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Major Event Impacts on S&P CNX NIFTY Stocks

Info: 5336 words (21 pages) Example Literature Review
Published: 6th Dec 2019

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Tagged: Finance

This project examines empirically the impact of major events on market volatility of S&P CNX NIFTY stocks as well as the index during the period of January 2005 – October 2010. For the purpose of this project we have considered dominant player of each sector based on their weightage given on NSE website. This research work is both an event study as well as a study of market volatility in the Indian context. The historical data of stock prices as given on NSE website have been used and alongside a chronological list of major events during this period i.e. January 2005 – October 2010 has been prepared for the purpose of technical analysis. The events, on the basis of their nature and volatility causing capacity have been segregated under the heads given below:

  • Budget.
  • Securities market related.
  • Macroeconomic and political.
  • International matters.
  • Man made/ Natural Disasters.

The results obtained in the final report can be used to see whether these events cause significant volatility or not and how the stock will react to a similar type of event taken in study which can be useful in allocating trading margins on the stock accordingly to mitigate or avoid potential risk due to volatility of that stock.

Generally, the financial market can be divided into two types of market, that is, Capital market and Money market. Securities market is an ordered capital market where transaction of capital is made easy by means of direct financing via securities as articles of trade. Securities market can be further alienated into a secondary market and primary market.

A stock market or equity market is a public market (a slack set-up of monetary transactions, not a material facility or any distinct unit) where the trading of company shares takes place, these company stock are securities, which are listed on a stock exchange and those which are traded privately.

A significant early incident in the expansion of the stock market in India was the creation of the native share and stock brokers’ association at Mumbai in 1875, the predecessor of the present day Bombay Stock Exchange. This was went after by the creation of exchanges in Ahmedabad in 1894, Kolkata in 1908, and Chennai in 1937. Additional to this, a huge number of ephemeral exchanges came into view primarily in buoyant times to go back into unconsciousness during depressing period afterwards. The BSE and NSE have been recognized as the two leading exchanges and account for about eighty per cent of the equity volume traded in India.


Stock Market Volatility is the most feared and respected word in the midst of the investors. Analysts are aware of its ability to outsmart the finest of the conclusions. Volatility is similar to the attractive lady who holds the breath of the investors and enthralls the market. The irregular ups and downs add excitement to the market functioning. Volatility does well to some investors, it works badly to some. When the irritability of the market turn out to be too much to tolerate and too difficult to recognize, the investors shift away from the market to look for greener pastures in some other areas like gold and real estates, etc.


Since the purpose of this research project is to study the class of relationship that exists between the stock market and events, so the detailed portrayal of variables taken up in the study and the relation between them has been done with the help of statistical tools used. It basically solves our purpose to represent stock market volatility and to demonstrate that how they are interrelated and interlinked to events at macro level and also the pattern followed by them during the study years.


Each year the union budgets affect the stock market as it brings in changes in policies and presents how the government is going to spend money in the upcoming years, which might be favorable for some and unfavorable for other sectors. This can potentially lead to market volatility in that period. In fact, volatility can be seen even before the budget day. This might be due to the pre-budget press leaks and expectations that are already built into the stocks .

Securities market matters

Securities market matters like SEBI policies, FII flows, privatization, etc also affect the stock markets as they have an impact on some or all companies and sectors directly which brings in volatility of stock market.

Macro-economic & Political matters

The relationship between macro economic factors and stock market movements has dominated the academic and practitioners‟ literature since long. Some fundamental macroeconomic variables such as growth rate of the economy, exchange rate, interest rate, industrial output and inflation have been argued to be determinants of stock prices. Given below are examples of individual macroeconomic factors that have an effect on stock prices.

