China is the capital exporting country worldwide. With Chinese OFDI activities increasing significantly, China’s exchange rate regime reforms have been undertaken step by step. Not only has the de jure exchange rate regime become more flexible, but also has the de facto exchange rate regime. Apart from the research on the exchange rate and OFDI based on the open macro economy, this paper explores how the bilateral exchange rate regime affects firms’ OFDI decisions from the microeconomic view, further enriching the research on exchange rate and OFDI. This paper builds a theoretical model under the general equilibrium framework and discusses the mechanisms between the bilateral exchange rate regime arrangement and firms’ OFDI activities based on a two-country open macroeconomic model. It also uses highly detailed micro data to test and analyze the related hypothesis. Specifically, it uses List of Overseas Investment Enterprises (institutions) data, China Industry Business Performance Data, bilateral de facto exchange rate regime data published on Shambaugh’s personal website, World Development Index data from the World Bank, the Gravity database from the CEPII, the IFS database, and the China Statistical Yearbook from 2000 to 2013.
This paper shows that compared to the floating exchange rate regime, the fixed exchange rate regime can lower the threshold productivity required for firms to conduct OFDI activities and to switch from export to OFDI activities. That is, the bilateral fixed exchange rate regime can stimulate firms’ OFDI activities. This paper also shows that compared to the bilateral de facto floating exchange rate regime, the bilateral de facto fixed exchange rate regime can increase firms’ inclination to undertake OFDI activities by 0.8%~55.4%. Furthermore, on average, one-unit increases in firm productivity can increase firms’ probability of undertaking OFDI activities by 0.04%~2.9%. The bilateral de facto fixed exchange rate regime stimulates firms to conduct OFDI more than firm productivity. Second, considering the difference in ownership, the location of firms, and the incidence of financial crisis, the bilateral de facto fixed exchange rate regime and firm productivity can still stimulate firms’ OFDI inclination but to a different scale. Lastly, considering sample selection bias and two-way causality, our conclusions still stand. Overall, the conclusions of this paper are theoretically and empirically supported with significant robustness.
The results of this paper show that the positive effects of the bilateral fixed exchange rate regime on firms’ OFDI activities should be appreciated. Specifically, firms in developing countries demonstrate lower productivity and lack international competition. The bilateral de facto fixed exchange rate regime can give them more opportunities to increase their core competitive capacity via international competition. In practice, the internationalization of the RMB is on the road. In the long run, the Chinese exchange rate regime arrangement will be more flexible, more and more nations will have more flexible bilateral exchange rate regime arrangements with China. Thus, Chinese firms must increase their own hardcore ability to face the significantly historical alterations of Chinese exchange rate arrangements with other countries.
Three aspects of this paper are noteworthy. First, this paper is not confined to the view of exchange rate level or exchange rate volatility, but through the fundamental aspect of exchange rate regime arrangement. Second, it builds a two-country open macroeconomic model with firms’ heterogeneity and further discusses the mechanism by which the exchange rate regime affects firms’ OFDI activities. Third, this paper uses highly detailed firm level data to verify the mechanisms by which the bilateral exchange rate regime between China and host countries affect Chinese firms’ OFDI activities.
Future breakthroughs in the following aspects may be made. Theoretically, we plan to build a two-country macroeconomic DSGE model and use simulation to argue how different exchange rate regime arrangements can affect firms’ OFDI levels with different firms’ total factor productivity level. Furthermore, we intend to incorporate Chinese characteristics into this medium-scale DSGE model, such as firms’ financial constraints, labor mobility, and factor misallocation. Empirically, if related data are accessible, we plan to decompose firms’ OFDI levels into intensive margins and extensive margins and to further elaborate on how exchange rate regimes can affect firms’ OFDI activities.

The People’s Bank of China has been using a more market-oriented method to determine the CNY central parity rate since August 11, 2015. However, the effect of this method on the RMB derivative markets remains unknown. Among the RMB FX derivatives, the onshore CNY options and offshore non-deliverable CNY options share the same underlying asset: the onshore CNY exchange rate. However, there are always differences in the prices of these two options due to the regulations that limit onshore-offshore arbitrage, which results in different option-implied FX distributions and information in the two markets.
