Chapter-6 Price Discovery in NSE Nifty Index and Nifty Futures Markets 6.1 Introduction The mechanics of price discovery arc important to both investors and regulators. Since the trading process may introduce noise that results in inaccurate prices, it has implications for traders interested in avoiding pricing errors and policy makers concemed with market stability. Poor price discovcry may lead to heightened price volatility, including bubbles or sudden market crashes, when priccs arc predominantly influenced by short-Hill disturbanccs. A recent concern for market participants is whether the proliferation of alternative trading venues may have adversely affectcd the price formation process through market fragmentation. Price discovery is the proecss of uncovering an asset's full-information or permanent value. The unobservable permanent price reflects the fundamental value of the stock. It is distinct from the observable price, which can bc decomposed into its fundamental value and its transitory effects. Thc latter consists of price movements due to the hid-ask bounce, temporary order imbalances, inventory adjustments, and rounding effects. Price discovery is the process of buyers and sellers arriving at a transaction price for a given quality and quantity of a product at a given time and place. Price discovery involves several intelTelated concepts, among them, • Market structure (number, size, location, and competitiveness of buyers and sellers); • Market behavior (buyer procurement and pricing methods); • Market information and price reporting (amount, timeliness, and reliability of information); and • Futures markets and risk management alternatives. Futures trade assumes significance in a volatile ready market and pnce risk management because of the price discovery. The price discovery is the process of determining the price of a commodity/stock, based on supply and demand factors. The 140
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Chapter-6 Price Discovery in NSE Nifty Index and Nifty Futures Markets
6.1 Introduction
The mechanics of price discovery arc important to both investors and regulators.
Since the trading process may introduce noise that results in inaccurate prices, it has
implications for traders interested in avoiding pricing errors and policy makers concemed
with market stability. Poor price discovcry may lead to heightened price volatility,
including bubbles or sudden market crashes, when priccs arc predominantly influenced
by short-Hill disturbanccs. A recent concern for market participants is whether the
proliferation of alternative trading venues may have adversely affectcd the price
formation process through market fragmentation.
Price discovery is the proecss of uncovering an asset's full-information or
permanent value. The unobservable permanent price reflects the fundamental value of the
stock. It is distinct from the observable price, which can bc decomposed into its
fundamental value and its transitory effects. Thc latter consists of price movements due to
the hid-ask bounce, temporary order imbalances, inventory adjustments, and rounding
effects.
Price discovery is the process of buyers and sellers arriving at a transaction price
for a given quality and quantity of a product at a given time and place. Price discovery
involves several intelTelated concepts, among them,
• Market structure (number, size, location, and competitiveness of buyers and
sellers);
• Market behavior (buyer procurement and pricing methods);
• Market information and price reporting (amount, timeliness, and reliability of
information); and
• Futures markets and risk management alternatives.
Futures trade assumes significance in a volatile ready market and pnce risk
management because of the price discovery. The price discovery is the process of
determining the price of a commodity/stock, based on supply and demand factors. The
140
expectations theory hypothesizes that the current futures price is a consensus forecast of
the value of the ready (spot) price in the future.
Price discovery is the process hy which markets attempt to find equilibriulll prices
(Schreiber and Schwarz. 1986). The concept of price discovery traces back to the mid
80's when both academics and governmental authorities tried to describe the mechanisms
of different markets and how the process ends in a concct price. Fair market prices retlect
the demand of all traders and should not be affected by incomplete information. sudden
change in the depth and width of the market or the trading system as a whole.
Security markets arc more apt to consist of diversely informed traders who
collectively possess incomplete information about the assets being traded. rather than
being characterized by asymmetric information. With the individual trade. the underlying
information is made public through the trade price itself. Trading activity based on less
than full infomlation and past prices. markets may collcctively error at times or convcrge
to a new price.
Numerous factors. in addition to the underlying information change and liquidity
trading, cause the price changes to occur (Schreiber and Schwarz, 1986). Even small
orders may have huge impacts on the share price for low volumes traded of stocks. Sticky
limit order books with outstanding orders can re!lect past prices and information
situation. And the process of finding the correct price will in itself cause the actual price
to !luctuate. The advent of new information will generate a succession of trades and price
changes while traders digcst the news, including the price movement. and the markct
searches for a new equilibrium priee (Schreiber and Schwarz. 1986).
