What can we learn from past price stabilization policies and market reform in Mexico?

This paper reviews experience with policy reforms in the maize sector in Mexico, beginning in the 1980s with particular reference to impacts on price variability. It analyses Mexico’s transition from past price stabilization policies under a state-trading enterprise to market reforms implemented during the 1990s. The nature, extent, and costs to producers and consumers of maize policies is discussed for both the pre-reform and the reform periods. Although wide ranging reforms have been introduced, impacts on efficiency and fiscal outlays have been less than expected.     

2006年石油价格展望

本文对影响2006年石油价格的因素做了系统分析。认为2006年形成油价风险的主要动因已从需求的波动转向供给的波动;2006年油价将由于供求的脆弱平衡维持高位运行的格局,并且,由于供给链中潜在的危机,油价波动性将会非常大;但在全球经济增速下降、石油需求增长放缓、石油生产国家和公司仍然在努力满足市场需求、炼油瓶颈有望缓和的大背景下,油价在2006年按2005年可比价格计不会大幅上升,不会对全球经济产生重大负面影响。     

Informed and uninformed trading on the Australian dollar

Using a high-frequency data set of the spot Australian/US dollar, this study examines the distribution of quotes, spreads, and returns across the trading day. By identifying the direction of trade and the subsequent quote returns from contributing banks, the segmented nature of the market into market-makers and informed and uninformed traders is investigated. The results suggest that the economic gain possible from private information is maximised over 2 to 5 quotes and is rapidly eroded by 20 quotes (about 2 min later during busy trading times) as other new information enters the market. Also, the analysis is revealing of discontinuities in trading and the volatility of pricing across the trading day.     

金融投机、实需与国际大宗商品价格——信息摩擦视角下的大宗商品价格影响机制研究

本文实证考察了2005-2015年金融投机和实需对国际大宗商品现货价格的影响及其作用机理。首先对具有信息噪音属性的金融投机进行了明确识别。其次,从多个维度出发区分市场信息摩擦状态,定量分析不同信息摩擦环境中金融投机和实需的影响差异。研究发现:大宗商品价格在长期中由实需因素主导,短期中由金融投机主导;短期中,相对于低信息摩擦环境,在市场波动性较高、金融压力上升以及投资者情绪高涨的高信息摩擦环境中,以金融投机为主的信息噪音对大宗商品价格的影响更强。进一步分析证实,相比于低信息摩擦环境,高信息摩擦环境中金融交易者的市场份额反而降低。据此,本文提出稳定大宗商品市场的关键在于提高市场透明度,减少信息摩擦,从市场质量出发降低信息噪音的影响。     

A new assessment of economic integration in East Asia: Application of an industry-specific G-PPP model

It is well known that intra-industry trade and cross-border production networks have promoted economic growth and regional integration in East Asia. However, regional supply and production chains may have been formed differently across industries, reflecting different degrees and a different scope of regional economic linkages at an industry level. This paper makes a threefold contribution. First, to assess industry-level differences, this study adopts the generalized purchasing power parity (G-PPP) model using industry-specific producer prices. Second, the momentum threshold autoregressive (M-TAR) model is employed to allow for possible nonlinearity arising from the dynamic nature of regional economic growth and development. Third, the Granger causality test is also conducted to assess whether regional economies have autonomously integrated. The empirical results reveal that economic integration has progressed more autonomously in the electrical industry, as well as in the transportation equipment industry, as China and the ASEAN countries have become the final destination markets for finished products in these two industries.     

Information,market power,and price volatility

We consider demand function competition with a finite number of agents and private information. We show that any degree of market power can arise in the unique equilibrium under an information structure that is arbitrarily close to complete information. Regardless of the number of agents and the correlation of payoff shocks, market power may be arbitrarily close to zero (the competitive outcome) or arbitrarily large (so there is no trade). By contrast, price volatility is always lower than the variance of the aggregate shock across all information structures. Alternative trading mechanisms lead to very distinct bounds as a comparison with Cournot competition establishes.     

Consumer experiences,attitude and behavioral intention toward online food delivery (OFD) services

Prior research has mostly examined consumer attitudes toward online services/retailing in general and a few researchers have addressed consumer experiences with online food delivery (OFD) services. The purpose of this study is to examine the structural relationship between convenience motivation, post-usage usefulness, hedonic motivation, price saving orientation, time saving orientation, prior online purchase experience, consumer attitude and behavioral intention towards OFD services. The study proposes an integrative theoretical research model based on the Contingency Framework and Extended Model of IT Continuance. 224 valid questionnaires were collected to empirically test the research model using the partial least square (PLS) path modeling approach. The results imply that the proposed hypotheses were supported, except for the relationship between prior online purchase experience and post-usage usefulness. Practical implications and limitations are discussed.     

Market maker competition and price efficiency: Evidence from China

We test the relationship between market maker competition and stock price efficiency. Using the number of market makers as a proxy for competition, the results show a strong positive correlation between competition and stock price efficiency. Moreover, price efficiency is higher when competing market makers have higher research ability. We suggest that market maker competition increases price efficiency through two channels: 1) Competition decreases transaction costs, and 2) Uninformed market makers learn from orders submitted by informed market makers through competition. The latter happens only in the group of market makers with higher experiences. The results imply that the price efficiency can be improved by enhancing the competition of market makers with high research ability and experiences.     

Competition in the stock market with asymmetric information

We build a game theoretical model to examine how the level of information advantage of insiders and the competition between insiders and sophisticated investors affect stock price movements and traders’ trading strategies and profits. We show that the competition between insiders and sophisticated investors can reduce the losses of less sophisticated investors, and thus alleviates the disadvantaged position of the less sophisticated investors. Further, traders’ profits are affected by the accuracy of insiders’ private information, and the number of days that insiders have obtained the information in advance. These findings show the importance of information transparency and the role of sophisticated investors in limiting insiders’ trading advantages and mitigating the expropriation of investors by insiders.     

A neural network based price sensitive recommender model to predict customer choices based on price effect

The impact of price and price changes should not be ignored while designing algorithms for predicting customer choice. Consumer preferences should be modeled with consideration of price effects. Businesses need to consider for efficient prediction of an individual's purchase behaviour. Personalized recommendation systems have been studied with machine learning algorithms. However, the price-aware personalized recommendation has received little attention. In this paper, we attempt to capture insightful economic results considered in the marketing and economics disciplines by employing modern machine learning architecture for predicting customer choice in a large-scale supermarket context. We extract personalized price sensitivities and examine their importance in consumer behaviour. The employed data collected from a supermarket chain in Germany consists of implicit feedback based on customer-product interactions and the price of every interaction. We propose a two-pathway matrix factorization (2way-MF) model that is price-aware and tries to memorize customer-product interaction's implicit feedback. The proposed models achieve better model performance than standard Matrix Factorization models widely used in the industry. The approach was re-validated with data from supermarket chain in Taiwan. Other industries can adopt the proposed framework of modeling customer's preferences based on price sensitivity. We suggest that further research and analyses could help understand the cross-price elasticities.