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Macroeconomic Fundamentals and Exchange Rate Dynamics in India

The present study investigates the relative importance of macro (interest rates, inflation, etc) and micro (order flows, information, etc) variables in determining the short-run exchange rate movements. Empirical analysis is based on a primary survey of the Indian foreign exchange dealers. It finds from a survey that a majority of the dealers feel short-term changes in the Indian rupee/US dollar market are basically influenced by the micro variables such as information flow, market movement, speculation, central bank intervention, etc. One of the findings of this study, which has policy implications, is that the dealers feel speculation would increase volatility, liquidity and efficiency in the market and, central bank intervention reduces volatility and market efficiency.

Macroeconomic Fundamentals and Exchange Rate Dynamics in India

Some Survey Results

The present study investigates the relative importance of macro (interest rates, inflation, etc) and micro (order flows, information, etc) variables in determining the short-run exchange rate movements. Empirical analysis is based on a primary survey of the Indian foreign exchange dealers. It finds from a survey that a majority of the dealers feel short-term changes in the Indian rupee/US dollar market are basically influenced by the micro variables such as information flow, market movement, speculation, central bank intervention, etc. One of the findings of this study, which has policy implications, is that the dealers feel speculation would increase volatility, liquidity and efficiency in the market and, central bank intervention reduces volatility and market efficiency.

N R BHANUMURTHY

I

A
fter the collapse of the Bretton Woods system in 1973, exchange rates have shown much volatility. Since then a lot of research has been undertaken to understand the behaviour of exchange rate movements. Some of the perennial questions that have been raised, are, for example: what are the determinants of the exchange rate? Do exchange rates follow a specific pattern? Is there any theory that help in predicting the rate movements near-accurately? Many approaches developed in the area of open economy macroeconomics have tried to address these questions. However, these approaches have had some success in explaining currency movements only in the medium and the long-term. But these macro fundamental theories, however, offer no explanation for the short run exchange rate movements in the market [Evans and Lyons 1999]. Particularly after the finding of Meese and Rogoff (1983) that forecasts based on the monetary approach to exchange rate determination do not out-perform the random walk forecasts; the macro models subsequently lost their allure. In fact, even after two decades of this finding, there is no unanimity that theories based on fundamentals can provide best forecasts for the exchange rate movement [see Mark 1995; Mark and Sul 2001; Cheung, Chinn and Pascual 2002; and Chinn and Meese 1995]. A recent study by Neely and Sarno (2002) raises an important query: why should fundamentals forecast exchange rate movement? There is a need to address this basic issue so as to strengthen research in exchange rate economics and also to chart the future direction for this. As exchange rate forecast is a necessary datum for policy-makers to determine the output and inflation in the economy as also for fund managers to plan their asset allocation, Neely and Sarno (2002) argue that instead of forecasting exchange rates through fundamentals, the agents can directly predict output, inflation and uncovered interest rate parity (UIP).

The above two views only question the relevance of existing macro approaches in exchange rates economics. But both the views ignore the role of the time horizon in judging the efficacy of macro theories. As the exchange rate is an output derived out of market behaviour, merely concluding that the exchange rate follows a random walk would mean that the market forces behind this rate are erratic irrespective of the time horizon. This is a conclusion to be contested and it needs to deliver answers both at the theoretical and the empirical level. On the other hand, an over dependence in macro theories to explain and forecast exchange rates fairly accurately at all time horizons is also not completely acceptable. From the literature, one may find that there are some mixed results regarding the macro fundamental theories’ ability to explain exchange rate behaviour in the long run. But in the short run, recent studies, particularly after the introduction of on-line trading systems that make the tick-by-tick (high frequency) data available, have shown that macroeconomic fundamentals are hardly useful in predicting the rate movement [see Sarno and Taylor 2001, for the survey]. Hence, there is a need to search for some factors that can explain the exchange rate movement based on the time horizon. In this study we try to investigate the factors that determine the exchange rate in different time horizons with the help of primary information collected from the Indian foreign exchange dealers. (The present author also examined this issue with the help of secondary data, which is available in Bhanumurthy (2004).)

This study is organised as follows. In Section II, we discuss briefly one of the alternative theories on asset price determination in the finance literature (namely market microstructure theory) and also present a review of the empirical literature. In Section III are laid down the specific objectives and database used in this study. It also discusses the empirical findings based on primary data. Accordingly, the conclusions are drawn in the last section.