To compare the market efficiency of the onshore and offshore option markets, we use the data on the onshore USD/CNY options and offshore non-deliverable USD/CNY options with one month maturities. The information implied in these options is comparable because they share the same underlying asset, the onshore USD/CNY exchange rate. Specifically, we divide our sample into three periods: before the FX reform, the brief period after the FX reform, and the later period after the FX reform. Following studies such as Jiang and Tian (2005) and Bakshi et al. (2003), we extract the model-free implied volatility and risk-neutral skewness from both the onshore and offshore one-month USD/CNY options. Based on the information extracted from the bid-ask Black-Scholes implied volatility price data of the USD/CNY options portfolio, we test the predictability of the implied volatility and risk-neutral skewness on the yield, volatility, and tail risk of the future exchange rates in the three subsamples. We also compare the information in the two markets and the variations in different periods to determine whether the FX reform improved the information content in both markets. We then empirically collect the closing prices of the onshore and offshore USD/CNY options, the closing spot prices, and the forward USD/CNY exchange rates from Bloomberg.
With respect to risk-neutral skewness, our results show that before the FX reform, the onshore risk-neutral skewness only covers the tail risk information and it has weak predictability on the variation in the future exchange rates. During the short period after the FX reform, the offshore risk-neutral skewness completely covers the information in its onshore counterpart. The information efficiency of the offshore market is also significantly better than that of the onshore market. In the later period after the FX reform, the risk-neutral skewness in both markets covers the information on the variation in the future exchange rates. In this case, the information efficiency of the onshore market is slightly better than that of the offshore market.
With respect to the implied volatility, the results show that before the FX reform, the implied volatility has weak predictability on the future volatility in both markets. During the brief period after the FX reform, the onshore implied volatility significantly predicts the future volatility of the USD/CNY exchange rate. However, the offshore implied volatility does not cover the information on the future volatility. In the later period after the FX reform, the implied volatility in both markets covers the information on the future volatility. Moreover, the offshore implied volatility covers all of the information about its onshore counterpart and the historical volatility. Thus, the offshore market is significantly information efficient.
In the two subsamples after the FX reform, we obtain different results when we test the information efficiency separately in terms of the implied volatility and risk-neutral skewness. However, when we conduct the full analysis, after the FX reform, as the central parity rate becomes more market-oriented, the FX option prices cover more and more information on the future exchange rate distribution. The information efficiency of both the onshore and offshore option markets also notably increases. These results indicate that the market-oriented mechanism of the CNY central parity rate can enhance the efficiency of the Chinese financial market. Therefore, in terms of balancing the financial security, steadily promoting the market-oriented mechanism of the CNY central parity rate will help improve the efficiency of the Chinese financial market.
Our findings have strong implications in regard to whether further exchange rate reforms should be implemented and how they should be promoted. However, the question remains as to why the implied volatility and risk neutral skewness produce different results and whether other factors affect the information efficiency of the two markets. These issues warrant further research attention.

Alibaba reported that on May 4, 2018, there were 870 million global active users of its Alipay application. During the 2018 Spring Festival, the number of WeChat monthly active accounts exceeded one billion. With the development of modern mobile technology and the popularization of mobile devices, mobile payments have rapidly replaced internet payments and become the backbone of third-party transactions. In China, electronic payments have brought great changes to people’s lives, especially mobile payment tools, such as Alipay and WeChat payment. These new payment tools, which combine liquidity and profitability, have caused a shock to the traditional payment methods. Moreover, the financial management tools provided by these applications have given households more money management options, and to some extent have replaced savings deposit. Thus, evidence of the impact of mobile payments on China’s household money demand can provide a theoretical and practical basis for formulating China’s cash management policy.
