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DRAFT COPY-SAMPLE GRADUATE DISSERTATION-

Hedging Strategies: Mitigating Risk in Copper Futures

By

Name

Date

Program/Professor

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Abstract

This dissertation poses the question whether an effective hedging strategy can

be devised that accounts for both price volatility in copper futures within the China

market as well as the exchange rate fluctuations of the Yuan versus the U.S. dollar.

Very few working models exist to account for both price volatility and exchange rate

fluctuations vis--vis the Chinese Yuan and copper hedging strategies for China. The

need for such a strategy is critical because China is currently the worlds largest

consumer of copper commodities. Additionally, copper demand in China is increasing

9% annually and much of Chinas current economic expansion indirectly relies on a

stable, steady, and adequate supply of copper commodities obtained at reasonable

market rates. To meet these market demands, a more effective hedging strategy should

be developed that allows the country to avoid the typical peaks and valleys in both price

and delivery of copper commodities that accompany the market. Accordingly, a series of

three models are developed that account for both aspects of price volatility and

exchange rate fluctuations, and which are intended to have immediate applicability to

the market. Furthermore, since this research relies on a grounded theory approach, a

hypothesis will be generated that state that because the Chinese Yuan is very likely to

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shift to a full float regime sometime within the next 3 to 5 years, these models will need

to be adjusted accordingly.

Table of Contents

List of Figures 6

List of Tables 7

I. Introduction 8

Problem Statement 8

Purpose of Study 8

Importance of Study 9

Scope of Study 10

Rationale 10

Definition of Terms 11

Overview 14

II. Literature Review 17

Approach 17

Commodities Markets 19

China, Copper and the LME 23

Managing Risk in Copper Futures 25

China Economy & Currency Risks 29

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Modeling Strategies 36

Importance of the Financial Markets 41

Conclusion 48

III. Methodology 56

Approach 56

Data Gathering Method 57

Database of Study 58

Validity of Data 63

Originality & Limitations 64

Summary 65

IV. Presentation of Findings 67

V. Conclusions & Recommendations 75

Conclusions 75

Recommendations 81

References 85

Appendices 89

Appendix One 89

Appendix Two 91

Appendix Three 94

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List of Tables

Table 1: Historical Copper Prices 58

Table 2: Historical Exchange Rates 59

Table 3: Assumption Basis 60



Table 6: Garch 1 67

Table 7: Garch 2 69

Table 8: Garch 3 69

Table 9: Durbin-Watson 70

Table 10: Working Assumptions 70

Table 11: Model Efficiencies 71

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Hedging Strategies: Mitigating Risk in Copper Futures

I. Introduction

Problem Statement

The predominance of existing research related to hedging strategies relative to the

futures markets is typically concerned with agricultural, foreign exchange (forex), and

petroleum products. Little research exists in the area of risk mitigation in hedging

strategies for copper futures. Since China is an abundant copper importer such a risk

mitigation strategy related to hedging copper in the futures markets are vital in

preserving its overall economic integrity. Under normal market conditions, the spot and

futures prices are positively correlated, and the futures price should reflect the cash

price, interest rate, insurance, and the cost of storage for copper. But most analysts

ignore the exchange rates as a primary driver of price. Since those factors are also

related to the purchase of copper are fluctuations in the price on the open market itself

and the exchange rate fluctuations across markets. The hypothesis is that utilizing these

commodity price and exchange rate fluctuations vis--vis copper futures in the China

market, a cohesive strategy to mitigate risk can be developed to support the following

imperatives:

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and in particular those of copper (Bryson, 2006, p.1). As China is a major importer of

copper and related products, significant growth in the price of this commodity can exert

a negative impact on the overall economy by contributing to inflationary pressures. This

circumstance is aggravated by the external pressure on China to revalue its currency,

the Yuan, to bring it more in line with the international free market forex forces. As

China does allow its managed float currency to slowly increase in value this also has

the negative effect of increasing the relative cost of copper commodities. Developing an

effective strategy to manage these risks is paramount to maintaining a strong economic

profile over the rest of this decade and well into the next.

Scope of Study

This research limits itself to the copper commodities and copper futures market.

Some research is undertaken in the forex markets as well as economic policy that

determine monetary policy as it impacts forex rates. Such research is undertaken with

a view to establishing the appropriate background to support the forex hedging

strategies relative to the Yuan versus the US Dollar insofar as it relates to mitigating

copper futures risk. This study does not attempt to explicate a comprehensive

commodities trading strategic platform across the spectrum of commodities and markets

but only one relative to the copper futures market in China. This study also does not

attempt to generalize a foreign exchange strategy for the forex markets but only develop

a strategic approach for forex trading within China as it relates to a hedging strategy for

copper futures. Yet, considering the massive size of Chinas forex reserves, just under

$800b as of 2005, a comprehensive understanding of how this market affects copper

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futures and related hedging strategies is vital (Morrison, 2006, p.11). For example, any

move to lessen this amount could have a far-reaching impact on copper futures.

Rationale

The underlying rationale for this study is based on the informed assumption that

Chinas significant importation of copper commodities is only going to increase over

time. Based on this assumption, China must have a well-developed copper futures

hedging strategy in place considering the great number of external forces that can

impact this market, such as increased energy prices and their impact on transportation

costs, regional instability, such as North Korea or Taiwan, as well as supply and

sourcing issues. Finally, a well-developed risk mitigation strategy in the copper futures

market in China ensures that the government can adequately adjust for inflationary

pressures as they arise.

Definition of Terms

Hedging: this is a financial strategy that allows a party to manage, reduce, or predict

risk related to various financial and commodities markets. The basic hedge strategy is

to take an offsetting position in a security, financial or commodity, which may be an

option to buy or a short to sale position which provides some degree of compensation

should the primary position fail (Mikdashi, 2001, p.43).

Commodities: refers to the physical materials traded on open markets. These are

typically food products, grains, and metals; i.e. copper. These physical items are made

interchangeable on an open market with similar products which are then bought and

sold as futures contracts which are agreements to buy or sell at a given point in time.

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The economics of supply and demand are intricately involved within the commodities

futures market and risk management is the underlying rationale (Meyer, 2003, p.21).

Foreign Exchange Markets: foreign exchange markets (FX, Forex, or Currency

Markets) are markets that exist solely for the trading of one currency for another. This

trading market typically takes place between banks, central banks, speculators,

corporations, governments and other large institutional bodies that have a high degree

of foreign capital moving from one market to another and wish to either capitalize on

fluctuations or reduce losses by managing risk and across all forex markets more than

$1.7trillion exchanges hands daily(Mikdashi, 2001, p.78)

Backwardation: this is a market condition where a futures price, in this case on copper,

is lower in the mid to long-term delivery months than in the more near term period

(Mikdashi, 2001, p.88)

Contango: contango is a market condition whereby the distant delivery prices for

futures commodities, in this case copper, exceeds those of the spot prices. Contango

results from costs associated with storing and/or insuring the supporting commodity and

contango is the opposite of backwardation (Mikdashi, 2001, p.88 )

Long: implies a position in financial security instrument, a contract option, or a

commodity position; i.e. ownership thereof (Mikdashi, 2001, p.37)

Short: to short a financial instrument such as a stock, other security, or a commodities

contract implies that an agent is going to borrow such financial instrument and sell it

only to be repurchased later with the idea that the repurchase price will be less than the

initial selling price (Meyer, 2003, p.27)

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Futures Contract: a futures contract refers to an agreement between parties a specific

action will be taken or refrained from being taken relative to an option to buy or sell;

especially in commodities (Mikdashi, 2001, p.78)

London Metal Exchange (LME): the LME is the largest futures exchange market

specializing in base metals as well as other metals. Among the various activities the

LME facilitates are futures contracts with daily to three month expiration dates, longer

term contract options, and an assortment of hedging, pricing, and storage services

(What, 2006)

Basis Risk: basis is the difference between a given cash price for a commodity and a

futures price for the same commodity and this amount is used to quantify the associated

risk of the commodity (Meyer, 2003, p.29)

Spot Market: a spot market is a commodities market in which commodities are sold or

purchased for cash or cash equivalents for immediate delivery (Mikdashi, 2001, p.80)

Floating Exchange Rates: this type of exchange rate regime is controlled primarily

through market forces within the foreign exchange markets themselves. The economic

theory of supply and demand determines the value of one currency in relation to

another and thus currencies managed under a floating exchange rate regime are

subject to fluctuate freely (Lee, 2002, p.32)

Currency Peg: a currency peg is nothing more than the value of one currency being

specifically tied to the value of another.

