Experimental evidence on trading behavior,market efficiency and price formation in double auctions with unknown trading duration

The reasons for the highly efficient market outcomes observed under the double auction remain unclear. This paper presents a series of experimental financial markets designed to investigate the importance of unknown trading period duration on trading behavior and the convergence tendencies of such markets. Using panel data techniques the results support the conclusions that individuals generally display more aggressive trading strategies, trading earlier in a period, and that markets exhibit reduced levels of informational efficiency when unknown duration is present. Markets with imperfect information structures are also studied and, in a unique result, are associated with significantly slower rates of trade, as traders become more cautious over their trading strategies. Investigation of the price formation process provides evidence that the pricing error varies over time and the estimation of a fixed effects model provides unique support that learning effects and unknown trading period duration influence the price formation process. Future refinement of theoretical models of the price formation process or institutions of exchange should recognize the effect of unknown trading period duration on market behavior, along with potential learning effects. Copyright © 2005 John Wiley & Sons, Ltd.     

Commodity-price volatility and macroeconomic spillovers: Evidence from nine emerging markets

The recent decade has witnessed wild swings in global commodity prices, with large increases preceding the Global Financial Crisis and steep declines following the crash. Many emerging markets find themselves destabilized by these fluctuations, not only when price increases lead to currency appreciations and reduced competitiveness, but also when price decreases cause capital outflows and deteriorations in the balance of payments. This study examines the volatility processes of six major commodity prices, before applying Multivariate GARCH analysis to examine spillovers among important commodity prices and output, exchange rates, interest rates and inflation in major emerging markets. While each commodity and each country behaves differently, we find that Chile is most closely tied to the copper price, and Indonesia to oil and tin, while neighbors such as Brazil and the Philippines are less affected. Perhaps surprisingly, Russia is found to be highly insulated from fluctuations in world oil prices.     

Unconventional monetary policy and financialization of commodities

Our paper has two stages of analysis. First of all, we examine whether volatility spillover between US equity and commodity markets has significantly changed with the heavy influx of index traders in commodity derivatives markets, which is a phenomenon referred to as financialization. Given that previous findings show institutional traders enter into commodity markets at high liquidity episodes, in the second stage of our analysis, we investigate the particular impact of US quantitative easing policy on spillover between commodity and US stocks. Our results indicate that during financialization period, spillover from stocks to commodities have significantly increased for almost all commodities. More importantly, we show that quantitative easing is one of the underlying reasons for increasing volatility spillover between markets. Including interest rate, currency factors or default spread does not diminish the explicit role of quantitative easing on spillovers.     

More hedging instruments may destabilize markets

This paper formalizes the idea that more hedging instruments may destabilize markets when traders have heterogeneous expectations and adapt their behavior according to performance-based reinforcement learning. In a simple asset pricing model with heterogeneous beliefs the introduction of additional Arrow securities may destabilize markets, and thus increase price volatility, and at the same time decrease average welfare. We also investigate whether a fully rational agent can employ additional hedging instruments to stabilize markets. It turns out that the answer depends on the composition of the population of non-rational traders and the information gathering costs for rationality.     

Partially overlapping time series: a new model for volatility dynamics in commodity futures

In commodity futures markets, contracts with various delivery dates trade simultaneously. Applied researchers typically discard the majority of the data and form a single time series by choosing only one price observation per day. This strategy precludes a full understanding of these markets and can induce complicated nonlinear dynamics in the data. In this paper, I introduce the partially overlapping time series (POTS) model to model jointly all traded contracts. The POTS model incorporates time‐to‐delivery, storability, seasonality and GARCH effects. I apply the POTS model to corn futures at the Chicago Board of Trade and the results uncover substantial inefficiency associated with delivery on corn futures. The results also support two theories of commodity pricing: the theory of storage and the Samuelson effect. Copyright © 2005 John Wiley & Sons, Ltd.     