II

The present study questions the relevance of macro theories in explaining and predicting day-to-day movements in the foreign exchange market. It is implicitly acknowledged that fads and/ or speculation are the most important aspects of intra day/dayto-day transactions in the foreign exchange markets rather than fundamentals. This is because the speculative agents’ role may be an important factor in influencing the short-term behaviour of the market. Further, it was found that the role of fundamentals is either insignificant or is tending to be so in recent years. The problems of policy inconsistency and the so-called “good news” and “bad news” effects seem to be playing a more dynamic role in the exchange market behaviour today. From the current macro approaches it is seen that these consider only fundamentals such as relative income, relative prices, interest rate differentials, relative cumulated current account balances, etc. But in practice, do the market participants (dealers) consider only macro economic fundamentals such as these or do any other variables (that are micro in nature) become relevant to these movements? Particularly in the short run, where transactions tend to occur in a very short time span, it may be easily understandable that practitioners do not consider these macro variables at the moment of forming their expectations; “... market participants do not in fact all use a common agreed-upon model for thinking about the foreign exchange market and do not all share the same expectations at any point of time” [Frankel and Froot 1990]. Also the frequency of changes in macro fundamentals is very low.

Now the question that remains is that, in the short run, what are the factors that affect dealers’ decision-making? In the literature it was found that more than macroeconomic fundamentals, the dealers consider other variables that are micro in nature [Lyons 1995]. The micro variables are bid-ask spreads, trading volume, own volatility, non-synchronous trading, information (both private and public), inventory cost, etc. In the financial economics literature, to study the behaviour of asset prices and the market participants the researchers mostly use the market microstructure theory, which considers all the micro variables. In the following sub-section we discuss this theory in brief.

Market Microstructure Theory

Market microstructure theory is defined as “the study of the process and outcomes of exchanging assets (ie, currency, stock, etc) under explicit trading rules” [O’Hara 1995]. While much of economics abstracts from the mechanics of trading, the microstructure theory analyses the way in which specific trading mechanisms affect the price formation process in the financial markets. These trading mechanisms may differ from one market to the other. For example, in the stock market, trading is centralised and synchronous but in the foreign exchange market trading is decentralised and non-synchronous. However, irrespective of the type of trading mechanism, prices emerge for the assets when buyers and sellers interact. But the question is whether the equilibrium price that emerges is based purely on the interaction of only demand and supply factors that emanate from the desires of the trading agents, as our microeconomic theory explains? This enquiry forms the beginning of the study of microstructure theory.

Microstructure theory consists of two models namely the inventory model and the information model. The crux of the inventory model is the problem of optimisation as the dealers’ objective is to maximise expected profit per unit of time. The model emphasises control of the inventory fluctuations through price adjustments to avoid bankruptcy and failure at the end of dealing. This model also explains the relationship between the transaction cost and the bid-ask spreads. Information models, which are based on the adverse selection problems, explain the behaviour of market prices through the information content of the traders. Since there exist asymmetries of information between the dealers, their behaviour in making the quote will be different. These information models also explain how the equilibrium market price emerges in the presence of asymmetric information.

Figure : Exchange Rate Determination

Chart 1: Distribution of Sample (Area, Total 91) Source: Evans and Lyons (1999). Exchange Rate Macro fundamentals Market microstructure Goods market Asset market Inventory model Information model
Mumbai 61.5 per cent Delhi9.9 per centOthers9.9 per centChennai 17.6 per cent

In microstructure theory there are two variables that occupy the centre stage, neither of which had any role in the macro approach. These variables are: (a) order flow, (b) bid-ask spread. Both these variables are synonymous with the “quantity” and “price” in traditional microeconomics. Order flow, as used in microstructure theory, is a variant of a key term in microeconomics, namely, “effective demand”. It measures the net buyer-initiated orders and seller-initiated orders.

Micro-Macro Divide

The core distinction between the microstructure approach and the macro approach is the role of trades. Under the macro approach, trades play no role, whereas in microstructure models they are the driving force. We frame this distinction by considering structural models within these two approaches with the help of the flow chart that is presented in the figure.

