Examination of Arbitrage Opportunities at Chinese Financial Market

The purpose of this thesis is to study arbitrage opportunities in Chinese financial markets and study how to use stock index futures and CSI 300ETF for arbitrage. This thesis uses a variety of arbitrage strategies to study arbitrage opportunities, such as geographic arbitrage, futures arbitrage, time arbitrage and other arbitrage strategies, and focuses on statistical arbitrage opportunities in China's financial market. This thesis uses two statistical arbitrage models, namely the least squares OLS constant volatility model and GARCH time-varying volatility model, select the 1-minute high-frequency trading data closing prices of stock index futures IF2101 and Huatai-Pinebridge CSI 300 ETF. Judging from the combination of traditional data and Sharpe ratio, using the GARCH model for forward arbitrage results is the best. Therefore, it is recommended that arbitragers prefer the GARCH model for the positive arbitrage operation, followed by the OLS model for the reverse arbitrage operation when conducting statistical arbitrage in China.The purpose of this thesis is to study arbitrage opportunities in Chinese financial markets and study how to use stock index futures and CSI 300ETF for arbitrage. This thesis uses a variety of arbitrage strategies to study arbitrage opportunities, such as geographic arbitrage, futures arbitrage, time arbitrage and other arbitrage strategies, and focuses on statistical arbitrage opportunities in China's financial market. This thesis uses two statistical arbitrage models, namely the least squares OLS constant volatility model and GARCH time-varying volatility model, select the 1-minute high-frequency trading data closing prices of stock index futures IF2101 and Huatai-Pinebridge CSI 300 ETF. Judging from the combination of traditional data and Sharpe ratio, using the GARCH model for forward arbitrage results is the best. Therefore, it is recommended that arbitragers prefer the GARCH model for the positive arbitrage operation, followed by the OLS model for the reverse arbitrage operation when conducting statistical arbitrage in China.154 - Katedra financívelmi dobř

Modelling dynamic financial linkages, spillover effects and volatility transmissions: empirical evidence from China and international financial markets

