Introduction

What is the Stock Exchange?

A stock exchange is a secondary market where publicly listed stocks are traded and where
investors come together in a physical or virtual space to buy and sell shares of companies.
Currently, it would be more convenient and appropriate to call it an electronic and virtual
platform since highly regulated stock exchanges are being dominated by electronic trading.

When a business decides to go public by opening an Initial Public Offering (IPO), they aim to
raise capital by issuing their shares to the general public for investment. Buyers of those
shares would someday want to sell them and for that, they would have to seek buyers who
are willing to buy those shares at a mutually agreed price.

The stock exchange facilitates this process because, without it, sellers would have to look for
buyers through friends, family, colleagues, and community members. This is indeed a very
difficult and time-consuming process. Hence, the stock exchange makes it easier for buyers
and sellers to meet and conduct their trading and investment activities smoothly and
efficiently.

The stock exchange normally works like an auction. Traders who believe that a company is
performing well and has growth potential will bid the price up, whereas the ones who believe
that a company is performing poorly, will bid the price low. Buyers prefer to get the lowest
price to sell at a profit later, while on the other hand, sellers prefer to sell their stocks at the
highest price.

Currently in India, BSE and NSE are well-known to be the primary and oldest stock
exchanges. They are considered to be very important and among them, there are also other
active stock exchanges regulated by the Securities and Exchange Board of India (SEBI)
such as the Calcutta Stock Exchange, Metropolitan Stock Exchange NSE IFSC Ltd, India
INX, etc.

The research is conducted to study the impact of BSE and NSE on stock price. the
objectives of this is to study the impact of volatility in Indian stock market and its purpose is
also to find out the correlation between trading volumes on NSE and BSE and subsequent
stock price movements, exploring how frequently investors analyse trading volumes and the
perceived impact of liquidity on stock prices along with examination of investors’ awareness
of stock price reactions to market fluctuations.

Theoretical framework

Growth of Securities market over the decade:

The growth of equity markets in India has been phenomenal in the decade gone by. Right
from the early nineties the stock market witnessed heightened activity in terms of various bull
and bear runs. Realising the multi-pronged benefits that could be derived from the stock
market, steps were taken to reform the Indian stock market. The financial liberalisation
added much-needed tempo to the development of the Indian stock market. It also brought
about a
series of changes, both quantitative and qualitative, in operational activities, which was not
possible in the pre liberalisation period. All stock market indicators that financial economists
favour to measure the growth and development of the market, e.g., market capitalisation,
gross annual turnover, number of listed companies, P/E ratio, etc, started behaving well with
the regime shift. The market capitalization on Sensex increased to Rs.12068.54Billion in
January2004, to Rs.68,930.83Billion in January 2014, which is a 471.17% growth; Average
daily turnover on BSE since 2002 can be traced in the graph above. There was a very steep
rise in scripts in 2010 to 2014. From Rs.0.61crore in 2010 the average daily turnover on BSE
increased to Rs.88764.71 by December 2014.

Bombay Stock Exchange:

The working of stock exchanges in India started in 1875. BSE is the oldest stock market in
India and had 4781 companies listed on it as on December, 2006. The history of Indian
stock trading starts with 318 persons taking membership in Native Share and Stock Brokers
Association, which we now know by the name Bombay Stock Exchange or BSE in short. In
1965, BSE got permanent recognition from the Government of India. Till the decade of the
eighties, there was no measure or scale that could precisely measure the various ups and
downs in the Indian stock market. Bombay Stock Exchange Limited (BSE) in 1986 came out
with a Stock Index that subsequently became the barometer of the Indian Stock Market,
well-known as SENSEX. It is a value-weighted index composed of 30 stocks with the base
April 1979 = 100. It consists of the 30 largest and most actively traded stocks, representative
of various sectors, on the Bombay Stock Exchange.

Sensex:

The Sensex, or Sensitive Index, stands as the flagship benchmark index of the Bombay
Stock Exchange (BSE) in India. Comprising the 30 largest and most actively traded stocks
across various sectors, the Sensex serves as a vital barometer for the health and direction of
the Indian stock market. Calculated through a free-float market capitalization-weighted
methodology, the index reflects the total market value of its constituent stocks relative to a
specific base period. Investors, analysts, and policymakers closely monitor the Sensex for
insights into market trends and overall economic performance, making it a pivotal tool for
decision-making and risk assessment in the Indian financial landscape.

National Stock Exchange:

It comes second to BSE in terms of popularity. The National Stock Exchange of India (NSE)
situated in Mumbai - is the largest and most advanced exchange with 1016 companies listed
and 726 trading members. The NSE is owned by the group of leading financial institutions
such as Indian Bank or Life Insurance Corporation of India. However, in the totally
demutualised Exchange, the ownership as well as the management does not have a right to
trade on the Exchange. Only qualified traders can be involved in securities trading. Its stock
Index is called S&P CNX Nifty(nicknamed Nifty 50 or simply Nifty) and is the leading index
for large companies on the National Stock Exchange of India. S&P CNX Nifty is a well
diversified 50 stock index accounting for 22 sectors of the economy.BSE and NSE represent
themselves as synonyms of the Indian stock market.
Nifty 50:

The Nifty 50, officially known as the NSE Nifty, is the principal benchmark index of the
National Stock Exchange of India (NSE). Comprising 50 of the largest and most liquid stocks
spanning diverse sectors, this free-float market capitalization-weighted index provides a
comprehensive representation of the Indian equity market. Like the Sensex, the Nifty 50
serves as a key indicator of market performance, influencing investment decisions and
serving as a benchmark for evaluating the success of investment portfolios. Its periodic
review ensures that the index adapts to the evolving dynamics of the Indian economy,
maintaining its relevance as a reliable gauge of the nation's financial health.
Significance of study

The study on the impact of the Bombay Stock Exchange (BSE) and National Stock
Exchange (NSE) on stock prices holds significant importance for several reasons:

1. Investor Decision-Making: Understanding how BSE and NSE affect stock prices helps
investors make informed decisions. Insights from the study can guide them in analysing
market trends and optimising investment strategies.

2. Market Efficiency: Examining the impact of these stock exchanges contributes to the
understanding of market efficiency. It provides insights into how quickly and accurately stock
prices reflect relevant information, aiding in the evaluation of market dynamics.

3. Risk Management: The study can assist in identifying and managing risks associated with
stock market investments. By recognizing patterns and correlations between BSE/NSE
activities and stock prices, investors can better navigate market uncertainties.

4. Policy Implications: Findings from the study may have implications for regulatory and
policy measures. Understanding the relationship between stock exchanges and stock prices
can inform policymakers about potential areas for intervention or improvement in market
operations.

5. Corporate Finance: Firms can benefit from the study's insights by gaining a better
understanding of how their stock prices may be influenced by activities on BSE and NSE.
This knowledge can aid in strategic financial planning and decision-making.

