Modelling profitability of Indian banks

This paper identifies the key determinants of profitability of Indian banks. It integrates the macroeconomic environment and industry level variables of India for predicting profitability of Indian banks. A simultaneous equation system has been formulated to derive the estimates of net interest income (NII) and Credit for the banking system as a whole. Net interest income as well as efficiency ratio have significant role in determining profitability in Indian banking scenario. The Net interest income reacts inversely to bond yields and positively to credit. This stems from the inverse relationship of credit demand to bond yields and positive relationship of GDP with credit creation. Further, Deposit mix (higher share of low cost deposit in the total deposits) has favourable impact on NII%.Profitability, Net Interest Income, GDP, Interest Rate, Efficiency Ratio

Meta-analysis of tRNA derived RNA fragments reveals that they are evolutionarily conserved and associate with AGO proteins to recognize specific RNA targets

BACKGROUND: tRFs, 14 to 32 nt long single-stranded RNA derived from mature or precursor tRNAs, are a recently discovered class of small RNA that have been found to be present in diverse organisms at read counts comparable to miRNAs. Currently, there is a debate about their biogenesis and function. RESULTS: This is the first meta-analysis of tRFs. Analysis of more than 50 short RNA libraries has revealed that tRFs are precisely generated fragments present in all domains of life (bacteria to humans), and are not produced by the miRNA biogenesis pathway. Human PAR-CLIP data shows a striking preference for tRF-5s and tRF-3s to associate with AGO1, 3 and 4 rather than AGO2, and analysis of positional T to C mutational frequency indicates these tRFs associate with Argonautes in a manner similar to miRNAs. The reverse complements of canonical seed positions in these sequences match cross-link centered regions, suggesting these tRF-5s and tRF-3s interact with RNAs in the cell. Consistent with these results, human AGO1 CLASH data contains thousands of tRF-5 and tRF-3 reads chimeric with mRNAs. CONCLUSIONS: tRFs are an abundant class of small RNA present in all domains of life whose biogenesis is distinct from miRNAs. In human HEK293 cells tRFs associate with Argonautes 1, 3 and 4 and not Argonaute 2 which is the main effector protein of miRNA function, but otherwise have very similar properties to miRNAs, indicating tRFs may play a major role in RNA silencing. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12915-014-0078-0) contains supplementary material, which is available to authorized users

Modelling profitability of Indian banks

This paper identifies the key determinants of profitability of Indian banks. It integrates the macroeconomic environment and industry level variables of India for predicting profitability of Indian banks. A simultaneous equation system has been formulated to derive the estimates of net interest income (NII) and Credit for the banking system as a whole. Net interest income as well as efficiency ratio have significant role in determining profitability in Indian banking scenario. The Net interest income reacts inversely to bond yields and positively to credit. This stems from the inverse relationship of credit demand to bond yields and positive relationship of GDP with credit creation. Further, Deposit mix (higher share of low cost deposit in the total deposits) has favourable impact on NII%

Dynamics of interacting bosons in a double well potential-harmonic versus chirp modulation

We present effects of an external driving on the tunneling dynamics of interacting bosons confined in a double well potential. At large values of a periodic driving potential, the dynamics become chaotic, with a distinct difference between tuning of the amplitude or the phase of the driving term with regard to the route leading to chaos. For example, we find that a controlled increase in the amplitude of the driving term with a fixed phase leads to quasiperiodic route to chaos. While tuning of the frequency with a fixed (large) amplitude leads to a crisis induced intermittency route to a chaotic dynamics, where the system intermittently visits different attractors in the phase space. Surprisingly, a chirp frequency superposed on a harmonic signal suppresses the chaotic motion, thereby yielding an orderly dynamics, pretty similar to a (damped) Rabi oscillation.Comment: 11 pages, 11 figure

Modelling profitability of Indian banks

This paper identifies the key determinants of profitability of Indian banks. It integrates the macroeconomic environment and industry level variables of India for predicting profitability of Indian banks. A simultaneous equation system has been formulated to derive the estimates of net interest income (NII) and Credit for the banking system as a whole. Net interest income as well as efficiency ratio have significant role in determining profitability in Indian banking scenario. The Net interest income reacts inversely to bond yields and positively to credit. This stems from the inverse relationship of credit demand to bond yields and positive relationship of GDP with credit creation. Further, Deposit mix (higher share of low cost deposit in the total deposits) has favourable impact on NII%

Artificial Neural Network Models for Forecasting Stock Price Index in Bombay Stock Exchange

Artificial Neural Network (ANN) has been shown to be an efficient tool for non-parametric modeling of data in a variety of different contexts where the output is a non-linear function of the inputs. These include business forecasting, credit scoring, bond rating, business failure prediction, medicine, pattern recognition, and image processing. A large number of studies have been reported in the literature with reference to use of ANN in modeling stock prices in the western countries However, not much work along these lines has been reported in the Indian context. In this paper we discuss modeling of Indian stock market (price index) data using ANN. We study the efficacy of ANN in modeling the Bombay Stock Exchange (BSE) SENSEX weekly closing values. We develop two networks with three hidden layers for the purpose of this study which are denoted as ANN1 and ANN2. ANN1 takes as its inputs the weekly closing value, 52-week Moving Average of the weekly closing SENSEX values, 5-week Moving Average of the same, and the 10-week Oscillator for the past 200 weeks. ANN2 takes as its inputs the weekly closing value, 52-week Moving Average of the weekly closing SENSEX values, 5-week Moving Average of the same, and the 5-week volatility for the past 200 weeks. Both the neural networks are trained using data for 250 weeks starting January, 1997. To assess the performance of the networks we used them to predict the weekly closing SENSEX values for the two year period beginning January, 2002 The root mean square error (RMSE) and mean absolute error (MAE) are chosen as indicators of performance of the networks. ANN1 achieved an RMSE of 4.82% and MAE of 3.93% while ANN2 achieved an RMSE of 6.87% and MAE of 5.52%.

Holographic dark energy through Kaniadakis entropy in non flat universe

By extending the standard holographic principle to a cosmological framework and combining the non-flat condition with the Kaniadakis entropy, we construct the non-flat Kaniadakis holographic dark energy model. The model employs Kaniadakis parameter $K$ and a parameter $c$. Derivation of the differential equation for KHDE density parameter to describe the evolutionary behavior of the universe is obtained. Such a differential equation could explain both the open as well as closed universe models. The classification based on matter and dark energy (DE) dominated regimes show that the KHDE scenario may be used to specify the Universe's thermal history and that a quintom regime can be encountered. For open and closed both the cases, we find the expressions for the deceleration parameter and the equation of state (EoS) parameter. Also, by varying the associated parameters, classical stability of the method is established. On considering the curvature to be positive, the universe favors the quintom behavior for substantially smaller values as opposed to the flat condition, when only quintessence is attained for such $K$ values. Additionally, we see a similar behavior while considering the curvature to be negative for such $K$ values. Therefore, adding a little bit of spatial geometry that isn't flat to the KHDE enhances the phenomenology while maintaining $K$ values at lower levels. To validate the model parameters, the most recent $30\;H(z)$ dataset measurements, in the redshift range $0.07 \leq z \leq 1.965$ are utilized. In addition, the distance modulus measurement from the current Union 2.1 data set of type Ia supernovae are employed.Comment: 17 pages, 12 figure