The linear absolute shrinkage and selection operator(Lasso) method improves the low prediction accuracy and poor interpretation of the ordinary least squares(OLS) estimate through the use of L1 regularization on the regression coefficients. However, the Lasso is not robust to outliers, because the Lasso method minimizes the sum of squared residual errors. Even though the least absolute deviatio...

Data mapping is the essence of being human. This report follows the process of data mapping; the transmission of a structured utterance from one domain to another. It starts with signals in the world and moves through experience and engagement with the world through those signals. The paper develops descriptions of the materials and mechanisms of data mapping. The descriptions are aids and conv...

this research applies and compares the market leverage lally method, ibbotson and sinquefield method and siegel method, to present alternative measures for market risk premium (mrp) estimation and test forecasting power of these methods in calculating expected rate of return. the higher level of leverage implies greater risk of investment in a specified stock, so higher return is expected by in...

Sun, Titman, and Twite (2014) find that risky capital structure characteristics, such as high leverage, a high share of debt due in the near future and a high share of variable-rate debt, significantly reduce the cumulative total returns of US REITs over the 2007-2009 financial crisis. In this paper we show that preparing ahead of the crisis significantly improved the cumulative return over the...

Digital inequality, or the unequal access and use of information communication technologies, inhibits under-privileged people from opportunities in the digital world. Although government and private organizations have devoted considerable resources to address this inequality, issues remain unsolved. A theory-based investigation of the phenomenon is essential for effective policy-making and inte...

The traditional estimation of mixture regression models is based on the normal assumption of component errors and thus is sensitive to outliers or heavy-tailed errors. A robust mixture regression model based on the t−distribution by extending the mixture of t−distributions to the regression setting is proposed. However, this proposed new mixture regression model is still not robust to high leve...

The banks’ response to their changes in leverage ratios is examined and evaluated in this paper. This reaction can be interpreted as if the coefficient of total debts to equity (lev1) and total assets to equity (lev2) are positive as anticipated in the banking network of Iran. The paper uses data from 31 Iranian banks’ annual databases during the course of 2006-13 in order to estimate an empiri...

This study investigates the effect of intra-organizational and macroeconomic factors on banking leverage in selected Iranian banks. For this purpose, after calculation of the Banking Leverage for each bank, by using Random-Coefficients Approach (Swamy model), the impact of explanatory variables during the period of 1999-2016 was examined separately by 10 selected Iranian public and private bank...

The detection of influential observations for the standard least squares regression model is a question that has been extensively studied. LAD regression diagnostics offers alternative approaches whose main feature is the robustness. In this paper a new approach for nonparametric detection of influencial observations in LAD regression models is presented and compared with other classical method...

Following EU’s Lisbon strategy development of knowledge-based economy has become one of the headline objectives for the government of Latvia. In this paper we conceptualize driving forces and responses of government’s commitment towards this objective. We investigate feedback loops that underlie dynamics of knowledge industry development. Increase in domestic Research and Development (R&D) acti...