The exchange rate determination within the macro approach is typically estimated at the monthly frequency, or lower, as the adjustment between the variables would take a time lag of one month or more and also due to the availability of some of the exogenous variables in this approach. The driving variables in this approach include current and past values of home and foreign interest rates, money supply, and other macro determinants like trade balance, fiscal deficits, etc. Exchange rate determination within the microstructure approach is derived from the optimisation problem faced by the actual price setters in the market, namely, the dealers. The driving variables in this approach include order flow, a measure of dealer net positions, or inventory, and other micro determinants like information (both public and private).

Review of Literature

Until recently the application of market microstructure theory was limited to the security markets. Its application to the foreign exchange market began only in the early 1990s, particularly after the introduction of trading systems of Reuters and telerates through which the market participants, mostly banks, can complete their transactions electronically in a short time span. These systems made the transactions very easy and reduced the time and transaction costs in the market. This also made available the high frequency data on exchange rates, which helped the

Economic and Political Weekly March 18, 2006

Chart 2: Distribution of Sample Chart 4: Average Daily Dealing

(Position) (in $ millions)

taken to represent a micro variable and interest rate is taken as macro variable. It is found that order flow and nominal exchange rates are strongly positively correlated. The study tests a portfolio shift model, where order flow was considered as the main microstructure variable and interest rate differentials were con-sidered the macro variable, and concludes that order flows are Dealer/junior dealer49.5 per centChief/senior dealer40.7 per cent Manager9.9 per cent 40 30 20 10 0 <2M 2-10M 10-50M 50-100M <100M Chart 3: Distribution of Sample (Work Experience)
6-10 Years 37 per cent 0-5 Years 57 per cent

researchers in this area study market behaviour in the short run and also in its forecasting in the short run.

One of the basic studies in this area is that of Goodhart and Figliuoli (1991). In this study, for the first time, high frequency data on exchange rates was analysed and many issues raised for further research. However, the application of microstructure theory to exchange rates was initiated by a pioneering study by Lyons (1995). As already mentioned, the models based on microstructure theory (particularly the information models) are very useful in explaining changes in the exchange rate movements. Under information models there are two types of studies that exist in the literature: one that concentrates on public information, which is uniformly available to all participants in the market and its impact on the exchange rates in the short run; second, the presence of private (and/or asymmetric) information, which is available to individual participants, and its impact on the volume and the rate changes. Researchers explored both the cases with the help of high frequency data and with advanced econometric tools. But there are not many studies that applied inventory models and this is due to an unavailability of information relating to the order book of the dealers in the foreign exchange market. A detailed survey of empirical studies purely on microstructure theory can be found in Sarno and Taylor (2001).

From a review of the studies on microstructures in the foreign exchange market, it may be found that most of them are fairly recent. This indicates that the study of micro issues in exchange rate behaviour is a recent phenomenon. We also find that most of the studies have concentrated on the leading currencies like deutsche mark/US dollar, yen/dollar and pound/dollar. This may be because of high market activism in these currencies and also due to availability of data at high frequency.

Only Evans and Lyons (1999) developed a model by including both micro and macro variables to test their comparative efficiency in tracking the changes in the exchange rate. For this purpose, the study considered the daily data of the deutsche mark/ dollar and yen/dollar exchange rates. Order flow, which is defined as the net of buyer initiated trades to seller initiated trades, is better predicators of the exchange rate changes. The model was robust and also produces better out-of-sample forecasts than a random walk model.

In India, with the introduction of economic reforms, particularly in the financial sector, and growing foreign investments, the volatility in exchange rates has been more intense. Now that there is talk of full convertibility on capital account also, it is very important to understand exchange rate dynamics. (In the Indian foreign exchange market, the daily transactions amount to more than one billion US dollars.) Further, until recently the transactions were completed only with telephone contacts while the Reuters screen helped to identify the dealing party. But the Reserve Bank of India (RBI) has now allowed the transactions to be undertaken directly through the Reuters’ system. This may lead to more activism in the market and would lead to an increase in both volume and the number of transactions. This situation would force the market players to properly understand the trends in the market. For this purpose, it is necessary to study the behaviour of high frequency data in the Indian foreign exchange market. Bhanumurthy (2000) does try to examine the role of information on the behaviour of the rupee/dollars rate in the short term. But this kind of analysis would be incomplete if the perceptions of traders, who are the real decision-makers in the market, about the importance of macro fundamentals in determining the exchange rates in the short run are not taken into account. Cheung and Chinn (1999) recognised this issue and undertook a survey on foreign exchange dealers in the US. This study probes the causes and determinants of bid-ask spreads and the predictability of exchange rates in the short run. It was found that a majority of the traders responded that the predictability of exchange rate changes is very low in the intra-day trading. And in the medium and long run more than two-thirds of the traders view that exchange rates cannot be predicted. Though this study did not focus on the factors that determine exchange rates over the time horizon, it has marked a beginning in the survey-based studies on the foreign exchange market.