  • Economic growth
  • Industrial production
  • Interest rates
  • Inflation
  • Exchange rate
  • Fiscal policy
  • Monetary Policy
  • Fuel Prices

Political instability generally propels investors into a selling spree. A fragmented election result usually indicates the formation of an unstable coalition government. Investors perceive this as leading to uncertainty on decisions for any major financial sector reform agenda or on the take of the government on fiscal or monetary policy etc. On the other hand, if election results bring back a stable and strong government to power, both domestic and foreign investors feel secure about investing in a stable financial sector policy regime.

International matters

Many international matters might also impact the stock markets, as they lead to changes in the mindset of investors. These international events could be either economic or non-economic.

Major disasters

Disasters like natural calamities and terror attacks effect the economy as well as the stock market leading to volatility though experts believe that these effects are generally short term as is mainly due the market sentiments and if the fundamentals of a company are strong they are able to pull up soon.


The research paper “Monetary Policy Announcements and Stock Price Behavior: Empirical Evidence from CNX Nifty” by Gaurav Agrawal (2007)1, focuses that how financial markets react to the monetary policy announcements. According to him monetary policy announcements contain important information which leads changes in the stock prices but Indian stock market is not efficient in the semi strong form of efficient market hypothesis. The article “The 1929 Stock Market Crash”, by Harold Bierman (2010)2 examines the causes of the 1929 stock market crash. It argues that one of the primary causes was the attempt by important people and the media to stop market speculators. In article “Pre-Announcement Effects, News, and Volatility: Monetary Policy and the Stock Markete”, Antulio N. Bomfim (2000)3 examined pre-announcement and news effects on the stock market in the context of public disclosure of monetary policy decisions.

Piyush Kumar Chowhan and Vasant Shukla (2000)4 in their research paper “Volatility in Indian stock markets” carried out an empirical study of BSE Sensex and a set of representative stocks are carried out to find the changes in their volatility in the last 2 years. Anuradha Guru (2009)5, in her research paper “What moves stock prices and How” showed what all events affect stock prices, which helped to classify events into major five categories. Movements of stock prices are observed to depend on macroeconomic factors, like, domestic and international, economic, social or political events, market sentiments or hopes about future economic growth path or important budgetary, monetary and fiscal policy announcements etc. Bernd Hayo and Ali M. Kutan (2004)6 in their research paper “The Impact of News, Oil Prices, and Global Market Developments on Financial Markets” argued that the international influence on financial markets depends upon the degree of financial liberalization.

In the research “The Stock Market’s Reaction to Unemployment News: Why Bad News Is Usually Good For Stocks” by John H. Boyd, Jian Hu and Ravi Jagannathan (2002)7 found that on average an announcement of rising unemployment is “good news” for stocks during economic expansions and “bad news” during economic contractions. K. Seth and Saloni Gupta (2005)8 in their research paper “Understanding Volatility at BSE : A Quality Control Approach” concluded that the volatility induced by confidential information is lesser than that induced by the big remarkable event and some information (private or public) can force prices away from stability.

Renuka Kinger (2009)9, in her article “Volatility of stock market and its causes” proposes that root cause of stock market volatility is surprising information breaking out in the market. So she concluded that portfolio should have margins to accommodate volatility caused due to various events. In research paper “Inflation News and the Stock Market: Macroefficiency or Overreaction” Johan Knif (2003)10 found significant market reactions to inflation shocks occur in different dynamic economic states. According to his research inverse relationship between daily stock returns and inflation shocks does not necessarily hold across all economic states and types of inflation shocks. Debashis Kundu (2009)11 in his research paper “Do unexpected events cause significant market volatility” concluded that major domestic and international events do not cause significant volatility in Indian stock market. He also found that a macroeconomic event some times affects stock market indexes but not all the time. In article “Impact of Terror Attacks on Indian Stock Prices” Poonam (2009)13 argues that terror attacks have its impact on the psychology of investors, consumption power, political environment, economic wealth. These attacks sometimes hinder the relations and deals from foreign investors affecting the stock market. The empirical results obtained in the research paper “Crude Oil Shocks and Stock Market Returns” by Babatunde Olatunji Odusami (2008)12 reveals that oil price shocks have significant nonlinear negative effect on aggregate stock return. In research paper “Macroeconomic news, announcements, and stock market jump intensity dynamics” by Jose Gonzalo Rangel (2010)14, the day of event was found to have little impact on jump intensities, employment releases being an exception. However, when macroeconomic surprises are considered, inflation shocks show persistent effects while monetary policy and employment shocks reveal only short lived effects. In research paper “Dynamics Of Stock Market Return Volatility: Evidence From The Daily Data Of India” by Banamber Mishra and Matiur Rahman(2010)15, it is argued that significant rise in stock market volatility, due to positive and negative information shocks, diminishes market efficiency and liquidity.

