c-theorem of the entanglement entropy

We holographically investigate the renormalization group flow in a two-dimensional conformal field theory deformed by a relevant operator. If the relevant operator allows another fixed point, the UV conformal field theory smoothly flows to a new IR conformal field theory. From the holographic point of view, such a renormalization group flow can be realized as a dual geometry interpolating two different AdS boundaries. On this interpolating geometry, we investigate how the c-function of the entanglement entropy behaves along the RG flow analyt- ically and numerically, which reproduces the expected central charges of UV and IR. We also show that the c-function monotonically decreases from UV to IR without any phase transition.Comment: 24 pages, 8 figure

Do Brokers Misallocate Customer Trades? Evidence From Futures Markets

In the context of futures markets, we study whether brokers allocate more favorable trades to their own accounts, and less favorable trades to their customers. We find that, within a thirty minute trading bracket, brokers on average buy at a lower price and sell at a higher price for their own accounts relative to their customers. We show evidence that brokers' price advantage may be compensation for providing liquidity to the market when brokers trade for their own accounts, but no evidence that they are due to brokers' superior information, or to greater effort by brokers when trading for themselves. Consistent with the idea that, in a competitive market for brokerage services, brokers may pass on some of their profits to customers, we find that brokers who trade for themselves also provide superior execution for their customers, relative to brokers who do not trade for themselves.futures, brokers, trading

Trading mechanisms and the price volatility : spot versus futures

Includes bibliographical references (p. 18-20)

Regression Models for Ordinal and Nominal Dependent Variables Using SAS, Stata, LIMDEP, and SPSS

A categorical variable here refers to a variable that is binary, ordinal, or nominal. Event count data are discrete (categorical) but often treated as continuous variables. When a dependent variable is categorical, the ordinary least squares (OLS) method can no longer produce the best linear unbiased estimator (BLUE); that is, OLS is biased and inefficient. Consequently, researchers have developed various regression models for categorical dependent variables. The nonlinearity of categorical dependent variable models makes it difficult to fit the models and interpret their results

Univariate Analysis and Normality Test Using SAS, Stata, and SPSS

Descriptive statistics provide important information about variables to be analyzed. Mean, median, and mode measure central tendency of a variable. Measures of dispersion include variance, standard deviation, range, and interquantile range (IQR). Researchers may draw a histogram, stem-and-leaf plot, or box plot to see how a variable is distributed. Statistical methods are based on various underlying assumptions. One common assumption is that a random variable is normally distributed. In many statistical analyses, normality is often conveniently assumed without any empirical evidence or test. But normality is critical in many statistical methods. When this assumption is violated, interpretation and inference may not be reliable or valid. The t-test and ANOVA (Analysis of Variance) compare group means, assuming a variable of interest follows a normal probability distribution. Otherwise, these methods do not make much sense. Figure 1 illustrates the standard normal probability distribution and a bimodal distribution. How can you compare means of these two random variables? There are two ways of testing normality (Table 1). Graphical methods visualize the distributions of random variables or differences between an empirical distribution and a theoretical distribution (e.g., the standard normal distribution). Numerical methods present summary statistics such as skewness and kurtosis, or conduct statistical tests of normality. Graphical methods are intuitive and easy to interpret, while numerical methods provide objective ways of examining normality

Linear Regression Models for Panel Data Using SAS, Stata, LIMDEP, and SPSS

Panel (or longitudinal) data are cross-sectional and time-series. There are multiple entities, each of which has repeated measurements at different time periods. U.S. Census Bureau’s Census 2000 data at the state or county level are cross-sectional but not time-series, while annual sales figures of Apple Computer Inc. for the past 20 years are time series but not cross-sectional. If annual sales data of IBM, LG, Siemens, Microsoft, and AT&T during the same periods are also available, they are panel data. The cumulative General Social Survey (GSS), American National Election Studies (ANES), and Current Population Survey (CPS) data are not panel data in the sense that individual respondents vary across survey years. Panel data may have group effects, time effects, or the both, which are analyzed by fixed effect and random effect models

China's policy toward the Korean Peninsula from 1978 to 2000

The Korean peninsula is crucial to China's political, economic and security interests because of a combination of geographic, historical, and political circumstances. China’s economic reforms and the end of the Cold War both provided new challenges and opportunities for Northeast Asian politics. This thesis will trace the shift in the policy of the People's Republic of China toward the Korean peninsula, and the resulting shift of primacy from North Korea to South Korea, as well as from political-military security to economic development. Yet this shift was not complete. The thesis will show how China has successfully maintained relations with both North and South Korea in what can be called a "double strategy" of ideological relations with the North and economic relations with the South. The two hypotheses of my research are: 1) China's economic reform policy was the most decisive factor which made China change from a "One Korea" policy to a "Two Koreas" policy, and 2) to maximize its national interest China has deftly used the "double strategy" to keep its traditional geo-strategic and military ties with North Korea, even as it has vigorously furthered new geo-political and economic ties with South Korea. The diplomatic history of Sino-Korean relations from 1978 to 2000 will be explored through an analysis of the empirical data of primary and secondary sources taken from documents, newspapers and academic texts

Regression Models for Binary Dependent Variables Using Stata, SAS, R, LIMDEP, and SPSS

A categorical variable here refers to a variable that is binary, ordinal, or nominal. Event count data are discrete (categorical) but often treated as continuous variables. When a dependent variable is categorical, the ordinary least squares (OLS) method can no longer produce the best linear unbiased estimator (BLUE); that is, OLS is biased and inefficient. Consequently, researchers have developed various regression models for categorical dependent variables. The nonlinearity of categorical dependent variable models makes it difficult to fit the models and interpret their results