Bull and Bear Phases: An Empirical Perusal of Indian Stock Market NSE and BSE Stock Markets?

2016 ◽  
Vol 6 (2) ◽  
Author(s):  
Sunaina Kanojia ◽  
Neha Arora
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Time Series Data ◽  
Series Data ◽  
Bear Market ◽  
Bull Markets ◽  
Indian Stock Market ◽  
Increases In Risk ◽  
Considerable Support

In general, any one known to stock market is acquainted with the phenomenon of bull and bear phases, but whether the traders or investors put air to these phases while making a decision to buy, sell, or stay invested. The present paper attempts to identify and analyze the two most popular market phases, i.e. bull and bear, for better investment decisions with the use of Bry and Boschan Algorithm and time series data. Further, it seeks to analyze the distributional characteristics of the variances in stock returns and search evidence of asymmetries, if any, in volatility under different market conditions which may help to shed light on the bull and bear phases of Indian equity market. The study arrange for evidence that in bull markets, stock prices run far ahead of earnings and for fairly long periods of time. The paper indicates 12 bull and bear phases in the Sensex and Nifty during the sample period of 19 years with the associated factors responsible for the shift of bull and bear market phases. The results provide considerable support for the view that markets choose to ignore adverse possibilities and react with zest to favorable possibilities and market declines can partly be explained by increases in risk.

Bull and Bear Phases: An Empirical Perusal of Indian Stock Market NSE and BSE Stock Markets?

GIS Business ◽  
2016 ◽  
Vol 11 (5) ◽  
pp. 11-24
Author(s):  
Sunaina Kanojia ◽  
Neha Arora
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Time Series Data ◽  
Series Data ◽  
Bear Market ◽  
Bull Markets ◽  
Indian Stock Market ◽  
Increases In Risk ◽  
Considerable Support

In general, any one known to stock market is acquainted with the phenomenon of bull and bear phases, but whether the traders or investors put air to these phases while making a decision to buy, sell, or stay invested. The present paper attempts to identify and analyze the two most popular market phases, i.e. bull and bear, for better investment decisions with the use of Bry and Boschan Algorithm and time series data. Further, it seeks to analyze the distributional characteristics of the variances in stock returns and search evidence of asymmetries, if any, in volatility under different market conditions which may help to shed light on the bull and bear phases of Indian equity market. The study arrange for evidence that in bull markets, stock prices run far ahead of earnings and for fairly long periods of time. The paper indicates 12 bull and bear phases in the Sensex and Nifty during the sample period of 19 years with the associated factors responsible for the shift of bull and bear market phases. The results provide considerable support for the view that markets choose to ignore adverse possibilities and react with zest to favorable possibilities and market declines can partly be explained by increases in risk.

Dynamic prediction of Indian stock market: an artificial neural network approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Himanshu Goel ◽  
Narinder Pal Singh
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Stock Market ◽  
Institutional Investors ◽  
Time Series Data ◽  
Gradient Algorithm ◽  
Series Data ◽  
Content Type ◽  
Artificial Neural ◽  
Indian Stock Market

Purpose Artificial neural network (ANN) is a powerful technique to forecast the time series data such as the stock market. Therefore, this study aims to predict the Indian stock market closing price using ANNs. Design/methodology/approach The input variables identified from the literature are some macroeconomic variables and a global stock market factor. The study uses an ANN with Scaled Conjugate Gradient Algorithm (SCG) to forecast the Bombay Stock Exchange (BSE) Sensex. Findings The empirical findings reveal that the ANN model is able to achieve 93% accuracy in predicting the BSE Sensex closing prices. Moreover, the results indicate that the Morgan Stanley Capital International world index is the most important variable and the index of industrial production is the least important in predicting Sensex. Research limitations/implications The findings of the study have implications for the investors of all categories such as foreign institutional investors, domestic institutional investors and investment houses. Originality/value The novelty of this study lies in the fact that there are hardly any studies that use ANN to forecast the Indian stock market using macroeconomic indicators.

scholarly journals The dynamic relationship between stock returns and trading volumes in Nepalese stock market

2020 ◽  
Vol 23 (2) ◽  
pp. 161-172
Author(s):  
Prem Lal Adhikari
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Trading Volume ◽  
Time Series Data ◽  
Stock Exchange ◽  
Causal Effect ◽  
Empirical Relationship ◽  
Insurance Companies ◽  
Series Data ◽  
Dynamic Relationship

 In finance, the relationship between stock returns and trading volume has been the subject of extensive research over the past years. The main motivation for these studies is the central role that trading volume plays in the pricing of financial assets when new information comes in. As being interrelated and interdependent subjects, a study regarding the trading volume and stock returns seem to be vital. It is a well-researched area in developed markets. However, very few pieces of literature are available regarding the Nepalese stock market that explores the association between trading volume and stock return. Realizing this fact, this paper aims to examine the empirical relationship between trading volume and stock returns in the Nepalese stock market using time series data. The study sample is comprised of 49 stocks traded on the Nepal Stock Exchange (NEPSE) from mid-July 2011 to mid-July 2018. This study examines the Granger Causality relationship between stock returns and trading volume using the bivariate VAR model used by de Medeiros and Van Doornik (2008). The study found that the overall Nepalese stock market does not have a causal relationship between trading volume and return on the stock. In the case of sector-wise study, there is a unidirectional causality running from trading volume to stock returns in commercial banks and stock returns to trading volume in finance companies, hydropower companies, and insurance companies. There is no indication of any causal effect in the development bank, hotel, and other sectors. This study also finds that there is no evidence of bidirectional causality relationships in any sector of the Nepalese stock market.