In continuation with the above study, Cheung, Chinn and Marsh (2000) did a survey on the UK-based foreign exchange dealers in 1998. This study focused on three aspects: (1) the microeconomic operation of the foreign exchange market; (2) the beliefs of dealers regarding the importance of macroeconomic fundamentals in understanding exchange rate movements; and (3) microstructure variables in the foreign exchange market. The study found that a majority of the dealers held the view that non-fundamental factors dominate the short-term exchange rate movements. Alternatively, it was found that speculation is an important factor in the short-term market. Further, the dealers believe that fundamentals have significant effects on exchange rates in a much

Chart 5: Trading

80 60 40 20 0

Technical Fundamentals Customer order Other 62 33 49 43 25 42 7 5 now 5 years ago

Chart 6: Determinants of Bid-Ask Spread

-i i i i l ii i ll i i i i 88.-15Potential costs 21.3 per cent Both 9 per cent Market convention 69.7 per cent Chart 7: Quotes 14 8 30 12 20 11 9 15 22 1 40 30 20 10 0 <1 <5 <10 <20 <30 (Per cent) Larger than convention Smaller than convention Chart 8: Reasons for Spread Differentfrom Market Convention 46 8.8 24.1 38.5 29.7 (Per cent) 30.8 15.4 5.5 9.9 4.4 Thin and quirt marketThin and hecticUnexpected changeMarket newsIncreased marketvolatilityHolding a positionSmall trading bankInformed trading bankKeeping positionCounter party quote 50 40 30 20 10 0 Chart 9: Reasons for Spreads Confirmingto Market Convention (Per cent) 60 45 30 15 0 8.8 53.8 46.2 22 11 Firm’s policy Relationship with other Market image Maximise trading profits Follow major players

shorter time frame than expected by the macro theorists. Regarding the concept of purchasing power parity, the study concludes that though the dealers accept it as representative of the exchange rate’s fundamental value, however the trading would not be based on this. Lastly, market convention has been found to be an important determinant of bid-ask spread. (Cheung and Wong (2000) further extended this survey to Hong Kong, Tokyo and the Singapore foreign exchange markets.)

Taking the cue from the above empirical and survey-based studies, the present study, which is the first of its kind on a developing country’s foreign exchange market, attempts a similar exercise in the Indian context. In the next section, we specify the objectives of the present study.

III

Objectives of Study

It is significant that the RBI’s Report on Currency & Finance, 1999-2000 (pp IV-18-19), it has raised the issue of studying the foreign exchange behaviour in a market microstructure framework. The apex bank has indicated that the movements in the macro fundamentals may not back exchange rate movement in India in all time horizons. In this context, the present study tries to analyse the factors behind changes in the exchange rate in the short run. An attempt has been made to discern dealers’ perception regarding the market movement and the forces behind it in the Indian foreign exchange market.

The specific objectives of the paper are as follows: (1) to test the importance of macroeconomic fundamentals in different time horizons by using primary information; (2) to examine the importance of microstructural factors in short-term rate movement; (3) to find out the predictability of exchange rates in different time horizons; and (4) to analyse the effects of speculation and central bank intervention on the rate movement.

Empirical Results

A structured questionnaire1 was prepared and mailed to the foreign exchange dealers, who are registered with the Foreign Exchange Dealers’ Association of India (FEDAI).2 In India, foreign exchange dealing rooms are located in seven cities (Ahmedabad, Bangalore, Chennai, Delhi, Kolkatta, Kochi and Mumbai). (The information on number of banks in each city can be found in the table.) But it has been observed that most of the operations are undertaken by the banks in Mumbai, Chennai and Bangalore. Some of the dealing rooms in Mumbai, Chennai, Bangalore and Delhi were visited and discussions held with dealers and the questionnaires filled. For the remaining dealers, questionnaires were mailed. A total 91 dealers (around 23.3 per cent of registered dealers) responded to our questionnaire. For

Table: Number of Dealing Rooms and Dealers in India

(Locationwise and only Banks)

Location Number of Dealing Rooms Number of Dealers
Ahmedabad 2 4
Bangalore 4 11
Chennai 17 37
Delhi 25 57
Kolkata 12 16
Kochi 5 14
Mumbai 79 252
Total 144 391

Source: The Indian Dealing Rooms Directory, 2001, Forex Association of India. (Only commercial banks and financial institutions are covered.)