In research paper “Stock Market Response to Unexpected Macroeconomic News: The Australian Evidence” prepared by Mehdi Sadeghi(2002)16, it was suggested that stock returns are positively correlated with any surprise news in the current account deficit, the exchange rate and growth rate of real GDP, and negatively correlated with surprise news about the inflation rate and interest rates. Stock returns are also positively correlated with the unexpected unemployment rate and negatively correlated to revisions in the expected unemployment rate. In article “An Analysis of Verbs in Financial News Articles and their Impact on Stock Price” by Robert P. Schumaker17 it is discussed that predicting market movements is a difficult problem that deals mostly with trying to model human behavior. In research paper “Testing Long-Run Relationship between Stock Market and Macroeconomic Variables in the Presence of Structural Breaks: The Turkish Case” by Efe Caglar Cagli and Dilvin Taskin (2010)18, stock exchange index was found as cointegrated with the variables, namely gross domestic product, crude oil price and industrial production. In research paper “Relationships between stock markets and macroeconomic variables” by Sezgin Acikalin, Rafet Aktas and Seyfettin Unal (2008)19 it was concluded that there is a clear effect of stock market on the moves of interest rate but the net impact whether positive or negative is uncertain. In research paper “Economic News and International Stock Market Co-movement”, Rui Albuquerque and Clara Vega (2007)20 concluded that public information is associated with increased liquidity in some countries, while the effect in other countries depends on the type of news released. The evidence in the paper “Political Events and the Stock Market: Evidence from Israel” by Tzachi Zach (2003)21, demonstrates that the returns on the Israeli stock market’s main index following political events are more extreme than the returns on the same index in other days. In research paper “Information salience and news absorption by the stock market” by Frederic Palomino, Luc Renneboog and Chendi Zhang (2005)22, it was found that stock markets react strongly to news about game results, generating significant abnormal returns and trading volumes.



The objective of the project is

  • To analyze the impact of major events on stocks of various industries/companies.
  • To find the volatility of the stock prices with the occurrence of these events.

This project aims at analyzing the impact of major events that have affected the Indian stock market in the last 5 years, that is, from January 2005 to October 2010, and finding the volatility of the stock prices with the occurrence of these events. This will be done with the help of statistical and technical indicators used, on historical data of the stocks to find a pattern of the price movement for each stock. From the resulting pattern we can get information on how a particular stock taken into study reacts to a particular event and how volatile it gets.

The outcomes of the study can facilitate the investors and market regulators to make the markets more efficient. In case of events causing significant volatility on a particular kind of stock, this analysis can be of use for the investors to lessen or avoid potential risk due to high volatility of that stock in that period.


Collection of historical data of S&P CNX Nifty stocks taken for the analysis from Secondary Sources.

Sector wise segregation of stocks.

Collection of list of various events occurred from Jan2005 to Oct2010.

Segregation of events in five major types.


Securities market related.

Macroeconomic and political.

International matters.

Man made/ Natural Disasters.

Identification of Event days.

6. Use of F- test

7. Detailed technical analysis will be done using MACD analysis, to find change in movement and crossovers on the determined significant events for dominant player of each sector, selected on the basis of their weightage in NSE NIFTY.