Over the last two decades, there has been a considerable change in the economic performance of China, making it the world’s most powerful emerging market and the second largest economy in the world. China’s stock market is now well developed and strongly influenced by global economic factors, regional financial development in Asia and local economic growth in China. Many crucial economic and financial reforms have been implemented, making the Chinese stock market more open to the world. Two well-established stock exchanges, based in Shanghai and Shenzhen are now operating with significant interdependence with other financial markets around the world. The degree of market co-movements is an essential factor for determining the diversification opportunities across different financial markets. International stock market linkages have been extensively examined by empirical literature, suggesting that financial market integration is able to influence market co-movements. Given the increased market integration between China and other financial markets, this thesis investigates the dynamic financial linkages, spillover effects and volatility transmissions among different financial markets within China and between China and global markets, as strong interdependence among financial markets could lead to higher exposure to contagious effects when one market experiences a serious crash. Furthermore, this study also provides important practical implications for investors, portfolio managers and policy-makers based on the empirical findings. The primary objective of this study is to investigate the nature and extent of market interdependence among the Chinese stock markets, the Chinese financial derivative markets and international stock markets. Various advanced econometrical models, including Vector Autoregression (VAR) models and Generalised Autoregressive Conditional Heteroscedasticity (GARCH) models, will be used to explore both return and volatility transmission mechanisms between different financial markets from China’s perspective. In order to achieve the key objective, this study conducts four inter-related research undertakings as follows: 1. An examination of spillover effect between the Shanghai and Hong Kong stock markets while evaluating the impact of the recently introduced Shanghai-Hong Kong Stock Connect; 2. An investigation of financial linkages, information transmission and market co-movement in the Asia-Pacific region; 3. The work further considers dynamic relationships between the Chinese stock market and its index futures market while evaluating the influence of Qualified Foreign Institutional Investors (QFII) scheme; and 4. An evaluation of dynamic spillovers among global oil price, equity and commodity markets in the Chinese region. The purpose of the first empirical focus is to investigate the impact of Shanghai-Hong Kong Stock Connect by analysing the dynamic interdependence between the Shanghai and Hong Kong stock markets. High-frequency data are used to deeply examine the price movement and volatility behaviours of the two markets. The newly introduced Stock Connect initiative contributes to the increasing importance of the Chinese mainland stock market. Particularly, the increased conditional variances in both stock markets together with a weak and unstable cointegration relationship are observed following the introduction of Stock Connect. The observed strengthened volatility spillover effect from Shanghai to Hong Kong indicates a leading role of the former over the latter after this financial liberalisation reform. Overall, the empirical results suggest that the opening of Chinese mainland stock market could enhance the leading power, influence the risk level and improve the market efficiency of the Shanghai stock market. The success of the Shanghai-Hong Kong Stock Connect initiative provides valuable operational experience for the forthcoming Shenzhen-Hong Kong Stock Connect. In this way, the Chinese government should continue liberalising its financial markets to improve their market efficiency. In the second empirical study, the price and volatility dynamics between China and major stock markets in the Asia-Pacific region around the Chinese stock market crash of 2015-2016 are analysed. Based on our estimation results of the Bayesian VAR and BEKK GARCH models, this study finds that price and volatility spillover behaviours are different during stable and stress periods. In particular, price spillovers from China to other regional markets are more significant during a bullish period, showing that ‘good news’ emanating from China has stronger impacts on its neighbours when China’s market increases. In the turbulent period, strong shock spillover effects from China to most Asia-Pacific stock markets and the enhanced volatility spillovers from China to the Asia-Pacific region are observed, implying an increasing degree of market interdependence across regional markets and the importance of China as a strategic financial centre in the region. The Asia-Pacific stock markets are also found to spill over their shocks to China during the crisis, showing that China is becoming more integrated with the regional financial markets. The impact of the Qualified Foreign Institutional Investors (QFII) reforms on the dynamic relationship between the Chinese stock index futures and spot markets is further examined. 5 minutes high-frequency data together with various dynamic methods including VECM, GJR, BEKK and DCC GARCH models are employed to investigate the price discovery role and volatility spillover effect. This study finds a bi-directional asymmetric lead-lag relationship between the Chinese stock index futures and its underlying markets, indicating the futures market leads the spot market significantly, but there is a weak lead from the spot market to the futures market from the perspectives of both magnitude and lasting time. It is observed that the introduction of the QFII has enhanced the price discovery role of the futures market and increased the predictive power of the futures market. In addition, the Chinese stock index futures market is found to become less volatile (risky) and probably more efficient after the introduction of QFII. The enhanced volatility spillover effect from the futures market to the spot market is evident after the participation of foreign institutional investors in trading stock index futures contracts, suggesting an improvement in information transmission running from the futures to the spot market. The dynamic conditional correlation between the futures and spot markets decreases and becomes more volatile after the introduction of QFII, implying that the futures and spot markets become less correlated after the QFII. Finally, the thesis provides a comprehensive analysis of dynamic spillover effects among the Chinese stock market, the Chinese commodity market and international oil market. Using a trivariate VAR-BEKK-GARCH model to estimate market volatility and its interactions, this study finds significant uni-directional return spillover effect from oil market to stock market, suggesting a strong dependence of the Chinese stock market on the oil market. The analysis results also indicate significant uni-directional return interaction from the Chinese stock market and global oil market to some key commodities in China. In particular, significant return contagions from the Chinese stock market to copper and aluminium futures and from oil market to silver, copper and aluminium markets are observed. The non-existence of return spillovers between gold and stock (oil) suggests the safe-haven role of the gold. In terms of the volatility spillovers, this study finds bi-directional shocks spillovers between oil and stock markets but uni-directional volatility spillovers from the oil market to the Chinese stock market. For commodities, the results show evidence of strong uni-directional shock and volatility spillovers from the stock market or oil market to some commodities. However, there are no spillover effects from all the commodity markets to either the stock market or oil market, meaning there are potential diversification benefits from the Chinese commodity markets. Finally, important implications for portfolio management and hedge strategy are provided. This research makes significant contributions to the empirical literature on the financial linkages and volatility transmissions by empirically examining the influence of several important Chinese financial liberalisation reforms and comprehensively analysing the dynamic interdependence between the Chinese stock market and its interrelated financial markets. Since understanding information transmission between financial markets is critical for both market participants and policy-makers, the results of this thesis will help to facilitate an enhanced understanding of information transmission mechanism and risk contagions. As volatility contagions greatly affect smooth functioning and economic viability of financial markets which are the major concerns of investors and policy-makers, therefore a better understanding of the drivers and origins of market volatility can assist them in the decision-making process. Policy-makers may also use this information to introduce new financial instruments, propose prudent financial regulations and implement policy tools in a timely manner. In addition, important practical implications can also be drawn from this thesis. As the findings of this thesis indicate more integration between the Chinese stock market and other markets, these markets have become more interdependent and improved their efficiency in terms of market information transmission. In addition, the increased level of financial integration also underpins cross-borders capital flow and international investment which are key drivers of local economic growth and fosters international risk management for portfolio optimisation. Consequently, it is suggested that investors and policy-makers actively monitor market movement and the degree to which China’s financial market is integrated. This will make it possible to predict future returns and volatility of other inter-related markets

