This study aimed to estimate the prevalence of uninsurance among California adults and Asian Americans, and to examine the associations of social-behavioral variables with uninsurance. A total of 24,136 adults (aged 18-64) including 2,060 Asian Americans were selected from the combined 2013-2014 California Health Interview Survey. Weighted univariate and multivariate logistic regression analyses were used to estimate the associations of potential factors with uninsurance. To evaluate the relationship of independent variables, the oblique principal component cluster analysis (OPCCA) was used to classify 9 variables into disjoint clusters. For Whites, African Americans, Latinos, and Asians, the prevalence of uninsurance was 8.5%, 10.3%, 24.7%, and 12.6%, respectively. Among Asians, the prevalence of uninsurance was 15.5%, 9.2%, 6.2%, 20.8% and 12.1% for Chinese, Filipinos, Japanese, Koreans, and Vietnamese, respectively. In the whole sample, multivariate logistic regression analysis revealed that being male, non-citizen, lower education, higher poverty, and current smoking were associated with uninsurance. Among Asians, compared to Koreans, being Filipinos and Vietnamese were associated with lower odds of being uninsured; meanwhile being male, non-citizen, lower education, and higher poverty were significantly associated with increased odds of uninsurance. Elder age groups and current smoking were significantly associated with increased odds of uninsurance in bivariate analysis; however, such associations disappeared after adjusting for other factors. Nine independent variables were divided into 2 clusters, where the variables in the same cluster were strongly correlated but had weak correlations with the variables in the other cluster. In conclusion, there are differences in the prevalence of uninsurance between Asians and Whites, and among Asian subgroups. Being male, non-citizen, lower education, higher poverty and current smoking were positively significantly associated with uninsurance.

Do financial inclusion and stock market development play the deterministic role of attracting foreign capital flows in developing countries. With this study, we tried to figure out the answer by investigating the magnitude of financial inclusion and stock market development towards capital flows in the economy considering a panel of 58 developing countries for the span of 1993–2017. Dynamic panel System-GMM estimation was performed by decomposing the development and degradation namely, positive and negative shocks in financial inclusion and stock market development. Study findings ascertain the asymmetric relationship between financial inclusion, stock market development, and cross-broader capital flows in developing countries. We also observed positive shock in financial inclusion and stock market development positive linked with cross-broader capital flows. In particular, development in financial inclusion in the financial system encourages foreign capital flows in the form of FDI, on the other hand well developed and efficient financial market particularly stock market development encourage the positive trend in foreign portfolio investment. The study also revealed that past behavior of foreign capital flows could consider as the future predictor for foreign capital flows in recipients countries. Dumitrescu and Hurlin (2012) Panel Causality Test was performed and estimation unveiled bidirectional causality between stock market development and capital flows and unidirectional causality from financial inclusion to foreign capital flows in the short-run.

The real options approach has been supporting investment decision-making processes for years. However, on competitive markets, the real options games approach is the more suitable way. In this article, a real options game subject to analysis is the situation in which two companies with different market share are exploring an opportunity to implement a new investment project. It is known that competition on the market reduces the scope of benefits a company can gain whilst implementing the project. In this paper, we show that this reduction can be mitigated by taking into account payoff transfer designated as a bargaining solution. We discuss three main types of games between companies that we can observe on the market; then we analyze their bargaining solutions, and finally-come up with recommendations to companies. A firm that dominates its respective market usually benefits by implementing the most advantageous strategy, but in certain situations it should pay special attention to its weaker competitor's opportunities and try to anticipate its movements. In the paper, we show that with high project risk and significant asymmetry in the firms' market share, a weaker company may still hold all the cards.

