EXCHANGE RATE DETERMINATION

by

Wendy M. JeffusInternational Finance

Boston College

INTRODUCTION

Exchange rates are prices that are determined by supply anddemand. For some countries the exchange rate is the singlemost important price in the economy because it determinesthe international balance of payments. (Levich, 2001)There is no general theory of exchange rate determination,but Eiteman et al (2001) divide the potential exchange ratedeterminants into five areas: parity conditions,infrastructure, speculation, cross-border foreign directinvestment and portfolio investment, and political risks.Although no model has been consistent in predicting short-term foreign exchange rate behavior, there are several majorconcepts that play a role in determining the long-termbehavior of foreign exchange rates. The first concept isbased on the idea that the current price of an assetreflects all available information; and therefore, onlyunexpected events cause exchange rates to fluctuate. (Levich,2001)

Exhibit 1: Factors that Affect Foreign Exchange RateMovementsDemand for Currency Price of Currency

National Income Demand for CurrencyReal Interest Rates Demand for CurrencyInflation Rates Demand for CurrencyNational Wealth ( Current Account) Demand

for CurrencyPreferred Currency Mix Demand for CurrencyFinancial Risk Demand for CurrencyPolitical Risk Demand for CurrencySupply of Domestic Bonds Demand for Currency

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Source: Levich (2001)

Levich (2001) points out that the character and the contextof the change will greatly affect the nature of the change.The nature of the change is the effect it has on theexchange rate, whether exchange rates move immediately,reach a new equilibrium, overreact, or continue to adjust.For example, “character” affects the nature of the changedepending on whether the change is unanticipated versusanticipated changes, permanent versus temporary changes,real versus nominal changes, and single industry versuseconomy-wide changes. Additionally, the extent that anopinion is held on the change and the level of the rate ofchange will affect the nature of the change. Levich (2001)also talks about the “context” of the change having anaffect on exchange rate movement. For example, regarding“context” he is referring to how monetary authorities areperceived, the demand for home country currency andsecurities, the level of liberalization, and the source ofthe change.

In the short term exchange rates seem to be affected by newsabout fundamental economic events, although economic modelsstill remain unreliable for short term forecasting. In thelast 25 years economists have adopted the asset approach toexchange rates in an attempt to explain exchange ratemovements. The asset approach emphasizes the role ofexpectations. In the monetary approach the exchange rateestablishes a relative price between two currencies. In theportfolio-balance approach, exchange rates reflect therelative risk and return of two currencies. (Levich, 2001)

PARITY CONDITIONS

Parity conditions are an explanation for the long-run valueof exchange rates. They include: relative inflation rates(purchasing power parity), relative interest rates (Fishereffect), forward exchange rates, exchange rate regimes, andofficial monetary reserves.

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Interest Rate ParityInterest rate parity connects the forward rate to the spotrate and interest rates in the domestic economy to thoseabroad. (Sercu-Uppal, 1995) This relationship holdsbecause the forward rate is known. Additionally, theforward rate is not affected by investors risk aversion oruncertainty. Interest rate parity is the strongestrelationship, and through arbitrage it is used to ensurethat financial prices reflect a forward premium predicted byinterest rate parity. (Sercu-Uppal, 1995)

Purchasing Power ParityPurchasing power parity1 (PPP) states that over the long-runthe exchange rate between two currencies adjusts to relativeprice levels. As shown below, the spot exchange rate at theend of the period (S1) over the spot exchange rate at thebeginning of the period (S0) is equal to one plus theforeign inflation rate (1 + IF) over one plus the domesticinflation rate (1+ ID).

(1)

An important major determinant of long-run behavior of realexchange rates is economic activity such as a rise inproductivity or growth in manufacturing. These factorsaffect the overall quality and quantity of goods producedand consumed, the “national consumption basket.” Whilethere is agreement that growth in economic activity anddifferences in productivity influence the long-term realexchange rate, calculation of these effects are stilldebated. (Solnik, 2000)

The International Fisher EffectThe Fisher effect describes the long-run relationshipbetween inflation and interest rates. This theory states1 The Economist’s Big Mac index stems from the purchasing power parity theory.