Managed Float: this is another currency regime in which a currency is allowed to

fluctuate freely in the forex markets but central banks manifest some degree of control

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over the value of the currency buy actively buying or selling currencies on the market

themselves (Lee, 2002, p.302)

Purchasing Power Parity (PPP): an economic theory related to exchange rates and

the balance between common currencies. PPP implies that equilibrium should exist

between two countries currencies and the prices of a basket of goods and services

within their respective economies (De Brouwer, 2002, p.232)

Overview

Based on the knowledge that many economic factors affect the copper futures

markets in China, including international forces, a broad background to the copper

futures market in China is established first with the understanding that within the global

economy it is impossible to isolate a single commodities market. Thus, even such

macroeconomic metrics, such as purchasing power parity (PPP), indirectly affect policy

decisions, both internal and external to the China market, that directly impact how the

markets eventually determine market prices of commodities and certainly of copper

commodities. Chinas market is so dynamic and evolving that the slightest interruption

of any of its requisite raw materials, especially one such as copper that is so critical to

so many industries, could derail increasingly distance components of its economy.

Where China currently attempts to hedge its copper futures to some degree it still has

yet to develop a sound approach to hedging within the context of its own currency

policies. China could hardly be expected to develop its own sound hedging strategies at

the same time it is attempting a managed float of its currency and trying to control its

export market. In fact, some of these imperatives are counter-productive to the other.

Thus, it is just as imperative that the financial markets within the economy develop their

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normative hedging strategies for the country that will account for its other economic

factors that are currently in such a state of flux both because of the expanding economic

activity and international purview.

II. Literature Review

Approach

This literature review seeks to establish a broad perspective of the commodities

markets and some of the techniques used in hedging strategies within them.

Additionally, because the hedging strategy being examined is specifically addressing

certain variables within the China market, additional research relative to the

commodities trading markets in China, the Chinese economy, as well as China

economic policy related to the Yuan exchange rate is also examined. Finally, some of

the analytical models used to examine and manage risk are examined in the context in

which they have appeared in existing research (see appendices two & three) and in how

they relate to the current research hypothesis being examined in this study.

Chinas economic expansion has been an amazing event over the last 5 years

although it has been instituting economic changes for over 20 years. Real gross

domestic product (GDP) growth has been 10% for the last 3 years and it is expected to

meet this growth rate for the current year (Bryson, 2006, p.1). It is inevitable that such

phenomenal economic growth results in just as equally phenomenal consumption of

natural resources and raw materials. China has become the manufacturer for the world

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in many respects and this degree of manufacturing capacity coupled with its own

internal economic demands has seen the need for raw material, and specifically copper,

reach almost unsustainable levels (Big, 2005). In addition, Chinas ever evolving

currency policy has been partially decoupled from its peg to the US dollar: On July 21,

2005, the Chinese government announcedthat Chinas currencywould no longer be

pegged to the dollar but instead would be a managed float regimeto a basket of

currencies (including the dollar)(Morrison, 2006, p.4). Thus, while partially removed

from its dependence on the dollar, the Yuan still mirrors the US dollar in all but minor

differences. The managed float approach is an effective strategy to appease free

market forces that continually clamour for full devaluation as well as appease Chinese

hardliners in the government who do not want to see China make any concessions

whatsoever to the outside world. However, this last viewpoint is rapidly becoming

marginalized because China, in all but its currency controls, has effectively joined with

the international community as evidenced by its World Trade Organization (WTO)

membership and its 30 year policy of kai fong or opening up (Brown, 2005). The

recent move to partially free its currency leads many researchers to suppose that China

does eventually intend to fully float its currency. However, it will do so completely on its

own terms rather than through the dictates of any other national interest, such as U.S.

intervention and request.

Yet, this managed float regime is expected to herald in a gradual release from its

basket of currencies reference into a more market derived pricing structure where

supply and demand will determine the relative exchange rates within certain

parameters. The importance of this economic policy related to the Yuan exchange rate

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for determining hedging strategies for copper futures in China cannot be understated

because exchange rates are primary drivers of the price of the commodity. (Peter

Hollands, 2003, p.1) Any sudden shifts in currency valuations would result in real losses

for traders and, currently, this is a risk that cannot be managed with existing hedging

strategies or models. Additionally, because so much of Chinas current economic

growth depends upon its ready access to raw materials, specifically copper, and

because its exchange rate is so intricately related to its foreign policies and trade

relations, it is simply not possible to overvalue the efficacy and worth that an effective

hedging strategy in copper futures would have on Chinas economic, political, and

foreign policy initiatives.

The Commodities Markets

Commodities markets are comprised of various agricultural products, metals and

related materials, as well as energy related products in which all of these items are

traded either physically or as derivative financial devices. These derivative financial

instruments may be futures contracts as well as options and are utilized to mitigate or

capitalize on the risk associated with pricing fluctuations. These fluctuations have been

used by researchers in the examination of financial markets, primarily stock markets, to

forecast price related to risk premiums: using the cross-section of returns allows us

to create a useful hedgingportfolio for aggregate volatility risk(Ang, Hodrick, Xing &

Zhang, 2003, p.3). These researchers designed a stochastic model that attempts to

assert control over seemingly random innovations:

)()( rfmt

mt

ait

rfmt

mit

rfit +=

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mt

b

it

p

vipp

vit

andmt

itmim

it

1212

=

=

(Ang, Hodrick, Xing & Zhang, 2003, p.7)

The result is a model that appears to define the relationship between a stocks risk-

exposure to market innovations as it relates to volatility. Thus, at least for stocks and

stock markets, an effective model can be constructed to account for market

interventions or variables. Typically, commodities and commodities markets are active

around the clock in all major regions of the globe and so their exposure to market

volatility is more omnipresent than in markets that shut down the majority of the day.

Speculative traders are often responsible for market fluctuations and have become an

added dimension of risk in the market and contribute to the necessity to devise methods

to account for volatility.

The pricing within commodities and commodity markets indirectly affects even

average consumers since the prices of most consumer products are also derived in part

from the cost of the raw materials required to produce them. These cost dimensions can

be considered to be raw material sourcing, transportation, as well as a risk premium

(Meyer, 2003). Commodities markets consist of two aspects: the buy side and the sell

side. The buy side of commodities markets is made up of market speculators who have

no real interest in a given commodity other than turning it over, producers who require

the raw material for vertical travel up the supply chain, and 3 rd party distributors

(Mikdashi, 2001). The sell side of most commodities markets consists of the same 3rd

party distributors who match buyers with sellers, brokers who are in essence market

speculators, and various market traders functioning in some aspect of these market

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related activities. Clearly, much of the activity that takes place on the commodities

markets in any given time period can have very little to do with actual utilization of the

raw material in question. Producers and manufacturers could simply source copper on

the spot market at cost and ignore risk mitigation and future supply strategies

altogether. However, long-term business strategies as well as sound economic policy

require active hedging in order to maintain steady production numbers and to reduce

the spectre of inflationary pressures due to wide price fluctuation risk exposure on the

spot market.