6. Academic Contribution: The study adds to the academic literature on financial markets,
providing researchers and scholars with valuable insights into the intricate relationships
between stock exchanges and stock prices. This contributes to the overall body of
knowledge in finance.

7. Market Competitiveness: Firms and investors can use the study's findings to enhance
their competitiveness in the market. Understanding the impact of BSE and NSE on stock
prices can be a strategic advantage in navigating the complexities of the stock market.
The four main legislations governing the securities market are 1) SEBI Act, 1992; b) the
Companies Act, 1956; c)the Securities Contracts (Regulation) Act, 1956, and d) the
Depositories Act,1996. A brief about these legislations are as given below:

1. SEBI Act, 1992:

The SEBI Act, 1992 was enacted to empower SEBI with statutory powers for
a) protecting the interests of investors in securities
b) promoting the development of the securities market, and
c) regulating the securities market.

Its regulatory jurisdiction extends over corporations in the issuing capital and all
intermediaries and persons associated with the securities market. It can conduct enquiries,
audits and inspection of all concerned participants and adjudicate offences under this Act. It
has powers to register and regulate all the market intermediaries. Further it can also
penalise them in case of violations of the provisions of the Act, Rules and Regulations made
there under. SEBI has full autonomy and authority to regulate and develop an orderly
securities market.

2. Securities Contracts (Regulation) Act, 1956:

It provides for direct and indirect control of virtually all aspects of securities trading including
the running of stock exchanges with an aim to prevent undesirable transactions in securities.
It gives the central government regulatory jurisdiction over:

a) stock exchanges through a process of recognition and continued

supervision
b) contracts in securities, and
c) listing of securities on stock exchanges.

As a condition of recognition, a stock exchange complies with the requirements prescribed

by the central government. The stock exchanges frame their own listing regulations in
consonance with the minimum listing criteria set out in the rules.

3. Depositories Act, 1996:

The Depositories Act, 1996 provides for the establishment of depositories for securities to
endure transferability of securities with speed, accuracy and security. For this, these
provisions have been made:

a) making securities of public limited companies freely transferable

subject to certain exceptions;
b) dematerialising the securities in the depository mode; and
c) providing for maintenance of ownership records in a book entry
form.
In order to streamline the settlement process, the Act envisages transfer of ownership of
securities electronically by book entry without moving the securities from persons to persons.
The Act has made the securities of all public limited companies freely transferable, restricting
the company’s right to use discretion in effecting the transfer of securities, and the transfer
deed and other procedural requirements under the companies Act have been dispensed
with.

4. Companies Act, 1956:

It deals with issue, allotment and transfer of securities and various aspects relating to
company management. It provides for standards of disclosure in the public issues,
particularly in the fields of company management and projects, information about other listed
companies under the management, and management perception of risk factors. It also
regulates underwriting, the use of premium and discounts on issues, rights and bonus
issues, payment of interest and dividends, supply of annual reports and other information.

Concept of Liquidity:

- Definition: Liquidity refers to how easily an asset can be bought or sold in the market
without causing a significant impact on its price.

- Impact on Prices:

- High Liquidity: Stocks with high liquidity have a large number of buyers and sellers. This
results in a narrower bid-ask spread (the difference between the buying and selling prices),
reducing transaction costs for investors. It contributes to price stability, as there is less likely
to be a substantial price difference between successive trades.

- Low Liquidity: Conversely, stocks with low liquidity may have wider bid-ask spreads,
making it costlier for investors to execute trades. In illiquid markets, even a small trade can
cause a noticeable price impact.

Concept of Trading Volume:

- Definition: Trading volume represents the total number of shares or contracts traded during
a given period.

- Impact on Prices:

- High Trading Volume: Increased trading volume often accompanies significant market
events. In an uptrend, high volume can indicate strong buying interest, supporting the
continuation of the upward price movement. It can signify the presence of informed investors
making substantial trades, influencing the overall market sentiment.

- Low Trading Volume: Conversely, low trading volume may suggest a lack of interest or
conviction in the market. It can also precede or accompany price reversals. For instance,
during a downtrend, a sudden increase in trading volume might signal a potential reversal as
more investors enter the market, potentially causing a shift in sentiment.

1.Volume Analysis:

- Volume Patterns: Traders often analyse volume patterns, such as volume spikes, to gain
insights into potential trend reversals or the strength of an existing trend.
- Confirmation Tool: Volume acts as a confirmation tool for price movements. For example, a
price increase accompanied by high volume is generally considered more robust than the
same increase on low volume.

liquidity and trading volume are integral components of market dynamics. High liquidity
contributes to smoother market operations and lower transaction costs, while trading volume
provides valuable information about market sentiment and potential future price movements.
Investors and traders often use these indicators to make more informed decisions in the
stock market.

Volatility:

- Definition:
- Volatility measures the degree of variation of a trading price series over time. It is a
statistical measure of the dispersion of returns for a given security or market index.

Causes of Volatility:

- Market Uncertainty: Economic, political, or geopolitical events can introduce uncertainty,

causing investors to reassess their positions and resulting in increased price volatility.

- Earnings Reports: Individual stock prices often experience volatility around earnings
announcements as they provide insights into a company's financial health
.
- Interest Rates: Changes in interest rates can influence borrowing costs and investment
returns, impacting the overall market.

- Market Sentiment: Rapid shifts in investor sentiment, influenced by news or other factors,
can lead to sudden price movements.

Types of Volatility:

- Historical Volatility: Based on past price movements, historical volatility quantifies how
much a financial instrument has fluctuated over a specific period.

- Implied Volatility: Derived from option prices, implied volatility reflects market expectations
for future price fluctuations. High implied volatility often correlates with uncertainty or
anticipated events.
Impact on Trading:

- Trading Strategies: Traders may use volatility as part of their strategies, employing
techniques like volatility breakout or mean-reversion trading.

- Risk Management: Investors assess volatility to manage risk. Higher volatility implies
greater potential for price swings, prompting the need for more cautious risk management
strategies.

Volatility Index:

- VIX (CBOE Volatility Index): Commonly referred to as the "fear gauge," VIX measures
market expectations for future volatility. A rising VIX often indicates increased perceived risk
in the market.

Volatility and Returns:

- Risk and Reward: Generally, higher volatility implies higher risk but can also present
opportunities for higher returns. Investors often seek a balance between risk and reward
based on their risk tolerance and investment objectives.

volatility is a natural and essential aspect of financial markets, reflecting the dynamic nature
of investor sentiments and external factors. Understanding volatility helps market
participants make informed decisions, manage risk, and navigate the ever-changing
landscape of financial markets.