Economic and Political Weekly March 18, 2006

a study of this kind, 23 per cent is a very good response. One Chart 10: Important Factors that Determine ExchangeRates over Time

of the problems that the researcher faced was that in most of 80 the dealing rooms, where there were many dealers, the response 70 was one or limited to a maximum of two. The reason for this 60

50poor response is due to the dealer’s assumption that all the dealers 40

30

in a dealing room would have the same perception and make 20the same decisions. But to the surprise of the researcher, it was 10 found that wherever the responses are more than one from a single 0 dealing room, no two dealers from same bank have same perception and possess same decision-making principle.

55.5 45.1 4.4 18.7 58.3 9.9 22.1 1.1 63.8 11 Bandwagon effect News Speculation Order flow Technical trading Long-runMediumIntra Ecofund 68.1 50.550.5

Chart 11: If Exchange Rate Does Not Reflect Changes inEconomic Fundamentals, What Are the Factors Responsible?

Distribution of the Sample(Spatial and Dealers’ Profile)

It may be noted from the table that in India, in 2001, there were 144 dealing rooms and 391 dealers. These dealing rooms were spread over seven cities specified earlier. For this study, we could collect information from 91 dealers. The spread of the sample can be seen in Chart 1. About two-thirds (61.5 per cent) of the sample is from Mumbai. Chennai and Delhi consists of

17.6 per cent and 9.9 per cent, respectively. From other cities like Bangalore and Kochi, we could get only nine samples. (The unspecified slice in Chart 1 is one sample from Kolkatta.) We could not get any response from Ahmedabad.

The profile of the sample includes managers, treasurers, chief/ senior dealers, and dealers/junior dealers. It may be noted from Chart 2 that a large portion of the sample (about 49.5 per cent) are dealers/junior dealers. Chief/senior dealers are about 40.7 per cent. We got only nine responses from the managers/treasurers. In terms of experience, around 57 per cent of people had less than five years of experience and around 37 per cent people have between 6 and 10 years and the remaining 6 per cent (exploded slice in Chart 3) have more than 10 years of experience. We have adopted this distribution basically to capture the changes in the trading systems and strategies over a five-year period.

Daily Dealing and Bid-Ask Spread

We also collected the information regarding the volume of transaction of the bank so as to determine the size of the bank. Given the sensitivity of this information we could get responses only from 69 dealers (about 75 per cent). It was also observed that most of the deals were in the Indian rupee/US dollar market and other foreign currencies like euro were traded in crosses with US dollar. The range of dealing was found to be very large (minimum is US $ 0.5 million and maximum US $ 500 million). From Chart 4 it may be noted that around 45 per cent of the responded banks has a daily dealing between $ 10 and 50 million. An interesting aspect is that about 19 per cent banks have a daily dealing of more than $ 50 million. This shows how important it is to study the India foreign exchange market behaviour.

The study tries to examine the basis of foreign exchange trading in India. In doing so the data on current trading and the trading five years ago was collected from the banks. It was found that in 1997 (five years before the 2002 survey), foreign exchange was traded mostly to adjust the changes in fundamentals and complete the customer orders. But presently there seems to be a significant shift from these trades to the trading based on technical factors (Chart 5). (Over the last five years technical trading increased substantially from 33 per cent to 62 per cent, whereas trading based on customer orders have declined significantly from 42 per cent to 25 per cent.)

