Operational Trans-Resistance Amplifier Based Tunable Wave Active Filter

In this paper, Operational Trans-Resistance Amplifier (OTRA) based wave active filter structures are presented. They are flexible and modular, making them suitable to implement higher order filters. The circuits implement the resistors using matched transistors, operating in linear region, making them well suited for IC fabrication. They are insensitive to parasitic input capacitances and input resistances due to the internally grounded input terminals of OTRA. As an application, a doubly terminated third order Butterworth low pass filter has been implemented, by substituting OTRA based wave equivalents of passive elements. PSPICE simulations are given to verify the theoretical analysis

The Expected Stock Returns of Malaysian Firms: A Panel Data Analysis

We used panel data set of 1729 observations (247 Malaysian companies listed on the Kuala Lumpur Stock Exchange for 1993-2000) to identify variables that could explain expected returns of Malaysian stocks. Our results are based on the fixed effects regression model as it performed better than the random effects model and OLS model without the firm effects. Results of the fixed-effect univariate regressions indicated that beta, size, book-to-market value (B/M) ratio, earnings-price (E/P) ratio and dividend yield individually played a significant role in explaining stock returns and payout and leverage had no effect. The explanatory power of size (natural log of market capitalisation) was the highest. The fixed-effect multivariate regression results showed that size was persistently a significant dominant variable together with other variables in explaining stock returns. Beta was found to have consistently a positive relation with stock returns by itself and together with other variables. But its explanatory power was less than size and other variables. Contrary to the results of Fama and French (1992), B/M ratio was not persistently a significant variable; its significance disappeared when we incorporated size and E/P ratio in regression.

Dividend Behaviour of Indian Companies Under Monetary Policy Restrictions

In this study we examine the dividend behaviour of Indian companies. We use GMM estimator, which is the most suitable methodology in a dynamic setting. Our results show that the Indian firms have lower target ratios and higher adjustment factors. The most significant result is that the restricted monetary policies have significant influence on the dividend behaviour of Indian firms, causing about 5-6 percent reduction in the payout ratios. The significance of macro economic policy variable suggest that monetary policy restrictions do have impact on cost of raising funds, and the information asymmetry between lenders and borrowers increases that forces companies to reduce their dividend payout.

Classification of Lie point symmetries for quadratic Lieˊ\acute{\textbf{e}}nard type equation x¨+f(x)x˙2+g(x)=0\ddot{x}+f(x)\dot{x}^2+g(x)=0

In this paper we carry out a complete classification of the Lie point symmetry groups associated with the quadratic Li$\acute{e}$nard type equation, $\ddot {x} + f(x){\dot {x}}^{2} + g(x)= 0$, where $f(x)$ and $g(x)$ are arbitrary functions of $x$. The symmetry analysis gets divided into two cases, $(i)$ the maximal (eight parameter) symmetry group and $(ii)$ non-maximal (three, two and one parameter) symmetry groups. We identify the most general form of the quadratic Li$\acute{e}$nard equation in each of these cases. In the case of eight parameter symmetry group, the identified general equation becomes linearizable as well as isochronic. We present specific examples of physical interest. For the nonmaximal cases, the identified equations are all integrable and include several physically interesting examples such as the Mathews-Lakshmanan oscillator, particle on a rotating parabolic well, etc. We also analyse the underlying equivalence transformations

Is There Seasonality in the Sensex Monthly Returns?

The presence of the seasonal or monthly effect in stock returns has been reported in several developed and emerging stock markets. This study investigates the existence of seasonality in Indias stock market. It covers the post-reform period. The study uses the monthly return data of the Bombay Stock Exchanges Sensitivity Index for the period from April 1991 to March 2002 for analysis. After examining the stationarity of the return series, we specify an augmented auto-regressive moving average model to find the monthly effect in stock returns in India. The results confirm the existence of seasonality in stock returns in India and the January effect. The findings are also consistent with the "tax-loss selling" hypothesis. The results of the study imply that the stock market in India is inefficient, and hence, investors can time their share investments to improve returns.