price linkages among emerging gold futures markets

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3rd International Symposium

Computational Economics

Finance

PRICE LINKAGES AMONG EMERGING GOLD FUTURES

MARKETS

3rd International Symposium in Computational Economics and Finance (ISCEF) ISCEF 2014, Pariswww.iscef.com

Hasan F. BAKLACI (Izmir University of Economics-

TURKEY)

Ömür SÜER (Galatasaray University-TURKEY)

Tezer YELKENCI (Izmir University of Economics-

TURKEY)

ISCEF Paris || 10-14 April 2014

WHY GOLD FUTURES IN EMERGING MARKETS?

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The most ancient financial asset.

One of the most popular instrument during turmoil periods.

The introduction of gold derivatives has enhanced the importance of gold futures.

Hasan F. BaklacıÖmür Süer

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WHY GOLD FUTURES IN EMERGING MARKETS?

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There is an upward trend in the trading volume of gold futures in emerging markets.

In 2012, India’s derivative exchange had the highest silver and gold future transactions in the world.

10 of the top 20 derivative exchanges are located in emerging markets.

Untapped area in finance literature.


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OBJECTIVE4

To examine the price linkages in gold futures exchanges of four emerging markets:

Turkey, India, China, Taiwan.


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WHY THESE COUNTRIES?5

I. Size of their gold markets

II. The trading activity in their derivative markets


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China, India and Turkey are the top three gold demanders in the world (World Gold Council Report, November 2013).

Turkey is the second largest gold exporter in the world behind Italy.

Turkey and India are among the top three gold producers after Italy.

In the ranking of the top 40 countries based on their official gold holdings worldwide, China, Turkey, India and Taiwan are placed among top 15 countries.


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I. Size of their gold markets



Top 30 derivatives exchanges list contained Indian, Chinese, Taiwanese and Turkish derivatives exchanges.

The trading volume in these countries’ derivatives exchanges corresponds to approximately one-fourth of total trading volume in top 30 derivatives exchanges globally.

The trading volume of gold futures traded in these markets represent more than 55% of total gold futures trading listed in the top 20 metals future contracts. (Annual Volume Survey 2012, published by Futures Industry Association).


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II. The trading activity in their derivative markets


RELATED STUDIES8

• Previous studies related with emerging gold futures markets have investigated predominantly the price discovery function of gold futures for spot market transactions [Pavabutr and Chaihetphon (2010), Thenmozhi and Priya (2011, Ho, Wang and Liou (2010)]

• The cross-market price linkage relationships are tested only among developed gold futures markets.


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RELATED STUDIES9

• Xu and Fung (2005) : analyzed the patterns of information flows for gold, platinum, and silver futures contracts traded in US and Japanese markets (1994-2001, ARMA-GARCH model). Their results demonstrate a strong pricing transmission between the two markets. However, they also discover that US market seems to lead Japanese market in terms of mutual information flows.

• Lin, Chiang and Chen (2008) : investigated the dynamic relationships between US and Japanese gold futures markets (1990-2006, bivariate GARCH model). Their results show that Japanese market leads US in the mean return. Volatility spillover effects are also observed in both markets. Their results, thus, are contradictory to the findings of Xu and Fung.

• Aruga and Managi (2011) : investigated the price linkage between the U.S. and Japanese gold and silver futures markets (January 2001-June 2010, causality tests). They uncover that the price linkage between the U.S. and Japanese gold and silver futures markets were led by the U.S. market; results consistent with Xu & Fung.


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DATA & METHODOLOGY10

Daily gold futures settlement prices

September 2, 2008 - December 20, 2012 (covers the crisis period)

1075 observations


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DATA



Johansen co-integration test

Vector Error Correction Model


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METHODOLOGY

Descriptive Statistics for Gold Future Price Series

Turkey Taiwan India China

Mean 69.86 4888.72 21022.53 280.84

Median 62.93 4914.51 19672 293.37

Maximum 107.75 6722.51 32636 394.09

Minimum 30.915 2846 11260 155

Standard Dev. 21.86 993.37 6115.05 58.72

Skewness 0.229 -0.123 0.352 -0.314

Kurtosis 1.576 1.846 1.742 1.816

Jarque-Bera 100.14 62.31 93.15 80.41

Probability 0 0 0 0

Observations 1075 1075 1075 1075




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Median values for all countries’ price series are close to the mean values indicating that the data are evenly distributed around the mean.

However, as revealed by Jarque-Berra statistics, the series do not fully conform to a normal distribution.

The kurtosis parameters point out that the price series conform to a platykurtic distribution with wider peak and shorter tail.


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DESCRIPTIVE STATISTICS



Unit root test results (ADF, PP, KPSS) indicate that all the price series are non-stationary.

All the price series exhibit I[1] process.


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DIAGNOSTIC TESTS



Johansen cointegrating relationship among price series will be estimated by means of the following vector auto regressive (VAR) specification:

: gold futures price series of the country assumed to be cointegrated with the price series of the other countries denoted as . (j = 1… 3) k : # of appropriate lags chosen based on lag length criteria.