Another important objective of this study is to know what are the determinants of the bid-ask spread of the quotations. It has

(Per cent)

70 60 50 40 30 20 10 0 speculation manipulation of bank manipulation of insti central bank intervention

46.2 19.8 23.1 3.3 16.5 8.8 4.4 7.7 8.8

yes

no

no opinion

Chart 12: Do You Believe Exchange Rate Changes AccuratelyReflect Changes in the Fundamentals

100

80

60

40

20

0 Intra day Medium Long-run

83.5 0 74.7 14.3 5.5 83.5 3.313.2

Yes

No opinion

No

been found that a majority of the respondents (around 70 per cent, see Chart 6) determine their spreads based on the market convention and around 21 per cent determine this based on their potential costs of making the quote. But the information on spreads in Indian rupee/US dollar market shows a different picture. About 60 per cent of the dealers quote the spread of half a paise and about 23 per cent of the dealers quote a one paise spread. Also the discussions with the dealers found that though the spreads are quoted on the basis of market convention, the conventional spread is not the same across the banks.

Market Convention and Spreads

For a smooth functioning of the market, it is necessary that the bid-ask spreads quoted should follow the market convention. If both differ, then it may lead to or be led by some factors that are exogenous to the market, like unexpected changes in the fundamentals, political news, etc. In this study we find mixed results (Chart 7). There were 30 per cent of dealers who had less than 5 per cent of their quotes as larger than conventional spread In the same way there were 22 per cent dealers who had less than 30 per cent of their quotes smaller than conventional spread.

But why should the dealers quote their spreads differently from the conventional one? Or, why should the dealers quote the conventional spread? For the first question, more than 30 per cent of the dealers answered that the presence of increased market volatility, holding position against the market trend, and unexpected change in the market activity due to various reasons are the prime factors (Chart 8). For the second question, more than 45 per cent of the dealers felt that securing a good market image of the bank and maintaining reciprocal relationship with other banks are the main reasons (Chart 9).

Chart 13: Effects of Speculation on the Market central bank plays a “spoil sport”4 in the foreign exchange market

80 60 40 20 0

14.3 70.3 41.8 34.1 62.6 19.6 53.8 25.3
Volatility Rate from Market liquidity Market efficiency
fundamentals
Increases Decreases

Chart 14: Effects of Central Bank Intervention on the Market

70 60 50 40 30 20 10

0 Volatility Rate from Market liquidity Market efficiency

increases decreases 20.9 64.8 44 39.6 50.5 23.1 22 52.7

fundamentals

Increases

Decreases

60 50 40 30 20 10 0

Chart 15: Assimilation of Economic Announcements When They Are Different from Market Expectations

Trade Inflation GDP Interest rate Money supply <10 sec <1 min <10 min 123123 <30 min 1212>30 min 29.720.9 12.1 24.2 40.7 20.9 4.4 20.9 7.7 12.1 20.9 14.3 9.9 38.5 2222 35.2 3.3 11 56 29.7 5.55.5 1.1 20.9 31.9 24.2 4.4 8.8

Determination of Exchange Rates

One of the important questions this study addresses is: What are the factors that determine the exchange rates in any economy? In the area of international money and finance, there are many theories that explain the exchange rates. But are these theories helpful in practical trading? To answer this, we have asked the dealers the important factors that determine exchange rates over a time horizon (like intra day, medium run, and the long run). It is interesting to note that in the intra day trade factors like news3 (68.1 per cent), bandwagon effect (50.5 per cent), speculation (50.5 per cent), and order flow (55.5 per cent) are important (Chart 10). One striking thing is that nobody expressed that economic fundamentals are important in the intra day trades. But in the medium run and long run, economic fundamentals seem to be a major factor in determining the rate movement. In other words, over the time horizon the importance of economic fundamentals is increasing. From this it can be concluded that macroeconomic theory may be useful only in the medium and long run. But to study the market behaviour in the short run one would need to consider non-macro fundamentals like news, order flow, etc. These are the major elements of market microstructure theory.

Macroeconomic fundamentals indeed have a role in the exchange rate determination. But it is not in the intra day. It may be noted from Chart 12 that more than 80 per cent of dealers feel that in intra day trading, fundamentals play an insignificant role. Over the time horizon the importance of fundamentals is increasing. If the intra day changes in exchange rate do not reflect changes in economic fundamentals, what are the other variables responsible? The response was loud and clear that both speculation and the central bank intervention are the major determinants (Chart 11). This vindicates the impression that in India the activity and the rates move accordingly. But one may be interested to know what would be the exact impact of speculation and central bank intervention on the market.

