1. The document discusses the relationship between trading volume, stock returns, and volatility based on an analysis of data from the Pakistan Stock Exchange from 2003-2013. It aims to understand how changes in these variables impact each other. 2. Previous research on the topic in developed markets found a positive relationship between trading volume, returns, and volatility, but little work has been done in Pakistan. 3. The study will analyze daily data from the KSE 100 index and 50 firms using ARCH and GARCH models to explore the explanatory power of past trading volume and returns on current market returns and volatility in Pakistan.

1. 1. Title
“Relationship between Trading Volume, Stock Return and Volatility”
Empirical Evidence from Pakistan Stock Exchange
2. Introduction:
Financial researchers have devoted considerable efforts in understanding the relationship
between return, trading volume and volatility. Trading volume can be defined as the
number of shares or contracts traded in a security or an entire market during a given
period of time, it is simply the amount of shares that trade hands from sellers to buyers as
a measure of activity. If a buyer of a stock purchases 100 shares from a seller, then the
volume for that period increases by 100 shares based on that transaction.
Volatility can be defined as a statistical measure of dispersion of returns for a given
security or market index. In other words volatility refers to the amount of uncertainty or
risk about the size of changes in a security’s value. A higher volatility means that a
security’s value can potentially be spread out over a larger range of value. Thismeans that
the price of the security can change dramatically over a short time period in either
direction. A lower volatility means that a security’s value does not fluctuate dramatically
but changes in value at a steady pace over a period of time.
(Attari, Rafiq, & Awan, 2013)The small and developing economies like Pakistan are
facing the problem of high volatility and great uncertainty in various areas including
financial sector. Volatility adversely affects the functioning of the financial system and
hence economic performance. Higher returns encourage the Investors to invest and
increase the capital inflow, whereas in volatile environments the returns are not certain
and hard to predict effecting investment eventually. Risk is the major factor that
determines the return. Higher the risk, higher will be the return. Most of the research in
order to measure this relationship has been undergone at the international level, but
relatively little work has been undertaken in our local market.

2. There are many reasons why stock price change from day to day? An important reason of
our study is that find the relationship between return, trading volume and volatility
change in trade volume and stock exchange are depend on flow of true information if the
information are true then investor have the confidence for investment then the price
fluctuation of stock exchange is less but if the investor do not have the confidence then
the price of fluctuation is so high.
3. Gap Analysis:
1. The relationship between trading volume, stock return and volatility is a well-researched
area. But in case of developing countries like Pakistan it is not well
researched.
2. We wanted to see the relationship between stock return, volatility and trading
volume based on daily data of KSE 100 index and on firm’s level in case of
Pakistan.
3. A research was made by Mubarik and Javaid in 2009 on the same topic but data has
been taken from 1998 upto 2008 and 70 firms are taken. We are taking data from
2003 to 2013 and 50 firms are taken
4. Research Question:
1. To check the relationship between trading volume, return and volatility in Pakistani
market form January 2003 to December 2013.
2. To identify the explanatory power of previous day’s trading volume and returns in
explaining the current market returns.
5. Significance of Study:
The study is about the relationship between stock return, trading volume and volatility
and their effect on each other. This area is very well researched in case of developed
countries but little research is made in the case Pakistani market. The significance of the
study lies in the area of stock market, by finding the link between mentioned variables.
Stock return, trading volume and volatility are essentials in the stock market. By

3. observing the connection of these three variables investors can easily judge the market
with the help of past data and results of this research.
6. Scope of Research:
Performance of the stock market is very important to investors and old market data is
considered as a base of forecasting future. Old data and situations are set as standard that
market will perform same as like it reacted in older times. This research will help us by
providing the results about the nexus between stock return, stock volume and volatility.
By the help of this we can understand the trend of market relating to these variables. As
all the data taken for this research is secondary and we are focusing on old data.
7. Research Objectives:
The objectives of our research are as follows:
1. To find the relationship between trading volume, return and volatility and how these
are affecting each other.
2. To facilitate the investor for finding out their desired return by observing the past
trend researched in this paper.
8. Literature review
The relationship between trading volume, return and volatility is a well-researched topic
in developed countries. In case of Pakistan there is no literature available on this very
topic after 2008. We gather following literature for this topic.
Brailsford (1994) has developed a model for analyzing the relationship between level of
trading volume, return and volatility for Australian market and concluded that there is a
positive relationship between price change and volume traded in the market.
Wang (2004) has found an empirical relationship between trading volume and stock
volatility. For volatility he used the ARCH and GARCH models and concluded that
there is contemporaneous positive correlation between trading volume and volatility.
Darat, Zhong, and Cheng (2005) has conducted a study to find the relationship between
volume and return volatility in large and small New York Stock Exchange (NYSE) by