Self-organization and the persistence of noise in financial markets

A dynamic model of financial markets with learning is demonstrated to produce a self-organized system that displays critical behavior. The price contains private information that traders learn to extract and employ to forecast future value. Since the price reflects the beliefs of the traders, the learning process is self-referencing. As the market learns to correctly extract information from the price, the market deemphasizes private information. Despite the convergence of the model towards the parameters producing efficiency, pricing deviations remain constant due to the increased sensitivity of the price to small errors in information extraction produced by the model's own convergence.     

Intermediaries in Entrepôt Trade: Hong Kong Re-Exports of Chinese Goods

In this paper, we examine Hong Kong's role in intermediating trade between China and the rest of the world. Hong Kong traders distribute a large fraction of China's exports. Net of customs, insurance, and freight charges, re-exports of Chinese goods are much more expensive when they leave Hong Kong than when they enter. Hong Kong markups on re-exports of Chinese goods are higher for differentiated products, products with higher variance in export prices, and products sent to China for further processing. These results are consistent with the view that traders resolve informational problems in exchange. Additional results suggest that traders price discriminate across destination markets and use transfer pricing to shift income from high-tax countries to Hong Kong.     

Forecasting stock prices with commodity prices: New evidence from Feasible Quasi Generalized Least Squares (FQGLS) with non-linearities

The complexities in modern stock markets make it imperative to unravel the possible predictors of their future values. This paper thus provides insights into the predictability of stock prices of the BRICS countries with large dependence on commodities either for foreign exchange earnings or industrial while accounting for the role of asymmetries. Essentially, empirical evidence abound for the high volatility in world commodity markets, thus making us to determine if positive and negative changes in commodity prices predict stock prices differently. In addition, unlike the traditional forecast models, our choice of forecast models additionally addresses certain statistical features, including conditional heteroskedasticity, serial dependence, persistence and endogeneity, inherent in the predictors, which have the potential of causing estimation bias. In all, we find evidence in favour of the ability of commodity prices to predict stock prices of Brazil, Russia and South Africa. Also, both the in-sample and out-of-sample forecast performances of the predicted models support asymmetries in a number of commodity prices in each of these three countries. Our results are robust to different data samples and forecast horizons.     

THE EMPIRICAL MERIT OF STRUCTURAL EXPLANATIONS OF COMMODITY PRICE VOLATILITY: REVIEW AND PERSPECTIVES

This paper presents both the history of and state‐of‐the‐art in empirical modeling approaches to the world commodity price volatility. The analysis builds on the storage model and key milestones in its development. Specifically, it is intended to offer a reader unfamiliar with the relevant literature an insight into the modeling issues at stake from both a historical and speculative viewpoint. The review considers primarily the empirical techniques designed to assess the merits of the storage theory; it does not address purely statistical approaches that do not rely on storage theory and that have been studied in depth in other streams of the commodity price literature. The paper concludes with some suggestions for future research to try to resolve some of the existing empirical flaws, and hopefully to increase the explanatory power of the storage model.     

经济全球化背景下国家矿产资源安全研究——基于自由贸易理论及我国当前贸易结构和贸易形势的考量

矿产资源贸易出于需求,而表现为价格差异导致.伴随经济全球化过程,掩盖在自由贸易体制下世界各主要工业国对矿产资源的争夺,是矿产资源在世界范围内配置的实质.获得商品定价权是取得矿产资源贸易有利地位的关键,从而提高本国矿产资源的安全程度.本文基于自由贸易理论,结合我国当前的贸易结构和贸易形势,研究我国矿产资源安全的现状,进而对确保矿产资源安全提出相应的对策建议.     