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that nominal interest rates in each country are equal to therequired real rate of return plus compensation for expectedinflation. See equation 2, where i is the nominal rate ofinterest, r is the real rate of interest, and π is theexpected rate of inflation over the period the funds are tobe lent. An approximation of the Fisher effect drops thefinal term. Equation 3 is an example of the InternationalFisher effect, where S1 is the spot rate at the beginning ofthe period and S2 is the spot rate at the end of the period,and i represents the respective national interest rates.The International Fisher effect then states that the spotexchange rate should change in an amount equal to, but inthe opposite direction of the difference in interest ratesbetween two countries.

(2)

(3)

Exhibit 2: The Four International Parity Relationships

Source: Sercu and Uppal (1995)

ForwardPremium

InterestDifferentia

l

InflationDifferentia

l

Rate of changeof spot rate

Fisher Open Relationship

Unbiased Expectations Hypothesis

Interest Rate Parity

Purchasing Power Parity

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In the above diagram Sercu and Uppal (1995) link threeformulas to imply the Fisher open relationship (or theInternational Fisher Effect). The interest rate parity2

relates to the forward premium to the interest differential.Purchasing power parity links the expected exchange ratechange to the inflation differential. As shown above, theInternational Fisher effect links the interest rates toinflation. Sercu and Uppal (1995) also discuss the unbiasedexpectations hypothesis that links the forward premium tothe expected change in the spot rate.

Unbiased Expectations HypothesisThe unbiased expectations hypothesis is the theory thatforward exchange rates are unbiased predictors of futurespot rates. This hypothesis assumes that there is nouncertainty about inflation. This leads to what is commonlycalled the Siegel Paradox. The Siegel Paradox is theobservation that if two investors from different countrieshave the same expectation of the probable distribution offuture exchange rates, the expected returns of the twocurrencies will not actually offset one another. Theunbiased expectations hypothesis also assumes that investorsare risk neutral and that exchange rate can be ignored forthe determination of the future spot rate. (Sercu-Uppal,1995)

BALANCE OF PAYMENTS AND THE ASSET MARKET

There are two models to calculate exchange rates: thebalance of payments approach and the asset approach. In thebalance of payments (BOP) approach the domestic price of aforeign currency is determined by the intersection of themarket demand and supply curves for that foreign currency.The asset approach is based on the idea that exchange ratesare based on relative real interest rates and expectationsfor economic growth and profitability. (Eiteman et al,2001)

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Balance of Payments (Flow Approach)According to Solnik (2000) the balance of payments approachwas the first approach for economic modeling of the exchangerate. The balance of payments approach tracks all of thefinancial flows across a country’s borders during a givenperiod. All financial transactions are treated as a creditand the final balance must be zero. Types of internationaltransactions include: international trade, payment forservice, income received, foreign direct investment,portfolio investments, short- and long-term capital flows,and the sale of currency reserves by the central bank.

Figure 1: Balance of Payments ExampleBOP = current account + capital account + official reserveaccount = 0

The current account includes the trade balance, balance ofservices, net income received, and unrequited transfers. Acurrent account deficit (surplus) tends to be correlatedwith the depreciation (appreciation) of the exchange rate.The capital account includes: direct investment, portfolioinvestment, other capital flows, and net errors andomissions. A capital account surplus (deficit) iscorrelated to the amount foreigners are willing to lend(borrow). The third part of the equation, the officialreserve account, includes the net changes in thegovernment’s international reserves. The BOP approach isalso not as accurate for short-term predictions.