Main theme of this research is "price discovery function that measures the
information content of quotes in forecasting the next transaction". Price discovery is one
of the central functions of financial markets. In the market microstructure literature, it has
been variously interpreted as, "The search for an equilibrium price" (Schreiber and
Schwartz (1986)), "gathering and interpreting news" (Baillie et. al. (2002)), "The
incorporation of the information implicit in investor trading into market prices"
(Lehmann (2002). These interpretations suggest that price discovery is dynamic in
nature, and an efficient price discovery process is characterized by the fast adjustment of
market prices from the old equilihrium to the new equilibrium with the alTival of new
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information. In particular, Madhavan (2002) distinguishes dynamic price discovery issues
from static issues such as trading cost determination.
One notable institutional trend of financial markets is the trading of identical or
closely related assets in multiple market places. This trend has raised a number of
important questions. Does the proliferation of alternative trading venues and the resulting
market fragmentation adversely affect the price discovery process? How do the dynamics
of price discovery of an asset depend on market characteristics, such as transaction eosts
and liquidity? What institutional structures and trading protocols facilitate the
information aggregation and price discovery process? In contrast to the wide literature on
transaction costs, however, the studies on price discovery arc relatively limited. In a
recent survey of market microstructure studies, Madhavan (2002) remarks, "The studies
surveyed above can be viewed as analyzing the influence of structure on the magnitude of
the friction variable. What is presently lacking is a deep understanding of how structure
aspects return dynamics, in particular, the speed (italics as cited) of price discovery." In
this research, we propose an approach to directly characterize the speed of price
discovery in the context of NSE Nifty Index and Nifty Futures markets.
Future markets contribute in two important ways to the organization of economic
acti vity:
(i) They facilitate price discovery;
(ii) They offer means of transferring risk or hedging.
In this Research it has been focused on the first contribution. Price discovery
refers to the use of future prices for pricing cash market transactions (Working, 1948;
Wiese, 1978; and Lake 1978). In general, price discovery is the process of uncovering an
asset's full information or permanent value. The unobservable permanent priee reflects
the fundamental value of the stock or commodity. It is distinct from the observable price,
which can be decomposed into its fundamental value and its transitory effects. The latter
consists of price movements due to factors such as bid-ask bounce, temporary order
imbalances or inventory adjustments.
Price discovery and risk transfer (i.e. Hedging) have been considered as the pivot
functions of the futures market in all the economics (Telser (1981)). As we know, futures
are the standardized forward contracts, which arc traded on stock exchanges. Cost-of-
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Carry model is followed to determine the price of the futures contract. which implies that
futures represent the prospective price of the underlying asset in the cash market
(Garbade and Sibler (1983». For example; if the Nifty futures is traded at 2500 level and
the Nifty cash market Index at 2450. (if cost-of-carry model holds good) it implies that
the futures will direct the next price move in the cash market. thus the next price of the
underlying asset will be approximately 2500. Price discovery is a function of the cost-of
carry model. which implies that price discovery. will be true only if cost-of-carry model
holds good (Turkington and Walsh (1999».
In other words. if at any timc the futurcs arc mispriced thcn lead-lag relationship
between futures and cash market may be disturbed. which will result into wrong decision
for the traders to take position in the cash market on the basis of the price movement in
the futures market. In addition, if the futures are mispriced then hedging through
arbitrage positions in the cash and the futures market will not work in the interest of the
traders.
In addition. an efficient cost-of-carry relationship between the futures and cash
market results in the comovement of price series in two markets. Comovement of price
series of both markets is an evidence that price movement in both markets is
cointegrated, but evidence of cointegration docs not tell anything regarding the speed of
price discovery in the market; rather it conveys very significant information regarding the
strength of the basis (i.e. Futures Price -Cash Price) (Booth et a1.. (1999». If on the date
of the maturity of the contract. price series in two markets converges (sec Fig-6.1). it
implies that cost-of-carry model holds good and both the series have long run
relationship. If reverse holds, then it implies that the futures arc mispriced and may not be
an efficient price discovery vehicle (Garbade and Sibler (1983)). For an efficient
convergence on the maturity date the basis is required to be predictable. but predictable
basis does not necessarily imply that speedier price discovery takes place in the futures
market (Fortenbery and Zapata (1997».