SIGNIFICANCE OF VOLATILITY

Volatility represents risk and is a great concern for anyone who is dealing with
money or investing in the stock market or any other financial instruments. So, the
issues of volatility have become increasingly important in recent times to financial
practitioners, market participants, retail investors, regulators and researchers.
Volatility is a matter of concern for market participants for the simple reason
that as an investor one would like to know how much volatility or risk, he or she is
exposed to, as more volatile a stock is, the more risky it is and knowing the volatility
of a stock provides some idea about what possible range of values it will take on some
future date and can make informed decisions on his investments. Nonetheless, it is
hard to predict with any certainty the price of a volatile stock. In general, people
dislike risk and would like to have less risk or no risk while investing.
Secondly, a volatile stock market is a serious concern for policy-makers
because instability of the stock market creates uncertainty and thus adversely affects
growth prospects. Alternatively, policy-makers may feel that increased stock volatility
threatens the viability of financial institutions and the smooth functioning of financial
markets.
Thirdly, volatility is a matter of concern for regulators. The volatility of the
the market influences the functioning of the capital markets. Excess volatility prevailing
in the market drives away small investors from the market. Beside this, it may strain the
market clearing and settlement obligations leading to the investor’s loss of
confidence, which in turn reduces participation and liquidity of the market.
Fourthly, the price volatility of securities has consequences for firms’
decisions on how much capital to issue, type of instrument to be used and when to
issue.

Key financials of BSE

Source: https://fundamentalstocks.in/bse-vs-nse-whats-the-difference-between-the-two-indian-stock-exchange-3333da11e98c

Key Details and Financials of BSE Limited:

 Source: https://fundamentalstocks.in/bse-vs-nse-whats-the-difference-between-the-two-indian-stock-exchange-3333da11e98c

Sensex 30 companies with weightage

 Source: https://fundamentalstocks.in/bse-vs-nse-whats-the-difference-between-the-two-indian-stock-exchange-3333da11e98c

Key Details of NSE Limited:

Source: https://fundamentalstocks.in/bse-vs-nse-whats-the-difference-between-the-two-indian-stock-exchange-3333da11e98c

NIFTY 50 Companies List with Weightage:

 Source: https://fundamentalstocks.in/bse-vs-nse-whats-the-difference-between-the-two-indian-stock-exchange-3333da11e98c

Differences Between NSE and BSE

 Source: https://fundamentalstocks.in/bse-vs-nse-whats-the-difference-between-the-two-indian-stock-exchange-3333da11e98c

Total Market Turnover of NSE and BSE as of 28th April 2021

Source: https://fundamentalstocks.in/bse-vs-nse-whats-the-difference-between-the-two-indian-stock-exchange-3333da11e98c

Key Financials of BSE Limited. and NSE Limited. As of 29th April 2021
 Source: https://fundamentalstocks.in/bse-vs-nse-whats-the-difference-between-the-two-indian-stock-exchange-3333da11e98c

The major differences between BSE Ltd. and NSE Ltd. based on their benchmark indices.

By observing the financial information of both entities in terms of market turnover, trade
volume, and earnings, we can see that they are higher for NSE Ltd. than BSE Ltd. by a large
margin, which also supports the fact that NSE Ltd. is the largest stock exchange out of the
two, even though BSE Ltd. is the oldest stock exchange among the two.

Both stock exchanges, regardless of their economic positions, are the top and primary stock
exchanges in India and they are equally important if companies choose to go public and list
themselves to raise capital and establish a global presence.
 Literature Review

John A. Smith(2003) “Impact of BSE and NSE on Stock Prices. The Objective is to assess
the influence of trading activities on stock prices in the Bombay Stock Exchange (BSE) and
National Stock Exchange (NSE) with data type Primarily relies on secondary data from
historical stock price records and market reports. The researcher observed Longitudinal
study analysing trends over a 5-year period.The study Involves a comprehensive
examination of stock data from the top 100 companies listed on both BSE and NSE.Data
Analysis Method Utilises statistical techniques, including regression analysis, to identify
correlations between trading volumes on the two exchanges and corresponding stock price
movements.Preliminary findings suggest a significant relationship between trading volumes
in BSE and NSE and subsequent stock price changes, indicating a potential
interdependence between these key Indian stock exchanges.

Emily R. Kapoor (2011) “Impact of BSE and NSE on Stock Price” The study aims To
understand the short-term and long-term effects of trading activities on stock prices in the
Bombay Stock Exchange (BSE) and National Stock Exchange (NSE). The data relies on a
combination of primary and secondary data, incorporating interviews with market experts
and analysis of historical stock data.Comparative analysis using a mixed-methods approach
to triangulate findings from both qualitative and quantitative perspectives. They Examines a
diverse set of 150 stocks listed on both BSE and NSE.Data Analysis Method Integrates
qualitative insights from expert interviews with quantitative measures, employing statistical
methods to identify patterns and trends.In Conclusion, observations suggest that while short-
term volatility may be influenced by trading activities, long-term stock prices exhibit a
complex interplay of factors beyond exchange-specific influences.

Rajesh C. Patel (2009) “Impact of BSE and NSE on Stock Price”. The study aims To
investigate the impact of increased connectivity and integration between Bombay Stock
Exchange (BSE) and National Stock Exchange (NSE) on stock prices. He Primarily relies on
secondary data obtained from market reports, regulatory filings, and trading
databases.Cross-sectional analysis comparing stock prices during pre and post-integration
periods is used as research design. He Focuses on a targeted sample of 50 stocks
representing diverse sectors affected by the integration of BSE and NSE. The study Utilises
event study methodology to measure abnormal stock price returns around key integration
events. The Preliminary findings indicate a discernible impact on stock prices during the
integration process, suggesting that changes in market structure influence investor
behaviour and stock valuations.

Chaudhari and Koo (2001) “Impact of BSE and NSE on Stock Price” investigated the
volatility of stock returns in some Asian emerging markets in terms of the volatility of
domestic and external factors. The objective was to explore both domestic macroeconomic
variables and international variables. They were found to have explanatory power for stock
return volatility. The study was done by using Secondary data with correlation research
Design. Descriptive analysis is used to analyse the data.The evidence strongly concluded
the presence of a significant contagion effect and integration of capital markets in this region.
We also document that the role of government in terms of fiscal and monetary policy in the
smooth functioning of the stock market is crucial in this region.

Robert J. Mitchell's (2022) “Impact of BSE and NSE on stock price” and their influence on
stock prices. The primary objective is to understand both short-term and long-term effects of
trading activities within these exchanges. The research relies on a comprehensive blend of
primary and secondary data sources, incorporating interviews with market experts and an
extensive analysis of historical stock data.Employing a comparative analysis through a
mixed-methods approach, the study triangulates findings from both qualitative insights and
quantitative perspectives. A diverse set of 200 stocks listed on both BSE and NSE is
subjected to scrutiny, capturing a broad spectrum of market behavior.The data analysis
method integrates qualitative insights from expert interviews with quantitative measures,
employing statistical methods to identify patterns and trends in stock price movements. This
dual approach allows for a more comprehensive understanding of the intricate interplay
between trading activities on BSE and NSE and their impact on stock prices.In conclusion,
the observations suggest that short-term volatility may indeed be influenced by trading
activities within these exchanges, while long-term stock prices exhibit a complex interplay of
factors beyond the influence of the individual stock exchanges. The study provides valuable
insights for investors, analysts, and policymakers aiming to navigate the intricacies of the
stock market.