Asset Approach (Stock Approach)The asset approach is based on the ideas that markets areefficient and that exchange rates are assets traded in anefficient market. The asset approach predicts that the spotrate behaves like any other asset--the value of the spotrate changes whenever relevant information is released.Therefore, prices are determined based on expectations aboutthe future. This approach focuses on the relationshipbetween the capital account and exchange rates.

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FORECASTING

“Forecasting transforms chaos into error”-Elliott Smith, Boston College

Exchange rate forecasting plays a fundamental role in manyaspects of international finance, such as the evaluation offoreign borrowing or investment opportunities, forecasts offuture spot exchange rates, short-term hedging, operatingand strategic decisions, and competitive analysis. (Levich,2001) Exchange rate forecasting involves the study ofrelative political, social, and economic conditions ofrelevant countries. There are two basic approaches toforecasting exchange rates: economic analysis and technicalanalysis. Economic analysis forecasts the present andfuture “fair values” of foreign exchange rates, based on thefundamentals of the relevant countries. Technical analysisuses quantitative models to estimate short-term fluctuationsin exchange rates. Technical analysis is based solely onprice information. While there is considerable disagreementon both the accuracy and appropriateness of forecasting, itremains a fundamental aspect of International Finance.Levich (2001) points out the difference between accurate anduseful forecasts. Accurate forecasts have small errorterms. Useful forecasts help make decisions that lead toprofitable speculative positions and correct hedgingdecisions.

ChallengesDue to the competitive and dynamic nature of the currencymarket, both consumers and producers of exchange rateforecasts face special problems. For example, choosing amethod has implications on the forecast. Additionally,there are numerous providers of analysis, and subsequentdecisions on how and where to implement analysis will have

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large implications on the outcome of the analysis. Theforecast horizon is also important in any analysis.Forecast horizons can range from minutes to decades.(Levich, 2001) Success depends on the economicrelationships that will persist in the future, andstructural changes in the international economy willcontinue to represent one of the biggest challenges toforecasters. (Levich, 2001)

Efficient Market HypothesisMarket efficiency represents a joint hypothesis regardingthe equilibrium of prices (or returns) in the market and theability of markets to set actual prices. When markets areefficient then market participants cannot earn abnormalreturns. The efficient market hypothesis (EMH) (Fama, 1970)states that a market cannot be outperformed because allavailable information is already built into all stockprices. In other words, no arbitrage opportunities shouldexist in an efficient market. (Wadhwani, 1999) Empiricalevidence supports market efficiency when transaction costsand other factors are taken into account. (Levich, 2001)This has been restated in terms of three degrees ofefficiency. The weak form of efficiency states the currentprices reflect all historic information. The semi-strong formof efficiency states that current prices reflect allpublicly available information. Finally, the strong form ofefficiency states that the current price of an assetreflects all available information including proprietary andinsider information.

The efficient market hypothesis is commonly tested underthree methods: tests of return predictability, eventstudies, and tests for private information. (Fama, 1991)Tests for return predictability are studies that examinewhether returns can be predicted by historic prices orhistoric information on fundamental variables. Eventstudies are studies that examine how prices respond topublic announcements. Finally, tests for private

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information indicate studies that examine whether specificinvestors have information that is not in market prices.

Policy ImplicationsWhen policy makers set interest rates, they can beinfluenced by their expectations for future interest rates.(Wadhwani, 1999) Public policy makers are interested in theefficiency of foreign exchange markets, because efficientmarkets mean that the level of exchange rates and volatilityis (on average) a fair reflection of the underlying economicfundamentals. Therefore, in an efficient market the leveland volatility of exchange rates are due to fundamentalfactors rather than a misreading of these factors by privateinvestors. (Levich, 2001) Sources of market inefficienciesare uncertain--they can reflect speculation, insidertrading, corruption, or poor decisions from central banksand governments. But what is certain is that they createchallenges for decision makers.

