Dynamic Price Adjustment in Spatially Separated Food Markets with Transaction Costs

This paper presents an alternative technique to analyze market integration using price data, linking the cointegration version of Ravallion's dynamic model with the recent switching regression approaches as in Baulch's Parity Bounds Model. The Band- Threshold Autogression (Band-TAR) model allows for dynamic analysis of the adjustment process as well as for trade discontinuities and transaction costs, thereby avoiding some of the unrealistic assumptions of both approaches. We apply the model to the same rice price data on the Philippines as Baulch and find that, contrary to Baulch, the efficient arbitrage conditions are often not satisfied and unexploited profits are common, albeit relatively small. At least on one important trade route, we find evidence of substantial inefficiences.

Bayesian Cointegrated Vector Autoregression models incorporating Alpha-stable noise for inter-day price movements via Approximate Bayesian Computation

We consider a statistical model for pairs of traded assets, based on a Cointegrated Vector Auto Regression (CVAR) Model. We extend standard CVAR models to incorporate estimation of model parameters in the presence of price series level shifts which are not accurately modeled in the standard Gaussian error correction model (ECM) framework. This involves developing a novel matrix variate Bayesian CVAR mixture model comprised of Gaussian errors intra-day and Alpha-stable errors inter-day in the ECM framework. To achieve this we derive a novel conjugate posterior model for the Scaled Mixtures of Normals (SMiN CVAR) representation of Alpha-stable inter-day innovations. These results are generalized to asymmetric models for the innovation noise at inter-day boundaries allowing for skewed Alpha-stable models. Our proposed model and sampling methodology is general, incorporating the current literature on Gaussian models as a special subclass and also allowing for price series level shifts either at random estimated time points or known a priori time points. We focus analysis on regularly observed non-Gaussian level shifts that can have significant effect on estimation performance in statistical models failing to account for such level shifts, such as at the close and open of markets. We compare the estimation accuracy of our model and estimation approach to standard frequentist and Bayesian procedures for CVAR models when non-Gaussian price series level shifts are present in the individual series, such as inter-day boundaries. We fit a bi-variate Alpha-stable model to the inter-day jumps and model the effect of such jumps on estimation of matrix-variate CVAR model parameters using the likelihood based Johansen procedure and a Bayesian estimation. We illustrate our model and the corresponding estimation procedures we develop on both synthetic and actual data.Comment: 30 page

Review of stochastic differential equations in statistical arbitrage pairs trading

The use of stochastic differential equations offers great advantages for statistical arbitrage pairs trading. In particular, it allows the selection of pairs with desirable properties, e.g., strong mean-reversion, and it renders traditional rules of thumb for trading unnecessary. This study provides an exhaustive survey dedicated to this field by systematically classifying the large body of literature and revealing potential gaps in research. From a total of more than 80 relevant references, five main strands of stochastic spread models are identified, covering the ‘Ornstein–Uhlenbeck model’, ‘extended Ornstein–Uhlenbeck models’, ‘advanced mean-reverting diffusion models’, ‘diffusion models with a non-stationary component’, and ‘other models’. Along these five main categories of stochastic models, we shed light on the underlying mathematics, hereby revealing advantages and limitations for pairs trading. Based on this, the works of each category are further surveyed along the employed statistical arbitrage frameworks, i.e., analytic and dynamic programming approaches. Finally, the main findings are summarized and promising directions for future research are indicated

DISTINGUISHING BETWEEN EQUILIBRIUM AND INTEGRATION IN MARKETS ANALYSIS

This paper introduces a new market analysis methodology based on maximum likelihood estimation of a mixture distribution model incorporating price, transfer cost, and trade flow data. Not only does this method obviate statistical problems associated with conventional price analysis methods, it also permits differentiation between market integration and competitive market equilibrium. The model generates estimates of the frequency of alternative regimes, combinations of which provide useful, intuitive measures of intermarket tradability, competitive market equilibrium, perfect integration, segmented equilibrium, and segmented disequilibrium. An application to trade in soybean meal among Pacific Rim economies demonstrates the usefulness of the method.international trade, law of one price, market integration, spatial equilibrium, International Relations/Trade,

Exchange Rate Dynamics, Intervention and Regime Shifts in China: A Market Microstructure Analysis

