基于贸易货流特征的中欧班列货运经济性研究

针对中欧班列发展的问题,从中国与欧洲、日韩与欧洲各国的贸易特征入手,分析贸易品类、货物流向、货物规模;基于不同运输方式的运费、运输周期构建经济分析模型,测算符合铁路运输经济性的货物特征,以及国际贸易中具备铁路运输经济性的货物总量规模,进而指导中欧班列实现更符合市场规律的高效发展。     

Bilateral trade between India and Bangladesh: A general equilibrium approach

India and Bangladesh have pursued policies of trade liberalization since the early 1990s. However, owing to the differential speeds of opening up, Bangladesh's bilateral trade deficit with India widened substantially over the years. This aggravated the economic and the political tensions between the economies. It has been held that promotion of free trade between the two economies may enhance the trade and hence economic cooperation between them. Against this backdrop the present paper proposes a theoretical framework that provides a general equilibrium determination of the commodity pattern of trade and hence locates the comparative advantages of the economies. The empirical implementation of the model considers trade in 25 sectors comparable in the input–output tables of the economies. The study isolates the gains from free trade accruing to either economy. The paper also explores the pattern of bilateral trade when each economy produces goods by utilizing their own as well as the other country's technology. The gains from this trading arrangement are also isolated.     

Sacred alliance or pact with the devil? How and why social enterprises collaborate with mainstream businesses in the fair trade sector*

Abstract

This paper uses institutional theory to highlight different patterns of cross-sector collaboration from the perspective of social enterprises. Specifically, it explores how and why social enterprises interact with mainstream businesses and to what extent their collaboration patterns reflect a vision of how their social mission should be implemented and institutionalized. The empirical analysis is derived from a qualitative study of ‘fair trade’ – a hybrid model created by social enterprises and using market mechanisms to support small-scale producers in developing countries and to advocate for changes in international trading practices. The findings highlight three strategies used by fair trade social enterprises to manage their interactions with mainstream businesses: sector solidarity, selective engagement, and active appropriation. This paper suggests that each strategy is motivated by a different vision of how best to articulate the social mission of fair trade via specific types of collaborations. It also notes how each vision has a distinct pattern of institutionalization at the field level. This paper adds to the emergent literatures on social enterprise and social entrepreneurship, fair trade, cross-sector collaboration and hybrid organizing.     

The influence of seller learning and time constraints on sequential bargaining in an artificial perishable goods market

This paper investigates the formation of prices in a perishable goods market where agents bargain repeatedly through pair-wise interactions. After extensive field observations, we chose to focus on two aspects that seem important to actors of this market: the passage of time and update in judgement when gathering information. The main feature of the market is that a seller bargaining with a buyer has incomplete information about buyer's willingness to pay and is not sure how her trading partner will evaluate an offer or compare it with other options. On the other hand, buyers have limited time to look for goods and cannot meet all possible sellers before making a decision. Hence agents cannot calculate the best price to offer but receive information through limited interactions, and use this information to choose their actions.An agent-based model was built to represent a framework that mimics the observed market institution and where agent's possible behaviors and learning was made as consistent as possible with gathered data. Simulations were run, first for sensitivity analysis concerning main parameters, then to test the dependance of agents’ learning to (a) the time buyers can spend on the market and (b) the frequency of update in learning by sellers. To validate the model, features produced by the simulated market are compared to the stylized facts gathered for negotiation about four goods. We reproduce the main features of the data on the dynamics of offers, transaction prices and agents’ behavior during the bargaining phases.     

Retail investors’ trading and stock market liquidity

The paper investigates the relation between retail investors’ participation in trading and aggregate stock market liquidity. The findings show a positive and significant relation between retail investors’ trading and stock market liquidity. Examination of the determinants of retail investors’ trading reveals that, on average, retail investors with more diversified trading activity tend to trade when liquidity is higher, the frequency of their arrival to the market is not affected by the level of liquidity, and retail investors are willing to trade at a lower liquidity level as sellers than as buyers. Moreover, retail investors’ trading does not create price noise at the aggregate market level. Overall, the evidence suggests that retail investors contribute to market quality.     

Stock prices and the location of trade: Evidence from China-backed ADRs

This study examines whether the trading location affects equity returns of China-backed American Depository Receipts (ADRs) traded in the US. If International Financial Markets are integrated, stock prices should be affected only by their fundamentals; otherwise, stock prices may also be affected by their trading locations/investor sentiment. We find that China ADRs’ returns are affected more by the US market fluctuations than by Chinese market returns. We interpret the results as suggesting that International Financial Markets are at least partially segmented and country-specific investor sentiment affects stock prices.     