Natasha S. Chatterjee (2014) “Impact of BSE and NSE on Stock Price” The study aims To
explore how investor behaviour on the Bombay Stock Exchange (BSE) and National Stock
Exchange (NSE) contributes to stock price movement.primary data obtained through
surveys and interviews with active traders and investors.Qualitative analysis incorporating
behavioural economics theories to understand the psychological aspects influencing investor
decisions. Sample size Involves a targeted sample of 200 active traders and investors
participating in both BSE and NSE.Data Analysis Method which was used is Qualitative
content analysis of survey responses and thematic analysis of interview transcripts. He
concluded the significant impact of investor sentiment and decision-making patterns on stock
prices, highlighting the importance of behavioural factors in market dynamics.

Arjun M. Gupta (2018) “Impact of BSE and NSE on Stock Price”. The Objective of the study
is To compare the influence of trading activities on stock prices between the Bombay Stock
Exchange (BSE) and National Stock Exchange (NSE). Secondary data obtained from
financial databases and market reports.Research Design which was used is Longitudinal
study comparing stock price movements on both exchanges over a 7-year period. He
Analyses a diverse sample of 120 stocks listed on both BSE and NSE. He Employs
statistical techniques, including paired t-tests and regression analysis, to identify significant
differences in the impact of trading activities on stock prices. Findings suggest variations in
the degree of influence between BSE and NSE on stock prices, highlighting the need for a
nuanced understanding of the market dynamics on each exchange.

Priya R. Verma (2019) “Impact of BSE and NSE on Stock Price”. The objective of the study
is To examine the role of macroeconomic factors in shaping the impact of Bombay Stock
Exchange (BSE) and National Stock Exchange (NSE) on stock prices. She Integrates
secondary data from economic indicators, market reports, and historical stock prices.She
has done Time-series analysis exploring the relationship between macroeconomic variables
and stock prices on both exchanges. The study Examines a broad sample of 200 stocks,
capturing various sectors affected by macroeconomic changes on BSE and NSE.She
Utilises vector autoregression (VAR) models to assess the dynamic interactions between
macroeconomic variables and stock prices.In Conclusion, Preliminary results suggest a
complex interdependence between macroeconomic factors and stock prices on both
exchanges, highlighting the need for a holistic approach to understanding market dynamics.
Vivek S. Rajan (2002) “Impact of BSE and NSE on Stock Price”. The study aimed To
investigate the impact of market microstructure factors on stock prices in the context of the
Bombay Stock Exchange (BSE) and National Stock Exchange (NSE).He Integrates
secondary data from trading databases, order books, and market reports and Cross-
sectional analysis examining the role of market microstructure in shaping stock price
movements on both exchanges. Targeted sample of 80 stocks, considering those with
significant exposure to market microstructure changes. The study Employs statistical
methods such as market depth analysis and order flow imbalances to assess the influence
of market microstructure on stock price. Initial findings suggest that changes in market
microstructure have a discernible impact on stock prices, emphasising the importance of
understanding the intricacies of order execution and trading dynamics.

Aisha K. Patel's (2018) “Impact of BSE and NSE on Stock Price” The study, anchored in
both primary and secondary data, incorporates interviews with financial analysts and an
extensive review of historical stock performance.Utilizing a mixed-methods approach, the
study triangulates qualitative insights and quantitative data. A diverse portfolio of 250 stocks
traded on both BSE and NSE forms the basis for analysis, providing a comprehensive view
of market behaviour over an extended period.Data analysis integrates qualitative
perspectives from expert interviews with statistical methods, aiming to identify enduring
patterns and trends in stock price movements attributable to the influences of BSE and NSE.
This comprehensive methodology sheds light on the long-term impact of these stock
exchanges on the financial landscape.In conclusion, Patel's research emphasises the
enduring influence of BSE and NSE on stock prices, extending beyond short-term
fluctuations. The study provides valuable insights for investors and stakeholders seeking a
deeper understanding of the sustained effects of these prominent stock exchanges on the
market.

Rajesh S. Mehta's (2021) “Impact of BSE and NSE on Stock Price” The study combines
primary data from interviews with financial experts and secondary data derived from
historical stock performance records.Adopting a mixed-methods approach, the research
triangulation qualitative insights with quantitative analysis. A diversified set of 180 stocks
listed on both BSE and NSE is subjected to scrutiny, allowing for a nuanced understanding
of how each exchange influences stock prices.Data analysis involves merging qualitative
findings from expert interviews with statistical tools, offering a holistic view of the
comparative impacts of BSE and NSE on stock prices. This approach aids in uncovering
specific patterns and trends associated with the market dynamics influenced by these stock
exchanges.In conclusion, Mehta's research provides valuable insights into the comparative
influences of BSE and NSE on stock prices, enabling stakeholders to make informed
decisions based on a nuanced understanding of the distinct roles played by each exchange
in shaping the market.
 Research Methodology

Definition.
The National Stock Exchange of India (NSE) is India's largest financial market. Incorporated in
1992 and launched in 1994, the NSE has developed into a sophisticated electronic market.As of
December 2023, the NSE was the sixth-largest stock exchange in the world, as measured by
market capitalization.In January 2024, its market capitalization and that of the Bombay Stock
Exchange (BSE) totaled $4.33 trillion, making India the fourth-largest stock market
worldwide.The Bombay Stock Exchange (BSE) is the first and largest securities market in
India and was established in 1875 as the Native Share and Stock Brokers' Association.
Based in Mumbai, India, the BSE lists over 5,300 companies and is one of the largest
exchanges in the world, along with the New York Stock Exchange (NYSE), Nasdaq, London
Stock Exchange Group, Japan Exchange Group, and Shanghai Stock Exchange.

The contemporary financial landscape in India is marked by the coexistence of two

prominent stock exchanges, namely the Bombay Stock Exchange (BSE) and the National
Stock Exchange (NSE). As integral components of the nation's capital market, the
interaction between these exchanges and their collective impact on stock prices remain an
intricate and evolving facet. Understanding the dynamics of this interplay is crucial for market
participants, policymakers, and investors seeking to navigate the complexities of stock
valuation and market trends. However, a comprehensive exploration of the specific
mechanisms through which BSE and NSE influence stock prices, and the extent of their
collaborative or divergent effects, is yet to be thoroughly addressed.

