Next Generation Therapy in Chronic Myeloid Leukemia

Bhattacharya, Pranab Kumar; Bhattacharya, Upasana; Bhattacharya, Ritwick; Bhattacharya, Ritwik; Bhattacharya, Soumyak; Bhattacharya, Rupsa; Mukherjee, Dalia; Mukherjee, Oindrila; Mukherjee, Dhiman; Barman, Debasis Roy; Das, Soma; Dey, Anuradha; Biswas, Rupa; Sarkar, S.

doi:10.1007/s12288-011-0139-2

Cited by 5 publications

(6 citation statements)

References 4 publications

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“…But studies of Chen (2009), Shiblee (2009), Madsen et al (2013), Hossain and Hossain (2015), and Alexius and Spang (2018) rejected the GDP value for modeling and forecasting the stock prices in USA. Similarly, in India, GDP is a significant determinant in one context (Reddy, 2012) and insignificant in another context (Bhattacharya & Mukherjee, 2006;Sarkar, 2006). Further, this same significant (Maysami et al, 2004;Wongbangpo & Sharma, 2002) insignificant (Maysami & Koh, 2000) nature can be discovered in Singapore as well.…”

Section: Gross Domestic Production (Gdp)mentioning

confidence: 99%

Determinants of Stock Price Volatility: A Literature Review

Hewamana

Siriwardhane

Rathnayake

2022

S. Asian J. Finance

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The movements of stock prices highly depend on the respective economic conditions (Chen, Roll, & Ross, 1986). If the economy is performing well, it may lead to a bullish capital market, whereas its poor performance may carry out a bearish capital market. Changes in macroeconomic fundamentals impact stock prices irrespective of the firm's industry. As an example, raising the inflation rate decreases the purchasing power of the customers, leading to lower revenue for the firms (Ball & Romer, 2003). After that, the stock price may decline slightly according to the degree of inflation impact. This common phenomenon was theoretically backed by Arbitrage Pricing Model (APT) introduced by Ross (1976). The APT extends the multifactor model capturing the linear impacts of risk factors on asset returns. Macroeconomic impact has been identified as risk factor in asset return leading to price variability. Different assets have their own degree of risk premiums based on the sensitivity of the asset return on macroeconomic fundamentals. In addition to that, company-specific fundamentals also influence stock prices, like return on assets, future expected cash flows, earning power, etc. However, macroeconomic factors primarily determine the overall market performance.

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Section: Gross Domestic Production (Gdp)mentioning

confidence: 99%

Determinants of Stock Price Volatility: A Literature Review

Hewamana

Siriwardhane

Rathnayake

2022

S. Asian J. Finance

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“…Consequently, numerous research studies have investigated the influence of exchange rates on share market returns, with Maheen's (2013) Asset Market Approach revealing weak associations due to other predetermined variables affected by exogenous factors rather than econometrics/regression theory. In their evaluation of stock prices and India's www.jrasb.com financial sector, Bhattacharya and Mukherjee (2001) discovered a negligible association between exchange rates and share market returns. Similarly, Pervaiz et al (2018) found that exchange rates and other macro factors affected Kenya's stock market returns, with the exchange rate demonstrating an unfavorable relationship with the Nairobi Stock Exchange (NSE).…”

Section: Introductionmentioning

confidence: 99%

Impact of Exchange Rates on Returns in Share Market: A Case of Pakistan

Ahmadzai,

Ebrahimi,

Arshad

et al. 2024

J. Res. Appl. Sci. Biotechnol.

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The study focused on appraising the influence of exchange rates on returns in the share market: a case of Pakistan. Time-series data spanning 36 years (1980 to 2016) was utilized. To capture the impact of exchange rates on returns in the share market, a theory-based model consisting of six sub-models was planned and estimated through the recursive simultaneous-equations econometric estimation technique. As the data was time series, augmented Dickey-Fuller (ADF) tests were employed to assess the stationarity of the considered variables. The autoregressive distributed lag (ARDL) model was chosen due to some variables being found at different levels, such as me (0) and I (1). Bounds tests in the conclusion declared that the value of F-statistics expressed long-run associations among variables. The results revealed that share market returns were positively influenced by the exchange rate. The model also indicated that share market returns were significantly influenced by Foreign Portfolio Investment (FPI). Furthermore, National Savings (NS) demonstrated a positive and significant association with share market returns (SMR). The study's outcomes also illustrated that National Income (NI) had a positive and significant influence on SMR. The study encompassed well-expanded details and estimation techniques of various models and measures required in this type of research, especially when utilizing time-series data. Based on research findings, it was suggested that potential researchers reproduce this research to achieve a better and relatively well-conceived, well-estimated model on the topic. Additionally, it was recommended that public and private sector planners and researchers seek guidance not only on statistically significant exogenous variables but also on other explanatory variables for their effects on the endogenous variables.

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“…The dynamic pattern of highly structured solar corona is produced owing to dense tube of solar plasma. Solar flare is one of the active phenomena in solar system wherein the magnetic energy is transformed into kinetic energy of the accelerated charged particle through magnetic reconnection [1][2][3]. The observation of white light corona is a complicated task due to appearance of aberrations and hence demanding an ideal instrument.…”

Section: Introductionmentioning

confidence: 99%

Variations of Signal Strength during Solar Bursts: A Probable Coronal and Surface Effects of the Sun

Halder

Raha²

2023

JAP

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Variations of signal strengths during solar bursts recorded at Kalyani corresponding to two different frequencies, 406.7 MHz and 100 MHz are reported. The amplitude of the signals received at 406.7 MHz is found larger and that the flares analyzed are mostly of M-type. The signal strengths of the coronal effect at such times were very high compared to the surface effect of the Sun. The signal level of surface effect of the Sun at the peak activity varies in amplitude from 0.06 volts to 0.1 volt while those related to solar corona vary in between 7.0 to 7.2 volts. Both the solar wind velocity and proton density are found to increase in the dates of severe bursts and there are sudden disturbances in the arrival direction of solar wind particles. Also the geomagnetic indices are enhanced at the time of solar bursts when the DST index reduces rapidly.

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Next Generation Therapy in Chronic Myeloid Leukemia

Cited by 5 publications

References 4 publications

Determinants of Stock Price Volatility: A Literature Review

Determinants of Stock Price Volatility: A Literature Review

Impact of Exchange Rates on Returns in Share Market: A Case of Pakistan

Variations of Signal Strength during Solar Bursts: A Probable Coronal and Surface Effects of the Sun

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