Emission trading and carbon market performance in Shenzhen, China

China has developed its own domestic carbon markets by setting up emission trading schemes. This study addresses concerns about the functioning of these schemes and the financial performance of the Chinese carbon market. It aims to assess an actual outcome of this policy intervention, i.e. trading records, which were used in our analysis to examine a key financial property of the allowance-based market in Shenzhen. In a mature market, assets that incur higher risks are likely to yield higher returns, i.e. a positive relationship. To examine this property, we solicited historical data on the price and trading volume of emission allowances. We statistically estimated the degree of volatility in the Shenzhen market and its relationship with expected return premium. We found that the rate of return was negatively associated with expected risk. This stands at odds with the usual expectation in the financial market and the prediction of asset pricing theory. Also, kurtosis in trading volume was excessively high and its fluctuations were highly concentrated. We discuss these findings in terms of market liquidity and information uncertainties, and offer some policy recommendations. More regulatory attention and economic fixes are needed to improve market efficiency and eliminate sources of market distortions

Understanding the cost of carry in Nikkei 225 stock index futures markets: mispricing, price and volatility dynamics

This dissertation studies the cost of carry relationship and the international dynamics of mispricing, price and volatility in the three Nikkei futures markets - the Osaka Exchange (OSE), the Singapore Exchange (SGX) and the Chicago Mercantile Exchange (CME). Previous research does not fully consider the unique characteristics of the triple-listed Nikkei futures contracts, or the price and volatility dynamics in the three Nikkei futures exchanges at the same time. This dissertation makes a significant contribution to the existing literature. In particular, with a comprehensive new 19-year sample period, this dissertation helps deepen the understanding of the Nikkei spot-futures equilibrium and arbitrage behaviour, cross-border information transmission mechanism, and futures market integration. The first topic of the dissertation is to study the cost of carry relationship, mispricing and index arbitrage in the three Nikkei markets. The standard cost of carry model is adjusted for each Nikkei futures contract by allowing for the triple-listing nature and key institutional differences. Based on this, the economic significance of the Nikkei mispricing is explored in the presence of transaction costs. The static behaviour of the mispricing suggests that it is difficult especially for institutional investors to make arbitrage profits in the OSE and SGX, and that index arbitrage in the CME is not strictly risk-free due to the exchange rate effect. Smooth transition models are used to study the dynamic behaviour of the mispricing in the three markets. The results show that mean reversion in mispricing and limits to arbitrage are driven more by transaction costs than by heterogeneous arbitrageurs in the Nikkei markets. The second topic of the dissertation is to investigate the price discovery process in individual Nikkei markets and across the Nikkei futures markets. With smooth transition error correction models, this dissertation reports the leading role of the futures prices in the pre-crisis period and the leading role of the spot prices in the post-crisis period, in the first-moment information transmission process. Moreover, there is evidence of asymmetric adjustments in the Nikkei prices and volatilities. The cross-border dynamics suggest that the foreign Nikkei markets (the CME and SGX) act as the main price discovery vehicle, which implies the key functions of the equivalent, offshore markets in futures market globalisation. The third topic of the dissertation is to study the volatility transmission process in individual Nikkei markets and across the Nikkei futures markets, from the perspectives of the volatility interactions in and across the Nikkei markets and of the dynamic Nikkei market linkages. This dissertation finds bidirectional volatility spillover effects between the Nikkei spot and futures markets, and the information leadership of the foreign Nikkei markets (the CME and SGX) in the second-moment information transmission process across the border. It further examines the dynamic conditional correlations between the Nikkei markets. The results point to a dramatic integration process with strongly persistent and stable Nikkei market co-movements over time

Managing incentives for greenhouse gas emission reduction