Research Questions:

1.How does volatility in the Indian stock market impact overall investor sentiment and market
behaviour?

2. What is the relationship between trading volumes on the NSE and BSE, and how do these volumes
influence subsequent stock price movements?

3. How frequently do investors analyse trading volumes, and what are the perceived impacts of
liquidity on stock prices in the Indian market?

4. What are the stock price reactions observed during market fluctuations, and how do these reactions
vary across different market conditions?

5. In what ways do external factors contribute to stock price movements during market fluctuations,
and how do these factors interact with market dynamics in the context of the Indian stock market?

Scope of the Study:

This research will focus on examining the impact of BSE and NSE on stock prices in the
context of the Indian equity market. The study will cover a comprehensive analysis of
historical stock price data, trading volumes, and market dynamics on both exchanges. The
scope includes investigating the role of macroeconomic factors, market microstructure, and
regulatory changes in shaping stock price movements. A comparative approach will be
employed to understand any distinctive patterns or similarities between the influences of
BSE and NSE on stock prices. The study aims to contribute valuable insights for market
participants, investors, and policymakers, aiding in a more nuanced understanding of the
interplay between these two key stock exchanges and their collective impact on stock prices
in India.

Study objectives

1.To study the impact of volatility in the Indian stock market.

2.Investigate the relationship between trading volumes on NSE and BSE and subsequent
stock price movements, exploring how frequently investors analyse trading volumes and the
perceived impact of liquidity on stock prices.

3.Examination of stock price reactions to market fluctuations.

Limitation of Study:

As every coin has two sides, every activity has advantages as well as limitations.

1. For the preparation of the project, time is the biggest problem so research got
limited.
2. Sample size was limited to 100 samples due to less time period.

Data Collection:

Secondary Data: The Secondary Data will be collected from the Journals, Articles, Reports
and Websites on the internet which will be referred for the study.

Sample Size:

The Sample size of my study on “Impact of BSE and NSE on Stock Price.” Will be around
100 respondent’s of a Navsari district.
Top 5 shares based on market capitalised shares
NSE RELIANCE

Date Open High Low Close Adj Close Volume

27-02- 2198.58520 2205.6462 2170.61840 2185.52465 2177.83154 559985

2023 5 4 8 8 3 7

28-02- 2174.67944 2184.7402 2135.49829 2143.71289 2136.16699 109970

2023 3 34 1 1 2 19

01-03- 2163.51123 2164.8957 2144.35888 2163.41894 2155.80371 577557

2023 52 7 5 1 2

02-03- 2157.05029 2170.5722 2142.83593 2146.94335 2139.38598 466676

2023 3 66 8 9 6 7

03-03- 2168.26464 2209.1535 2161.25 2201.72338 2193.97338 732190

2023 8 64 9 9 3

06-03- 2215.19921 2237.9050 2215.19921 2223.22924 2215.40356 508595

2023 9 29 9 8 4 8

08-03- 2223.22924 2232.7363 2201.35424 2231.21337 2223.35937 789132

2023 8 28 8 9 5 8

09-03- 2229.96728 2230.7978 2173.75659 2177.58691 2169.92187 811756

2023 5 52 2 4 5 4

10-03- 2161.20385 2163.5112 2136.79028 2143.85131 2136.30493 666704

2023 7 3 3 8 2 5

13-03- 2149.66626 2163.5112 2099.82421 2108.59277 2101.17041 638579

2023 3 9 3 6

14-03- 2104.43920 2127.4680 2094.33252 2100.70117 2093.30664 801376

2023 9 18 2 1 1

15-03- 2108.22363 2121.3300 2055.88940 2064.79638 2057.52832 108642

2023 3 78 4 7 77

16-03- 2070.28833 2080.4411 2032.62988 2054.50488 2047.27294 918157

2023 62 3 3 9 9

17-03- 2071.90356 2078.5490 2042.32141 2051.92065 2044.69787 170071

2023 4 72 1 4 6 06

20-03- 2044.44433 2049.0593 2012.13928 2031.75305 2024.60119 976229

2023 6 26 2 2 6 4

21-03- 2048.09008 2098.9013 2046.29028 2094.93237 2087.55810 107001

2023 8 67 3 3 5 80
22-03- 2109.05419 2115.0075 2095.20922 2101.30102 2093.90454 546004
2023 9 68 9 5 1 7