This paper is divided into seven parts. The first part introduces the research background and the related literature. The second part outlines the theoretical framework of money demand, and the third part introduces the empirical model, data, and variables. In the fourth and fifth parts, we report the empirical results and analyze the heterogeneity, respectively. The sixth part provides the robustness tests and the seventh part concludes the paper.
In this paper, we use the data from the fourth round of the nationwide China Household Finance Survey (CHFS) conducted by Southwestern University of Finance and Economics in 2017 to examine the impact of mobile payments on monetary demand at the household level based on the Baumol-Tobin model. To overcome the endogeneity of mobile payments, we use two stage least squares (2SLS) to do the estimation.
We find that mobile payments lead to a 25% decrease in household cash and have a significant negative impact on the level of money demand. Specifically, the proportion of M₁ decreases by 36.1% and the proportion of M₂ decreases by 21.7%, indicating that mobile payments reduce the money demand to different degrees. We also find that the coefficient of the cross-terms between the transaction cost proxy variables and mobile payments is significantly negative, indicating that changes in transaction costs may be an important channel for mobile payments to affect the demand for cash. Furthermore, using a quantile regression, we find that the effect of mobile payments on the precautionary money demand is greater than that of transactions.
The impact of mobile payments on the money demand also varies significantly for different age levels, education levels, urban and rural areas, Eastern and Western regions, and different cities. Specifically, mobile payments have a greater negative impact on the proportions of M₀ and M₁ among elderly households. For households with a lower education level, mobile payments have a relatively large negative impact on M₀ and M₁, but a relatively small negative impact on M₂. We also find that the level of urban development has a significant effect on the role of mobile payments.
Finally, we analyze the effects of debit card, credit card, bank card, and computer payments on the proportion of cash, and the estimated coefficients are all significantly negative. This shows that the change in the method of payment has had a profound impact on the amounts of cash that households hold.
Although mobile payments are very convenient, the web-based and immaterial characteristics of the system pose numerous possible risks in terms of security. To encourage the use of mobile payments, it is necessary to strengthen the supervision of risk during use, formulate laws and regulations to regulate the behavior of both sides of the transaction, and strengthen the security of the platform using fintech, so that mobile payments can play a key role in cash management.
Overall, this paper makes the following contributions. First, from a micro perspective, we study the impact of mobile payments on monetary demand at the household level. Second, we define the M₀, M₁, M₂ of a household according to the monetary level standards set by the People’s Bank of China. Third, we analyze the influence of transaction costs on the demand for cash and confirm the findings of the Baumol-Tobin model.

With the Chinese economy entering a “new normal” and undergoing transformation, the scale of debt and potential risks have increased rapidly. The central government has paid close attention to this. At the Central Working Conference in 2015, “de-leverage” was listed as one of the five major tasks of supply-side structural reform. How to de-leverage has become a focus of attention and discussion in all sectors of society. Studies mainly focus on the factual changes in corporate leverage and less on the logic behind these changes. Considering that China is in the process of transforming from a planned economy to a socialist market-oriented economy, the government may still intervene through various economic policies. Frequent economic policy changes may increase the uncertainty of economic policies. Economic policy uncertainty is an important source of external environmental uncertainty that enterprises in transition economies face and may affect corporate financing decisions. This issue is worthy of more attention and in-depth study in China, which is undergoing an economic transformation.
We link economic policy uncertainty from the macro perspective to micro-level corporate financing decisions. We also explore the logic behind the change in the leverage of enterprises in transitional China from the new perspective of policy uncertainty. First, we use the quarterly data of listed companies from 2002 to 2016 to describe the empirical facts of structural changes in corporate leverage and carry out the corresponding literature review and theoretical analysis. We then use China’s economic policy as constructed by Baker et al. (2016) to empirically analyze the relationship between policy uncertainty and corporate leverage. The main results show that the higher the uncertainty of economic policy is, the lower the leverage ratio of enterprises is. For every 1% increase in economic policy uncertainty indicators, the average leverage of firms decreases by 0.03 to 0.07 percentage points. This negative effect has obvious structural characteristics, which are even more significant in the samples of short-term debt ratios, private enterprises, small scales, and manufacturing companies. Furthermore, considering the economic transformation background of the region in which an enterprise is located, the model is extended and analyzed. We find that the negative effect of policy uncertainty on the leverage ratio of enterprises decreases significantly as the regional marketization level, the gradual advancement of the privatization reform, and the degree of openness increase. The above conclusions demonstrate strong robustness when examining endogeneity problems, replacing key variables, and setting various models.