This thesis applies the market microstructure approach to investigate exchange rate dynamics, intervention and regime shifts in China’s exchange rate system. This research first examines exchange rate determination and dynamics from a microstructural perspective. An index of order flow is constructed in the Chinese context to reflect excess demand pressure. A VAR model is then estimated to explore to what extent order flow may explain long-term determination and short-term fluctuations of the renminbi exchange rate. Focusing on the cointegrating relationship between cumulative order flow and the exchange rate of the RMB against the US dollar, this research find that in the new Chinese exchange rate regime in place since 2005, order flow is able to explain a significant part of fluctuations in the RMB-dollar exchange rate. China is internationally noted for its intervention in the foreign exchange market. Based on high-frequency data this thesis adopt a multi-dimensional approach to explore how interventions are conducted in China, what the consequences are, and to what extent they are effective. This thesis identify evidence of China’s extensive intervention and find that the authority is more likely to intervene to curb devaluation. Decomposition analysis shows that the direct impact of intervention on the exchange rate is more important than the impact via order flow. Intervention via the central bank’s involvement in trading is effective in influencing both the exchange rate and order flow, but tends to increase volatility. Intervention by the central bank’s varying the central parity condition plays some role in ‘leaning against the wind’, but cannot reverse the trend. China announced the reform of its exchange rate system in 2005. The reform was disrupted by the breakout of the global financial crisis around 2008, but was reiterated in 2010. The thesis analyses the behaviour of China’s exchange rate policy since then. This research detect 21st June 2010 as the date of regime shift, since when the RMB has been allowed greater room for flexibility, and consequently exchange rate volatility has increased. This research unearths evidence confirming that the renminbi no longer pegs only to the dollar. During the crisis period, deviations from the central parity rate (CPR) increase the possibility of government intervention, and the intervention correlates with bid-ask exchange rate spread. The Chinese monetary authority is found to act to keep the exchange rate stable. In the post-crisis period, the correlation becomes time-varying and the government prefers the RMB exchange rate to gradually appreciate. This research finds evidence that appreciation of the RMB exchange rate is order flow driven during the post-crisis period. There is a significant negative currency exposure during the financial crisis, caused by changes in the RMB exchange rate, indicating that the Chinese stock market exhibits a negative reaction in the period. However, no significant impact is found in the post- crisis period. In order to modify the exchange rate exposure to fluctuations of the US dollar, the Chinese government seems to have adopted the relatively more efficient exchange rate regime to handle the effects of the global financial crisis

A hidden Markov model for statistical arbitrage in international crude oil futures markets

In this work, we study statistical arbitrage strategies in international crude oil futures markets. We analyse strategies that extend classical pairs trading strategies, considering the two benchmark crude oil futures (Brent and WTI) together with the newly introduced Shanghai crude oil futures. We document that the time series of these three futures prices are cointegrated and we model the resulting cointegration spread by a mean-reverting regime-switching process modulated by a hidden Markov chain. By relying on our stochastic model and applying online filter-based parameter estimators, we implement and test a number of statistical arbitrage strategies. Our analysis reveals that statistical arbitrage strategies involving the Shanghai crude oil futures are profitable even under conservative levels of transaction costs and over different time periods. On the contrary, statistical arbitrage strategies involving the three traditional crude oil futures (Brent, WTI, Dubai) do not yield profitable investment opportunities. Our findings suggest that the Shanghai futures, which has already become the benchmark for the Chinese domestic crude oil market, can be a valuable asset for international investors

Real convergence and regime-switching among EU accession countries

Real convergence among the ten EU 2004 accession economies is investigated with respect to long-run real interest parity. We employ a novel approach where unit-root tests for real interest differentials are embedded within a Markov regime-switching framework. Whereas standard univariate unit-root tests provide mixed support for parity, we find parity is present in all cases where differentials either switch between regimes of stationary and non-stationarity behaviour, or between alternative regimes of stationarity characterized by differing degrees of persistence. Further insights are obtained from the inferred probabilities of being in each regime, and the regime-switching nature of the differential variances

The cointegrating relationship in Asian markets with applications to stock prices, exchange rates and interest rates

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The aim of this research is to investigate the long-run co-integrating relationships in the Asian markets. Our research focuses on 4 areas; pair trading, out-of-sample forecasting, testing the unbiased forward exchange rate hypothesis and testing the expectation hypothesis of the term structure of interest rates. The introduction is provided in chapter one. In chapter two, we develop a pairs trading strategy using individual stocks listed in the Stock Exchange of Thailand. Engle and Granger approach is used to identify the potential pairs that are cointegrated. The results show that pairs trading strategy is profitable in this market. Chapter three examines the forecasting performance of the error correction model on daily share price series from the Stock Exchange of Thailand. The disequilibrium term is classified into “correct” and “mix” sign based on Alexander (2008)’s criterion; the results indicate that the error correction component can help to improve the predictability in the long run. Chapter four tests the unbiased forward rate hypothesis of 11 Asian exchange rates using linear conventional regression, ECM and logistic smooth transition regression with the forward premium as the transition variable. Out-of-sample forecasting results also suggest that inferior forecasting performance could be obtained as a result of using linear models. In chapter five, we investigate the expectation hypothesis of the term structure of interest rate for four Asian countries. We employ linear models and nonlinear approaches that allow to capture asymmetric and symmetric adjustments. The result also indicates that the term structure can be better modeled by means of LSTR models. The forecasting exercise also confirms these findings