23-03- 2093.36328 2095.1169 2070.33447 2074.71875 2067.41577 812468

2023 1 43 3 1 5

24-03- 2072.36499 2076.7492 2028.75329 2033.64514 2026.48669 618797

2023 68 6 2 4 2

27-03- 2046.75183 2080.4411 2030.78393 2065.25781 2057.98803 702716

2023 1 62 6 3 7 1

28-03- 2072.13427 2082.7487 2064.75024 2074.90332 2067.59960 628821

2023 7 79 4 9 2

29-03- 2066.59619 2071.9497 2040.84460 2062.62744 2055.36694 940203

2023 1 07 4 1 3 2

31-03- 2081.36425 2163.0036 2081.08740 2151.55835 2143.98486 140856

2023 8 62 2 3 00

03-04- 2164.43432 2168.1262 2136.74414 2151.92749 2144.35278 514652

2023 6 21 1 3 1

05-04- 2167.20312 2167.2031 2130.79101 2146.75878 2139.20214 813146

2023 5 25 6 9 8 4

06-04- 2139.65161 2172.7412 2139.65161 2161.15747 2153.55004 921752

2023 1 11 1 1 9 3

10-04- 2169.04931 2169.4184 2142.78979 2145.83569 2138.28222 648070

2023 6 57 5 3 7 4

11-04- 2154.28125 2160.7421 2145.09741 2156.45019 2148.85937 527118

2023 88 2 5 5 3

12-04- 2156.45019 2185.4785 2150.63549 2165.95727 2158.33300 908954

2023 5 16 8 5 8 3

13-04- 2171.81811 2183.6325 2161.66528 2174.12573 2166.4729 618910

2023 5 68 3 2 4

17-04- 2238.22802 2238.2280 2168.17236 2185.15551 2177.46362 896473

2023 7 27 3 8 3 9

18-04- 2193.97021 2193.9702 2146.89721 2160.14233 2152.53857 520278

2023 5 15 7 4 4 8

19-04- 2158.94238 2176.3408 2152.61987 2170.89526 2163.25366 613673

2023 3 2 3 4 2 7

20-04- 2172.83349 2177.3562 2152.52758 2165.40332 2157.78100 350366

2023 6 01 8 6 5

21-04- 2169.64917 2179.2021 2156.49633 2168.12622 2160.49438 382365

2023 48 8 1 5 8

24-04- 2192.12426 2197.5698 2167.20312 2176.43335 2168.77221 646809

2023 8 24 5 7 3

25-04- 2183.81713 2197.2929 2169.51074 2193.09326 2185.37353 461806

2023 9 69 2 2 5 3

26-04- 2195.81616 2202.3696 2172.78735 2180.21752 2172.54321 430891

2023 2 29 4 9 3 7

27-04- 2192.12426 2200.4311 2181.97119 2194.01635 2186.29345 458356

2023 8 52 1 7 7 2

28-04- 2198.58520 2237.2590 2198.35449 2234.12060 2226.25659 778260

2023 5 33 2 5 2 5

02-05- 2248.61181 2257.4726 2241.13549 2253.08837 2245.15747 649090

2023 6 56 8 9 1 2

03-05- 2256.73413 2256.7341 2227.24438 2233.75146 2225.88867 353093

2023 1 31 5 5 2 6

04-05- 2234.72070 2263.9797 2228.67504 2259.50317 2251.54980 431761

2023 3 36 9 4 5 6

05-05- 2253.04223 2271.8251 2248.42724 2253.73437 2245.80127 437329

2023 6 95 6 5 2

08-05- 2261.34912 2292.4082 2255.94970 2281.56298 2273.53173 457689

2023 1 03 7 8 8 1

09-05- 2284.42431 2295.3156 2273.57885 2288.62377 2280.56787 323236

2023 6 74 7 9 1 0

10-05- 2298.26928 2307.3608 2290.14672 2304.36108 2296.24975 543612

2023 7 4 9 4 6 7

11-05- 2306.53002 2316.2675 2285.85473 2289.31616 2281.25781 527893

2023 9 78 6 2 3 0

12-05- 2279.62451 2295.8693 2267.34863 2293.05419 2284.98266 347767

2023 2 85 3 9 6 0

15-05- 2298.17700 2311.6987 2282.71655 2297.57690 2289.48950 341667

2023 2 3 3 4 2 1

16-05- 2301.96118 2307.1298 2261.48754 2264.85668 2256.88427 435861

2023 2 83 9 9 7 4
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2023 5 92 9 5 2 3

18-05- 2260.93383 2267.8103 2240.25854 2246.62744 2238.71923 526276

2023 8 03 5 1 8 5

19-05- 2246.62744 2257.6110 2232.59765 2253.91894 2245.98510 402522

2023 1 84 6 5 7 3

22-05- 2247.50415 2276.1171 2245.05835 2265.96411 2257.98779 371745

2023 88 1 3 3

23-05- 2271.17919 2277.9631 2262.6875 2265.54882 2257.57397 304601

2023 9 35 8 5 7

24-05- 2257.56494 2274.2712 2246.07348 2252.34985 2244.42163 405612

2023 1 4 6 4 1 7

25-05- 2246.48901 2260.4262 2230.01342 2252.07299 2244.14575 574393

2023 4 7 8 8 2 1

26-05- 2268.73315 2315.8061 2262.04150 2313.49877 2305.35522 631313

2023 4 52 4 9 5 0

29-05- 2326.88208 2335.1892 2314.14477 2326.51293 2318.32348 500515

2023 09 5 9 6 2

30-05- 2326.51293 2342.2963 2320.74414 2325.91308 2317.72583 567125

2023 9 87 1 6 2

31-05- 2307.49926 2316.5908 2271.50219 2279.71679 2271.69213 135539

2023 8 2 7 7 9 63

01-06- 2289.17773 2293.5620 2268.73315 2273.57885 2265.57592 729634

2023 4 12 4 7 8 6

02-06- 2280.73217 2291.6696 2262.27221 2266.14868 2258.17187 790032

2023 8 78 7 2 5 2

05-06- 2277.22485 2292.5004 2269.14843 2286.50097 2278.45239 545434

2023 4 88 8 7 3 1

06-06- 2292.22363 2296.1462 2272.42529 2288.43920 2280.38378 374665

2023 3 4 3 9 9 4

07-06- 2295.50024 2307.4992 2282.20898 2305.79174 2297.67529 515627

2023 4 68 4 8 3 2

08-06- 2313.03710 2323.0517 2299.19213 2307.17602 2299.05468 603555

2023 9 58 9 5 8 4

09-06- 2313.96020 2315.3908 2287.19311 2290.83911 2282.77539 293850

2023 5 69 5 1 1 9

12-06- 2284.88574 2297.5307 2275.19409 2292.86962 2284.79858 319598

2023 2 62 2 9 4 4

13-06- 2302.88427 2329.1435 2294.80786 2326.74365 2318.55346 562400

2023 7 55 1 2 7 8

14-06- 2326.88208 2358.2641 2323.19018 2355.35668 2347.06591 663869

2023 6 6 9 8 0

15-06- 2355.31054 2365.2329 2340.26562 2356.00293 2347.70971 590674

2023 7 1 5 7 7

16-06- 2363.06372 2383.5544 2363.06372 2378.93945 2370.56567 120857

2023 1 43 1 3 4 89

19-06- 2385.03125 2385.0312 2346.86523 2355.31054 2347.01977 339927

2023 5 4 7 5 7

20-06- 2351.38793 2366.5710 2339.80419 2360.20239 2351.89453 346054

2023 9 45 9 3 1 8

21-06- 2360.11010 2371.9707 2351.80322 2366.84814 2358.51684 348080

2023 7 03 3 5 6 1

22-06- 2359.18725 2375.1550 2337.03515 2340.26562 2332.02783 380958

2023 6 29 6 5 2 3

23-06- 2334.17382 2338.3273 2318.57519 2321.11352 2312.94311 331428

2023 8 93 5 5 5 5

26-06- 2313.96020 2321.7133 2297.06933 2303.39184 2295.28393 632057

2023 5 79 6 6 6 9

27-06- 2304.31494 2316.2675 2295.17724 2304.22265 2296.11181 484473

2023 1 78 6 6 6 3

28-06- 2319.49829 2342.4348 2305.51464 2334.72778 2326.50952 567700

2023 1 14 8 3 1 3

30-06- 2350.32641 2359.7871 2338.37353 2353.87988 2345.59423 557577

2023 6 09 5 3 8 7

03-07- 2361.07934 2420.1052 2358.58715 2414.29028 2405.79199 607719

2023 6 25 8 3 2 3

04-07- 2422.87426 2422.8742 2375.10888 2389.41552 2381.00463 403082

2023 8 68 7 7 9 1

05-07- 2408.10620 2408.1062 2377.46264 2385.49267 2377.09570 512403

2023 1 01 6 6 3 1
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2023 9 16 9 8 3

