Interdependence between the US and Chinese Agricultural Futures Markets: Underlying Mechanisms in Spillovers and the Quantile Trading Strategies
Author(s)
Primary Supervisor
Roca, Eduardo
Todorova, Neda
Other Supervisors
Su, Jen-Je
Year published
2017-06
Metadata
Show full item recordAbstract
Over the past 15 years, the global food price has increased signi cantly in association
with high market volatility (Naylor and Falcon, 2010; Wright, 2011; Ivanic et al., 2012).
It is claimed that the world food prices have been strongly driven by the operation of the
agricultural derivatives markets (Du et al., 2011; Gutierrez, 2013; Juvenal and Petrella,
2015). Moreover, the agricultural commodities markets have become integrated globally
resulting in price transmissions across countries (Liu 2009; Liu and An 2011; Shi and He
2013, among others). The US and China, the leading economies in the world, are the
two biggest ...
View more >Over the past 15 years, the global food price has increased signi cantly in association with high market volatility (Naylor and Falcon, 2010; Wright, 2011; Ivanic et al., 2012). It is claimed that the world food prices have been strongly driven by the operation of the agricultural derivatives markets (Du et al., 2011; Gutierrez, 2013; Juvenal and Petrella, 2015). Moreover, the agricultural commodities markets have become integrated globally resulting in price transmissions across countries (Liu 2009; Liu and An 2011; Shi and He 2013, among others). The US and China, the leading economies in the world, are the two biggest producers and consumers of agricultural commodities globally and engage in massive trade in these products between each other. The US agricultural futures market is the world's most active while that of China is the fastest growing (Acworth, 2013). Despite the importance of the US and Chinese agricultural futures markets in relation to food security as well as to international investors, among others, there is still a dearth of studies which have investigated the interaction between these two markets. This thesis seeks to ll this vital knowledge gap by investigating the manner and structure of interdependence between the US and Chinese agricultural commodities futures markets and its implications on international investment, pro tability and risk. Specifically, it rst investigates the return spillovers and directional predictability between these two countries. Second, it examines the volatility transmission pattern between the US and Chinese agricultural futures markets. Third, given the ndings from study 1, it designs a rolling quantile trading strategy that can be applied in practice. This thesis focuses on four important commodities: soybeans, wheat, corn and sugar with more than a decade (2000 to 2016) of daily frequency data, i.e. opening, closing, daily high and daily low prices, which take into account the Global Financial Crisis (GFC). The studies apply newly developed and powerful econometric methodologies. The rst study performs the cross-quantilogram (Han et al., 2016) and the stationary bootstrap (Politis and Romano, 1994) which permit the analysis of directional predictability at arbitrary quantiles and lags. The second study applies the multivariate heterogeneous autoregressive model of Corsi (2009), a model that allows the joint analysis of short- , mid- , and long-term volatilities and their interaction. The third study designs a rolling quantile trading strategy that can trade on arbitrary quantiles of the return distributions based on the direction of relevant historical spillovers. The rst study applies the cross-quantilogram with stationary bootstrap to analyse the return spillovers and directional predictability between the US and Chinese agricultural futures markets. The results show a more signi cantly positive one-day predictability from the US to China than from China to the US in the same quantiles. Moreover, the bilateral lead-lag impact between countries is stronger than the return autocorrelations. The bi-directional daily return spillovers from one country to the decomposed overnight and intraday returns show a stable structure from the US to China and a mixed pattern from China to the US among commodities. The rolling crossquantilogram shows the dynamics of the cross-country directional correlation. These ndings o er valuable insights into investor behaviour, market integration, dissimilarity, and market e ciency in both countries, and have important implications for portfolio choices and the debate on nancial market integration. The existing literature commonly documents that volatility in the US agricultural futures market results in more signi cant spillovers from the US to China than vice versa. The second study aims to provide further insights into the spillovers from China to the US, as well as the time horizon and dynamics of the bi-directional spillovers through the application of a multivariate extension of the heterogeneous autoregressive (HAR) model. The results con rm the existence of signi cant spillovers from the US to China for soybeans, wheat, corn and sugar, which are primarily generated by the shorter term volatility components in the US, and provide evidence for the increasing pricing power of the Chinese market. The ndings are robust against various speci cations and have important investment and policy implications. The third study is the rst one known to formulate and examine the pro tability of the trading strategy based on signals generated from di erent quantiles in the return distributions. The rolling quantile trading strategy is conducted on a cross market basis in relation to the US and Chinese agricultural futures over a range of holding periods (daily, intraday, and overnight) for soybeans, wheat, corn, and sugar. Overall, the greatest pro t is generated from trades based on extreme quantiles. This result highlights the value of harvesting information from the di erent parts of the return distributions which has so far been neglected in the trading strategy literature. To the best knowledge of the author, this is the rst research of its kind on the linkage between the US and Chinese agricultural futures markets. The thesis contributes to the literature on nancial market integration, futures markets, commodities market, market e ciency, predictability and food security. It has important implications for international investors as well as for programs that are aimed at food security.