This study investigates empirically the Environmental Kuznets Curve hypothesis within a financial development and natural resource extraction context for aggregate and sectoral carbon dioxide (CO2) emissions in Tunisia. Using annual time-series data covering the period 1971–2016 it is found that financial development increases aggregate CO2, CO2 emissions from the transport sector, and CO2 consumption from liquid fuel but reduces CO2 emissions from manufacturing and construction as well as the residential and building. Natural resource extraction exerts upward pressure on CO2 emissions from the manufacturing and construction sector as well as from the consumption of gaseous fuels whiles the contrary is found for CO2 emissions. The existence of the EKC hypothesis or otherwise within the context of financial development and natural resources extraction is found to be dependent on the source of CO2 emissions in Tunisia. The findings among other things imply the enforcement of stringent environmental laws that ensure environmental quality amidst natural resources extraction and financial development.

In this paper, portfolio selection problem is studied under Asymmetric Laplace Distribution(ALD) framework. Asymmetric Laplace distribution is able to capture tail-heaviness, skewness, andleptokurtosis observed in empirical financial data that cannot be explained by traditional Gaussiandistribution. Under Asymmetric Laplace distribution framework, portfolio selection methods basedon di erent risk measures are discussed. Moreover, we derived the Expectation-Maximization (EM)procedure for parameter estimation of Asymmetric Laplace distribution. Performance of the proposedmethod is illustrated via extensive simulation studies. Two real data examples are complemented toconfirm that the Asymmetric Laplace distribution based portfolio selection models are effcient.

Empirical multifactor models of excess returns are theoretically grounded in Merton’sICAPM. Merton modeled investors who maximize expected utility of their own consumption. Multiplepriced factors arise as “hedge portfolios” most closely correlated with state variables that driveintertemporal changes in the investment opportunity set. It is puzzling that empirically useful factorshave not been convincingly identified as those portfolios, despite massive e ort. But the majorityof asset demand now arises from style investors, i.e. institutionally managed funds that try to eithermeet (index funds) or beat (actively managed) returns from style-specific benchmark portfolios. Sowe modify Merton’s derivation to incorporate the aggregate demands derived from style investors’di erent objective functions. In addition to resolving the aforementioned puzzle, we show that thisstyle investing version of the ICAPM is more consistent with recent empirical evidence documentingcomovement among assets held in a style benchmark. Finally, the model casts doubt on the widespreadbelief that individual investors will necessarily benefit from funds with positive multifactor alpha.

This paper analyzes the information content of statistical tests for bubble detection in the context of international real estate markets. We derive binary indicators from the causal application of five statistical tests to log house prices, and via logit regressions we assess the indicators’ out-of-sample performance in the forecasting of tipping points of housing bubbles and systemic financial crises. In our assessment, three of the indicators - two based on the identification of super-exponential trends and one based on the scaled ratio of the sum of squared forecast errors - exhibit significant out-of-sample results. Combining the indicators via simple threshold-rules yields the most robust and best results.

With this study, we try to explore new insights about the existence of an asymmetric relationship between financial innovation, banking sector development, and economic growth of Asian countries for the period of 1974Q1 to 2016Q4. In this study, we apply Autoregressive Distributed Lag (ARDL) bound testing to capture long-run association and nonlinear Autoregressive Distributed Lagged (NARDL) to capture the existence of an asymmetric relationship between studied variables. ARDL-bound testing confirms long-run cointegration and nonlinear ARDL confirms the existence of an asymmetric relationship between financial innovation, banking sector development and economic growth of Asian countries. For a directional relationship, we perform Granger-causality under error correction model. Study support feedback hypothesis between financial innovation and economic growth and banking sector development and economic growth both in short and long run. The study suggests, the government should encourage financial innovation in the financial system through technological advancement and institutional integration and formulated economic policy favor of banking sector development by allowing institutional development, enterprise risk management and encouraging healthy competition in the financial system.

The Binomial Model and the Black Scholes Model are the popular methods that are used to solve the option pricing problems. Binomial Model is a simple statistical method and Black Scholes model requires a solution of a stochastic differential equation. Pricing of European call and a put option is a very difficult method used by actuaries. The main goal of this study is to differentiate the Binominal model and the Black Scholes model by using two statistical model -t-test and Tukey model at one period. Finally, the result showed that there is no significant difference between the means of the European options by using the above two models.