Established commodities markets are vital to stable economic activity because of

the services they perform relative to copper futures. Market researchers and industry

professionals must have access to pricing data in order to develop comprehensive

supply strategies based on supply and demand. Researchers examine data from a

variety of commodities markets and futures exchanges where historical price

movements and international events are quick to impact futures contracts (Meyer,

2003). Commodities markets function as clearing houses for this type of data and

information as well as for the commodities themselves. Finally, commodities markets

employ many of the same trading strategies as the other traditional financial markets

such as the stock, bond, and currency markets where mapping risk structures is

paramount for successful mediation of the market (see appendix four). It should be

noted that many of these risk maps and risk models developed for the stock and

currency markets have applicability in the commodities futures markets as well and they

have been partially relied to build the models in this present research.

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China , Copper and the LME

Chinas expansion has been the engine driving the global economy over the last

few years and not simply its own economy. This has traditionally been a role filled by

the US but since Chinas growth curve is steeper, its rate of expansion can be

maintained higher for a longer period of time than the other leading global economies.

Brown describes the Chinese economy in these terms:

Chinas economy has been growing at an annual breakneck pace of 9.5%. If it

now were to grow at eight percent per year...income per person in 2031 for

Chinas projected population of 1,450,000,000 would reach $38,000. (At a more

conservative six percent annual growth rate, the economy would double every 12

years...(2005, para.2)

Chinas determination to maintain a consistently high growth rate is seen as a primary

motivating factor in its reticence to float its currency. While China has been wary of

allowing its economy to overheat, its recent partial float of its currency is largely viewed

as nothing more than a minor appeasement since its partial float is anchored by a

basket of foreign currencies that is not published. This type of Byzantine currency policy

is seen by the current administration in the US as a symptom of the broad movement

across the spectrum of Chinese politics toward centralized, authoritarian control of free-

market processes: The US is concerned by an anti-reform backlash in China. This has

capped foreign investment in banks and brokeragesand emboldened Xinhua, the

official news agency, to threaten new controls over financial news(McGregor & Guha

par.5). China and the US, if not the rest of the developed world are at a crossroads

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regarding its currency exchange policies since, in many respects, China cannot

reasonably be considered a developing nation for very much longer.

While copper futures are traded worldwide across many markets it is largely the

London Metal Exchange (LME) which dominates the metal commodities market and

particularly the copper market. The LME handles approximately 90% of the world trades

in copper and copper ranks 3rd behind only iron and aluminium in total volume traded

(What, 2006). Chinas exposure to commodities trading began in 1992 with the

establishment of the Shenzhen Non-Ferrous Metal Exchange and later with the

Shanghai Metal Exchange which both take their lead from the LME (Lien & Li, 2006).

These and other researchers all confirm that although China does have a vibrant

commodities trading environment, hedging strategies are little understood in the market.

Additionally, copper futures are more susceptible than most other metal futures to

political instability since many of the top copper producing countries, Chile, Congo and

Zambia, are politically unstable markets to one degree or another (Meyer, 2003, p.118).

Managing Risk in Copper Futures

Managing risk in the copper futures market, whether in China, the LME or other

commodities markets, relies on the same fundamental tools. Hedging is the most

common form of risk management within the futures market and requires some

fundamental assumptions to be made about the market relative to the commodity being

managed. To appropriately hedge a commodity one must determine whether a

long/short futures hedge is desired based on when a commodity will be bought/sold as

an asset in the future and thus a locked in price is the objective (Chiu, Wu, Chen &

Cheng, 2005). This basic concept requires market traders, whether speculators,

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producers or otherwise, to establish the cost basis versus the purpose of the action.

That is, traders regardless of market rationale who take a short position want to monitor

the payoff amount of the futures contract versus a terminal spot price where the position

taken plus the hedge results in a flat line or less outcome which, in a market that

typically sees 20 to 40% price fluctuations annually, involves some degree of volatility

(Cortazar, Schwartz & Riera, 1999, p.2). Conversely, long hedges in the copper

commodities market often take the form of agreeing to purchase copper in set amounts

up to or at a point in the future at a given price. Many producers, speculators and others

often take long positions in copper because while the spot price for the commodity

might be lower at the agreed upon purchase/delivery date (and it might be higher), there

are not storage or interest costs associated with the purchase and all expenses can be

accounted for (Howard & DAntonio, 2005). The primary disadvantage to long positions

on copper is that there is typically no raw material on hand but given that most

producers or manufacturers plan production well in advance, this is not usually a factor.

Since the LME allows futures to be traded as well as other commodity related

options, it also trades based on an index fund comprised on the six primary metals that

it specializes in (LME, 2006). One method that many market strategies have learned to

gauge the commodities market is through its negative correlation that it has with the

securities markets; that is, when one goes down, the other goes up. One common

conception of commodities that tends to keep many uninitiated traders out of the market

is the fear of actually ending up in possession of the underlying commodity that the

futures are based on. In fact, this is a real risk although it happens rarely. Futures

contracts all have a specified delivery date, known as the prompt date, and all open

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positions in the commodity must be closed at least two days prior to the given prompt

date or the actual commodity will be delivered (LME, 2006). Options are an extension of

futures contracts and are an important method to further diversifying the risk exposure

in the market. Options accomplish the following objectives (Osano & Tachibanaki, 2001,

pp.43-9):

Potential losses are limited to the premium paid for the option

Options ensure that a price floor is attained but do not limit the buyer from

executing on positive price movements; i.e. speculation

Options allow the hedging part to enact a staged hedging strategy of various cost

levels and degrees of risk protection

Options provide industries as well as investors to develop comprehensive

hedging strategies based on market research regarding volatility of future copper

prices

Options can be used alone or in tandem with other futures contracts as a method

of cross-hedging but with infinite more risk profiles, time horizons, and price

considerations

Companies usually hedge to manage risk. Several strategic arguments are made

for this risk management solution: 1) hedging allows companies to focus on their

primary line of business, 3) hedging allows known quantities of raw material to be

available and thus production and delivery can be accurately forecast based on supply,

and 3) normally hedging allows competitors to ignore market variables such as interest

rates (Howard & DAntonio, 2005). Yet, this last is a characteristic of copper hedging

strategies in the China market that must be accounted for because the demand for

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copper is constantly increasing and the Yuan is under extreme pressure to revalue

which does effect real prices paid on the markets; both spot and commodities. Foreign

exchange variables are an important part of determining the basis of the commodity in

order to accurately hedge on the futures market. The basis is normally conceptualized

as the extent that a given spot price of a commodity, copper, exceeds the futures price

of the contract that is employed in hedging:

F

contractofpricefutures

S

itycomofpricespotbbasis =

mod)(

Or simply, basis is the difference between spot and the futures contract. The factors

involved in determining hedge risk relative to basis points are:

it (Time & i = 1 or i = 2)

iF (Futures price at i)

iS (Spot price at i)

*iS (Commodity price supporting the futures contract)

ib (Basis at i)

These factors are figured in the following manner to determine buy/sell strategies for

commodities where:

( ) 2112

2

2bF

FFgainfuturesS

S +=

=

This scenario results in a short position to sell at time of t1. While these basic hedging

strategies are adequate for most organizations, they are inadequate to fully compensate

for market forces and external variables such as exchange rates market wide. Hence,

the need for a comprehensive modelling strategy that mitigates market risk for copper

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futures in the China market where so much of its economic growth is indirectly

dependent upon not only a steady access to copper commodities but optimized pricing

structures that allow for forecasting and intervention. Additionally, there is also room for

derivatives of copper futures provided the market can be stabilized through better

regulatory and oversight structures (see appendix one). Without the proper regulatory

and oversight structures, derivatives tend to result in capital flight issues that can be

devastating to any economy, regardless of economic health and stability predating the

capital flight. Sudden movement of capital would be certain to destabilize all Chinese

markets including commodities markets and this would dramatically affect negative

price movement because of the exchange rate risks involved.