Statistical Tools used for analysis are:


2. MACD Analysis


The F-distribution is formed by the ratio of two independent chi-square variables divided by their respective degrees of freedom.

F = ((df1.s12 / σ12)/df1)/((df2.s22 / σ22)df2)

Since F is formed by chi-square, many of the chi-square properties carry over to the F d istribution.

The F-values are all non-negative

The distribution is non-symmetric

The mean is approximately 1

There are two independent degrees of freedom, one for the numerator, and one for the denominator.

There are many different F distributions, one for each pair of degrees of freedom.

The “F-test” is designed to test if two population variances are equal. It does this by comparing the ratio of two variances. So, if the variances are equal, the ratio of the variances will be 1.

F = S12 / S22

S12 : Variance of first group.

S22 : Variance of second group.

All hypothesis is done under the assumption that null hypothesis is true.

Two Tail F-Test

Since the left critical values are a pain to calculate, they are often avoided altogether. The two-tail F test can be conducted as right tail test by placing the sample with the large variance in the numerator and the smaller variance in the denominator. It does not matter which sample has the larger sample size, only which sample has the larger variance. The numerator degrees of freedom will be the degrees of freedom for whichever sample has the larger variance (since it is in the numerator) and the denominator degrees of freedom will be the degrees of freedom for whichever sample has the smaller variance (since it is in the denominator). NOTE: If a two-tail test is being conducted, we still need to divide alpha by 2, but we only look up and compare the right critical value.

Assumptions / Notes

The larger variance should always be placed in the numerator

The test statistic is F = s1^2 / s2^2 where s1^2 > s2^2

Divide alpha by 2 for a two tail test and then find the right critical value

If standard deviations are given instead of variances, they must be squared

When the degrees of freedom aren’t given in the table, go with the value with the larger critical value (this happens to be the smaller degrees of freedom). This is so that you are less likely to reject in error (type I error)

The populations from which the samples were obtained must be normal.

The samples must be independent

Here it is used to find volatility in logarithmic daily returns. Volatility in returns has been measured through variance of returns over blocks of three (3) trading days. Six such blocks have been considered, three before the event (X1, X2, X3) and three after (Y1, Y2, Y3), for each event. The blocks have been used to understand changes in volatility as one move towards the event day, and later away from it. Only three such blocks were considered on either side because consecutive events happening in quick succession tend to affect one another. This comparison of variances through F-tests can be pictorially viewed as





























Figure 1 Classification of Blocks for F-Test

The study has used the statistical technique of hypothesis testing with the help of F-test. The test statistic F is calculated as follows:-

F = s (Xi)^2 / s (Yi) ^2

Here, Xi and Yi are the two sample time periods, s (Xi) 2 and s (Yi) 2 being the sample return variances. In all the cases, variance of return of the succeeding period (say, X2) has been compared with the preceding period (say, X1).

Hypothesis is,

H0: There is no change in Variance.

H1: There is change invariance between the succeeding period and the preceding period.

MACD Analysis

The most popular formula for the “standard” MACD is the difference between a security’s 26-day and 12-day Exponential Moving Averages (EMAs). Of the two moving averages that make up MACD, the 12-day EMA is the faster and the 26-day EMA is the slower. Closing prices are used to form the moving averages. Usually, a 9-day EMA of MACD is plotted along side to act as a trigger line. A bullish crossover occurs when MACD moves above its 9-day EMA, and a bearish crossover occurs when MACD moves below its 9-day EMA. The histogram represents the difference between MACD and its 9-day EMA. The histogram is positive when MACD is above its 9-day EMA and negative when MACD is below its 9-day EMA.