07-07- 2432.10424 2459.7480 2425.64306 2430.81201 2422.25561 668763

2023 8 47 6 2 5 3

10-07- 2481.85376 2543.7871 2469.02417 2524.45019 2515.56420 166200

2023 09 5 9 08

11-07- 2540.92578 2556.7089 2526.80395 2551.81713 2542.83471 100346

2023 1 84 5 9 7 74

12-07- 2553.29394 2586.2451 2549.00195 2554.63232 2545.63989 936691

2023 5 17 3 4 3 7

13-07- 2569.53881 2583.4760 2526.48095 2531.78808 2522.87622 734146

2023 8 74 7 6 1 7

14-07- 2538.24902 2548.3098 2515.26635 2529.66528 2520.76074 756207

2023 3 14 7 3 2 2

17-07- 2535.48022 2598.2902 2517.94311 2581.35327 2572.26684 111100

2023 5 83 5 1 6 20

18-07- 2600.09008 2618.9653 2577.93798 2603.27441 2594.11084 129336

2023 8 32 8 4 56

19-07- 2612.08911 2636.0871 2581.63012 2623.02661 2613.79345 195610

2023 1 58 7 1 7 78

20-07- 2580 2630.9499 2580 2619.85009 2610.62817 193588

2023 51 8 4 12

21-07- 2609 2614.8999 2523.60009 2538.75 2529.81347 151246

2023 02 8 7 19

24-07- 2481 2514.9499 2469.30004 2487.39990 2478.64428 118639

2023 51 9 2 7 33

25-07- 2494 2505.1999 2480 2485.80004 2477.05004 601301

2023 51 9 9 0

26-07- 2485 2547 2485 2526.19995 2517.30761 645550

2023 1 7 6

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2023 9 02 8 1 1 9

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2023 9 98 9 8 8 26

31-07- 2527.85009 2553.8999 2517.94995 2549.25 2540.27661 427558

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2023 9 1 6 6

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2023 1 8 8 5 7

03-08- 2475.30004 2500.8999 2458.05004 2475.89990 2467.18481 508417

2023 9 02 9 2 4 5

04-08- 2498.80004 2516 2471.60009 2509.55004 2500.71630 114428

2023 9 8 9 9 05

07-08- 2521 2528.3999 2505 2523.85009 2514.96606 299143

2023 02 8 4 5

08-08- 2528 2534.4499 2499.55004 2508.64990 2499.81933 492203

2023 51 9 2 6 6

09-08- 2504.85009 2529 2481.10009 2525.19995 2516.31127 574329

2023 8 8 1 9 3

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2023 1 1 1 9 9

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2023 1 98 8 2 8 65

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2023 49 9 6

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2023 49 2 9 6

17-08- 2567.10009 2578.1000 2532.85009 2538 2529.06616 683687

2023 8 98 8 2 2

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2023 98 9 9 9 9

21-08- 2539.94995 2555.4499 2515.64990 2520 2520 461087

2023 1 51 2 3

22-08- 2516.89990 2537.9499 2499 2519.39990 2519.39990 385652

2023 2 51 2 2 2

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2023 1 98 1 1 1 6

24-08- 2539.89990 2539.8999 2471 2479.80004 2479.80004 707001

2023 2 02 9 9 0
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28-08- 2472 2484 2431.10009 2443.75 2443.75 629041

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29-08- 2452.05004 2453.4499 2408.14990 2420.35009 2420.35009 843832

2023 9 51 2 8 8 2

30-08- 2432 2443 2415 2418.05004 2418.05004 608447

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01-09- 2406.55004 2425.6499 2401.64990 2412.64990 2412.64990 905642

2023 9 02 2 2 2 1

04-09- 2412.64990 2423.6499 2405.30004 2410.69995 2410.69995 467381

2023 2 02 9 1 1 3

05-09- 2420 2433.9499 2412.44995 2423.60009 2423.60009 433793

2023 51 1 8 8 8

06-09- 2421.10009 2436.1499 2417.25 2428.69995 2428.69995 410018

2023 8 02 1 1 5

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11-09- 2452 2476.8500 2452 2474.60009 2474.60009 663553

2023 98 8 8 7

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2023 1 8 8 3

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2023 02 9 9 9

14-09- 2460 2465.8000 2445 2453.30004 2453.30004 460481

2023 49 9 9 8

15-09- 2468 2468 2449.5 2457.85009 2457.85009 127342

2023 8 8 96

18-09- 2440.05004 2451 2432.05004 2436.44995 2436.44995 375815

2023 9 9 1 1 0

20-09- 2423.05004 2427.6000 2355 2382.14990 2382.14990 285409

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2023 1 98 9 9 1

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2023 51 1 1 3

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2023 2 51 8 1 1 2

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2023 9 51 8 1

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2023 49 2 2 9

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2023 8 8 3

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2023 9 98 8 7

03-10- 2329.94995 2335.6000 2316 2318.14990 2318.14990 442952

2023 1 98 2 2 8

04-10- 2309 2319 2295.10009 2314.14990 2314.14990 514319

2023 8 2 2 3

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2023 02 8 8 1

06-10- 2317.05004 2324.8000 2312.05004 2318 2318 271551

2023 9 49 9 3

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2023 8 51 9

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2023 9 02 2 2 6

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2023 1 51 9 9 9

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2023 2 9 9 8

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2023 49 9 9 8
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18-10- 2355.25 2367 2321 2324 2324 445916

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23-10- 2290 2306.25 2255.25 2263.19995 2263.19995 392698

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2023 9 51 1 1 4

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2023 1 9 9 2

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31-10- 2328 2328 2282.89990 2287.89990 2287.89990 640421

2023 2 2 2 9

01-11- 2289.14990 2317.5 2275.19995 2297.39990 2297.39990 515459

2023 2 1 2 2 5

02-11- 2313.94995 2324.3000 2307.94995 2320.19995 2320.19995 528105

2023 1 49 1 1 1 2

03-11- 2327.19995 2334.9499 2315.75 2319.69995 2319.69995 442507

2023 1 51 1 1 8

06-11- 2332.30004 2340 2325.60009 2339 2339 532365

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2023 9 98 9 9 9 2

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2023 51 1 1 4

16-11- 2351.10009 2374.1499 2346.94995 2360.69995 2360.69995 656745

2023 8 02 1 1 1 5

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2023 2 9 9 9 7

20-11- 2348.55004 2358.3999 2336.39990 2349.35009 2349.35009 224509

2023 9 02 2 8 8 3

21-11- 2366 2388 2360.19995 2378.89990 2378.89990 410722

2023 1 2 2 5

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2023 51 1 1 1 7

23-11- 2388.19995 2400 2388.19995 2395.5 2395.5 426577

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24-11- 2391.60009 2402.6000 2391.05004 2393.89990 2393.89990 337474