The Paris Agreement sets out the goal of limiting the increase in global average temperature to within 2°C. Incentive mechanisms and low-carbon policies, such as emission trading schemes (ETS), feed-in tariffs, carbon taxation, renewable obligation and emission performance standards, are key instruments for achieving greenhouse gas emissions reduction. The cap-and-trade ETS is one of the most popular policy instruments in controlling greenhouse gas emissions. The carbon price quoted from the ETS allowances price is usually considered by investors as the economic value of carbon emissions in formulating a long-term investment decision. However, the allowances price is currently quite low across jurisdictions. Thus, in order to incentivise large-scale and long-term low-carbon investment, a clear and strong carbon pricing signal is essential. There are divergent but increasingly prevalent views that additional policies may affect carbon prices, as the emission reduction effect of parallel policies would reduce the demand for allowances in the ETS, thus lower carbon prices could hamper the ETS’s capacity to promote low-carbon technologies over the medium and long term. This PhD study investigates how parallel energy and climate policies might affect carbon pricing in ETS and illustrates stakeholders’ views on this impact. The study defines the ‘cross-over effect’ of parallel energy and climate policies. A two-stage survey, including a closed-form questionnaire followed by open interviews, was conducted to elicit views and expectations of stakeholders on one of the carbon markets in China, the Guangdong ETS pilot, with an emphasis on perspectives on how the ETS may interact with other existing or proposed low-carbon and clean energy policies. Our survey results show that academic stakeholders, more than stakeholders from other sectors, viewed the policy interactions as a significant issue for developing a carbon market in China, and there was a positive correlation between recognition of such policy interactions and the time spent on energy saving and emission reduction policies. Relatively few respondents identified correctly the fact that both increasing renewable targets and imposing a carbon tax in addition to an existing ETS would be expected to depress prices in the ETS. Apart from government respondents, all other key stakeholders generally lacked confidence in China’s carbon markets, due to their lack of knowledge and information about the market and their concerns regarding uncertainties and failures in government policy and regulation. Subsequently, an empirical study was conducted to probe the underlying rationality of pricing behaviour and the effect of policy interaction with low-carbon policy in seven ETS pilots in China using ordinary least square and event-based regression. The empirical results show that, first, crude oil and domestic liquid natural gas are positively linked to the allowance price in the Beijing, Shanghai and Guangdong pilots, while coal price lacks explanatory power. Second, extreme weather is positively correlated with Shenzhen carbon prices. Third, in contrast to existing studies, a positive correlation is found between renewable energy supply and carbon prices in the Tianjin carbon market, and low-carbon policy that intends to promote renewable energy would increase carbon prices in the Guangdong pilot. Finally, ETS regulatory events, such as the announcement on surrender date (adjustment) and offset limitation, will increase price variations in the Shenzhen and Tianjin pilots respectively. Overall, the empirical results currently indicate that ETS pilots in China are segmented, but not as rational as previous studies suggest. Finally, the potential benefits of linking emissions markets across countries and regions are well recognised. In theory, a global market provides more flexibility for parties to achieve reductions in emissions at the lowest marginal cost across all covered sectors. Therefore, quantifying the impact of emission trading market linkage would generate essential references for the forming of a global market. Driven by the above motivation, the GTAP-Energy (GTAPE) model was employed to assess the impact of carbon market linkage. Our results indicate that, although the abatement costs increase in the Chinese carbon market after the linkage, the strong and robust carbon price could give investors a correct signal on the value of carbon emission. Furthermore, a linkage between the Chinese carbon market and the international markets leads to a significantly smaller GDP reduction in China, 0.04% compared to the non-linkage scenario (0.88%). In addition, allowing multilateral trading of emissions among these countries shifts the burden of the reduction away from oil products in the relatively carbon-efficient economies towards coal in the less carbon-efficient regions. This induces a substantial reduction of the marginal abatement costs in the above economies. In summary, this PhD research investigates stakeholders’ views on the Chinese carbon market as well as interactions between energy and climate change policies; it also discovers the price drivers for carbon prices in China’s pilot ETSs and assesses the impact of including Chinese ETSs in a global emission trading system. Moving forward, as the results suggest that the Chinese pilot ETSs may not be rational and most market participants are not fully aware of the function of the carbon market since they merely fulfil the need for government. The next step would be to discover whether there is a media effect driving carbon prices