MACD measures the difference between two Exponential Moving Averages (EMAs). A positive MACD indicates that the 12-day EMA is trading above the 26-day EMA. A negative MACD indicates that the 12-day EMA is trading below the 26-day EMA. If MACD is positive and rising, then the gap between the 12-day EMA and the 26-day EMA is widening. This indicates that the rate-of-change of the faster moving average is higher than the rate-of-change for the slower moving average. Positive momentum is increasing, indicating a bullish period for the price plot. If MACD is negative and declining further, then the negative gap between the faster moving average and the slower moving average is expanding. Downward momentum is accelerating, indicating a bearish period of trading. MACD centerline crossovers occur when the faster moving average crosses the slower moving average.

MACD Bullish Signals: MACD generates bullish signals from three main sources:

1. Positive Divergence

2. Bullish Moving Average Crossover

3. Bullish Centerline Crossover

MACD Bearish Signals

MACD generates bearish signals from three main sources. These signals are mirror reflections of the bullish signals:

1. Negative Divergence

2. Bearish Moving Average Crossover

3. Bearish Centerline Crossover


Sector wise list of S&P CNX Nifty stocks

Sector wise list of S&P CNX Nifty stocks used for the project S&P CNX Nifty is divided in to 19 sectors as follows. The stock having maximum weightage , in accordance to Annexure II of S&P CNX Nifty, april-2010, have been selected to represent each sector.

Electrical Equipment – Bharat Heavy Electricals Ltd.

2) Refineries –Reliance Industries Ltd.

3) Telecommunication Services – Bharti Airtel Ltd.

4) Gas – GAIL(India) Ltd.

5) Pharmaceuticals – Cipla Ltd.

6) Construction – DLF Ltd.

7) Oil Exploration / Production – Oil and Natural Gas Ltd.

8) Computer- Software – Infosys Technologies Ltd.

9) Banks – ICICI Bank Ltd.

10) Automobiles – Mahindra & Mahindra Ltd.

11) Aluminium – Hindalco Industries Ltd.

12) Diversified – Hindustan Unilever Ltd.

13) Finance – Housing development Finance Corporation Ltd.

14) Cigarettes – ITC ltd.

15) Cement And Cement Products – Grasim Industries Ltd.

16) Power – Tata Power Co. Ltd.

17) Steel and Steel products – Tata Steel Ltd.

18) Metals – Sterlite Industries (India) Ltd.

19) Engineering – Larsen and Toubro Ltd.

List of major events affecting Indian stock market from Jan 2005 – October 2010

The research period has witnessed very high GDP growth rates, substantial growth in international trade, rise of regional parties in politics, large numbers of terrorist attacks, etc. Following is the list of events which have been chosen based on the fact that they impact stock market as a whole. These events are taken into consideration, in order to find out their impact on specific industry or company. The events are divided into five categories, which are as follows:


Securities market related.

Macroeconomic and political.

International matters.

Man made/ Natural Disasters.





Second budget presented by P. Chidambaram.


Chidambaram presents the budget for 2006-07.


Chidambaram presents the budget for 2007-08.


Budget for 2008-09 tabled in Parliament


Budget (Interim) for 2009-10 tabled by Pranab Mukherjee


Pranab Mukherjee presents budget for 2010-11

Table 2 Budgets


Table 3 Security Market Matters




MFs and FIIs allowed to participate in gold, silver and crude futures.


SEBI unearth large-scale multiple application scam in Yes Bank IPO.


SEBI to allow short selling by institutional investors.


Deptt. of Post to invest Rs. 10,000 crores in stock market.


Margin fees of traders are hiked.


SEBI allows companies to privately place shares to QIBs.


FII inflows cross $10 billion.


SEBI raises investment limits of MFs


Stocks crash due to crisis in Lehman Bros and Merill Lynch.


Massive fraud at Satyam Computers stuns the industry


Overseas Investor Inflow Touches Rs. 15,000 crore level

MAJOR DISASTERS (Man-made & Natural):




Floods in Mumbai


Serial bomb blasts in Delhi. 59 killed.


170 killed in serial train blasts in Mumbai.