We mainly extend the literature in two aspects. First, we explore the logic behind the change in the leverage ratio of Chinese enterprises from the new perspective of policy uncertainty andenhance the research on the interaction between macroeconomic policies and micro-enterprise financing behaviors. However, we do not focus on a specific economic policy, but on the perspective of the uncertainty of the overall economic policy, and further expand the literature on existing policy evaluation. Second, using the quarterly data of Chinese listed companies provides comprehensive and meticulous empirical evidence for the impact of economic policy uncertainty on corporate financing behavior. This is especially true for examining a series of reform variables, such as marketization, property rights reform, and opening up, in the process of economic transformation.
Our conclusions have direct policy implications. First, in implementing the de-leveraging policy, it is necessary to clarify the structural and time-varying characteristics of leverage, to fully recognize the impact of policy uncertainty on the polarization of corporate leverage, and to prevent the development of a “one-size-fits-all” de-leveraging policy. Second, reducing or mitigating the negative impacts of government intervention and policy uncertainty on corporate financing decisions relies on the further reform of China’s economic system.

As a policy guarantee of economic development in the 13th Five-Year Plan for Economic and Social Development of China, “employment first,” which concerns people’s well-being, is prioritized. According to the report of the 19th National Congress of the Communist Party of China, “Employment is pivotal to people’s wellbeing” and we should “adhere to the strategy of giving priority to employment and the active employment policy so as to achieve higher quality and full employment.” The Report on the Work of the Government in 2019 further promotes the employment-first policy to the same high level as the fiscal and monetary policies. Social networks play an important role in employment. They not only affect information acquisition during the job search process but are also closely related to employment quality. To investigate the effect of social networks on employment quality, we first introduce the accumulation decision of family social networks into the endogenous discount factor model, analyze the mechanism through which family social networks affect employment quality, and explain the employment motivation to accumulate social networks. We then discuss two important dimensions of employment quality (i.e., employment satisfaction as it relates to individual welfare and the match between job and skill/major as it relates to resource allocation efficiency), thus analyzing micro welfare and macro efficiency in an integrated framework. Third, we explore the mechanism through which family social networks affect employment quality. We discuss the direct effect of social networks on employment and analyze their indirect effect via experiences during college.
Based on the endogenous discount factor model in Becker and Mulligan (1997), we introduce the accumulation decision of family social networks and discuss the mechanism through which family social networks affect employment decisions. Specifically, family social networks influence the utility of households via the discount factor and the probability of industry entry, leading to the heterogenous optimal accumulation decision of social networks. We find that family social networks complement the major disadvantage of graduates. Considering the difficulty of admission into popular majors, individuals with wider family social networks strategically apply for majors with higher admission probabilities and enter high-income industries with the help of their social networks. Such decisions increase the employment satisfaction of these graduates but decrease the match between job and skill.
We then use data from the 2009 to 2015 National College Graduates Employment Investigation to empirically test the model hypotheses. The empirical results indicate that family social networks increase employment satisfaction but decrease the match between job and skill. We test three potential mechanisms leading to such results: (1) family social networks help graduates from various majors enter high-income industries, as indicated by the model; (2) family social networks help graduates obtain high-quality internships; and (3) family social networks give graduates more opportunities to change majors in college. We find that the first mechanism is the most significant.
Furthermore, we conduct robustness tests on four aspects: the time trend of the effect, the scope of the effect, the strength of the effect, and the regional limitation of family social networks. We obtain four findings. First, the marginal impact of family social networks on employment quality weakens gradually. Second, for families with wider social networks, social networks have a stronger marginal effect on employment quality. Third, there is no significant difference in the intensity between sons and daughters when families use social networks, but utilization intention is diluted by the number of children. Furthermore, the effect of social networks in families with multiple children is lower than that in single-child families. Fourth, family social networks are limited by geographic distance, but their impact on employment quality does not diminish as geographic distance increases.