China Economic & Currency Risks

One of the primary macroeconomic concerns in establishing a stable currency

relative to a commodities futures market and in unifying fiscal policy with all financial

markets is the stabilization of the Yuan exchange rates which, up till recently, was a

simple matter since the Yuan was pegged to the dollar. But now, with the Yuan on a

manager float tied to a basket of currencies, the exchange rate now becomes a matter

of volatility in the futures market as well as a potential disruptive force within the broader

economic market. Several researchers point out that exchange rates are a disruptive

force in financial markets as well as destabilizing forces in home markets where

fluctuations cause the value of debt to suddenly shift up or down and interrupt nominal

yield flows (Pomfret, 2005). Clearly establishing stable exchange rates is one of the

primary concerns of Chinas central bank and one that it has been fairly successful at

doing in the past.

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For many countries whose economies do not need to experience significant

growth to measure real gains over the previous decade, the exchange rate of a given

country can have an indelible impact on the character of this expansion. Analysts have

observed that for many countries the 1990s ended with no real growth in disposable

incomes over the entire decade (Globalization, 2005). This implies that the cost of living

and inflation kept pace with income levels, or worse, lost ground on an international

basis. In fact, some researchers have illustrated that removing such countries as China

and India from the global gross domestic product (GDP) and global GDP has only grew

by a few percentage points (Globalization with, 2005). Countries whose currencies

suffered during this period and that have still not recovered completely are set to

continue such lackluster economic performance unless they can appreciate their

currencies relative to their larger trading partners and export markets.

The reality of slowly expanding economies has led many countries to embrace

the global economy and to expand trade relationships as a method to attempt to

stimulate economic growth (Chinn & Meredith, 2004). Yet, how a countrys exchange

rate fluctuates vis--vis its larger trading partners has a great impact on its current

account deficit or surplus. Foreign exchange markets are a function of degrees of

scarcity and degrees of demand that establish a given currencys valuation (Akbar,

2006). Yet, the relationships between a countrys foreign exchange strategies and its

current accounts and trade policies are all inter-related. Thus there is a newfound

willingness to expand current account portfolios which directly results in mutual benefits

that have a significant impact on tax revenues, employment figures, export values as

well as commodities on international and localized markets. Furthermore, this emphasis

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on strengthening export economies seems to be combined with a strategy on the part of

many central banks to control the value of the currency in a fashion that exerts a

positive impact on the respective economies of a given country (Trades 2004). While

these two economic strategies might appear unrelated, export expansion and a

strategic control of the primary currency indicate a unified approach to expanding

overall GDP and is one reason why controlling or managing the risk associated with

fluctuating copper prices is so important for Chinas economic health. Relevant to this

current research is the fact that the result of these strategies is a stronger national

currency which stabilizes the exchange rate risk factor for the Yuan against the dollar,

thereby controlling some of the risk associated with exchange rate fluctuations.

Under normal circumstances global inflationary pressures might be considered a

negative development for most economies; particularly those with a significant global

aspect. Inflation was expected to increase gradually through 2005 and in fact it did

albeit not as drastically as might have been predicted (Global, 2004). However, for

many countries, including China, these inflationary pressures resulted in unexpected

economic gains because of increasing emphasis on developing energy or petroleum

export markets that have experienced extreme valuation. Normally, a stronger

exchange rate would be a negative for a given countrys export markets but copper and

other commodities functions independent other export products (Chinn & Meredith,

2004). Normally, a stronger national currency results in a growth in the overall current

account or an expansion of the overall trade deficit. This development is what tempts

some countries to manipulate their currencies in an attempt to continue their export

market expansion on the back of an under-valued currency (Chinn & Meredith, 2004).

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stable and this is good for both domestic and the world economy (Perspectives, 2005,

para.12), it first began to give signals that it would accede to the pressure to float, full or

partial, its currency:

China is quietly building the infrastructure and gaining the experience it needs

before it can safely float its currency and open its capital account. This week

reports from the official press said that seven international banks would join two

domestic ones as market-makers for foreign-exchange trading. HSBC, Citigroup,

Deutsche Bank, ABN Amro, ING, Royal Bank of Scotland and Bank of Montreal

have been selected to work alongside Bank of China and the smaller CITIC

Industrial Bank. (Soft, 2005, para.2)

Such behind the scenes moves are an indication China is willing, from within its rhetoric

at any rate, to passively cooperate in working within the global infra-structure of the

worlds economic paradigm which is so dependent on a balanced exchange rate

system. This unwillingness to initially revalue or float its currency was slowly causing its

major trading partners to question the overall benefit of allowing China to: (1) join the

WTO and (2) continue to receive such huge amounts of FDI. Primarily, voices in the

West are becoming somewhat more inflammatory: It is estimated that Chinas currency

may be undervalued by as much as 20 percentChinese manufacturers garner an

unfair advantage of 20 percent in competition with America and other free-trade nations

(Debus, 2005, para.6). This 20 percent undervalue is substantial and results in a 20

percent advantage for its export trade market and a 20 percent disadvantage for most of

the Wests, and especially the United States, import trade market. Although China did

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revalue its Yuan and put it on a partial float system whereby it is now pegged to a

basket of similar currencies, China has not revealed the currencies it is using and the

overall revaluation vis--vis the dollar has been minimal. Clearly, exchange rates

function at the apex of a given countrys economic policy and dictate the overall health

or dysfunction of an economy.

Modelling Strategies

Modelling volatility within the commodities markets, especially as it relates to

copper, has not received a great deal of academic attention. Siddique and Harvey

undertook a study of autoregressive conditional skewness which utilized GARCH

techniques wherein they concluded that autoregressive models might be successful at

modelling time-series variations relative to asset pricing such as stock returns but not

necessarily for futures and related hedging strategies (1999, p.17). Their use and

application of GARCH (1,1,1)-M models successfully modelled skewness in a given

financial market and this has some application in the futures market both long and short

strategies exist as well.

Garch (Generalized Autoregressive Conditional Heteroscedasticity): GARCH is a

modelling technique that allows researchers to predict for variances. According to the

GARCH Toolbox, GARCH, is a mechanism that includes past variances in the

explanation of future variances(2006, p.15). GARCH is a time-series modelling device

to measure heteroscedacity which is time related variance and in relation to copper

futures this model is effective at predicting volatility in the market. Volatility in the futures

market is always associated with risk. GARCH methodology is very effective at

examining and determining the nature of risk in the financial markets and certainly in the

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futures markets (GARCH, 2006, p.15). GARCH models and techniques are particularly

useful in commodities markets because commodity prices are subject to excessive

amounts of volatility in ways that other financial markets are not. Predicting, managing,

and leveraging the uncertainty in commodity futures vis--vis volatility is vital if a

comprehensive market strategy is going to be developed that enables China to

efficiently control, or at least manage, the cost-basis of its copper futures. GARCH

techniques can be used to construct models that control, to some degree, conditional

variances related to futures as well as spot market prices and allow better management

of commodities portfolios with an emphasis on copper. The following model introduces

the basis for such a GARCH model which is applied in later sections of this study

(Benet, 1990, p.290):

GARCH (1, 1) model

The model for traditional hedging of copper price and copper future.

( ) ( ) ttttt FFSS ++= 1101

2

1 ,0~ ttt N +

2

1

1

2

1

0

2

=

=

++= tq

i

ijt

j

jt

tS : Copper spot price

1tS : After 3 months copper spot price

tF : Copper Future Price

1 tt FF : The price difference of copper future with after 3 months copper future

ij , : Beta, Alpha

1: Minimum variance hedge ratio

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t: The error at time t

Durban-Watson. The Durban-Watson test is the standard method for predicting

or measuring auto-correlation phenomena. Various techniques are used in the Durban-

Watson test to correct for autocorrelation such as applying a parameter to address this

factor in the data before regression is performed (Myers & Well, 2003, pp.18-29).