View less >
View more >Over the past 15 years, the global food price has increased signi cantly in association with high market volatility (Naylor and Falcon, 2010; Wright, 2011; Ivanic et al., 2012). It is claimed that the world food prices have been strongly driven by the operation of the agricultural derivatives markets (Du et al., 2011; Gutierrez, 2013; Juvenal and Petrella, 2015). Moreover, the agricultural commodities markets have become integrated globally resulting in price transmissions across countries (Liu 2009; Liu and An 2011; Shi and He 2013, among others). The US and China, the leading economies in the world, are the two biggest producers and consumers of agricultural commodities globally and engage in massive trade in these products between each other. The US agricultural futures market is the world's most active while that of China is the fastest growing (Acworth, 2013). Despite the importance of the US and Chinese agricultural futures markets in relation to food security as well as to international investors, among others, there is still a dearth of studies which have investigated the interaction between these two markets. This thesis seeks to ll this vital knowledge gap by investigating the manner and structure of interdependence between the US and Chinese agricultural commodities futures markets and its implications on international investment, pro tability and risk. Specifically, it rst investigates the return spillovers and directional predictability between these two countries. Second, it examines the volatility transmission pattern between the US and Chinese agricultural futures markets. Third, given the ndings from study 1, it designs a rolling quantile trading strategy that can be applied in practice. This thesis focuses on four important commodities: soybeans, wheat, corn and sugar with more than a decade (2000 to 2016) of daily frequency data, i.e. opening, closing, daily high and daily low prices, which take into account the Global Financial Crisis (GFC). The studies apply newly developed and powerful econometric methodologies. The rst study performs the cross-quantilogram (Han et al., 2016) and the stationary bootstrap (Politis and Romano, 1994) which permit the analysis of directional predictability at arbitrary quantiles and lags. The second study applies the multivariate heterogeneous autoregressive model of Corsi (2009), a model that allows the joint analysis of short- , mid- , and long-term volatilities and their interaction. The third study designs a rolling quantile trading strategy that can trade on arbitrary quantiles of the return distributions based on the direction of relevant historical spillovers. The rst study applies the cross-quantilogram with stationary bootstrap to analyse the return spillovers and directional predictability between the US and Chinese agricultural futures markets. The results show a more signi cantly positive one-day predictability from the US to China than from China to the US in the same quantiles. Moreover, the bilateral lead-lag impact between countries is stronger than the return autocorrelations. The bi-directional daily return spillovers from one country to the decomposed overnight and intraday returns show a stable structure from the US to China and a mixed pattern from China to the US among commodities. The rolling crossquantilogram shows the dynamics of the cross-country directional correlation. These ndings o er valuable insights into investor behaviour, market integration, dissimilarity, and market e ciency in both countries, and have important implications for portfolio choices and the debate on nancial market integration. The existing literature commonly documents that volatility in the US agricultural futures market results in more signi cant spillovers from the US to China than vice versa. The second study aims to provide further insights into the spillovers from China to the US, as well as the time horizon and dynamics of the bi-directional spillovers through the application of a multivariate extension of the heterogeneous autoregressive (HAR) model. The results con rm the existence of signi cant spillovers from the US to China for soybeans, wheat, corn and sugar, which are primarily generated by the shorter term volatility components in the US, and provide evidence for the increasing pricing power of the Chinese market. The ndings are robust against various speci cations and have important investment and policy implications. The third study is the rst one known to formulate and examine the pro tability of the trading strategy based on signals generated from di erent quantiles in the return distributions. The rolling quantile trading strategy is conducted on a cross market basis in relation to the US and Chinese agricultural futures over a range of holding periods (daily, intraday, and overnight) for soybeans, wheat, corn, and sugar. Overall, the greatest pro t is generated from trades based on extreme quantiles. This result highlights the value of harvesting information from the di erent parts of the return distributions which has so far been neglected in the trading strategy literature. To the best knowledge of the author, this is the rst research of its kind on the linkage between the US and Chinese agricultural futures markets. The thesis contributes to the literature on nancial market integration, futures markets, commodities market, market e ciency, predictability and food security. It has important implications for international investors as well as for programs that are aimed at food security.
View less >
Thesis Type
Thesis (PhD Doctorate)
Degree Program
Doctor of Philosophy (PhD)
School
Dept Account,Finance & Econ
Copyright Statement
The author owns the copyright in this thesis, unless stated otherwise.
Subject
Chinese agricultural futures markets
United States agricultural futures markets
Quantile trading strategies