A Sectoral Analysis of the Role of Stock Market Development on Economic Growth: Empirical Evidence from Indian Economy

2017 ◽  
Vol 18 (4) ◽  
pp. 911-923 ◽  
Author(s):  
Madhu Sehrawat ◽  
A.K. Giri
Keyword(s):  
Economic Growth ◽  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Time Series Data ◽  
Trade Openness ◽  
Series Data ◽  
Causality Test ◽  
Long Run ◽  
Short Run

The present study examines the relationship between Indian stock market and economic growth from a sectoral perspective using quarterly time-series data from 2003:Q4 to 2014:Q4. The results of the autoregressive distributed lag (ARDL) approach bounds test confirm the existence of a cointegrating relationship between sector-specific gross domestic product (GDP) and sector-specific stock indices. The empirical results reveal that sector-specific economic growth are significantly influenced by changes in the respective sector-specific stock price indices in the long run as well as in the short run. Apart from that, the control variables, such as trade openness and inflation, act as the instrument variables in explaining the variations in the sector-specific GDP of the economy. The results of Granger causality test demonstrate unidirectional long-run as well as short-run causality running from sector specific stock prices to respective sector GDP. The findings suggest that economic growth of the country is sensitive to respective sub-sector stock market investments. The findings highlight the reasons for cyclical and counter-cyclical business phase for the overall economy.

scholarly journals Does Macroeconomic Indicators Influence Stock Price Behavior? Evidence from Nigerian Stock Market

2019 ◽  
Vol 6 (2) ◽  
pp. 26
Author(s):  
Peter Ego Ayunku
Keyword(s):  
Stock Market ◽  
Significant Influence ◽  
Stock Prices ◽  
Stock Price ◽  
Time Series Data ◽  
Unit Root Test ◽  
Series Data ◽  
Price Behavior ◽  
Market Growth ◽  
Integration Test

This paper investigate whether macroeconomics indicators influences stock price behavior in Nigerian stock market, using an annual time series data spanning from 1985-2015. The study employed some econometric tools such as Augmented Dicker Fuller (ADF) Unit Root test, Johansen’s co integration test, Vector Error Correction Model (VECM) to analyze the variables of interest. The study found out that Money Supply (MS) has an inverse but statistically significant  influence on stock prices in Nigerian stock market also Treasury Bill Rate (TBR) has an inverse and statistically insignificant influence on stock market prices. While on the other hand, Market Capitalization (MCAP) has a positive and statistically significant influence on stock prices while Exchange Rate (EXR) has positive but statistically insignificant relationship with stock prices in the Nigerian Stock Market. In view of the above, the study recommends amongst others that monetary authorities should try as much as possible to implement sound macroeconomic policies that would enhance stock market growth and development in Nigeria. 

scholarly journals The Determinant of Indonesian Stock Returns’ Volatility: Evidence from Islamic and Conventional Stock Market

2021 ◽  
Vol 6 (3) ◽  
pp. 277-296
Author(s):  
Septiana Indarwati ◽  
Agus Widarjono
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Money Supply ◽  
Time Series Data ◽  
Negative Impact ◽  
Stock Exchange ◽  
Series Data ◽  
Macroeconomic Variables ◽  
Distributed Lag ◽  
Macroeconomic Indicators

Islamic stock market is apparently different from the conventional stock market due to the prohibition of unlawful goods and excessive risk-taking behavior. This study explores the extent to which the Indonesian Islamic and conventional stock returns' volatility responds to the macroeconomic indicators. This study employs Jakarta Islamic Index (JII) and Indonesian Stock Exchange (IDX) and uses monthly time-series data covering 2001: M1 - 2019: M12. The volatility of stock returns is measured using Generalized Autoregressive Conditional Heteroskedasticity (GARCH). By employing the Autoregressive Distributed Lag Model (ARDL), the results validate the evidence of the long-run relationship between the stock market's volatility and macroeconomic variables. A rising in money supply and an economic upturn reduce the volatility of conventional stock returns but only an expansionary money supply diminishes the volatility of Islamic stock returns. Conversely, high inflation and sharp depreciation of the Rupiah boost the stock returns' volatility. The results further show an interesting finding that the Islamic stock market's volatility is more responsive to changes in macroeconomic indicators than the volatility of their counterpart conventional stock market. Policymakers should take strict rules during the worst economic conditions to minimize the negative impact of the instability of macroeconomic variables.

scholarly journals What Does Vietnam Gain When Its Currency Depreciates?

