Global analysis of solar neutrinos (assumed to be Majorana particles) together with the new KamLAND data

Assuming neutrinos are Majorana particles having non-zero transition magnetic moments, a global analysis of solar neutrino data, together with the new KamLAND data, is presented in the resonant spin flavor precession (RSFP) framework. The allowed regions from solar data combined with new KamLAND data are examined at 0.95 confidence level (CL). The electron antineutrino flux from the Sun is calculated, and via the results obtained several limits are set for muB.Comment: 13 pages, 6 figure

Filtered Extreme Value Theory for Value-At-Risk Estimation

Extreme returns in stock returns need to be captured for a successful risk management function to estimate unexpected loss in portfolio. Traditional value-at-risk models based on parametric models are not able to capture the extremes in emerging markets where high volatility and nonlinear behaviors in returns are observed. The Extreme Value Theory (EVT) with conditional quantile proposed by McNeil and Frey (2000) is based on the central limit theorem applied to the extremes rater than mean of the return distribution. It limits the distribution of extreme returns always has the same form without relying on the distribution of the parent variable. This paper uses 8 filtered EVT models created with conditional quantile to estimate value-at-risk for the Istanbul Stock Exchange (ISE). The performances of the filtered expected shortfall models are compared to those of GARCH, GARCH with student-t distribution, GARCH with skewed student-t distribution and FIGARCH by using alternative back-testing algorithms, namely, Kupiec test (1995), Christoffersen test (1998), Lopez test (1999), RMSE (70 days) h-step ahead forecasting RMSE (70 days), number of exception and h-step ahead number of exception. The test results show that the filtered expected shortfall has better performance on capturing fat-tails in the stock returns than parametric value-at-risk models do. Besides increase in conditional quantile decreases h-step ahead number of exceptions and this shows that filtered expected shortfall with higher conditional quantile such as 40 days should be used for forward looking forecasting.Value at-Risk; Filtered Expected shortfall; Extreme value theory; emerging markets

N-fractional calculus operator NmuN^mu method to a modified hydrogen atom equation

By means of fractional calculus techniques, we find explicit solutions of the modified hydrogen atom equations. We use the N-fractional calculus operator $N^mu$ method to derive the solutions of these equations

ショウジョウバエの交尾を制御する遺伝子とニューロンの同定

Tohoku University山元大輔課