Employment ImplicationsForecasts of exchange rates are not straightforward. Manyprofessional economists earn their livings based on thebelief that exchange rates evolve with detectable trends.Grossman (1995) makes this point, markets cannot beperfectly efficient when information is costly; otherwisethere would be no incentive to devote significant resourcesto collect information. Grossman (1995) adds that forreasons unrelated to future expected payoffs, prices move by“noise” created by uninformed investors, allowing informedinvestors to earn a return for their data gathering efforts.(Wadhwani, 1999)

Economic modeling is used in currency forecasting, andprofessional economists judge a forecast by its ability toearn abnormal returns. Professionals also use technicalanalysis to predict exchange rates. Structural changes inthe international economy represent one of the biggestchallenges for professional forecasters. (Levich, 2001)Because there are several decisions to make that require

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insight not currently available by computer analysis,forecasters continue to be employed. Some of this insightis based on four relationships. (Sercu-Uppal, 1995) First,exchange rates should never be considered in isolation. Theinflation differential is also important. Second, interestrates would never be compared in isolation. The spot rateand associated risk are important factors. Third, riskneeds to be considered when calculating the expected futurevalue. Finally, the forward rate has not proven to be agood predictor of future spot rates.

CURRENCY PUZZLES

There are several puzzles in exchange rate forecasting.Solnik (2000) lists some of the common currency puzzles.The first is the forward premium puzzle, which states that aregression analysis between the realized exchange ratemovement and the forward premium (or discount) reveals thatthe slope coefficient (β) is significantly smaller than 1,and sometimes negative. This finding implies that asuccessful trading strategy would be to bet against theforward exchange rate, in other words, expected exchangerates vary over time in a somewhat predictable manner as afunction of the interest rate differential. A second commonpuzzle is that exchange rates follow trends.

Another puzzle is that the implied difference for theappropriate level of the interest rate between the exchangerate conventions is substantial and that sometimes exchangerates move without any associated move in the interestdifferential. (Wadhwani, 1999) Wadhwani (1999) looks atthis puzzle in the context of two classes of investors.Those that invest in information and make a decision on thefuture of interest rates and those that transact incurrencies as a normal course of business without estimatingfuture changes. An example of the second type of investoris someone who makes “carry trades” where the investorborrows in the low interest rate country and lends in thehigh interest rate country. These different sets of

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investors trade for different reasons making it difficult toexamine strategies. Wadhwani (1995) concludes that it is“hardly surprising that we do not always agree about thebest way to forecast exchange rates.” A final currencypuzzle is that financial market volatility changes over timein a somewhat predictable fashion, and researchers havefound evidence of GARCH effects.

ITMEERThe Intermediate-term model-based equilibrium exchange ratemodel (ITMEER) was created as a modified uncovered interestrate parity model. The ITMEER model suggests that exchangerates move to reflect interest rate differentials and anadditional risk premium. The risk premium introduced in themodel is influenced by fundamental variables such as thecurrent account, unemployment rates, net foreign assets,relative prices, and yield differentials on financialassets. The model for ITMEER is shown below. The first twoterms are the estimated deviations from the equilibriumexchange rate, and Z is a set of variables that helpspredict the returns on other assets. The variables CAD<UNED, NFAD, DY, EQR, and PI are the differentials of currentaccount over GDP, unemployment rate, net foreign assets,lagged dividend yield, lagged equity return, and pastinflation. RWPCP is the relative productivity and YS is thelagged yield spreads.

(4)

The model has three components, the interest ratedifferential, the deviation from equilibrium, and therelative returns from the various assets.

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ARCH/GARCH ModelsThe ARCH/GARCH models have become standard tools forquestions about volatility. The assumption ofhomoskedasticity, that the squared expected values of allerror terms at any given point are equal, is the focus ofARCH/GARCH models. Heteroskedasticity is a problem wherethe variances of the error terms are not equal and thus areexpected to be larger for some ranges. ARCH/GARCH modelstreat heteroskedicity as a variance to be modeled. Thesimplest specification of the conditional variance is theARCH model, in which the conditional variance is simply theweighted average of past squared forecast errors. In thefollowing ARCH equation (p) represents past squared forecasterrors.

