Han Qiao

Cooperation in two-stage games on undirected networks

In the paper, cooperative two-stage network games are studied. At the first stage of the game, players form a network, while at the second stage players choose their behaviors according to the network realized at the first stage. As a cooperative solution concept in the game, the core is considered. It is proved that some imputations from the core are time inconsistent, whereas one can design for them a time-consistent imputation distribution procedure. Moreover, the strong time consistency problem is also investigated.

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets.

Abstract This paper proposes a new time‐varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov‐switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time‐varying causal effects. Time‐varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.

Transformation of Characteristic Function in Dynamic Games

Abstract The problem of transformation of characteristic function, using a transformation matrix and connected with associated consistency of a solution concept, was investigated for the class of so-called “one-shot” games. The same problem also arises in dynamic games when players move step by step along the cooperative trajectory. In this case the evolution of characteristic function is, in general, unpredictable and may lead to time-inconsistency of a fixed cooperative solution concept. There are different approaches to overcome this problem based on transformation of characteristic function. In this paper, the step-wise transformation is used, which is a generalization of similar transformation of characteristic function for dynamic games with perfect information, and it leads to the time-consistent solution. The general form of such transformation is proposed.

A Dynamic Formation Procedure of Information Flow Networks

Abstract A characterization of the equilibrium of information flow networks and the dynamics of network formation are studied under the premise of local information flow. The main result of this paper is that it gives the dynamic formation procedure in the local information flow network. The research shows that core-periphery structure is the most representative equilibrium network in the case of the local information flow without information decay whatever the cost of information is homogeneous or heterogeneous. If the profits and link costs of local information flow networks with information decay are homogeneous empty network and complete network are typical equilibrium networks, which are related to the costs of linking.

Platform Competition in Peer-to-Peer Lending Considering Risk Control Ability

Abstract As a new e-commerce phenomenon in financing, peer to peer (P2P) lending has received increased attention recently. For P2P lending platforms, risk control ability (i.e., the ability to accurately assess and screen borrowers to control the credit risk of loans) is a competitive differentiator. The paper models a three-stage game to investigate optimal risk control ability and corresponding optimal prices of P2P lending platforms under different tariffs and agents’ homing choices. Risk-price coefficients for lenders and borrowers are introduced to measure the impact of risk control ability on prices, where higher risk-price coefficients indicate that prices are more sensitive to risk control ability. Moreover, the paper investigates the role of platforms’ scales in deciding optimal risk control ability, prices and market shares. To our best knowledge, this is the first theoretical paper to study the competition in P2P lending considering risk control ability based on game theory. The analytical results show that: 1) In equilibrium, optimal risk control ability decreases in risk-price coefficients; 2) The risk-price coefficient for lenders contributes less than that for borrowers to optimal risk control ability if some lenders multi-home; 3) Smaller platforms have higher risk control ability, prices and attract more borrowers than larger platforms under specific conditions.

A study on transport costs and China’s Exports: An extended gravity model

This paper suggests an extending conventional gravity model design to empirically analyze the effect of transport costs and port efficiency on China’s export flows. It shows that factor endowment and transport costs variables affect export trade value in directions that New Trade Theory (NTT) predicted. Also, the evidence indicates that, controlling for the effects of transport costs on trade, variables in traditional gravity model are consistent with previous empirical studies in both magnitudes and directions. Moreover, more than 22% of the variation in Chinese export trade can be explained by those three variables alone. The findings reported in this paper empirically explains how seriously transport costs and port efficiency affect China’s export growth by comparing effects of labour production factor costs on external trade. It suggests that the improvement of port efficiency and reduction of road transport costs play a vital role in China’s export competitiveness in the global market.

Does Interval Knowledge Sharpen Forecasting Models? Evidence from China’s Typical Ports

Substantial studies integrating experts’ point knowledge with statistical forecasting modes have been implemented to investigate a long-lasting and disputing issue which is whether or not expert knowledge could improve forecasting performance. However, a large body of current forecasting studies neglect the application of experts’ interval knowledge where experts are expected to be more competent, considering that humans do much better in fuzzy calculation like interval estimation than in accurate computation like point estimation. To fill in this gap, this paper first proposes a novel forecasting paradigm incorporating interval knowledge generated by a Delphi-based expert system into the SARIMA and SVR models. For validation purposes, the proposed paradigm is applied to several representative seaports from the top three dynamic economic regions in China. The empirical results clearly show that interval knowledge, following the proposed paradigm, significantly improves the forecasting performance. This finding implies that the proposed forecasting paradigm has the good potential to be an effective method for sharpening the statistical models for container throughput forecasting.

An empirical investigation on the risk-return relationship of carbon future market

This paper examines the risk-return relationship for the carbon future market during Phases I, II and III of the European Union Emission Trading Scheme (EU ETS). The risk factors derived from the newly developed LSW model, are embedded into a GARCH framework. This new specification is compared with several GARCH-M type models analyzing the risk-return relationship in the carbon market. The results show that the new specification consistently achieves a good fit and possesses superior explanatory power for the European Union Allowance (EUA) data. Some policy suggestions regarding market efficiency are also provided.

Improving Forecasting Performance by Exploiting Expert Knowledge: Evidence from Guangzhou Port

Expert knowledge has been proved by substantial studies to be contributory to higher forecasting performance; meanwhile, its application is criticized and opposed by some groups for biases and inconsistency inherent in experts’ subjective judgment. This paper proposes a new approach to improving forecasting performance, which takes advantage of expert knowledge by constructing a constraint equation rather than directly adjusting the predicted values by experts. For the comparison purpose, the proposed approach, together with several widely used models including ARIMA, BP-ANN and the judgment model (JM), is applied to forecasting the container throughput of Guangzhou Port, which is one of the most important ports of China. Forecasting performances of the above models are compared and the results clearly show superiority of the proposed approach over its rivals, which implies that expert knowledge will make positive contribution as long as it is used in a right way.

The Return and Volatility Spillover between Carbon Futures Market and Global Financial, Energy and Commodity Futures Markets

Financialization of carbon market and global economy have made the fluctuation of carbon emission allowance prices vulnerable to international shocks and risk management become more and more complicated for both investors and fossil fuel consumption enterprises. Based on studying the ergodicity of the Granger causality test for different lag-lengths, this paper investigates the return and volatility transmission between carbon futures price and a data set of 19 financial, energy and commodity time series results show that there exists several causal relationships between carbon futures market and financial, energy and commodity futures markets. The connections between carbon futures market and financial markets are especially strong. Despite that spillovers in different phases are different, volatility linkage between carbon futures markets and these markets is closer and stronger than the return linkage in general. Moreover, extreme returns and risks also have significant leading impacts on regular returns and risks.