Speculation, Central Bank Intervention,and the Foreign Exchange Market

In the intra day trading, we found that there are two factors that affect the exchange rate movement, i e, speculation and central bank intervention. But what is the exact effect of these factors on market behaviour (like on market volatility, liquidity and market efficiency)? Though it is known that both speculation and central bank intervention could either increase or decrease volatility, liquidity and efficiency, this question was asked basically to bring out the dealers’ general perception about the effect of these two factors on market movement. The dealers were asked the samequestion separately and these are presented in Charts 13 and 14.

It was found that a majority of the dealers (more than 50 per cent) feel speculation leads to an increase in market volatility, liquidity and efficiency. Contrary to this, more than half of the dealers feel that central bank intervention would reduce both volatility and efficiency in the market. One of the arguments given for the central bank intervention is to “bring orderly movement” by removing speculation in the market. But the dealers perceive this in the other way. They feel that without speculation there is no “charm” in the market and the central bank’s intervention is very “depressing”.5

Macroeconomic Announcements and Exchange Rate

In intra day trading, it may be concluded from our survey results that exchange rates do not follow macroeconomic fundamentals. This is true only when the new economic data coincides with the expectations already formed and which are already discounted in the market. But if the new macroeconomic data deviates from market expectations, the market tries to adjust to this new information. Now the question is how fast does the market assimilate the news. This depends on the kind of macroeconomic news. To analyse this, we have taken the interest rate, trade deficit, money supply, GDP, and inflation. It was found that among all these variables, interest rate announcements are assimilated within 10 seconds (Chart 15). The remaining variables take more than a minute. Further, for the question of which economic announcement has a bigger impact on the market movement now and five years earlier, it was found that the importance of interest rate changes has increased substantially over the period (response was 50 per cent five years back and now it is 73 per cent) (Chart 16). This may be due to a substantial increase in the capital mobility and also the gradual integration of financial markets (both domestic and foreign), which has an immediate impact on the market. But the importance of money supply, GDP and inflation has declined over the period. One reason for this could be that these variables are behavioural and is predictable (unlike interest rate, which is still a policy variable).

Purchasing Power Parity and the Exchange Rate

Macroeconomic researchers believe that market practitioners strongly believe in purchasing power parity (PPP) theory. It is assumed that the dealers hold their position based on this theory. The dealers’ views are in contradiction to the macroeconomic researchers’ belief that the PPP condition would be helpful in tracking the exchange rate movement (Charts 17 and 18). Almost

Economic and Political Weekly March 18, 2006

Chart 16: Which Economic Announcement Has a BiggerRBI should also develop a more efficient and more vibrantImpact on Market Movement?

foreign exchange market. This is particularly necessary when the financial markets are highly integrated both domestically

80 60 40 20 0

72.5 49.5 25.3 24.2 11 16.5 18.7 8.8 15.48.8 2002 1997

Interest rate Trade deficit Money supply GDP Inflation

50 40 30 20 10

0 Computer fair spot Parity Academic jargon Other

Chart 17: Use of Purchasing Power Parity Condition

25.3 26.4 44 6.6

80

60

40

20

0 Intra day Medium Long

Chart 18: Do You Think PPP Condition Can Be Used to Predict the Rate? (Per Cent)

17.6 60.4 8.8 31.9 38.5 16.5 51.6 24.2 17.6

123

No

123 Yes

No opinion

45 per cent of the dealers were of the view that this is basically academic jargon. Further, more than 60 per cent of dealers felt that the PPP condition could not help in predicting the rate change in the short run. But it can help predict only in the long run.

Conclusion

In the present study we tried to discern the factors that affect exchange rate movements in different time horizons by using survey data. It was found that the dealers perceive, compared to fundamentals, order flow has a more significant impact on the exchange rates in intra day movements. But it was found that fundamentals are more useful in predicting the rates in the long run. This is a significant finding for any developing country’s foreign exchange market. These results might differ between the countries as it depends on the specific country’s market regulations, “maturity” and the economy itself.