4. applying ARCH, GARH and EGARCH and finds that " volume unidirectional Granger-causes
volatility even during the periods without public news."
Khan(2006) has made a study on the future markets, its impact on volatility and spot
market price. He use the GARCH model approach for measuring volatility of spot and
future markets and concluded that the volatility of future market does not a ffect volatility
of the spot market.
Mubarik and javid (2009) has used the Dickey-Fuller test for stationary time series and
relationship of volatility. The volume and return was found by using ARCH and
GARCH-M models. Their empirical results show that there is a significant interaction
between volume, return and volatility.
Pbandrapala (2011) has analyzed the relationship between the trading volume and stock
returns. He chose 266 stocks from Colombo stock Exchange (CSE). He applies
conventional methodology and concluded that there is a positive relation between stock
returns and contemporary change in trading volume.
Osei-wusu (2011) studied the relationship of return, volume, and volatility for Ghana
Stock Exchange (GSE) by applying simple GARCH, GJR, and EGARCH models on
trading volume and return series from 1st Aug, 2005 to 31st Dec, 2010. He found that
there is no significant impact of lag trading volume on the raw trading returns but the
volume has significant impact on the volatility.
Jafari andtaliti (2013) has applied vector error correction model (VECM) variance
decomposition technique, impulse responds function, pair wise granger causality and
Johasens co- integration test. They have reported significant relationship between trading
volume and return volatility.
Attari, Rafiq and Awan (2013) have conducted an empirical study regarding the
relationship between change in trading volume and returns of the stocks in Pakistan.They
apply unit root test and GARCH model and concluded that there is a significant positive
relationship between trading volume and return.

5. Aziz, and Uddin (2014) has examined the volatility for Dhaka Stock Exchange (DSE) by
applying ARCH and GARCH models. He finds that there is a decline in Dhaka Stock
Exchange Returns over the time period.
9. Theoretical Framework
In Pakistani
Stock Market
Figure 1
10. Hypothesis:
H(0): There is significant relationship between trading volume, return and volatility in
Pakistan.
H(A): There is a very weak relationship between trading volume, return and volatility in
Pakistan.
11. Research Instruments:
Secondary data will be gathered from different websites as research instrument. Websites are
mentioned under the heading of data collection tools.

6. 12. Analysis Tools:
Following analysis tools will be used for analyzing the data.
1. Stationary Test
2. Auto Regressive Conditional Heteroscedasticity (ARCH)
3. GeneralizedAuto Regressive Conditional Heteroscedasticity (GARCH)
13. Methodology:
For this research purpose secondary data will be collected from different websites as
mentioned under the heading of research instrument. Data from January 2003 to
December 2013 will be collected of KSE-100 index and of 50 companies for analysis.
ARCH and GARCH models will be used to check the data with the help of some other
tests as mentioned before.
14. Work Plan:
Table 1
Work Plan
Sr. Activity From To Remarks
1. Submission of synopsis 1st March, 2014 31st March, 2014
2. Reviewing more literature 31st March, 2014 20th April,2014
3. Writing theoretical area 20th April,2014 24th April, 2014
4. Data collection 24th April, 2014 1st May, 2014
5. Applying tests 1st May, 2014 15th May, 2014
6. Analyzing results 15th May, 2014 8th June, 2014
7. Recommendation 8th June, 2014 20th June, 2014
8. Review 20th June, 2014 30th June, 2014
9 Submission 30th June, 2014
15. Data Collection Tools:
1. Yahoofinance.com
2. Brecorder.com
3. KSEstock.com

7. 4. Statebank.gov.pk
5. Sites of companies

8. References
Al-Jafari, M. K., and Tliti, A. (2013). An empirical investigation of the relationship between
stock return and trading volume: Evidence from the Jordanian Banking Sector. Journal
of Applied Finance and Banking , 45-64.
Attari, M. I., Rafiq, S., and Awan, M. H. (2013). The Dynamic Relation Between Stock Volatility
and Trading Volume. Asian Economic and Financial Review, 1085-1097.
Aziz, M. I., and Uddin, M. (2014). Volatility Estimation in Dhaka Stock Exchange (DSE) Return
by Garch Models. Asian Business Review.
Brailsford, T. J. (1994). The Empirical Relationship Between Trading Volume, Returns and
Volatility. Research Paper.
Campbell, J. Y., Grossman, S. J., and Wang, J. (1993). Trading Volume and Serial Correlation
in Stock Returns. The quarterly Journal of Economics.
Darrat, A. F., Zhong, M., and Cheng, L. T. (2006). Trading without Public News: Another look
at the Intraday Volume - Volatility Stock Relations.
Khan, S. U. (2006). Role of the Future Market on Volatility and Price Discovery of the Spot
Market: Evidance from Pakistan's Stock Market. The Lahore Journal of Economics, 107-
121.
Lee, B.-S., and Rui, O. M. (2002). The Dynamic Relationship Between Stock Returns and
Tradind Volume: Domestic and Cross-country Evidance. Journal of Banking and
Finance , 51-78.
Mubarik, F., and Javid, A. Y. (2009). Relationship between stock return trading volume and
volatility: Evidence from Pakistani Market. Asia Pacific Journal of finance and banking
research.
Mustafa, K., and Nishat, M. (2007). Testing for Market Efficiency in Emerging Markets: A Case
Study of Karachi Stock Market. The Lahore Journal of Economics, 119-140.
Osei-Wusu, E. (2011). Relationship Between Return, Volume and Volatility in Ghana Stock
Market.
Patbirawasam, C. (2011). The Relationship Between Trading Volume ans Stock Returns. Journal
of Competitiveness.

9. Sheikh, M. F., and Riaz, K. (2012). Over confidence Bias, Tradind Volume and Return Volatility:
Evidance from Pakistan . World Applied Sciences Journal, 1737-1748.
Wang, H. (2004). Dynamic Volume - Volatility Relation. EFMA.