Cadres, gangs and prophets: the commodity futures markets of China

In China's market reforms, the emergence of commodity futures markets marked the way in which the country took up more sophisticated components of capitalist markets. Based on seven months of ethnographic fieldwork in 2005, this thesis is the first ethnography conducted in the commodity futures markets of China. It provides field records of the relationship between state structures, quasi-public organisations and the private sector in a post-Communist market. It shows how social groups align to form capital factions, and how these factions attempt to calculate the actions of each other. It also provides an account of how knowledge is circulated, and how reputation, authority and expertise are developed within the markets. The author argues that the notion of"performativity" can be applied to the case of Chinese futures markets. The consensus held by market actors and their subsequent actions are a major contribution to market reality. In the context of Chinese markets. political power plays a particularly crucial role-it links up a politicized feedback loop between perception, action and reality. The thesis applies the concept of technology transfer to assess whether futures markets have an inherent "script" that unfolds and is implemented under different social, cultural and political contexts. Relaxing assumptions held by neoclassical economists (such as individualized rationality), the author believes that the feedback loop of knowledge, action and reality is th e "vanilla core" of markets. One of the key factors in success in market construction is the successful implementation of s.uch feedback loops

The political economy of hedge fund regulation

The currency crises and episodes of market unrest of the 1990s sparked a series of regulatory initiatives to reform the Global Financial Architecture. One of these initiatives tackled the activities of hedge funds, a type of investment vehicle that was frequently cited as one of the causes of these crises. The key research question of this thesis is why efforts to regulate an apparently destabilising aspect of financial markets failed, despite the setting up of an ad hoc forum at the international level (the Financial Stability Forum) and various domestic initiatives in the US, the country where most hedge funds operate. The thesis develops a theoretical framework that examines this regulatory inaction through three explanatory models. The first model draws upon mainstream economic accounts and argues that the empirical evidence did not justify more interventionist public regulation of hedge funds. The second model assumes that a form of relational power has been exercised at the regulatory table: those actors with an interest in leaving hedge funds unregulated prevailed over those that favoured a more mandatory approach. The third model argues that it was not just relational power that determined outcomes, but mainly the power of the structure of meaning within which discussions took place and problems were framed. This structure of meaning led to a particular formulation of the problem at stake, which excluded other concerns and actors from the regulatory agenda. Each model is analysed for its policy implications. The first model leads to regulatory solutions that rely upon private actors' due diligence and self-assessment of risk. The second model leads to policy options that favour a greater inclusion of developing countries and other stakeholder groups in decision-making processes in global finance. The third model leads to a rethinking of the very tenets of financial market regulation and of the financial theories used to explain and govern the market. The thesis argues that the third model is better able to grasp the complexity of power beyond the seemingly technical nature of financial regulation. For this reason, it is deemed more suitable to provide policy solutions that challenge the current neo-liberal framework of regulation