(5)

A generalization is to allow past conditional variance toenter the equation, this brings us to the Generalized ARCH(GARCH) equation. This generalization was introduced byBollerslev (1986). This model used the weighted average ofpast squared residuals, but has declining weights that nevergo to zero. (Engle, 2001) In the following GARCH equation(p) represents the number lags for the squared error termsand (q) represents the past variances.

(6)

The most widely used GARCH specification, “GARCH(1,1),”states that the best predictor of the variance in the nextperiod is the weighted average of the long-run averagevariance (the variance predictor for this period), and newinformation is captured by the most recent squared residual.The simplified GARCH (1,1) model is shown below.

(7)

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The ARCH-in-Mean model (ARCH-M) was proposed by Engle,Lilien, and Robins (1987). The ARCH-M model allows theconditional variance to be a determinant of the mean. TheTARCH model is a modification of ARCH and GARCH models. In aTARCH process the past time increment affects thecalculation in a different way depending on its sign. TARCHaccounts for the fact that traders react differently topositive and negative increments of a factor.

Additional currency puzzles are brought forth by Sergio andServén (2002). First, despite the presumed rigidity of thepeg underlying currency boards, currency premiums tend to beuniformly positive, suggesting that markets persistentlyanticipate a devaluation of the exchange rate. Sergio andServén (2002) ask whether currency boards are reallyyielding sufficient credibility as to minimize currencyrisk. Second, according to Sergio and Servén (2002)political and economic events seem to be important factorsin the behavior of currency premiums. Third, yield curvestend to slope upwards but flatten at the peak of a crisisleading to the implied possibility of arbitrageopportunities. Fourth, currency risk seems to differ acrossmarkets; and finally, domestic and foreign monetary andfinancial factors exert a systematic effect on the currencypremium and its structure.

EXCHANGE RATE REGIMES

In general a fixed exchange rate is preferred if monetarychanges affect the general level of prices. Examples offixed exchange rate regimes are pegged exchange rates andcrawling pegs. A pegged exchange rate is where the countrysets the value of its national currency according to thevalue of a foreign currency like the U.S. dollar or theFrench franc, or to a basket of currencies. Central banksintervene to keep the rate between narrow bands through

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international reserves. A pegged exchange rate may helpestablish the credibility of a program to reduce inflation.As the expectations of inflation are reduced through theknowledge that government policy must be subordinated to theneeds of maintaining the peg, the threat of chronicinflation is reduced. For example, the government cannotincrease borrowing while trying to maintain a peggedcurrency. With crawling pegs the country sets its exchangerate according to a criterion such as the relative change ininflation. Countries with higher inflation rates than theirtrading partners often depreciate their currencies toprevent loss of competitiveness. (Caramazza and Aziz, 1998)A pegged exchange rate is not sustainable in the long run.(Levich, 2001) A floating exchange rate system is where theexchange rate is free to adjust to respond to changes inrelative macroeconomic systems. Floating exchange ratesreflect the speculative dynamics of the market. (Levich,2001)

Economic shocks such as a steep rise in internationalinterest rates, a slowdown of growth in the industrialworld, and the debt crisis often require currencydepreciations and the adoption of more flexible exchangerate regimes. The increased capital mobility and waves ofcapital inflows and outflows have heightened the potentialfor shocks and the pressure for flexibility. (Caramazza andAziz, 1998) In general a floating exchange rate ispreferred if real changes such as technology changes orshifts in consumer preferences affect the relative prices ofdomestic goods. Examples of floating exchange rate regimesare managed floating or independently floating. A flexibleexchange rate enables governments to allow inflation to rise(and effectively increase tax revenue). Many developingcountries have thin financial markets where a few largetransactions can cause extreme volatility.