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Fig -6.1 Movement of Futures and Equity price
Price
\ Equity Pric>"
I, I, Time'
Price discovery mechanism refers to absorbing the new infonnation, and
reflecting it into the market prices. P,ice discovcry in the cash market has been a serious
issue for debate for the traders, professionals, regulatory bodies and the academicians.
Thrce different schools (i.e. Fundamental Analysis. Technical Analysis and Efficient
Market Hypothesis) have emerged to analyze the reaction of the prices to new
information. Fama made significant efforts in this regard and in 1970. he came out with
formal definitions of the market efficiency. He classified the market efficiency into three
categories i.e. Weak Form Efficiency. Semi-Strong Form Efficiency and Strong Form
Efficiency.
A market is said to be weak form efficient if the cunent market price and past
price are uncorrelated (i.e. the asset price movements are random). A market is known as
semi-strong efficient, if it absorbs and reflects the market information as well as the
public information (viz; corporate actions. political announcement etc.). Strong form
efficient market is one. which neglects the chances of even insiders to make abnormal
profits on the basis of first hand information.
In the developed economies viz; U.S.A. and U.K.. markets are found to be
efficient but reverse holds in case of the emerging markets like India. Taiwan,
144
Bangladesh etc. (Mobarek and Keasey (2000)). Thus in the emerging markets. relative
pricing efficiency of the futures market may work like a lantern in the dark coal mine. If
in emerging markets, futures market is able to react to the market information
immediately, when these becomes available then, it will certainly help the regulators to
control the volatil ity in the cash market and the confidence of the traders can be restored
in a market like India. where people burnt their hands in early and mid 90's due to the
overwhelming participation in the market hy one trader (i.e. Big Bull Ilarshad Mehta). If
in India, futures market acts as an efficient price discovery vehicle, traders will be getting
more confidence to trade in the cash market because they will know that futures market is
their to guide their prospcctive actions in the market and they can protect themselves
from the possible loss by tak.ing (Beta weighted) reverse positions in the futures market
(Branllen and Ulvcling (1984)).
Efficient price discovery m the futures market has many advantages for the
traders as well as for the regulators. Traders can manage their risk exposure in the cash
market by taking reverse positions in the futures market. In many stock markets it has
been observed that the volatility in the cash mark.et has reduced in the post futures trading
era as compared to the volatility in the pre futures trading era (Gulen and Mayhew
(2000)). Reductioll in the magnitude of volatility will certainly work for the benefit of all
traders (both retail as well as big traders). Reduction in volatility ensures relatively stable
price movements in the market, which will help the traders to take their decision in the
market (subject to the experience and exposure of the trader in the market) (long and
Donders (1998)). The regulatory bodies can also be benefited through efficient price
discovery in the futures market (Raju and Karande (2003)). They can simulate the
reforms through futures market and then directly implement the same in the cash market.
The reaction of the futures market to such reforms will certainly help the regulatory
bodies to evaluate the probability of success/failure of the reform in the cash market, thus
they can make appropriate modifications, if necessary.
In India, equity futures are of relatively recent origin and were introduced in the
phased manner. In the first phase index futures trading was introduced on l2'h June 2000
and in the second phase, stock futures trading was permitted on 9th Nov 2001. The trade
volume in both the markets has been increasing by leaps and bounds. These days'
145
significant efforts are being taken to investigate the efficiency of Indian equity futures
market. Raju and Karande (2003) investigated the price discovery cfTiciency of the Indian
equity futures market but they could not conclude anything on the basis of short time
dimension. Gupta and Singh (2006) also made an attempt to investigate the price
discovery efficiency of the Nifty futures by considering lengthy time frame and their
results showed lead-lag relationship between the two markets.
6.2 Importance of Price Discovery
When a market experiences stress and its negative impacts persist over a period of
time, the market's liquidity declines and market conditions become unstable. Under such
stress, the price discovery function an important mechanism in markets is debilitated,
which leads to higher price volatility and lower market liquidity. At the most general
modeling perspective, each of the observable prices of an asset in multiple markets can
be decomposed into two components: one retlecting the common efficient (full
information) price shared by all these markets (Garbade and Silber (1979)); and one
retlecting the transitory frictions that arise from the trading mechanism, such as the bid
ask bounce, liquidity effects, and rounding errors. Evolving as a random walk, the
common efficient price captures the fundamental value of the financial asset and its
innovation impounds the expectation revisions of investors (thus new information) about
the asset payoff of observed prices respond to the common efficient price innovation
characterizes the dynamics of price discovery. Unfortunately, as emphasized by
Hasbrouck (2002), the common efficient price (and its innovation) is generally
unobservable. Therefore. identifying the common efficient price innovations is a
necessary step before any meaningfuimcasure of price discovery can be constructed.