Essays in Robust and Data-Driven Risk Management

Risk defined as the chance that the outcome of an uncertain event is different than expected. In practice, the risk reveals itself in different ways in various applications such as unexpected stock movements in the area of portfolio management and unforeseen demand in the field of new product development. In this dissertation, we present four essays on data-driven risk management to address the uncertainty in portfolio management and capacity expansion problems via stochastic and robust optimization techniques.The third chapter of the dissertation (Portfolio Management with Quantile Constraints) introduces an iterative, data-driven approximation to a problem where the investor seeks to maximize the expected return of his/her portfolio subject to a quantile constraint, given historical realizations of the stock returns. Our approach involves solving a series of linear programming problems (thus) quickly solves the large scale problems. We compare its performance to that of methods commonly used in finance literature, such as fitting a Gaussian distribution to the returns. We also analyze the resulting efficient frontier and extend our approach to the case where portfolio risk is measured by the inter-quartile range of its return. Furthermore, we extend our modeling framework so that the solution calculates the corresponding conditional value at risk CVaR) value for the given quantile level.The fourth chapter (Portfolio Management with Moment Matching Approach) focuses on the problem where a manager, given a set of stocks to invest in, aims to minimize the probability of his/her portfolio return falling below a threshold while keeping the expected portfolio returnno worse than a target, when the stock returns are assumed to be Log-Normally distributed. This assumption, common in finance literature, creates computational difficulties. Because the portfolio return itself is difficult to estimate precisely. We thus approximate the portfolio re-turn distribution with a single Log-Normal random variable by the Fenton-Wilkinson method and investigate an iterative, data-driven approximation to the problem. We propose a two-stage solution approach, where the first stage requires solving a classic mean-variance optimization model, and the second step involves solving an unconstrained nonlinear problem with a smooth objective function. We test the performance of this approximation method and suggest an iterative calibration method to improve its accuracy. In addition, we compare the performance of the proposed method to that obtained by approximating the tail empirical distribution function to a Generalized Pareto Distribution, and extend our results to the design of basket options.The fifth chapter (New Product Launching Decisions with Robust Optimization) addresses the uncertainty that an innovative firm faces when a set of innovative products are planned to be launched a national market by help of a partner company for each innovative product. Theinnovative company investigates the optimal period to launch each product in the presence of the demand and partner offer response function uncertainties. The demand for the new product is modeled with the Bass Diffusion Model and the partner companies\u27 offer response functions are modeled with the logit choice model. The uncertainty on the parameters of the Bass Diffusion Model and the logic choice model are handled by robust optimization. We provide a tractable robust optimization framework to the problem which includes integer variables. In addition, weprovide an extension of the proposed approach where the innovative company has an option to reduce the size of the contract signed by the innovative firm and the partner firm for each product.In the sixth chapter (Log-Robust Portfolio Management with Factor Model), we investigate robust optimization models that address uncertainty for asset pricing and portfolio management. We use factor model to predict asset returns and treat randomness by a budget of uncertainty. We obtain a tractable robust model to maximize the wealth and gain theoretical insights into the optimal investment strategies