CURRENCY CRISES

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According to Solnik (2000) most currency crises have thefollowing pattern. First, the country runs a growing currentaccount deficit. Thus, the currency is regarded asovervalued by PPP standards. In instances where foreignerswere investing in a “booming” economy and lending to localfirms at attractive interest rates this capital accountsurplus is covered up by the current account deficit.However, once prospects for economic growth weaken anduncertainty builds, these foreign investors begin to exitthe market. As investors exit, the current account deficitis revealed, and governments are forced to raise interestrates to attract capital. These high interest rates slowthe economy and hurt economic prospects furthering the needfor capital control measures. At this instance the IMFoften steps in to provide additional reserves; and sincemarkets begin to become highly speculative the country isforced to devalue its currency or let the exchange ratefloat. This process can create a vicious cycle wherecurrency depreciation leads to increased inflation whichleads to further depreciation of the currency.

CONTAGION

Contagion is a significant increase in cross-market linkagesafter a shock to an individual country (or a group ofcountries). (Forbes and Rigobon, 2001) There are two mainchannels of contagion--through trade links and through thefinancial system. (Economist, 2001) Forbes and Rigobon(2001) go on to specify that “shift-contagion” refers to asignificant increase in cross-market linkages after a shock,such as the correlation in asset returns, the probability ofa speculative attack, or the transmission of shocks orvolatility.

The theoretical literature on contagion can be divided intotwo groups: crisis-contingent and non-crisis-contingenttheories. Forbes and Rigobon (2001) define crisis-contingent theories as those that explain why transmissionmechanisms change during a crisis and, therefore, why cross-

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market linkages increase after a shock. Non-crisis-contingent theories are those that assume transmissionmechanisms are the same during a crisis as during morestable periods and, therefore, cross-market linkages do notincrease after a shock.

The first group of theories can be divided into threegroups: multiple equilibria, endogenous liquidity, andpolitical economy. Multiple equilibria is based on investorpsychology and occurs when a crisis in one countrycoordinates investors’ expectations for another economy.Endogenous liquidity causes portfolio re-composition when acrisis in one country reduces the liquidity of marketparticipants. Political contagion affects exchange rateregimes when the political pressure to maintain a fixedexchange rate is reduced by the actions of another marketparticipant.

The second group of theories can be divided into four broadchannels: trade, policy coordination, country reevaluation,and random aggregate shocks. Trade works throughdevaluation of currency or the reduction of exports ofcompeting products. Policy coordination occurs as onecountry responds to another country’s economic shock.Country reevaluation or “learning,” is the idea thatinvestors apply lessons learned after a shock to othercountries with similar macroeconomic policies. Randomaggregate shocks or “global shocks,” such as internationalinterest rates, international supply of capital or a declinein international demand affect the fundamentals of severalcountries.

The following is a typical example of an exogenous liquidityshock. Sets xt and yt are two stock market indices, zt is aliquidity shock, and εt and nt are idiosyncratic andindependent shocks. The model of an endogenous liquidityshock assumes that shocks are transmitted from country xt tocountry yt through the variable β, and that the liquidityshock has different effects on two countries, zt is

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independent of εt and nt. A liquidity shock would have anegative impact on both xt and yt.

(8)

On the other hand, an endogenous liquidity shock is a casewith two regimes. When the realization of xt is positive,the spread of shocks from xt to yt is β; but when therealization is negative, then the propagation of shocks is β+ αγ. This would continue to increase the variance of bothmarkets.

(9)

There are four different approaches to measure thetransmission of shocks and test for contagion: analysis ofcross-market correlation coefficients, GARCH frameworks, co-integration, and probit models. Analysis of cross-marketcorrelation coefficients test the correlation in returnsbetween two markets during stable periods and then test fora significant increase in the correlation coefficient afterthe shock. The GARCH (or ARCH) framework estimates thevariance-covariance transmission mechanism across countries.Co-integration tests for changes in the long-runrelationship between markets rather than short-run changesafter a shock. Probit models such as variance matrices usesimplifying assumptions and exogenous events to identify amodel and directly measure changes in the spread.