However, weighted regression lines often fail this test. That said then the Durban-

Watson test is effective in forecasting through its standard time series analysis when

appropriate confidence levels have been established. Additionally, the Durban-Watson

test is just as effective at modelling predictive behaviour of markets when beset by

events that affect change in the time series; in this case, sudden exchange rate

fluctuations of the Yuan which affect the efficacy of hedging strategies employed in

copper futures as has been recognized in other financial markets (Kim, In & Viney,

2001). This application of the Durbin-Watson test can be used to factor in risk for

independent market variables such as interest rates or currency exchange rates by

predicting the effect that certain scenarios might have on the price of copper in both the

spot market and the futures market (N. Jensen, 2005):

We observe ( )11 , yx ,, ( )nn yx , .

nnn XY

+

+ ++= 11~

++=

+

nnn XyX 1

Note that ( ) =1;cov nn .

Hence

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dk

n

n

n

k

n

n

==

=

=

1

2

1

2

Here

nnn Xy

=

Hypotheses:

Accept 0H if uu ddd 4 ---------------no serial correlation

Accept 1H if Ldd or Ldd 4 ----------serial correlation

Omega. The Omega function has several uses in mathematics but in this specific

application, its f=(g) wherein f expresses constrains g is a given manner has some

relevance to risk determination in the copper commodities market in China. Shadwick,

Cascon, and Keating make some use of the Omega function where they develop a

working model to display cumulative distribution based on a financial application of the

Omega function (2003, p.2). In their model they let f represent a financial instrument, in

this case it could be either copper or the Yuan, and the variable, D=(a,b, etc) defines

the domain of F. These researchers manage risk according to the Omega function by

determining a return level, r=L in (a,b, etc) which becomes their loss threshold

(Shadwick, Cascon, & Keating, 2003, pp.2-3). While their model is extensive, the

application and relevance to managing risk within the China commodities market vis--

vis copper and related exchange rate risk is clear in that by determining loss thresholds

in advance, certain limiters on purchase instruments can be predetermined. This work

on the Omega function has led to other extended research on Omega as it applies to

financial instruments where Shadwick, Cascon, and Keatings original definition of

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Omega is reworked into a new model termed the Sharpe-Omega (Kazemi, Schneeweis

& Gupta, 2003, p.2):

iceOptionPut

ThresholdturnExpectedOmegaSharpe

Pr

Re =

These researchers essentially redefine Omega in the financial risk management model

to represent:

)(

)()(

LP

LCL =

C(L) represents a call option device while P(L) would be a put option.

These and other statistical models are able to offer greater insight into the copper

commodities trading market in China. Proof that such a model specifically designed for

this market and accounting not only for price fluctuations but also for market variables

such as interest rates and exchange rates is plausible can be found some existing

research in this area. Other researchers have applied the GARCH(1,1) model to

forecasting volatility with some success in the futures market. One such model that has

been demonstrated effectively is the following volatility model of Watkins and McAleer:

,1,1


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copper. Their success in the following factors proves that this present research has the

potential to develop a functional model that can accurately incorporate intervention

related to exchange rate fluctuations into a futures volatility model: shifting parameter

estimates, t-ratios, one-step ahead forecasts, and forecast evaluation criteria (Watkins

& McAleer, 2002, p.6). If these principles can be incorporated into the present research,

the accuracy of the resultant model can be improved.

Importance of the Financial Markets

A note should be made about the financial markets in China, Hong Kong, and

Great Britain because any strategy directed at controlling or managing risk in the futures

markets will rely on the underlying assumption of stable financial markets. Financial

markets are so important to a countrys overall economic growth that how Chinas

markets develop cannot be overlooked in this or any other related study. Commodities

markets are inherently related or dependent upon foreign exchange risk factors and the

devices that are developed to be bought and sold across financial markets are the

primary method that market players control for transaction risk in all exchanges. This

involves not only the futures markets but, because of the degree of financial integration,

other financial markets as well, including the currency exchange markets as well as the

equity markets. This aspect is extremely important because China is still in the process

of establishing more reliable financial markets as well as erecting the legal structures

requisite to engender the faith in the markets that any futures trading strategy or,

indeed, any financial trading strategy, requires. For China, it suffers from a banking

sector that is still weighed down with inordinate amounts of debt which affect interest

rates and transaction premiums across the markets. Investment devices such as

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derivatives or credit transactions cannot really be implemented effectively until the

investors, both internal and external, believe that the market is not weighted unfairly

against them and this implies China needs a much more robust regulatory commission.

Great Britain has well-developed financial markets, very much on a par with that

of the United States. The British government reduced its high tax rate on many capitalist

structures, created flexibility across the labour markets, and reduced the amount of

regulatory reporting requirements for industry operators which created good will in the

open markets (Karmel, 2002). These actions truly served to elevate the financial equity

market to first choice status for many investors that were truly seeking growth capital.

Furthermore, Great Britains financial industry, which includes the LME, is supported by

an extremely viable and liquid stock market. The London Stock Exchange, one of the

leading exchanges in the world, went so far as to create a separate market specifically

for various investor classes of which commodities and futures traders are represented.

Great Britain, with a smaller population that many of continental Europes largest

countries have consistently produced doubles the amount of capital investments as

larger countries (Karmel, 2002). This is due primarily to the faith in the market that

investors and traders have. Such market faith could never have taken place in Great

Britain without much attention given to its regulatory environment as well as its related

enforcement policies. This last observation is critical because the most well thought out

body of regulations to control a financial market is useless if the mechanisms are not in

place to enforce the regulations.

The financial markets are based on a fairly regulated business and investment

environment that can more easily gauged as far as risk relative to political, economic,

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and technological factors. Great Britain generally has created a ready environment for a

wider array of investment options through stressing a uniform compliance code

established by the OECD (Organization for Economic Cooperation and Development)

that is not too far removed from Sarbanes-Oxley in the U.S.: 1) adequate accounting

requirements, 2) independent external audits, 3) internal company controls and internal

controls as characterized by, 1) control environment, 2) performance and risk

management, 3) information and communication, 4) control activities and 5) audit and

evaluation (Tarantino, 2005, p.37). In Britain this has resulted in several legislative

reforms regarding corporate governance and reporting procedures. These are reforms

that the China market has yet to fully implement or embrace but that it is keen to

introduce over the next several years as it continues to privatize its banking sector.

One particular target of reform has been a call to end a practice known as

private briefings which, by any measure of the common sense litmus test, is not

congruent with contemporary trends in global reporting and accountability oversight

regulations (Al-Hawamdeh & Snaith, 2005). This practice, while appearing sensible in

that performing due diligence on the part of private investors into the corporate health of

a company seems reasonable, smacks of corporate and financial elitism as private

briefings are awarded only privileged investors who are given key corporate access

and, as the name implies, this dialogue is kept secure from the public. Private briefings

are described as: the ability of institutional investors and investment managers to

become involved in corporate governance and monitoring corporations management

(Al-Hawamdeh & Snaith, 2005, p.490). While Britain has undertaken significant

corporate oversight reform as contained in the Financial Services and Markets Act 2000

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(FSMA 2000), the practice of private briefings was left uninhibited. While some might

argue that as substantial investors with significantly more risk in a given company, these

parties merit greater access and input in a given enterprise, the corresponding reality is

that it also engenders a greater risk of insider trading and other abuses of the financial

markets that depend on fair access to information by all. So while Britains stock

exchange and corporate governance is considerably more sophisticated than that of

Chinas, it too also suffers some deficiencies. The primary risk is that complete investor

faith in the markets will crumble if continued abuse of privileged access is seen as the

norm rather than the occasional excess.

However, in the spirit of self-regulation and oversight that the FSMA 2000 in

Britain, as well as Sarbanes-Oxley in the U.S., is supposed to engender, many UK

public companies have moved to form a compliance board consisting of corporate

governance officers with the eventual mandate to ensure that Britains public companies

operate in an environment that is accountable both to government regulators and to

public investors alike (Jackson, 2005, p.565). Combined with FSMA 2000 and other

measures, this increased regulatory environment has accomplished much in providing

and restoring, public trust in the comportment of public companies and is the exact

environment necessary for investors and market players to thrive in wherein other

finance channels with less qualifying restrictions might not justify the risk associated

with them.