How do markets arrive at prices? There is perhaps no question more central to
economics. This research focuses on price formation in financial markets, where the
question looms especially large: How, if at all. is news about macroeconomic
fundamentals incorporated into stock prices, bond prices and foreign exchange rates?
Unfortunately the process of price discovery in financial markets remains poorly
understood. Traditional "efficient markets" thinking suggests that asset prices should
completely and instantaneously retleet movements in underlying fundamentals.
146
Conversely, several prominent authors have recently gone so far as to assert that asset
prices and fundamentals may be largely and routinely disconnected. Experiences such as
the late 1990s U.S. technology-driven market bubble would seem to support that view,
yet simultaneously it seems clear that financial market participants pay a great deal of
attention to data on underlying economic fundamentals. The notable difficulty of
empirically mapping the links between economic fundamentals and asset prices is indeed
striking.
The central price-discovery question has many dimensions and nuances, including
but not limited to the following. How quickly, and with what patterns, do adjustments to
news occur? Does announcement timing matter? Are the magnitudes of effects similar for
"good news" and "bad news," or, for example, do markets react more vigorously to bad
news than to good news'? Quite apart from the direct effect of news on assets prices, what
is its effect on financial market volatility? Do the effects of news on prices and volatility
vary across assets and countries. and what are the links? Are there readily identifiable
herd behavior and/or contagion effects? Do news effects vary over the business cycle?
Just as the central question of price discovery has many dimensions and nuances,
so too docs a full answer. In this research we progress by characterizing the simultaneous
response of foreign exchange markets as well as the domestic and foreign stock and bond
markets to real-time India macroeconomic news. More precisely, we seek to better
understand the links between asset prices and fundamentals by simultaneously
combining:
• High-quality and ultra-high frequency asset prIce data across markets and
countries, which allows us to study plicc movements in (near) continuous time;
• Synchronized survey data on market participants' expectations, which allow us to
infer "surprises" or "innovations" when news is announced; and
• Advances in statistical modeling of volatility. which facilitates efficient
inference.
By so doing, we can probe the workings of the marketplace in new and powerful
ways, focusing on episodes where the source of price movements is well identified,
leading to a high signal-to-noise ratio.
147
6.3 Price Discovery in Different Markets
a. Price Discovery in Tick Time
A central question in market microstructure is how information about the
value of an asset is incorporated in its market price. In fragmented markets,
information about the value of an asset arrives to the market from multiple
sources. The process of how information from different sources is incorporated
into the value of an asset has become known as price discovery. An example of
such a fragmented market is the NSE India, a multiple dealer market where each
dealer contributes to the price discovery process. Interesting questions for such a
market are which dealer contributes most, how quick the discovery process
works, and how it depends on markct circumstances like liquidity, volatility and
trading intensity.
An important measure for the contribution to pnce discovery is the
information share introduced by Hasbrouck (1995). Infornlation shares are
defined as the part of the variance of the random walk component of returns that
can be attributed to a particular market or dealer. Unfortunately this variance
decomposition rs not unique when price changes are contemporaneously
correlated. As a solution, Hasbrouck (1995) suggests alternative Choleski
decompositions to establish upper and lower bounds. The Choleski
decompositions work well in many cases where the number of different markets
or market participants is small and the differences among them are large enough.
b. Price Discovery in Multiple-Dealer Markets
"Price discovery" is a dynamic process in which a diverse group of traders
and market makers gather, evaluate, and interpret disparate pieces of information;
coordinate trading demands; and generate market-clearing prices. Though it is a
principal function of securities markets, price discovery has received littIe, but
groWlllg attention from financial economists. The literature includes few
theoretical models or empirical studies, especially for multiple-dealer markets.