Overall, from the micro perspective, family social networks increase the employment satisfaction of graduates, thus improving individual welfare. However, from the macro perspective, they decrease the match between job and skill, distort the allocation efficiency of human capital resources, and influence labor productivity in the short run. Our findings provide further theoretical support for improving employment policy and can contribute to strengthening the nation through human resource development.

Innovation is the driving force for economic growth and provides sustained support for economic growth and development, especially in China’s manufacturing industry. Although the literature has have documented the effects of bank competition on firm innovation, we are still curious about the channels through which bank competition is affecting firm innovation.This paper contributes to the literature by examining the impact of bank competition on enterprise innovation from a financing constraint perspective. In addition, we use China’s entry into the WTO as a policy shock, which allows us to use a difference-in-differences method to deal with the endogeneity issues. Unlike previous studies, which uses either short term data or single innovation measures, this paper allows us to examine the effects of heterogeneous business environments on firm innovation.
The data used in this paper are from the China Industrial Enterprise Database from 1998 to 2007, the Enterprise Patent Database of the State Intellectual Property Office, and the information on commercial bank branches disclosed by the China Banking Regulatory Commission. We construct a mediation effect model to test the impact of bank competition on firm innovation through mitigating the firms’ financial constraints. The results are as follows. First, bank competition is found to significantly promote firm innovation. Second, bank competition can reduce firms’ financing constraints. Finally, after controlling for financial constraints, the impact of bank competition on corporate innovation remains positive, although it is slightly weaker. These results indicate that financing constraints have a partial mediating effect on the relationship between bank competition and corporate innovation. In addition, we add the interaction between bank competition and financing constraints to further verify the channel through which bank competition affects firm innovation. The results exhibit a significantly negative coefficient for the interaction term, indicating that the monopoly power of the banking industry strengthens the adverse effect of financing constraints on firm innovation. This shows that bank competition can promote firm innovation by reducing firms’ external financing constraints.
We address the endogeneity issues by using a difference-in-differences method and an instrumental variable approach. After China joined the WTO, the government began to gradually eliminate the restrictions on foreign banks establishing branches in China and conducting business in RMB. This policy change created a quasi-natural multi-period experimental setting, which allows us to use a difference-in-differences method to address the endogeneity issues. We further use the average bank competition of three cities with similar GDP within the same province as an instrumental variable for bank competition and use a two-stage regression to disentangle the endogeneity issues. We also conduct a series of robustness tests with different financing constraint measures, different competition variables, more recent industry survey data, and more rigorous estimation methods. Our main findings are robust to the above changes.
We then conduct split-sample analyses to test the heterogeneity effect. Our results show that the effect of bank competition on firm innovation is more pronounced for firms that are more dependent on external financing, small and medium-sized firms, private firms, firms from regions with higher levels of marketization, and firms from regions with better legal protection. In addition, we find that the competition between non-SOE banks and city commercial banks can better promote enterprise innovation.
The results of this paper show that a moderate competition in the financial sector is crucial for promoting corporate financing and innovation, which in turn can affect a country’s financial stability and economic growth. The development of small and medium-sized banks has broadened the channels for corporate financing and injected new vitality into firm innovation in China. Therefore, further reforms of the financial system should focus on optimizing the structure of the financial system and establishing a multi-layer and diversified financial market to effectively alleviate the financing constraints of SMEs and encourage innovation through the provision of better financial services.