Perhaps the most important observation that can be made relative to the China

and UK financial sector is that these two financial and banking markets cannot and

should not be compared. In the first instance it likely is not a fair analogy for China in

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that Chinas markets are still relatively young and developing as well as operating under

a different set of constraints in that the political system, no matter how progressive, is

still somewhat constrained. In the second instance, Great Britain has had over 200

years to fully develop its market economy and, in fact, has heavily influenced all the

major developed economies of the world regarding their economic and financial

structures. To compare the two would be a patent disservice to Chinas ever expanding

banking and financial sector and would undermine the advances it has made thus far in

meeting the regulatory and structural demands placed upon it by its World Trade

Organization membership.

Rather, the more correct option would be to model Chinas financial and banking

institutions more after the pattern of the British system while making allowances for the

political and cultural constraints placed upon the operations. This approach would allow

a systematic introduction of more effective futures trading strategies where risk could

better managed. The Hong Kong bourse is an illustrative example of how successful

such a blend can be given that Hong Kong has been a successful investment incubator

for over 150 years (Osano & Tachibanaki, 2001). Therefore, the observations that can

be made between the two systems consist of the same clinical observations that market

analysts and pundits alike have made for the past 20 years: 1) China must reform and

privatize its banking sector, China must institute a liquid and transparent equities

market, and China must implement a regulatory apparatus for public and private

enterprise along the lines of the FSMA 2000 in Great Britain or even Sarbanes Oxley in

the US in order to develop a stable but active futures market with international appeal.

In so doing, Chinas financial sectors would engender greater trust and faith on the part

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of the international trading community that will come to sustain Chinas long-term

economic health and growth through effective commodities trading strategies that have

its long-term economic health in mind.

Conclusion

One of the most important conclusions to be drawn from this research is that

copper spot prices fluctuate; i.e. copper spot prices are highly volatile resulting in the

need to develop sound hedging strategies. This high degree of volatility is what traders

and investors of all financial instruments find so attractive. While rapid and wide price

fluctuations are not market characteristics attractive for everyone, savvy investors

understand that these characteristics are what make financial instruments so profitable

or, just as equally, so devastating. For example, if one examines a year of spot prices

taken from the LME during one of the years that the data, presented later, is drawn

from, it is apparent that copper prices fluctuate widely as a rule rather than as an

exception:

LME Copper spot price movements Jan - Oct

2002

$1 250,00$1 300,00$1 350,00

$1 400,00$1 450,00$1 500,00$1 550,00$1 600,00$1 650,00$1 700,00$1 750,00

119

37

55

73

91

109

127

145

163

181

199

Day

Spot

(ICSG, 2002)

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The reasons for these rapid and wide price fluctuations relate both to the geo-political

climate within which all commodities function and to the unique dynamic between actual

production and the eventual delivery of the commodity. This dynamic exists because

during periods of high demand, producers search far and wide for additional sources of

the commodity. This is the state that China is in across most of its commodity demands,

especially regarding copper because of its extreme integrated relationship with the

nations economic expansion.

Eventually, as these new sources are located and developed, the prices of the

commodity revert back to lower levels as demand is met by existing supplies, and the

eventual glut of new copper supplies as these newly discovered mines come online

drives prices down even more (Fama & French, 1998). The average volatility for copper

over typical 10 year periods is over 24% and this degree of volatility underscores why it

is paramount for producers, suppliers, and users to employ the most effective hedging

strategies possible. Admittedly, speculators are primarily concerned with appropriately

anticipating these market price fluctuations because by developing a sound short or

long strategy, they can profit enormously. The strategy for hedgers who seek to stabilize

copper supplies, the emphasis in on creating price stability and constant supply with

price, albeit important, occupying only a secondary position in terms of importance.

Furthermore, when inventory levels are relatively high, investors have learned

that a rapid increase in demand can be artificially created by a reduction inventory

levels. This is usually accomplished by an interruption of production, delivery, or

availability and, of course, the opposite holds true regarding low inventory levels (Fama

& French, 1988, p.1901-3). This is simple supply side economics and both spot and

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future prices are deeply impacted by any of these artificial manipulations of the market.

The presence of this speculative action in the market may be why commodities markets

in China have yet to rival any in the West. The government is well aware that

unscrupulous investors, especially institutional hedge funds, make every effort to

destabilize such markets in order to create accuracy for their long or short strategies.

Such market manipulations require collective markets such as China and its individual

suppliers and users to control for these external strategies designed to benefit in price

or minimize in risk almost exclusively the interests of the producers who control the

market; both spot and futures, to a degree. These artificial manipulations result in

market scenarios such as contango and backwardation that can define the futures

market. The copper market is typically in a state of backwardation where speculators in

the futures markets are net long on their futures contracts with the net result being the

fact that speculators are compensated for their degree of risk exposure in the market

(LME, 2006). Conversely, contango ensures that speculators are net short on their

futures contracts which results in the need for the futures price to decline over the life of

the commodity position. Contango scenarios normally arise when copper has been

inventoried resulting in a surplus somewhere in the commodity channel. Since

inventorying large amounts of copper supplies is something that most hedge investors

and strategists do not want to do, they will work to manipulate a given commodities

market, or any market for that matter, in order to recoup losses or gain far larger income

levels that might otherwise be possible.

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The typical baseline measurement of a demand curve is always established

under the assumption that all other factors relative to the product or item are

constant. While in reality this is rarely the case, when the copper market is

examined nothing is ever constant because the copper industry is so

politically, socially, and economically charged due to both environmental and

economic issues. Because copper has become so integrated into much of

societys technological infrastructure, its perceived economic necessity is

perhaps higher even than its actual necessity level which is also high

nonetheless. This perceived necessity of copper supplies is elevated not

necessarily by desire for that product itself but rather by the wants, needs, and

desires on the part of individuals for ancillary products. Therefore, the typical

demand curve does not apply as it otherwise might in relation to copper:

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In a typical demand curve the demand, in conjunction with supply, dictates the price

and, for the most part, the copper industry attempts to adhere to these principles.

However, because of the political, social, and economic dimensions of the non-

ferrous metals industry and particularly the copper industry, it is often the case

that the industry sheds typical supply and demand principles in favour of its own

artificial dynamics; hence contango and backwardation. To researchers such as

Fama and French (1988) the copper industry has created its own economy that,

when conditions merit it order is reintroduced to maintain or increase margins or

to avoid potential losses in the marketplace. On the supply side, the copper

industry is able to directly influence and affect change in the market because of

its ultimate control over most aspects of the distribution channel. This is a clear

danger for China because, as with its petroleum industry, it is an abundant

importer of copper commodities.

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Because of the nature of the Copper industry it is very easy for the industry to

create the appearance of supply interruptions of copper which can have long and

lasting effects on the economy in question and demand for copper. Producers

can create a supply interruption by merely declaring a maintenance issue at the

source. Essentially, financial markets do not want to develop the avenues for the

kind of manipulation that was seen with the electricity markets in the U.S.

instituted by Enron. Enron managed to gain control of the energy trading market

and used its position to artificially create supply interruptions, delivery and

distribution breakdowns, and political chaos which, collectively, allowed it to profit

billions in U.S. currency. The common conception that copper is extremely

susceptible to supply interruptions at the source is simply not the case unless

one counts the intentional adjustments made to inventory levels to control for

price and supplies. While supply interruptions can and do occur, they are rarely

at the source. This is because copper mines are not like a water tap in a typical

house that can be simply shut off when not in use or not needed. In fact, the

opposite is true. Once mines are productive, they are largely desired to be kept

in operation until no longer productive. It is this conception of great susceptibility

to decreased or limited supplies that allows the major corporate entities in the

copper industry to perpetuate the myth of justifiable exorbitant commodity prices.