The classical notion of price discovery involves a Walrasian auctioneer who
observes quantities supplied and demanded at different prices and determines the
148
price that clears the market. With this framework economists ask. "How do prices
work?" but not "How are prices set?" And. while tbis model yields obvious
practical advantages, it trivializes complex and economically important pricing
decisions. In reality, many individuals generate prices concurrently, and the
interactions among institutional features, preferences. and asset characteristics
imply that the quotes we observe in markets vary in their informative quality.
c. Price Discovery in Thinly Traded Markets
Price discovery is an important function performed by futures markets.
Effective futures markets should generate prices that express consciously formed
opinions on cash prices in the future, and should transmit that information
throughout the marketing system in a timely manner (Working, 1942; Tomek,
1980). Because of its importance, the effectiveness of futures markets in
performing this function has been investigated extensively in the literature. The
more recent studies have shown that futures prices playa dominant role in the
discovery and transmission of price information. In the absence of effective price
discovery. researchers have conjectured that limited trading volume associated
with thin markets has adversely affected price discovery.
Traditionally, a thin market has been understood to be a market in which
the number of transactions over a given period of time is insufficient to ensure
efficient price discovery. Peterson identifies three major concerns related to thin
markets: first, those prices may not accurately renect supply and demand
conditions in the market; second, that thinness will contribute to higher price
volatility; and third, that thinness (duc to the magnified impact of individual
transactions) increases the incentive for market manipulation.
d. Price Discovery in Informationally Linked Markets
When a security is traded in more than one market, investors have several
avenues to trade and exploit information. An investor who wants to trade the
Nikkei 225 stock index, for example, can do so in the spot market in Tokyo and,
during the same opening hours, in the futures market in Osaka or Singapore.
Where frictionless and continuous information sharing across markets exist,
trading should be considered as taking place in a single market with simultaneous
149
prIce changes in the stocks, stock indices, and derivative instruments. If the
markets were not frictionless, some markets would appear to be more attractive
than others because of concerns relating to transaction costs, regulation, and
liquidity, leading to differences in price discovery across the exchanges. As the
process of globalization of trading and competition among exchanges for order
flow accelerates, it is impot1ant to determine the nature and location of price
discovery.
e, Price Discovery in Commodity Markets
Instability of commodity prices has always been a major concern of the
producers as well as the consumers in an agriculture-dominated country like
India. Farmers' direct exposure to price fluctuations, for instance, makes it too
risky for them to invest in otherwise profitahle activities. There are various ways
to cope with this problem. Apart from increasing stability of the market through
direct government intervention, various actors in the farm sector can better
manage their activities in an environment of unstable prices through derivative
markets, These markets serve a risk-shifting function, and can be used to lock-in
prices instead of relying on uncet1ain price developments. This problem can be
sorted out by making survey of the price risk management system prevailing in
agricultural commodity markcts and to empirically investigate how efficicnt is the
price discovery function of futures for ensuring bettcr hcdge against price
uncertainty in some selected commodities.
6.4 Efficient Market Hypothesis of Price Discovery
Paul Sammuelson developed Efficient Market Hypothesis (EMH) in 1965.
Eugene Fama formulated EMH later in 1970. The EMH suggests whether, at any given
time, prices fully reflect all available information on a particular stock and/or market.
Thus, according to the EMH, no investor has an advantage in predicting a return on a
stock price since no one has access to information not already available to everyone else.
In other words, the hypothesis says that capital markets are efficient and that security
prices fully rellect all available information.
150
Based on EMH, there are three identified classifications of market efficiency,
which arc aimed at reflecting the degree to which it can be applied to markets.
• Strong efficiency. This is the strongest version, which states that all information
in a market, whether public or private, is accounted for in a stock price. Not even
insider information could give an investor an advantage.
• Semi·strong efficiency· This form of EMIl implies that all public information is
calculated into a stock's current share price. Neither fundamental nor technical
analysis can be used to achieve superior gains.
• Weak efficiency· This type of EMH claims that all past prices of a stock are
reflected in today's stock price. Therefore, technical analysis cannot be used to
predict and beat a market.
The EMH is an appealing description of competitive market equilibrium. An
efficient market impounds new information into prices quickly and without bias. Prices
fully reflect available information. Market participants adjust the available supply and
aggregate demand in response to publicly available information soars to generate market·
clearing prices. In major stock markets, where millions of dollars are 'voting', it seems
plausible that a rational consensus will be reached as to the share prices which best reflect
the prospects for future cash flows givcn available information.