Given these conclusions, it can be inferred that the studies on exchange rate determination models should concentrate on shortterm forecasting with the help of micro variables like bid-ask spreads, volume of transaction, order flows, and public and private information. A study of this kind may be greatly useful not only in predicting the exchange rates near-accurately but also in maintaining orderly movement that helps the risk managers in the market. One of the criticisms of this conclusion could be that a greater emphasis has been given to the views of the dealers whose objective may be fairly different from that of the market regulator. Though this may be true to some extent, however one cannot completely ignore the dealers’ perception about the established theories in the area of international macroeconomics, as they are the major players in the market and the rate (or price) is an outcome of these people’s behaviour. The RBI has been intervening, both directly and indirectly, in the market to achieve its goal of orderly movement in the market. Besides having this as an important objective, the and at international level.

rr;

Email: nrbmurthy@yahoo.com

Notes

[This is part of a study sponsored by ICICI Research Centre. An earlier versionof this paper was presented in a seminar at the Institute of Economic Growth,and at the Sixth Money and Finance conference held at IGIDR, Mumbai inMarch 2004. The author would like to thank the anonymous referee for usefulcomments and suggestions. However, any errors and omissions in the paperare the author’s alone.]

1 The structured questionnaire is available in Bhanumurthy (2004).

2 Although there are some private primary dealers in the market, in this study we have covered only dealers from the commercial banks (public sector, private and foreign banks) and domestic financial institutions.

3 Here the news could be either political, economic, or some thing else which distorts the dealers’ expectations.

4 Some of the dealers have used this word at the time of discussions.

5 From the discussions with the dealers it was found that most of the big players in the foreign exchange market have shifted to other markets. Also it was viewed by these big players that there is no foreign exchange market in India.

References

Bhanumurthy, N R (2000): ‘Information Effects in Indian Foreign Exchange Market’, presented in Fourth Capital Markets Conference, UTI Institute of Capital Markets, Mumbai.

– (2004): ‘Microstructures in the Indian Foreign Exchange’, Institute of Economic Growth, Working Paper (E/250/2004), Delhi. Cheung, Yin-Wong and M D Chinn (1999): ‘Traders, Market Microstructure and Exchange Rate Dynamics’, NBER Working Paper, No 7416.

Cheung, Yin-Wong, M D Chinn and W Ian Marsh (2000): ‘How Do UKbased Foreign Exchange Dealers Think their Market Operates’? NBER Working Paper No 7524.

Cheung, Yin-Wong, M D Chinn and A G Pascual (2002): ‘Empirical Exchange Rate Models of the Nineties: Are Any Fit to Survive?’ University of California, Working Paper, May.

Cheung, Yin-Wong and Clement Yuk-Pang Wong (2000): ‘A Survey ofMarket Practitioners’ Views on Exchange Rate Dynamics’, Journal of International Economics, 51, pp 410-19.

Chinn, Menzie D and Richard A Meese (1995): ‘Banking on Currency Forecasts: How Predictable Is Change in Money?’ Journal of International Economics, February, 38(1 and 2), pp 161-78.

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Frankel, Jeffrey, K A Froot (1990): ‘Chartists, Fundamentalists and Trading in the Foreign Exchange Market’, American Economic Review, Vol 80, May, pp 181-85.

Goodhart, A E, Charles and L Figliuoli (1991): ‘Every Minute Counts in Financial Markets’, Journal of International Money and Finance, 10, pp 23-52.

Lyons, R (1995): ‘Tests of Microstructural Hypotheses in the Foreign Exchange Market’, Journal of Financial Economics, 39, pp 321-51.

Mark, Nelson C (1995): ‘Exchange Rates and Fundamentals: Evidence of Long Horizon Predictability’, American Economic Review 85(1), pp 201-18.

Mark, Nelson C and Donggyu Sul (2001): ‘Nominal Exchange Rates andMonetary Fundamentals: Evidence from a Amall Post-Bretton Woods Panel’, Journal of International Economics, 53(1), pp 29-52.

Meese, R and K Rogoff (1983): ‘Empirical Exchange Rate Models of the Seventies: Do They Fit Out of Sample?’Journal of International Economics, 14, pp 3-24.

Menkhoff, Lukas (2001): ‘Short-Term Horizons in Foreign Exchange? SurveyEvidence from Dealers and Fund Managers’, KYKLOS, 54(1), pp 27-48.

Neely, J Christopher and Lucio Sarno (2002): ‘How Well Do Monetary Fundamentals Forecast Exchange Rates?’ Federal Reserve Bank of St Louis Review, September/October, 84(5), pp 51-74.

O’Hara, Maureen (1995): Market Microstructure Theory, Blackwell Publishers Inc.

Sarno, Lucio and Mark P Taylor (2001): ‘The Microstructure of the ForeignExchange Market: A Selective Survey of the Literature’, Princeton Studies in International Economics-89.

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