A typical supply curve indicates that a steady supply provides the most stable

market:

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In reality a typical copper supply curve is distorted beyond all relation to reality or

normal market fluctuations because of the artificial gaming of the system by the major

produces. Admittedly, supply interruptions do occur and these are most often at a

regional level and hardly ever because of source supply issues but more normally

related to some sort of transportation or delivery issue. However, there are other

associated issues with the copper industry that also lead to price instability or risk and

environmental policies and impact two of the most important. This is because the

environmental aspect raises the risk premium in two ways: 1) first by contributing to real

costs of development, production, and delivery because of the environmental

procedures that must be followed, and 2) the threat of environmental regulation or the

ongoing compliance with it can in themselves lead to higher market prices or the spot

price.

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III. Methodology

Approach

The mixed method approach to this research relies on both a qualitative and a

quantitative approach. The qualitative component relies on the review of the literature to

determine: 1) what has been done previously regarding efforts to develop effective

hedging strategy vis--vis copper futures in China, and 2) the actual practicality of doing

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so since futures are extensions of risk. Hedging strategies by nature are, being

projections of market risk of a single commodity, in this case copper, in relation to a

common factor, in this case exchange rates of the Yuan to the U.S. dollar, entirely risk

dependent. Following the qualitative component, this study intends to establish

quantitative based assumption models that lead to an accurate risk assessment, in

effect a risk mitigation model, for the development of a comprehensive trading strategy

regarding copper futures in China. This two pronged approach in intended to result in a

functional quantitative trading model based on statistical analysis of historical copper

and currency price fluctuations over the same given period in the China market forming

one strategic prong. The other consists of the qualitative model established through the

literature and analysis of the market in order to provide a sound rationale to support the

use and adoption of the risk model. The result is that both an effective model is

developed to better hedge for copper futures and a new hypothesis is proposed that

demands further research and which will build upon this existing research.

Data Gathering Method

The three models are time-series data collected from DataStream. The data

gathering method consists of a review of the relevant literature as well as

documentation of associated trading strategies regarding derivatives in the futures

market. Due to the restricted duration of currency forward series, the first Yuan to US 3

Month Forward Contract starts on 11 February of 2002. Therefore the three models are

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time-series based running over a period three years from January of 2003 to December

of 2005. The data gathered is both primary and secondary research material which

ensures that this study is both academic and empirical in nature.

Database of Study

This chart contains the first thirty days of historical copper prices included in this

study for referential purposes. The calculations utilized to arrive at the working

assumptions included in the presentation of findings can be reproduced in miniature

through these figures:

Sample-Historical Copper Prices

This chart contains the first thirty days of historical exchange rates included in

this study for referential purposes. The calculations utilized to arrive at the working

assumptions included in the presentation of findings can be reproduced in miniature

through these figures:

Sample-Historical Copper and Futures Prices

Frequency

Name Spot 3MF

Code LCPCASH LCP3MTH

CURRENCY U$ U$

2003/1/1 1535.75 1553.5

2003/1/2 1544.25 1562.25

2003/1/3 1591.75 1608.25

2003/1/6 1600.75 1617.752003/1/7 1598.75 1617.5

2003/1/8 1597.5 1618.5

2003/1/9 1633.75 1650.5

2003/1/10 1641.25 1658.5

2003/1/13 1620.5 1640.5

2003/1/14 1637.25 1656.5

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2003/1/15 1661.75 1681.25

2003/1/16 1654.25 1674.75

2003/1/17 1661.25 1681.5

2003/1/20 1668.5 1686.5

2003/1/21 1685.75 1705.52003/1/22 1680.5 1701.75

2003/1/23 1686.25 1705.75

2003/1/24 1690.5 1710.75

2003/1/27 1671.25 1690.25

2003/1/28 1657.75 1677.5

2003/1/29 1663.5 1683.75

2003/1/30 1681.25 1702.25

2003/1/31 1713.25 1733.5

2003/2/3 1727.5 1745.25

2003/2/4 1715.75 1734.75

2003/2/5 1699.5 1718.5

Sample-Historical Exchange and Forward Rates

Frequency Daily Daily

Name Ut At

Code CHIYUA$ USCNY3FCURRENCY US $ US $

2003/1/1 8.2770 8.2685

2003/1/2 8.2770 8.2665

2003/1/3 8.2768 8.2643

2003/1/6 8.2768 8.2453

2003/1/7 8.2767 8.2597

2003/1/8 8.2766 8.2601

2003/1/9 8.2766 8.2636

2003/1/10 8.2766 8.26912003/1/13 8.2768 8.2683

2003/1/14 8.2768 8.2698

2003/1/15 8.2770 8.2705

2003/1/16 8.2770 8.2680

2003/1/17 8.2770 8.2680

2003/1/20 8.2772 8.2692

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2003/1/21 8.2770 8.2700

2003/1/22 8.2770 8.2685

2003/1/23 8.2770 8.2645

2003/1/24 8.2768 8.2598

2003/1/27 8.2768 8.2638

2003/1/28 8.2767 8.2702

2003/1/29 8.2767 8.2687

2003/1/30 8.2766 8.2704

2003/1/31 8.2769 8.2714

2003/2/3 8.2769 8.2714

2003/2/4 8.2769 8.2724

2003/2/5 8.2769 8.2694

2003/2/6 8.2769 8.2694

2003/2/7 8.2769 8.2694

2003/2/10 8.2773 8.2698

2003/2/11 8.2775 8.2690

2003/2/12 8.2777 8.2722

This chart contains the first thirty days of the relevant calculations for model one

included in this study for referential purposes. The calculations utilized to arrive at the

working assumptions included in the presentation of findings can be reproduced in

miniature through these figures:

Model 1-Assumption Basis

Model 1

Name St-St-1 Ft-Ft-1

CURRENCY US $ US $

2003/1/1 89.250 85.750

2003/1/2 80.000 75.7502003/1/3 137.000 132.500

2003/1/6 165.000 162.250

2003/1/7 170.250 167.250

2003/1/8 157.250 157.250

2003/1/9 198.500 193.250

2003/1/10 191.500 188.000

2003/1/13 156.500 155.000

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2003/1/14 176.500 176.250

2003/1/15 197.500 199.000

2003/1/16 196.750 201.500

2003/1/17 163.750 169.750

2003/1/20 166.750 169.500

2003/1/21 185.500 189.7502003/1/22 165.250 172.000

2003/1/23 165.750 168.250

2003/1/24 176.750 181.500

2003/1/27 142.750 145.750

2003/1/28 108.500 116.000

2003/1/29 134.000 137.750

2003/1/30 156.000 160.750

2003/1/31 177.750 185.000

2003/2/3 171.250 174.500

2003/2/4 133.000 137.250

2003/2/5 128.750 132.0002003/2/6 116.000 118.500

2003/2/7 105.000 109.000

2003/2/10 113.000 115.500

2003/2/11 139.750 140.250

2003/2/12 119.000 121.500

This chart contains the first thirty days of the relevant calculations for model two