Although the EMil may be an elegant economic concept, even a normatively
desirable condition, it may not be true. Prices in securities markets may not fully reflect
available information due to all kinds of outside factors. The early literature on market
efficiency was widely interpreted as supportive. But. by the late 1970s, the anomalous
evidence was growing and began to command attention. There is now a substantial body
of empirical research, which casts doubt upon the degree of market efficiency (Fall,
1992).
6.5 Price Discovery Processes
Prices of a financial product are discovered through trading activities among
market participants. This process by which prices adjust to incorporate new infomlation
is referred to as the price discovery (hereafter PO) process.
Analyses will be conducted according to the following framework.
IS I
i. Intraday and Intraweek patterns
Information is generated (24 X 7) 24 hours a day, 7 days a week. However, no
financial market is open for such long hours. In this sense, all market participants face
a price risk in not being able to trade at the prices, which ret1ect the generated
information when the market is closed. In addition, there may be some clustering of
important public information at certain times of the day or week, which also affects
trading activity in the market. Presumably, there are some distinct intraday and
intraweck patterns of PO, ret1ecting market participants' behaviour in coping with
these issues.
ii. PD process after arrival of public information
There must be some type of public information, which systematically affects the
PO process in government securities market. The paper analyses the effect of
statistical announcements, notification of open market operations by central banks,
and releases of policy rate changes on the PO process, as examples of such
information. Presumably, some unique patterns in trading volume, price volatility,
and bid-ask spread are observed after the arrival of this information.
iii. Inter-linkage between the cash and futures markets
If similar products are traded in more than one market, this leads to the question
of which market incorporates new information first. This question regarding PO
speed is examined, with a focus on the relationship between the cash and futures
government securities markets. This is based on the assumption that PO speed is a
proxy for market liquidity, i.e., the market is more liquid when PO speed is high,
because the degree of information content is high. Presumably, PO speed depends on
relative accessibility to the two markets.
6.6 Pricing of futures
Futures can be priced in following manner.
6.6.1 The Pricing of Futures Contracts
The price of futures is dependent on the spot price of the underlying asset
and the cost of holding (or carrying) the underlying asset until the delivery date of
the futures contract. The caITying costs refer to the costs associated with purchasing
152
and carryll1g a commodity for a specified period time l9. Basically, there are four
costs associated with can'ying: storage costs, insurance costs, transportation costs,
and financing costs. For financial futures storage, transportation and insurance costs
arc almost zero; therefore, they can be ignored in calculations of financial futures
pnces.
Based on arbitrage arguments20, the theoretical futures pnce can be
determined by adding the calTying costs to the cash price of the underlying asset.
This can be expressed as follows:
F = P + P X C or F = P (1 + C) -------------------------------- (6.1)
F= Futures Price.
P= Cash Market Price.
C= Cost of can'ying, expressed as a fraction of the cash price.
According to arbitrage principles, the futures price must be equal to or less
than the cash price of the underlying commodity plus the carrying charges
necessary to hold the spot commodity forward until delivery. Mathematically, this
rule can be expressed as follows:
F:SP (1 + C) -------------------------------------------------- (6.2)
If prices do not meet this criterion, a trader can bOlTOW funds to buy the
spot commodity, sell the futures contract, and can'y the commodity to delivery
against the futures contract. This is called 'cash-and-caITy' arbitrage; it continues
until the difference between cash and futures prices n,UTOWS relevant carrying
costs.
The futures price must be equal to or greater than the cash price plus the cost of
carrying the goods to delivery. This rule can be expressed as follows:
F ~ P (1 + C) -------------------------------------------------- (6.3)
If the price of futures does not conform to this rule, there will be an
arbitrage opportunity for traders. This is called 'reverse cash-and-carry' arbitrage.
Response of DIFl[LN[NIFTYll to a unit shock in DIFI[LN[NM FUTURES]] --------------~--- .. ----- --.~--"-,. --;1.11£.1[-002 ,---------.---~----- ---<---,
\
1
~~:~~~: ~I ~I~~----------------------------------~! .. . I
Rcsponse ofDIFl[LN[NIFTYll to a unit shock in D1FI[LN[NM FUTURES)]
\' ..