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VECTOR ERROR CORRECTION MODEL (VECM)

: vector to be examined for cointegration

where : vector of speed of adjustment vector : cointegrating vectors : vector of deterministic term or trend


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RESULTS17


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Johansen Cointegration Analysis Results

𝜆𝑡𝑟𝑎𝑐𝑒 𝜆𝑚𝑎𝑥

H0 H1 Statistic Critical Value

(5%) H0 H1 Stat.

Critical Value

(5%) Eigenvalue

𝑟= 0 𝑟> 0 123.34* 47.85 𝑟= 0 𝑟> 0 106.12* 27.58 0.094

𝑟≤ 1 𝑟> 1 17.21 29.79 𝑟≤ 1 𝑟> 1 9.71 21.13 0.009

𝑟≤ 2 𝑟> 2 7.49 15.49 𝑟≤ 2 𝑟> 2 5.47 14.26 0.005

* denotes rejection of the hypothesis at the 0.05 level.


RESULTS18

There is cointegrating relationship among the gold futures price series of sample countries

The results imply a long-term price linkage and dependency among the gold futures markets in the selected countries.

The risk diversification as well as cross-hedging opportunities among these countries gold futures is limited.


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Johansen Cointegration Analysis


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Vector Error Correction Model Estimates

Variable/Country Turkey Taiwan India China

vt-1 -9.78E-05 -0.0138* -0.0083 0.0063*

[-1.762] [-3.922] [-0.539] [ 9.793]

Turkeyt-1 0.0153 25.4548* 95.2549* 0.7414

[ 0.413] [ 10.818] [ 9.217] [ 1.725]

Turkeyt-2 -0.0007 4.8648 29.8796* 0.0444

[-0.019] [ 1.953] [ 2.731] [ 0.097]

Taiwant-1 -0.0021* -0.3088* -0.5740* -0.0161*

[-3.6735] [-8.344] [-3.531] [-2.395]

Taiwant-2 -0.0013* -0.1208* 0.0593 0.0066

[-2.368] [-3.419] [ 0.382] [ 1.029]

Indiat-1 0.0005* 0.0494* -0.0749* 0.0025

[ 4.321] [ 6.109] [-2.108] [ 1.716]

Indiat-2 -6.89E-05 0.0136 -0.1915* -0.0007

[-0.535] [ 1.663] [-5.329] [-0.533]

Chinat-1 -0.0021 -0.4873* -0.1348 0.0779

[-0.792] [-2.861] [-0.180] [ 2.506]

Chinat-2 -0.0036 -0.0795 -0.4104 -0.0017

[-1.355] [-0.469] [-0.551] [-0.057]

Constant 0.0585 0.8756 16.7151 0.0780

[ 2.165] [ 0.510] [ 2.218] [ 0.249]

* denotes significance at 5% level. Numbers in square brackets correspond to t-statistics.


RESULTS20

Taiwanese gold futures market: has bidirectional causality with all other countries has the largest significant speed of adjustment

coefficient. is the single market to correct for the short run

deviations from long-run price equilibrium among the four countries’ futures markets.

acts as an anchor market in the establishment of long-term price linkages between the gold futures markets of the sample countries.

Bidirectional causality exists between Taiwan, India and Turkey.

Chinese gold futures market: has a bi directional causality relationship only with

Taiwan. is relatively isolated market.


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Vector Error Correction Model


RESULTS21

Trading in Chinese gold futures market is available only for domestic investors.

China had banned foreign banks to import gold since January 2014 and has recently granted gold import licenses to foreign banks.


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Why is China isolated?


CONCLUDING REMARKS22

Presence of a long-run price linkage & bidirectional causality among the sample countries’ gold futures markets.

Limited risk diversification opportunities between the gold futures markets in majority of these countries.

China is an exception which seems to be a relatively isolated market due to restrictions on gold trading particularly for foreign investors.

Taiwanese market seems to be the most integrated gold futures market among the sample.

Strikingly, the causality results denote that none of the countries in the sample carry a leading role in price discovery and linkage mechanism among the gold futures markets since all causality relationships are bi-directional.


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CONCLUDING REMARKS23

This paper is the first study to examine the price linkages and dependencies among emerging gold futures markets.

The policy making issue is particularly important for China, which does not yet allow foreign investors to engage in gold trading in futures markets.

Ascending gold trading volume coupled with the presence of tight cross-market price linkages among the sample countries point out the heightened role of emerging gold futures markets in global perspective.


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Thank you for patience

Assoc. Prof. C. Coşkun KüçüközmenOpRisk Turkey 2012, Istanbul

www.opriskturkey.com

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3rd International Symposium in Computational Economics and Finance (ISCEF) ISCEF 2014, Pariswww.iscef.com

3rd International Symposium

Computational Economics

Finance

price linkages among emerging gold futures markets

Economy & Finance

gold markets

emerging gold futures

japanese gold futures

gold futures exchanges

developed gold futures

importance of gold futures

trading volume of gold

gold demanders