As of the end of 2017, the operating mileage of China’s high-speed railway exceeded 25,000 kilometers, accounting for 66.3% of the world’s total high-speed rail. From a global perspective, investment in transportation infrastructure is extremely expensive. In 2016 alone, China spent around RMB11.89 trillion on infrastructure. However, we still have limited academic and practical understanding of the real effects of transportation infrastructure. Given the increasing economic and social effects of high-speed rail, it is of great theoretical and practical significance to explore the impact of the extension of China’s high-speed rail network. Although, intuitively, the rapid development of transportation infrastructure can be seen to directly affect supplier-customer relationships, few studies have focused on this area. This paper focuses on a general economic characteristic of supplier-customer relationships, namely the extension of trade credit. Using the exogenous impact of the rapid development of China’s high-speed rail network, we examine the causal effects of transportation infrastructure on supplier-customer relationships.
The development of high-speed rail can reduce a company’s transportation costs, and thereby increase the transaction volume between the company and its customers. The increased transaction volume not only reduces the degree of information asymmetry between the company and its customers (from a signal transmission perspective), but also facilitates long-term cooperation between them and improves the product quality (from a moral hazard perspective). These factors reduce the company’s motivation to provide trade credit for product quality guarantees.
Using data on the time high-speed rail is introduced in the areas in which listed companies are located, we use a difference-in-differences approach to examine the causal relationship between the introduction of high-speed rail and a company’s decision to extend trade credit. The results of this paper show that the introduction of high-speed rail has a significant negative impact on companies’ decisions to extend trade credit. Specifically, after high-speed rail is introduced, companies reduce their extension of trade credit by 3.51%. Moreover, the increase in trading volume is shown to be an important channel through which high-speed rail can reduce companies’ extension of trade credit. Further support is found for stronger treatment effects among firms with ex ante greater information asymmetry, more relationship-specific investments, and lower requirements for product quality guarantees. We also conduct a series of robustness tests to further validate the causal effects of the baseline results. The results show that our basic research findings are robust and reliable.
This paper makes the following contributions to the literature. First, this paper contributes to the research on the motives for extending trade credit by incorporating the exogenous changes in China’s transportation infrastructure in the analysis of a company’s decision to extend trade credit, and using the impact of high-speed rail to integrate the two research perspectives of the product quality guarantee theory of trade credit. Moreover, this paper examines the heterogeneity of the treatment effects and provides further support for the product quality guarantee theory of the extension of trade credit.
Second, this paper contributes to the research on the effects of transportation infrastructure on the decision-making and behavior of micro-economic entities, and provides empirical evidence for the micro-pathway through which transportation infrastructure promotes economic growth. To a certain extent, our findings shine light on the black box of the macro-economic effects of traffic infrastructure.
Third, this paper uses the expansion of China’s high-speed rail network as a quasi-natural experiment to alleviate endogeneity problems. The use of a quasi-natural experiment based on exogenous changes helps to alleviate the adverse effects of important omitted variables on the causal inferences. In this paper, the extension of China’s high-speed rail network serves as a quasi-natural experiment to identify the causal effect of transportation infrastructure on companies’ decisions to extend trade credit.
This paper provides timely feedback on the impact of high-speed rail, and provides supplementary empirical evidence on the micro-pathways and intermediate mechanisms through which the construction of infrastructure promotes economic growth. Overall, the findings of this paper enhance our understanding of the economic effects of transportation infrastructure and the factors that influence companies’ decisions on the supply of trade credit.

In recent years, the rapid development and continuous innovation of Internet finance in China have greatly affected the traditional financial industry and portfolio theory. Against such a backdrop, it is a relatively new and important issue to study the changes in public liquidity preferences, investment behavior, and asset selection. However, the research is relatively lacking and has little connection with portfolio theory. This paper analyzes liquidity preference, investment behavior change, and asset selection under Internet financial innovation to reveal the influencing mechanism of Internet finance on public investment behavior. It also attempts to build a multi-objective portfolio model based on the CRRA’s expected utility maximization and VaR minimization at the end of the period. Finally, this paper introduces the multi-objective optimization NSGA-Ⅱ genetic algorithm to solve the model. It determines the optimal portfolio weights and proposes the corresponding countermeasures and suggestions.
