insurance market. There is a complementary relationship between the insurance and stock markets in the U.K., but a substitution relation in the U.S. Moreover, in Japan the insurance asset is a highly diversified tool because of no causal relationship finding. Nevertheless, the results suggest that policy-makers not merely place emphasis on the development of stock and bond markets, but also consider the interaction influence with insurance market. With optimal decisions, policy-maker allocates resources more efficiency and makes the monetary policy working better. The remainder of this paper is organized as follows. The next section details the possible dynamic interrelationships among the insurance (life and non-life) premiums, stock prices, as well as long-term government bond returns. The third section then introduces the estimation methodology to be employed for the empirical results that are discussed in the fourth section. Concluding remarks and implications are contained in the final section.
نتیجه گیری انگلیسی
In the past decade, theoretical and empirical researches on the insurance issue have proved that insurance market activity is closely associated with economic performance. One of these indicates that complementarity (a positive correlation) exists between the insurance and financial markets. Others show that these financial markets either exhibit a substitution effect (a negative correlation) or no significantly correlated. However, most of the prior studies which lack the dynamic connections of cross-sectional analysis in these markets as discussed by the panel approach might have difficultly showing obvious conclusions. To improve this drawback, this article not only investigates the causal relationships, i.e., the substitutive or complementary relationships, among the stock, insurance and bond markets, but also illustrates the unexpected impact on these linkages as shocks occur. This provides long-term investors with important trading information to diversify risk away as well as earn abnormal returns, and policy-makers to allocate resources more efficiently. First, in this article we apply the VAR model developed by Toda and Yamamoto (1995) which is able to be neglected in models that require differencing and pre-testing to lessen the loss of data in several developed countries, namely, Canada, France, Italy, Japan, the United Kingdom and the United States, over the 1979–2007 periods. In order to derive more general empirical results, we separate the insurance premium data into life and non-life premiums. The empirical results show that there are various patterns of dynamic relationships across developed countries. For instance, the U.K. and U.S. stock markets are the leading indexes of the insurance market and the bond market in the next period will be affected by the insurance market. Moreover, we can find that there is a complementary between the insurance and stock markets is in the U.K., but substitution in the U.S. By contrast, in Japan the insurance asset is a highly diversified tool because of no causal relationship among them. Secondly, we make use of the generalized impulse response function to detect the on these dynamic relationships when unexpected shocks occur. In France, Japan, the U.K. and the U.S., there is a unidirectional significant influence between the life insurance premium and the long-run interest rate. In referring to the stock market, only the shock in Japan has a significant effect on the life and non-life insurance premiums. Thirdly, form the analysis of the generalized variance decomposition, life and non-life insurance premiums are not usually the most exogenous assets compared with those in other financial markets. These are valuable applications for investors to readjust their trading strategies appropriately and policy-makers to implement either monetary policy or financial support carefully when unexpected changes take place. Finally, we organize the empirical results based on our hypotheses and provide some beneficial suggestions for investors and policy-makers. For example, under complementary cases, if the financial markets are growing as in the cases of the stock or bond markets, investors should either long stock or bond assets, and then short their insurance assets to regulate their hedging strategy, or else long insurance and other financial assets to earn abnormal returns. Furthermore, with respect to policy-makers, this paper implies that the insurance market really plays a vital intermediary role that a number of studies usually ignore. And it could give empirical ground to the micro-insurance policy strategy of the stock and the bond markets and complement the theory of the wealth effects of insurance. Therefore, policy-makers not merely place emphasis on the development of stock and bond markets, but also consider the influence of insurance markets together to make optimal decisions that allocate resources more efficiently so that the monetary policy works better.