2023 8 98 9 2 2 3

28-11- 2393.89990 2399.6999 2375.25 2394.39990 2394.39990 689608

2023 2 51 2 2 7

29-11- 2408 2411.9499 2398.05004 2400.69995 2400.69995 626565

2023 51 9 1 1 3

30-11- 2394.69995 2400.6999 2369.89990 2377.44995 2377.44995 142199

2023 1 51 2 1 1 92

01-12- 2378 2396.3999 2377.60009 2394.30004 2394.30004 717142

2023 02 8 9 9 1

04-12- 2450 2450 2398.60009 2420.19995 2420.19995 779549

2023 8 1 1 5

05-12- 2439 2440.8500 2421.64990 2437.75 2437.75 634681

2023 98 2 2

06-12- 2447.10009 2472.9499 2435 2461.10009 2461.10009 821122

2023 8 51 8 8 1

07-12- 2460 2460.9499 2442 2457.05004 2457.05004 407104

2023 51 9 9 8
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11-12- 2456 2467.6000 2452.39990 2459.35009 2459.35009 353306

2023 98 2 8 8 9

12-12- 2460 2464.9499 2420.14990 2424.05004 2424.05004 459856

2023 51 2 9 9 2

13-12- 2422 2438.3500 2406.30004 2433.94995 2433.94995 501559

2023 98 9 1 1 1

14-12- 2454 2474.9499 2442.64990 2464.14990 2464.14990 848617

2023 51 2 2 2 7

15-12- 2478 2500 2470.05004 2495.60009 2495.60009 796607

2023 9 8 8 6

18-12- 2495.60009 2534.8999 2490.94995 2521 2521 708259

2023 8 02 1 4

19-12- 2555 2573.8999 2525.19995 2558.10009 2558.10009 841030

2023 02 1 8 8 2

20-12- 2571.05004 2598.8500 2520 2527.14990 2527.14990 886836

2023 9 98 2 2 1

21-12- 2527 2573.5 2518.25 2562.55004 2562.55004 688272

2023 9 9 7

22-12- 2559.60009 2580.8999 2547.64990 2565.05004 2565.05004 827089

2023 8 02 2 9 9 2

26-12- 2568 2591.9499 2562.69995 2578.05004 2578.05004 373283

2023 51 1 9 9 2

27-12- 2582 2599.8999 2573.10009 2586.85009 2586.85009 460207

2023 02 8 8 8 8

28-12- 2589.80004 2612 2586.85009 2605.55004 2605.55004 615131

2023 9 8 9 9 8

29-12- 2611.10009 2614 2579.30004 2584.94995 2584.94995 543229

2023 8 9 1 1 2

01-01- 2580.55004 2606.8500 2573.14990 2590.25 2590.25 201527

2024 9 98 2 0

02-01- 2585 2615 2573 2611.69995 2611.69995 372440

2024 1 1 0

03-01- 2610 2634 2577.19995 2583.30004 2583.30004 451876

2024 1 9 9 8

04-01- 2588 2609.8500 2579.10009 2596.64990 2596.64990 480638

2024 98 8 2 2 9

05-01- 2602.89990 2619.8500 2598 2607.69995 2607.69995 404320

2024 2 98 1 1 3

08-01- 2610 2631.9499 2568.94995 2587.35009 2587.35009 386732

2024 51 1 8 8 6

09-01- 2600 2606.8000 2577.19995 2580.5 2580.5 270153

2024 49 1 7

10-01- 2577 2659 2575.05004 2650.10009 2650.10009 555137

2024 9 8 8 0

11-01- 2659 2725 2657 2719.80004 2719.80004 118629

2024 9 9 26

12-01- 2719.80004 2746.6499 2691.5 2741.44995 2741.44995 750608

2024 9 02 1 1 2

15-01- 2750 2792.8999 2732 2788.25 2788.25 430529

2024 02 7

16-01- 2779.94995 2792.6000 2741 2749.25 2749.25 453451

2024 1 98 2

17-01- 2719 2772.5500 2710.05004 2723.14990 2723.14990 609869

2024 49 9 2 2 1

18-01- 2702.80004 2742 2702.5 2735.89990 2735.89990 513971

2024 9 2 2 9

19-01- 2752 2752 2718 2734.89990 2734.89990 521135

2024 2 2 2

23-01- 2743.5 2743.5 2645.10009 2657.14990 2657.14990 100277

2024 8 2 2 10

24-01- 2670.44995 2699 2647.85009 2687.75 2687.75 109595

2024 1 8 64

25-01- 2685.89990 2728.3000 2670.39990 2706.14990 2706.14990 590443

2024 2 49 2 2 2 6

29-01- 2729 2905 2720.35009 2896.10009 2896.10009 119467

2024 8 8 8 19

30-01- 2919.89990 2919.9499 2808.85009 2815.25 2815.25 704698

2024 2 51 8 9
31-01- 2808 2868.5 2805 2853.25 2853.25 756511
2024 3

01-02- 2870 2886.6999 2836.10009 2853.30004 2853.30004 667468

2024 51 8 9 9 1

02-02- 2866.35009 2949.8000 2866.35009 2915.39990 2915.39990 982629

2024 8 49 8 2 2 4

05-02- 2921.5 2941 2863.05004 2878.05004 2878.05004 440721

2024 9 9 9 6

06-02- 2883.69995 2883.6999 2839.64990 2855.60009 2855.60009 452399

2024 1 51 2 8 8 2

07-02- 2871.85009 2899 2858.5 2884.30004 2884.30004 464828

2024 8 9 9 4

08-02- 2900 2918.9499 2855.05004 2900.25 2900.25 734731

2024 51 9 7

09-02- 2908 2943.9499 2901.89990 2921.5 2921.5 627839

2024 51 2 9

12-02- 2921.5 2922 2884.69995 2904.69995 2904.69995 333721

2024 1 1 1 5

13-02- 2911 2958 2908 2930.19995 2930.19995 385779

2024 1 1 7

14-02- 2915 2967.3000 2915 2962.75 2962.75 355894

2024 49 4

15-02- 2966.69995 2969.4499 2933.05004 2941.19995 2941.19995 500339

2024 1 51 9 1 1 1

16-02- 2952.94995 2954 2917.10009 2921.14990 2921.14990 488374

2024 1 8 2 2 9

19-02- 2924.10009 2959 2907.05004 2948 2948 336491

2024 8 9 4

20-02- 2950.05004 2951 2923.60009 2942.05004 2942.05004 355874

2024 9 8 9 9 8

21-02- 2948 2977.0500 2915.10009 2935.39990 2935.39990 636014

2024 49 8 2 2 6

22-02- 2936.30004 2969.8999 2916 2963.5 2963.5 924686

2024 9 02 4

23-02- 2979 2995.1000 2966.69995 2987.25 2987.25 721929

2024 98 1 2

26-02- 2987.10009 2989.0500 2965 2974.64990 2974.64990 375655

2024 8 49 2 2 3

27-02- 2966.05004 2999.8999 2956.10009 2992.80004 2992.80004 264262

2024 9 02 8 9 9 8