Economies ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 185
Author(s):  
Nguyen Thi Thanh Binh
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Regime Switching ◽  
Stock Price ◽  
Time Series Data ◽  
Series Data ◽  
The Us ◽  
High Volatility ◽  
Short Run ◽  
The Impact

The study investigates how the depreciation of the Vietnam dong (VND) against the US dollar (USD) affected export turnover and the stock market in Vietnam during the period from 2000 to 2020. A Markov triple regime-switching model is developed for time-series data involving multistructural breaks. Empirical results reveal that the impact of exchange rates on export turnover and stock price existed both in the long and short run. In the short run, the depreciation of VND led to (i) an increase in export turnover after 12 months; (ii) a decrease in export turnover of the high-growing regime in the short term; (iii) a reduction in stock returns in most cases. In addition, the common cycle from order receipt, preparation, production, and export is about 12 months for all states. The high volatility of export turnover was associated with high export growth. The commonly used phrase of “high risk, high return” seems to not be true for Vietnam’s stock market. The results of this study suggest the feasibility of a slight appreciation of VND against USD, which is the key to escape from being labeled a currency manipulator by the US Treasury.

scholarly journals Stock Returns And Volatility İn An Emerging Equity Market. Evidence From Kenya

2016 ◽  
Vol 12 (4) ◽  
pp. 79 ◽  
Author(s):  
David Ndwiga ◽  
Peter W Muriu
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Risk Premium ◽  
Time Series Data ◽  
Stock Exchange ◽  
Significant Risk ◽  
Series Data ◽  
Volatility Clustering ◽  
Cross Listing ◽  
Daily Returns

This study investigates volatility pattern of Kenyan stock market based on time series data which consists of daily closing prices of NSE Index for the period 2ndJanuary 2001 to 31st December 2014. The analysis has been done using both symmetric and asymmetric Generalized Autoregressive Conditional Heteroscedastic (GARCH) models. The study provides evidence for the existence of a positive and significant risk premium. Moreover, volatility shocks on daily returns at the stock market are transitory. We do not find any significant leverage effect. Introduction of the new regulations on foreign investors with a 25% minimum reserve of the issued share capital going to local investors (in 2002), introduction of live trading, cross listing in Uganda and Tanzania stock exchange (in 2006) and change in equity settlement cycle from T+4 to T+3 (in 2011) significantly reduce volatility clustering. The onset of US tapering increase the daily mean returns significantly while reducing conditional volatility.

scholarly journals Causal Correlation between Exchange Rate and Stock Index: Evidence from VN-Index

2016 ◽  
Vol 12 (8) ◽  
pp. 43
Author(s):  
Tri Dinh Nguyen ◽  
Quang Hung Bui ◽  
Tan Thanh Nguyen
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Time Series Data ◽  
Stock Index ◽  
Series Data ◽  
Sample Period ◽  
Integration Test ◽  
Adf Test

This paper will examine the causal correlation of exchange rates and stock prices in Vietnam. The data is collected daily from March 1<sup>st </sup>2007 to March 1<sup>st</sup> 2014. The whole sample period is divided into two sub-groups as before the stock market bottom, after stock market bottom and full sample period. Unit root tests are employed for checking the stationary of time series data such as ADF test, PP test and KPSS test. This paper employs the co-integration test and Granger causality test to identify the causal correlation between two variables. The results of paper prove that there is no causal correlation between exchange rate and stock price. It means that the stock price has no effect on exchange rate and vice versa. However, after stock market bottom from February 25<sup>th </sup>2009 to March 1<sup>st </sup>2014, this research finds that it has a long-run co-movement between these variables by applying the Johansen test.

Sports sentiment and behavior of stock prices: a case of T-20 and IPL cricket matches

2019 ◽  
Vol 11 (3) ◽  
pp. 266-276 ◽  
Author(s):  
Gourishankar S. Hiremath ◽  
Hari Venkatesh ◽  
Manish Choudhury
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Negative Impact ◽  
Positive Impact ◽  
Moving Average ◽  
Stock Market Returns ◽  
Content Type ◽  
And Behavior ◽  
Indian Stock Market

Purpose The purpose of this paper is to examine whether the emotions and sentiments related to the outcome of the sporting event influence the investment making process. Design/methodology/approach This study uses the data on stock prices of firms sponsoring the Indian premier league (IPL) teams and data on Indian stock market. The event-study frameworks along with autoregressive moving average and GMM regression are employed to empirical quantify the impacts of the performance of the IPL teams on the stock market returns of the sponsors’ stocks and response of Indian stock market to the outcome of T-20 international matches. Findings The paper finds that the team winning IPL title in a season has a positive impact on the returns of the sponsors’ stocks of a particular team, whereas loss of team has a negative impact on returns. The outcome of the cricket matches played by team India in the T-20 has a negligible effect on the Indian stock market. Practical implications The finding of the study implies the coexistence of emotions and rationality at different points in time and the relevance of adaptive market hypothesis to explain such time-varying behavior. Originality/value The present investigation is first of its kind to test whether the performance of the IPL cricket team can influence the stock returns of the sponsors. This research shows that sentiment related to sports event such as cricket influences the decision-making process and thus affects underlying stock prices.

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