Bangalore hit by serial bomb blasts


Delhi bomb blasts


Mumbai terror attacks


Nine killed, 45 injured in west India terrorist attack


India on alert as hackers mark India for cyber attacks


Floods in northern India sweep away homes, crops

Table 4 Major Disasters





President’s Rule imposed in Bihar ending 15-year RJD rule. RJD is an important ally of the Central Government.


CP(I)M assures UPA govt. of continuing support.


Petrol and diesel prices hiked.


RBI raises reverse repo rate by 25 bps.


Left warns Govt. of serious consequence if India votes against Iran in UNSC.


Inflation rate falls to 4.24%.


Govt. opens up the retail sector to FDI


Indo-US nuclear deal signed.


Foreign exchange reserves touch new high. Current account deficit narrows.


Foreign Trade policy outlines $120 billion target.


Petrol and diesel prices are hiked


RBI hikes repo and reverse repo rates.


Govt. clears 46 new SEZ proposals.


RBI raises CRR to 6% in 2 phases


RBI hikes repo rate to 7.75% and CRR by 50 bps


Government declares 9.3% first quarter GDP growth


RBI hikes CRR by 50 bps


Inflation at 2.97%, the lowest in 5 years


Petrol and diesel prices hiked


RBI raises CRR o 8.25%




RBI hikes Repo and CRR by 50 bps each


RBI raises Repo and CRR both to 9%


Government accepts 6th Pay Commission Report


Inflation shoots up to 12.40%.


RBI cuts CRR by 100 bps


Petrol and diesel prices reduced


Petrol, diesel and LPG prices reduced


General elections results declared


Petrol, diesel and LPG prices hiked


Petrol, diesel and LPG prices hiked


Oil Price falls to $72


CWG closing ceremony to be even more spectacular

Table 5 Macroeconomic and Political Events





Terrorist explosion in London subway.


China appreciates yuan by 2% and removes its dollar peg.


Federal Reserve raises US interest rates.


Oil rises fearing US action against Iran.


WTO talks fail.


Iranian President calls for elimination for Israel


US and Chinese markets crash suddenly and swiftly.




Barack Obama is sworn in as the 44th President of the United States.


$825billion stimulus plan cleared by the US Senate.


Mutiny by Bangladesh BDR. Many officers killed.


Terrorists attack a bus carrying the Sri Lankan cricket team in Lahore Pakistan.


India’s Tata Motors launches the Nano – the world’s cheapest car which is priced at less than 2,000 USD.


After 25 years of fierce fighting, the LTTE is completely defeated by the Sri Lankan army.


General Motors Company files for bankruptcy.


Swine Flu (H1N1) is officially declared as a global pandemic.


Dubai suddenly requests debt deferment.


Female Suicide Bombers Kill 39 in Russian Subway Stations


Spain Beats Netherlands 1-0 to Win FIFA World Cup


Russia Bans Grain Export in Response to Drought.

Table 6 International Events



F– test values from budgets


X2 ON X1

X3 ON X2

Y1 ON X3

Y2 ON Y1

Y3 ON Y2





































Table 7 F– Test Values From Budgets : BHEL

Figure 2 MACD Analysis of BHEL Jan 05 – Jun 05

F-Test results in show that there was significant instant volatility. In MACD analysis, there are no crossovers, indicating that there wasn’t any kind of trend reversal. Stock prices went up instantaneously and came down, which indicates that the effect of the event was temporary.



Figure 4 MACD Analysis of BHEL Jan 09 – Jun 09

F-Test Analysis shows that there was significant volatility on 4 out of 11 events. Out of these 4 events on 1 event there was significant instant volatility, and on 3 events there was significant post event volatility. MACD analysis shows that, these events didn’t result into any crossovers but, in most cases there was an existing bullish trend, and after the event there was a significant increase in stock prices but only for around 3 days. This shows that Government announcements impact stocks of this sector but the impact is temporary in nature.



F– test values from budgets


X2 ON X1

X3 ON X2

Y1 ON X3

Y2 ON Y1

Y3 ON Y2











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