··-----~~---·~1'.051Q[ 001
I " .' ~'.('!"'"=:,..' c.......,...... : "7 . , S::;. : '7'" , !' • I 1 I I
. It -"'LL I II -"'LLI --"'LLI -'.' _IL---~I_ILLI -'.'--.lol -"'~' -,-I -"'LL I -,-I -"ILL I -'.I-"ILLI -'.I-"ILL' ~I..JILLI ~I..JILL' -"t..JIL----"'~1 -,-I ..JILL~---'--.:I L;} .051 0£-002 ~ l' ~
Responsc of DIFI [LN[NM FUTURES]] to a unit shock in DIFl[LN[NIFTYll . ----- --- --------- -- .... - •.....
Response of DIF1[LN[NIFTYll to a unit shock in DIFl[LNINM FUTURES]]
Figure 6.7 (b) Year 2001-02 Nifty Future Index
Response of DIFI [LN[NM FUTURES II to a unit shock in DIFI [LN[NIFTY])
Figure 6.8 (a) Year 2002-03 Nifty Cash Index
Response ofDIFI[LN[NIFTY]) to a unit shock in DIF1[LN[NM FUTURES]) ~------------~--- 1026E-003
.. <- •
191
Figure 6.8 (b) Year 2002-03 Nifty Future Index
Response of DIFl[LN[Nl\I FUTURES]] to a unit shock in DIFl[LN[NIFTY]] ... ~~~~ .. ~.~ .. ~ _. - -~.~~~ .. ~----~ - ·--"-·~~---·--~-~-~.1492[.OO)
! ~------, ~------;I
u I I -'-".tj-"I-'-~~~I-'-I---JL.---.l---.Lli I I I I I I I LLLj,-,--,--,-,---,--,-I_,IL.L-'--'-"-' '-.;;1 19 J.4a}[ _0111 50
Figure 6.9 (a) Year 2003-04 Nifty Cash Index
Response of DIFl[LN[NIFTY]] to a unit shock in DIFI [LN[Nl\I FUTURES]]
•---,--1 LI -,-I~ILL-,--,~ILLI m'-'-'~--'-' -,-I-,---,-I-,-I-'-LI LI -,-I~I-,-I -,--,-1--,1-,-1 -'--'--'-LI LI -'-1~1--,---,--,-I-,-I-'--'--'--'-LL.LJLL,jI. 1.(12'8[-0112 I til ~
Figure 6.9(b) Year 2003-04 Nifty Future Index
Response of DIFl[LN[Nl\I FUTURES]] to a unit shock in DIFl[LN[NIFTY]]
: , .
192
Figure 6.10 (a) Year 2004-05 Nifty Cash Index
Rcsponse of DIFI[LN[NIFTYJj to a unit shock in DIF1[LN[NM FUTURESJj
-"-~-r'-
I .--'-,--'--"-, .LI """--"''---'-'--''_'L.L' ~-LI -,-I--,---,~-,-,--,--I .LI """--"'-L' -,-I ",',,-"''-'--'---'--'---'-'.-'-L' -,-I--'--LL----''--'---'-'--'--.LI --'I--"I--.;il, 4311£ 002 D SI)
Figure 6.IO(b) Year 2004-05 Nifty Future Index
Response of DIFI[LN[NM FUTURESll to a unit shock in DIFl[LN[NIFTYll -~-.~.-----,,-...... " ...... _ ... __ ._._-_._--_._ ..• -----.~-~-.------,
r-"-r-'~~~~~~~~~~~~------------------------~
r LI -'-'--'--.L..l~L..L--'--'--..L1 --"'-L' i\;' _. -L"--,--,I_IL.L..L-'-LI -,-I ..... I--,I'-'--'-'--'--.LI -,-I -,'--,--I -'-'-'-.--L-'--"--,---,--"LL..LI-.[J"l '.''':'802 8 U ~
Figurc 6.11 (a) Year 2005-06 Nifty Cash Index
Response of DIF 1 [LN[NIFTYll to a unit shock in DIFI [LN[NM FUTURESll ------,1.0941£.002
193
Figure 6.11 (b) Y car 2005-06Nifty Future Index
Response of D1Fl[LN[NM f'UTURES]l to a unit shock in D1Fl[LN[NIFTYll
1 • I 1 I ) ! I I
j 1
I I I I I L_J-,I~I'-LI -'-11-,--1 LI -"--,1-,--1 -'--J.I-"I_-,--,-,--I LI -,-I U--L l, 1mr 00' . 'ill