Commodity market reform in Africa: some recent experience

Since the early 1980s, dramatic changes in export commodity markets, shocks associated with resulting price declines and changing views on the role of the state have ushered in widespread reforms to agricultural commodity markets in Africa. The reforms significantly reduced government participation in the marketing and pricing of commodities. This paper examines the background, causes, process and consequences of these reforms and derives lessons for successful reforms from experiences in markets for four commodities important to Africa—cocoa, coffee, cotton, and sugar. The commodity focus of the paper highlights the special features associated with these markets that affect the reform process. The paper complements the current literature on market reforms in Africa, where grain market studies are more common. We suggest that the types of market interventions prior to reform are more easily classified by crop than by country. Consequently, there are significant commodity-specific differences in the initial conditions and in the outcomes of reforms related to these markets. However, there are general lessons as well. We find that the key consequences of reform have been significant changes in or emergence of marketing institutions, and a significant shift of political and economic power from public to private sector. In cases where interventions were greatest and reforms most complete, producers have benefited from receiving a larger share of export prices. Additionally, we conclude that the adjustment costs of reform can be reduced in most cases by better understanding the detailed and idiosyncratic relationships between the commodity subsector, private markets, and public services. Finally, while there are significant costs to market-dependent reforms, experiences suggest that they are a necessary step toward a dynamic commodity sector based on private initiative. Indeed, this is particularly true in countries and sectors where interventions were greatest and market-supporting institutions the weakest.     

股价波动源模型下欧式下出局期权的鞅定价

机游走模型(Random Walk)和对数正态分布模型是两种最常见的描述股票价格的模型,但是这两种都存在着一定的缺陷,距离实际上的波动还具有较大的差距。波动源模型更全面的考虑了大量散户交易者对股票价格的影响,以及其他的一些因素,能够更加接近实际的描述出股票的价格变动以及波动现象.在股票价格波动源模型下,利用Martingale Pricing方法推导出欧式下出局期权(买权)的定价公式.作为特例,同时得到了传统的对数正态分布模型下欧式下出局期权的定价公式。     

Modelling the conditional volatility of commodity index futures as a regime switching process

Commodity index futures offer a versatile tool for gaining different forms of exposure to commodity markets. Volatility is a critical input in many of these applications. This paper examines issues in modelling the conditional variance of futures returns based on the Goldman Sachs Commodity Index (GSCI). Given that commodity markets tend to be ‘choppy’ (Webb, 1987 ), a general econometric model is proposed that allows for abrupt changes or regime shifts in volatility, transition probabilities which vary explicitly with observable fundamentals such as the basis, GARCH dynamics, seasonal variations and conditional leptokurtosis. The model is applied to daily futures returns on the GSCI over 1992–1997. The results show clear evidence of regime shifts in conditional mean and volatility. Once regime shifts are accounted for, GARCH effects are minimal. Consistent with the theory of storage, returns are more likely to switch to the high‐variance state when the basis is negative than when the basis is positive. The regime switching model also performs well in forecasting the daily volatility compared to standard GARCH models without regime switches. The model should be of interest to sophisticated traders who base their trading strategies on short‐term volatility movements, managed commodity funds interested in hedging an underlying diversified portfolio of commodities and investors of options and other derivatives tied to GSCI futures contracts. Copyright © 2001 John Wiley & Sons, Ltd.     

Adverse effects of leverage and short-selling constraints in a financial market model with heterogeneous agents

This paper investigates the impact of leverage and short-selling constraints on financial market stability. Investors׳ demand is modelled in a well-known asset pricing model with heterogeneous beliefs. In particular, I generalise the heterogeneous agents model of Brock and Hommes (1998) and Anufriev and Tuinstra (2013) to allow for leverage constraints as well as a short-selling tax. I consider two examples of adaptive belief systems describing the coevolution of prices and investors׳ beliefs. First, if the market is inhabited by fundamentalist and chartist traders, demand constraints have potential adverse effects and may restrict the stabilising fundamentalist strategy such that mispricing and price volatility increase. Second, if the market is inhabited by fundamentalists, optimists and pessimists with fixed beliefs, demand constraints drive down price volatility, but mispricing remains. The results suggest the stabilising effects of demand constraints in financial markets are limited. Only if asset prices are too high compared to fundamentals, policy makers should consider constraining leverage ratios in order to deflate financial bubbles.     

The impact on the pricing process of costly active management and performance chasing clients

One of the necessary features of markets to produce efficient pricing is competition between information-based investors who quickly impound new information into price. However, a significant proportion of funds invested in today’s equity markets are in the hands of managers who pursue a style that utilises little or none of the available information. We simulate such a market where the funds are being managed using the following three investment styles: fundamental, momentum and index. We confirm that the major pricing anomalies that have been highlighted previously in the literature are a natural consequence of competition between managers utilising these three investment styles. More importantly, we show that this situation is unlikely to change as long as markets continue to be dominated by costly active managers with clients who pursue outperformance.     