Noise Trading and the Management of Operational Risk; Firms,Traders and Irrationality in Financial Markets*

abstract Efficient market models cannot explain the high level of trading in financial markets in terms of asset portfolio adjustment. It is presumed that much of this excessive trading is irrational ‘noise’ trading. A corollary is that there must either be irrational traders in the market or rational traders with irrational aberrations. The paper reviews the various attempts to explain noise trading in the finance literature, concluding that the persistence of irrationality is not well explained. Data from a study of 118 traders in four large investment banks are presented to advance reasons why traders might seek to trade more frequently than financial models predict. The argument is advanced that trades do not simply occur in order to generate profit, but it does not follow that such trading is irrational. Trading may generate information, accelerate learning, create commitments and enhance social capital, all of which sustain traders' long term survival in the market. The paper treats noise trading as a form of operational risk facing firms operating in financial markets and discusses approaches to the management of such risk.     

Transaction taxes, greed and risk aversion in an agent-based financial market model

Recent agent-based financial market models came to the result that taxing financial transactions does not per se increase financial stability and that the response of volatility and misalignments to rising tax rates seem to be u-shaped. Moreover, greed and the risk appetite of traders are often blamed for financial instability and there is no evidence how greed and risk aversion affect the effectiveness of regulations in financial markets. We aim to add to this gap in the literature by analyzing how the effectiveness of transaction taxes depend on different behavioral patterns within an agent-based framework. Our simulations indicate that a tax rate of 0.1% demarcates the stabilizing tax regime from the destabilizing one. We figure out that transaction taxes are less effective, either when chartists trade more aggressively, fundamentalists trade less aggressively, agents switch more frequently between trading strategies or only have short memory in their fitness measures. Lower risk aversion of agents, however, makes higher tax rates more effective as indicated by a flatter volatility response curve. We conclude that additional regulations should concentrate on the traders’ responsibilities for their risk-exposure.     

Inferring trader behavior from transaction data: A trade count model

We present a model that uses trade counts to infer the arrival of private news and the probability of informed trading (PIN). Although similar in approach, our model avoids problems with factor-driven biases and standard errors associated with estimating the buy-sell model of Easley et al. (1996). In particular, tests using the probability of informed trading may suffer from spurious correlations between the Easley et al. (1996) PIN and firm or market characteristics. Results for our model suggest that trade counts, independent of trade direction, are able to capture important features of a firm’s information environment. (JEL C51, D82)     

Structural estimation of behavioral heterogeneity

We develop a behavioral asset pricing model in which agents trade in a market with information friction. Profit‐maximizing agents switch between trading strategies in response to dynamic market conditions. Owing to noisy private information about the fundamental value, the agents form different evaluations about heterogeneous strategies. We exploit a thin set—a small sub‐population—to point identify this nonlinear model, and estimate the structural parameters using extended method of moments. Based on the estimated parameters, the model produces return time series that emulate the moments of the real data. These results are robust across different sample periods and estimation methods.     

Speculative behavior and the dynamics of interacting stock markets

We develop a simple agent-based financial market model in which heterogeneous speculators apply technical and fundamental analysis to trade in two different stock markets. Speculators׳ strategy/market selections are repeated at each time step and depend on predisposition effects, herding behavior and market circumstances. Simulations reveal that our model is able to explain a number of nontrivial statistical properties of and between international stock markets, including bubbles and crashes, fat-tailed return distributions, volatility clustering, persistent trading volume, coevolving stock prices and cross-correlated volatilities. Against this background, our model may be deemed to have been validated.     

Consuming durable goods when stock markets jump: A strategic asset allocation approach

In this paper we show the impact of considering jumps in the return process of risky assets when deciding how to invest and consume throughout time. Agents derive their utilities from consumption over time. We consider an agent that invests in the financial market and in durable and perishable consumption goods. Assuming that there are costs for transacting the durable good, we show that an agent who does not consider the possibility of jumps will make suboptimal decisions, not only regarding the fraction of wealth invested in the stock market, but also with respect to the timing for trading on the durable good. Furthermore we also show that jumps cause a non-obvious asymmetric impact on the thresholds that lead the consumer to trade the durable good, even when the jump distribution is symmetric.     

Matching, search and intermediation with two-sided heterogeneity

This paper analyzes the role played by intermediation in a decentralized market, where trade is carried out through bilateral bargaining, and where the bargaining outcome depends on the process of search for suitable trading partners. To this purpose, a monopolistic intermediary is embedded in a dynamic model of random-matching and two-sided search with heterogeneous agents. It is shown that intermediation might speed up the matching process and might induce separation of the agents’ types, thus enhancing sorting efficiency with respect to a pure search market, where sorting externalities cause multiplicity of equilibria to arise and determine inefficient matching outcomes. Nonetheless, intermediation might also introduce frictions that do not exist in a decentralized market operating in isolation, and this impairs efficiency.      