Model 2

Name

UtSt Ut-1St-1 UtFt Ut-1Ft-1 UtSt-Ut-

1St-1

UtFt-Ut-

1Ft-1

CURRENCY US $ US $ US $ US $ US $ US $

2003/1/112711.40

28

11973.11

45

12858.31

95

12149.00

71738.2883 709.3124

2003/1/212781.75

73

12120.03

65

12930.74

33

12304.20

65661.7207 626.5368

2003/1/3 13174.59

64

12041.40

22

13311.16

36

12215.22

55

1133.194

2

1095.938

1

51


52/90

2003/1/613249.08

76

11884.13

35

13389.79

32

12047.61

02

1364.954

1

1342.183

1

2003/1/713232.37

41

11824.12

31

13387.56

23

12004.15

43

1408.251

1

1383.407

9

2003/1/813221.86

85

11921.09

33

13395.67

71

12094.91

24

1300.775

2

1300.764

7

2003/1/913521.89

53

11879.70

78

13660.52

83

12061.80

40

1642.187

5

1598.724

3

2003/1/1013583.96

98

11999.58

08

13726.74

11

12171.32

85

1584.389

0

1555.412

6

2003/1/1313412.55

44

12117.38

16

13578.09

04

12295.33

50

1295.172

8

1282.755

5

2003/1/1413551.19

08

12090.33

56

13710.51

92

12251.73

32

1460.855

2

1458.786

0

2003/1/1513754.30

48

12119.15

80

13915.70

63

12268.13

86

1635.146

8

1647.567

7

2003/1/1613692.22

73

12063.29

03

13861.90

58

12193.64

83

1628.937

0

1668.257

5

2003/1/1713750.16

63

12394.50

80

13917.77

55

12512.45

24

1355.658

3

1405.323

1

2003/1/2013810.50

82

12429.53

42

13959.49

78

12555.75

39

1380.974

0

1403.743

9

2003/1/2113952.95

28

12417.26

92

14116.42

35

12545.55

96

1535.683

6

1570.863

9

2003/1/2213909.49

85

12541.72

43

14085.38

48

12661.74

08

1367.774

3

1423.644

0

2003/1/23 13957.0913

12585.0265

14118.4928

12725.7338

1372.0648

1392.7590

2003/1/2413991.93

04

12529.30

88

14159.53

56

12657.60

23

1462.621

7

1501.933

4

2003/1/2713832.60

20

12651.70

02

13989.86

12

12784.13

54

1180.901

8

1205.725

8

2003/1/2813720.69

94

12823.60

70

13884.16

43

12925.00

40897.0924 959.1603

2003/1/2913768.29

05

12659.97

74

13935.89

36

12796.55

12

1108.313

1

1139.342

4

2003/1/30

13915.03

38

12624.64

68

14088.84

24

12759.14

97

1290.387

0

1329.692

7

2003/1/3114180.39

89

12709.33

35

14348.00

62

12816.93

45

1471.065

4

1531.071

7

2003/2/314298.34

48

12881.23

69

14445.25

97

13001.25

48

1417.107

9

1444.004

9

2003/2/4 14201.09

12

13100.89

66

14358.35

23

13222.98

68

1100.194

6

1135.365

5

52


53/90

2003/2/514066.59

16

13001.09

78

14223.85

27

13131.46

05

1065.493

8

1092.392

2

2003/2/613990.03

02

13030.22

47

14143.15

29

13162.65

83959.8055 980.4946

2003/2/713865.87

67

12997.11

63

14035.55

32

13133.68

84

868.7604 901.8647

2003/2/1013792.05

11

12856.56

09

13961.73

58

13005.55

05935.4902 956.1853

2003/2/1114129.69

25

12972.12

83

14284.89

56

13123.18

35

1157.564

3

1161.712

1

2003/2/1213962.41

05

12976.42

35

14132.10

33

13125.41

13985.9869

1006.692

0

This chart contains the first thirty days of the relevant calculations for model three





Model 3

Name

UtSt Ut-1St-1 UtFt Ut-1Ft-1

UtSt-Ut-1St-1

UtFt-Ut-

1Ft-1Ut-At-

1

CURRENCY US $ US $ US $ US $ US $ US $ US $

2003/1/112711.4

028

11973.1

145

12858.3

195

12149.0

071

738.288

3

709.312

4

-

0.003

8

2003/1/212781.7

573

12120.0

365

12930.7

433

12304.2

065

661.720

7

626.536

8

-

0.004

1

2003/1/313174.5

964

12041.4

022

13311.1

636

12215.2

255

1133.19

42

1095.93

81

-

0.005

0

2003/1/613249.0

876

11884.1

335

13389.7

932

12047.6

102

1364.95

41

1342.18

31

-0.004

3

2003/1/713232.3

741

11824.1

231

13387.5

623

12004.1

543

1408.25

11

1383.40

79

-

0.005

1

2003/1/8 13221.8 11921.0 13395.6 12094.9 1300.77 1300.76 -

53


54/90

685 933 771 124 52 470.004

7

2003/1/913521.8

953

11879.7

078

13660.5

283

12061.8

040

1642.18

75

1598.72

43

-

0.004

2

2003/1/1013583.9

698

11999.5

808

13726.7

411

12171.3

285

1584.38

90

1555.41

26

-0.004

9

2003/1/1313412.5

544

12117.3

816

13578.0

904

12295.3

350

1295.17

28

1282.75

55

-

0.005

2

2003/1/1413551.1

908

12090.3

356

13710.5

192

12251.7

332

1460.85

52

1458.78

60

-

0.005

1

2003/1/1513754.3

048

12119.1

580

13915.7

063

12268.1

386

1635.14

68

1647.56

77

-

0.005

0

2003/1/1613692.2

273

12063.2

903

13861.9

058

12193.6

483

1628.93

70

1668.25

75

-

0.004

7

2003/1/1713750.1

663

12394.5

080

13917.7

755

12512.4

524

1355.65

83

1405.32

31

-

0.004

6

2003/1/2013810.5

082

12429.5

342

13959.4

978

12555.7

539

1380.97

40

1403.74

39

-

0.004

5

2003/1/21 13952.9528

12417.2692

14116.4235

12545.5596

1535.6836

1570.8639

-

0.004

3

2003/1/2213909.4

985

12541.7

243

14085.3

848

12661.7

408

1367.77

43

1423.64

40

-

0.004

5

2003/1/2313957.0

913

12585.0

265

14118.4

928

12725.7

338

1372.06

48

1392.75

90

-

0.003

8

2003/1/2413991.9

304

12529.3

088

14159.5

356

12657.6

023

1462.62

17

1501.93

34

-

0.004

5

2003/1/2713832.6

020

12651.7

002

13989.8

612

12784.1

354

1180.90

18

1205.72

58

-

0.004

6

2003/1/28 13720.6

994

12823.6

070

13884.1

643

12925.0

040

897.092

4

959.160

3

-

0.004

8

54


55/90

2003/1/2913768.2

905

12659.9

774

13935.8

936

12796.5

512

1108.31

31

1139.34

24

-

0.004

5

2003/1/3013915.0

338

12624.6

468

14088.8

424

12759.1

497

1290.38

70

1329.69

27

-

0.004

5

2003/1/3114180.3

989

12709.3

335

14348.0

062

12816.9

345

1471.06

54

1531.07

17

-

0.004

4

2003/2/314298.3

448

12881.2

369

14445.2

597

13001.2

548

1417.10

79

1444.00

49

-

0.004

5

2003/2/414201.0

912

13100.8

966

14358.3

523

13222.9

868

1100.19

46

1135.36

55

-

0.004

6

2003/2/5 14066.5916

13001.0978

14223.8527

13131.4605

1065.4938

1092.3922

-

0.003

8

2003/2/613990.0

302

13030.2

247

14143.1

529

13162.6

583

959.805

5

980.494

6

-

0.003

5

2003/2/713865.8

767

12997.1

163

14035.5

532

13133.6

884

868.760

4

901.864

7

-

0.003

5

2003/2/1013792.0

511

12856.5

609

13961.7

358

13005.5

505

935.490

2

956.185

3

-

0.003

1

2003/2/1114129.6

925

12972.1

283

14284.8

956

13123.1

835

1157.56

43

1161.71

21

-

0.003

5

2003/2/1213962.4

105

12976.4

235

14132.1

033

13125.4

113

985.986

9

1006.69

20

-

0.003

4

Validity of Data

All of the data, both qualitative and quantitative are gathered from reliable

sources in DataStream. The sources are both primary and secondary in nature. The

quantitative data are all market based and are real historical figures that have been

accurately reproduced in order to create these functional models. The data presented

55


56/90

and analyzed represents both accurate representation of previous research and, in the

case of the statistical models, is primary research based on the authors own

interpretation and analysis. The validity of the data ensures that the results of this study

at least have applicability int

sample dissertation -英語畢業論文

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