Option pricing with discrete time jump processes

In this paper we propose new option pricing models based on class of models with jumps contained in the Lévy-type based models (NIG-Lévy, Schoutens, 2003, Merton-jump, Merton, 1976 and Duan based model, Duan et al., 2007). By combining these different classes of models with several volatility dynamics of the GARCH type, we aim at taking into account the dynamics of financial returns in a realistic way. The associated risk neutral dynamics of the time series models is obtained through two different specifications for the pricing kernel: we provide a characterization of the change in the probability measure using the Esscher transform and the Minimal Entropy Martingale Measure. We finally assess empirically the performance of this modelling approach, using a dataset of European options based on the S&P 500 and on the CAC 40 indices. Our results show that models involving jumps and a time varying volatility provide realistic pricing and hedging results for options with different kinds of time to maturities and moneyness. These results are supportive of the idea that a realistic time series model can provide realistic option prices making the approach developed here interesting to price options when option markets are illiquid or when such markets simply do not exist.     

COMMODITY MARKET REGULATION AFTER FINANCIAL CRISIS: A COMPARATIVE APPROACH

The United States Federal Government has imposed remarkably similar regulations on commodity markets after financial crises, particularly after the Great Depression and the recent financial crisis beginning in 2007. A comparison of these two great economic recessions will help identify the changes in commodity regulation policy over the past century.     

Multidimensional noise and non-fundamental information diversity

This paper relaxes the common assumption of the standard competitive noisy rational expectations framework that noise is one-dimensional. Within an environment characterized by multidimensional noise, I explore the strategic interactions between different traders that are informed about different components of the noise inherent in the market price. If noise is two-dimensional, several new types of complementarities in traders’ interactions arise that cannot be studied in the classical one-dimensional framework. The higher-dimensional case uncovers that higher dimensionality of noise mitigates the possibility of a market breakdown by weakening adverse selection. On the basis of the theoretical results, I discuss some predictions and implications concerning the effects of the increased usage of “payment for order flow” in financial markets.     

Dependent relationships between Chinese commodity markets and the international financial market: Evidence from quantile time-frequency analysis

In this article, the quantile time–frequency method is utilized to study the dependence of Chinese commodities on the international financial market. The impacts of risk management and diversification benefits of different portfolios are examined by calculating the reduction in downside risk. Moreover, we estimate and compare Sharpe Ratios (SRs) and Generalized Sharpe Ratios (GSRs) based on the frequencies of the investigated portfolios. Our empirical results reveal a strong asymmetric response from Chinese commodity markets. Specifically, we find that gold is a safe-haven asset, and due to negative correlations found at lower quantiles in medium and long term, an increase in the USD index damages bull commodity markets but boosts bear conditions under long-term investments, and negative (positive) tail correlations with interest rates (IRs) in bull (bear) markets are observed. It is proven that WTI can decrease short-run risks while USD and GOLD are more efficient in the diversification of downside risk. Adding international commodities may not improve the returns of Chinese commodities at given risk levels in the short and medium term through SRs and GSRs. In brief, investors should consider these dependence structures and modes of risk management in terms of time and frequency.     

Multi-scale systemic risk and spillover networks of commodity markets in the bullish and bearish regimes

This paper proposes a new network topology approach based on the STVAR model to identify asymmetric impacts of market conditions on multi-scale systemic risk spillovers of commodity markets. The results show that bearish market conditions enlarge low-frequency systemic risk spillovers in commodity markets, and bullish market conditions have more striking impacts on high-frequency systemic risk spillovers. Furthermore, the center of risk spillover networks varies across the market conditions and frequencies. Specifically, at the high-frequency level, sugar is the largest risk transmitter in bad regimes, and heating oil is in the center of the network in good regimes. At the intermediate frequency level, soybean becomes a more important risk transmitter in both regimes. In other cases, heating oil is the center of risk spillover networks.