Optimal selling mechanisms for multiproduct monopolists: incentive compatibility in the presence of budget constraints

We analyze the nonlinear pricing problem faced by an incomplete information monopolist operating in a market populated by agents with budget constraints. We show that if other goods are available and if the monopolist's goods are nonessential relative to other goods, then there exists an optimal, individually rational, and incentive compatible selling mechanism for the monopolist (Theorem 1). Moreover, we show that a solution to all such nonlinear pricing problems exists if and only if the monopolist's goods are nonessential (Theorem 2). In the absence of nonessentiality, we show that if the monopolist's profit function is independent of quantity (e.g., if all costs are fixed), then an optimal selling mechanism exists (Theorem 3). Finally, we show that if there is reporting (of types by agents) and partial recognition of types (by the monopolist), then an optimal selling mechanism exists, even in the absence of nonessentiality, provided agents' utility functions are affine and continuous in goods (Theorem 4).     

A Pilot Exploration of Random Period Duration in Experimental Financial Markets: A Treatment Variable?

This exploratory paper reports a pilot study of the impact of random period duration on the trading behaviour observed in experimental financial markets. Results reported in earlier experimental studies, many of which report a flurry of trade just prior to the end of a trading period, may have been influenced by knowledge of trading period duration. These exploratory findings suggest that the introduction of random period duration results in an increased volume of trade early in a period, which may then impinge upon the informational efficiency of the asset markets. These findings necessitate that future refinements to theoretical models of bid, ask and transaction price behaviour in double auctions explicitly address the influence of known period duration. However, no significant difference between the two markets is found with respect to allocational efficiency. © 1997 John Wiley & Sons, Ltd.     

货押贸易融资风险分析及对策

近年来,我国经济实力不断提升,贸易量持续上涨。随着货物贸易市场的扩大,从事货物贸易的企业所面临的一大问题就是如何获取资金以保障正常经营。不断增大的融资需求使货押逐渐成为企业向金融机构申请融资时一项主要的担保措施。货押贸易融资业务不断增加的同时,其风险不断暴露。论文从货押贸易融资的概念与方式入手,针对货押贸易融资所产生的政策法律风险、权属风险、重押风险等,提出完善押品登记手段、细化押品监管及货押贸易融资业务的管理流程、制定标准化监管流程、搭建监管信息共享平台等措施建议。     

沪深300股指期货在现货交易和非交易时段交易特征的比较研究

我国沪深300股指期货交易2010年4月16日正式推出,但沪深300股指期货市场与沪深300现货市场的交易时间存在显著的差异,即相对于股票现货市场,沪深300股指期货市场提前15分钟开盘,延迟15分钟收盘。运用日内分笔数据和分钟数据,对沪深300股指期货不同交易时段的交易特征进行比较。研究表明,不同交易时段知情交易者市场参与度存在明显差异,提前交易时段知情交易的概率最高,现货交易时段次之,延迟交易时段最低;沪深300股指期货在开盘时段的交易提供了较大的价格发现,特别是开盘的第一笔交易包含有大量的私有信息,价格贡献最大;提前交易时段私有信息的价格发现贡献度最高;尽管提前交易时段的交易提供了较大的价格发现,但定价效率较低。     

江苏碳排放期权价格测算及清洁发展机制对策——基于B-S模型的定价分析

发展低碳经济,提升碳交易与清洁发展能力已是大势所趋。文章通过对CDM项目进展、经济基础与资源禀赋等方面对江苏省内企业发展碳交易市场进行潜力分析后发现,该地区存在巨大的节能减排空间。实证研究中将实物期权理论引入碳交易机制,借助B-S模型及欧盟碳交易市场相关数据构造出碳排放期权定价模型,根据欧盟与江苏经济发展的相似性折扣给出江苏地区碳交易的市场定价,同时,围绕技术、管理及政策三个层面提出该地区CDM机制的新型思路建议,旨在为江苏企业在清洁发展机制下逐步开发完善碳交易市场提供有利依据与参考。     

我国31个省份贸易强省建设实证分析

运用因子分析法和分类聚合,探讨我国31个省份的贸易指标,实证分析贸易强省建设情况。得到6个指标大类:贸易规模指标、贸易前景指标、贸易贡献指标、贸易分布指标、贸易优势指标及贸易市场指标。其中,贸易规模指标对贸易强省建设的影响率最高。京、沪、粤、浙及苏等省份居于全国贸易层级的前列,其贸易能力高于其他地区。针对贸易能力不高的省份,应根据其实际情况及规划目标,从各指标大类中的各细化指标出发,补齐短板。     

东盟对外FTA战略的有效性:基于商品竞争性与互补性的分析

以东盟与中国、澳大利亚新西兰、韩国、印度、日本5个代表性经济体的双边贸易为对象,通过贸易密集度指数、修正后显性比较优势指数、相对贸易竞争指数和贸易互补性指数的详细测算,分析比较这些经济体与东盟可贸易品的竞争优势及互补程度,以此对当前东盟对外自由贸易区战略作出科学评价,也为今后本地区区域经济一体化树立参照。