Suliman (2002) gives an example of a typical ARCH/GARCHmodel of international reserves where R is internationalreserves and X’s are variables that affect changes in theinternational reserves, εs are innovations to international

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reserve changes with zero mean and conditional variance σ2t,Yt-j are variables other than past squared innovations orlagged forecast variance that may explain internationalreserves’ volatility.

(10)

(11)

Some economists argue that it is impossible to definecontagion based on simple tests of changes in cross-marketrelationships. (Forbes and Rigobon, 2001) Several modelshave been created to predict which country is most likely toincur problems. (Economist, 2001) Foreign debt is the levelof debt and its growth rate. Debt that is 200% of exportsis typically a warning signal. High budget deficits andexcessive short-term borrowing is also concerning toinvestors. Other models include current-account deficitsthat continue to rise and exchange rates. (Economist, 2001)Caramazza and Aziz (1998) argue that misalignments andcurrency “crashes” are equally likely under pegged andflexible exchange rate regimes. This is based on thestatistics that half of the recent crashes occurred underfixed exchange rate regimes while the other half occurredunder floating exchange rate regimes; although, they admitthat this may reflect the fact that relatively fewdeveloping markets have truly floating exchange rates.

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REFERENCES

Bollerslev, Tim. (1986) “Generalized AutoregressiveConditional Heteroskedasticity.” Journal of Econometrics, April,31:3, pp. 307-327.

Caramazza, Francesco and Aziz, Jahangir, (1998), Fixed orFlexible: Getting the Exchange Rate Right in the 1990s.Economic Issues International Monetary Fund.

(2001) How the bug can spread, Economist, July 19.

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Eiteman, David K., Stonehill, Arthur I., and Moffett,Michael H. (2001) Multinational Business Finance 9th

edition, published by Addison-Wesley Longman, Inc.

Engle, Robert (2001) GARCH 101: The Use of ARCH/GARCH Modelsin Applied Econometrics, Journal of Economic Perspectives, Vol. 15,Numer 4, p. 157-168.

Engle, Robert, Lilien, David, and Robins, Russell, (1987)"Estimation of Time Varying Risk Premia in the TermStructure: the ARCH-M Model," Econometrica 55: 391-407

Fama, Eugene. (1970) "Efficient capital markets: A review oftheory and empirical work," Journal of Finance 25, 383-417.

Fama, Eugene (1991) "Efficient capital markets: II", Journalof Finance 46, 1575-1617.

Forbes, Kristin and Rigobon, Roberto, (2001) MeasuringContagion: Conceptual and Emperical Issues, Editor StijnClaessens International Financial Contagion, Kluwer AcademicPublishers p. 43-66.

Grossman, Stanford J (1995) “Dynamic Asset Allocation andthe Informational Efficiency of Markets,” Journal ofFinance, Vol L, No 3, July, pp 773-787.

Levich, Richard M. (2001) International Financial Markets,2nd edition, published by McGraw-Hill.

Markowitz, Harry (1952) “Portfolio Selection,” Journal ofFinance 7, No. 1 (March 1952), pp. 77-91

Rockefeller, Barbara, (2001), CNBC 27/7 Trading: Around theclock, around the world Published by John Wiley & Sons,Inc., Copyright CBNC

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Schmukler, Sergio L. and Servén, (2002) “Pricing CurrencyRisk: Facts and Puzzles from Currency Boards” NBER WorkingPaper

Sercu, Piet and Uppal, Raman, (1995) International FinancialMarkets and the Firm, published by SouthWestern.

Solnik, Bruno, (2000) International Investments 4th editionPublished by Addison-Wesley Copyright Addison Wesley Longman

Suliman, Osman, (2002) Contagion in Gulf Countries

Wadhwani, Sushil B., (1999) “Currency Puzzles” Speechdelivered at London School of Economics, September 16.

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