This paper constructs a multi-objective portfolio selection model of Internet financial assets based on the maximization of the expected utility of the CRRA and the minimization of the VaR. Furthermore, it introduces a multi-objective optimization NSGA-II genetic algorithm to solve the model. To overcome the subjectivity of the model parameter setting, this paper calculates the return rates of various assets on the basis of calculating the actual data of various assets and combining the characteristics of Internet financial products. The data come from the Wind database and Internet Loan Home. The simulation results show that in the portfolio of public Internet financial assets, the weight of low-risk financial assets is 59.62%, of which 27.71% are Internet Monetary Fund products and 31.91% are Internet insurance products. The weight of high-risk Internet financial assets is 40.38%, of which 27.91% are crowdsourcing products and 12.47% are P2P products. This shows that low-risk Internet financial products are popular with public investors, whereas high-risk products meet the investment needs of some investors who pursue high yield with high yield and convenience.
This paper suggests that the public should follow the principle of optimizing platform, diversifying investment, pursuing income, and ensuring safety in the investment decision-making process. Internet financial enterprises or financial institutions should fully reflect three relatively unified characteristics when developing Internet financial products. Effort should be made to give the developed products the advantages of high yield, high liquidity, and low risk and to better provide personalized financial services for the general public. The regulatory authorities should establish and improve relevant laws and regulations, standardize the development of Internet finance, create a good market environment, promote innovation of Internet financial products, meet diversified investment needs, and safeguard the rights and interests of investors.
This paper makes three main contributions.First, it proposes that Internet finance accounts for the relative unity of the liquidity, profitability, and security of financial assets and carries out a theoretical analysis and numerical simulation. Second, on the basis of comparing traditional financial products with Internet financial products, this paper constructs a multi-objective portfolio model based on the CRRA to maximize the expected utility of wealth at the end of the term and to minimize the VaR, which can be used to analyze the public portfolio behavior under Internet financial innovation. Third, it introduces the multi-objective optimization NSGA-II genetic algorithm to solve the multi-objective model. The actual yield data of various Internet financial products are used to simulate the model and the optimal portfolio is obtained, which can serve as a reference for public investors.

In recent years, most research on the causes of corporate tax avoidance has focused on internal factors, such as a company’s managerial characteristics, or external factors, such as the macroeconomic cycle. Few studies have investigated corporate tax avoidance in relation to the interaction between the tax avoidance of companies in the same industry. The social economics research on non-market interaction effects has shown that it is challenging to identify the strategic responses of a company. Manski (1993) stated that the similarities between group members’ responses can be considered the result of exogenous effects, correlated effects, and endogenous effects (i.e., strategic reactions). To overcome the omitted variables and “reflection” problems, Manski (2000) later proposed an instrumental variable that only affects the behavior of certain individual group members without affecting the behavior of all of the members. Leary and Roberts (2014) validated the effectiveness of the instrumental variable of idiosyncratic returns in the tax avoidance literature.
We use data on China’s A-share listed companies from 2007 to 2016 and use the idiosyncratic stock returns of enterprises in the same industry as the instrumental variable to test the relationship between the tax avoidance behaviors of competitors in the same industry (Leary and Roberts, 2014). In particular, we model a firm’s tax avoidance as a function of (i) its own firm-level characteristics, (ii) its common industry-level characteristics, and (iii) the tax avoidance decisions of its industry competitors (Rajan and Zingales, 1995; Leary and Roberts, 2014). We find that the tax avoidance of private enterprises in the same industry exhibits strategic complementarities whereby a change in a firm’s tax avoidance leads to a direct change in the tax avoidance of its industry competitors, and vice versa. We then explore the possible mechanism of the strategic complementarities and find that it may be explained by the leader-follower mechanism. Large firms arguably have more resources and stronger incentives to gather private information about the optimal level of tax avoidance. In turn, smaller firms might monitor the tax avoidance activities of their larger industry competitors to infer private information from their tax avoidance decisions. We also find that the attenuation of geographical distance is conducive to lowering the cost of collecting information in the same industry, and thus leads to a more significant strategic complementarity within the same industry. That is, the imitation of corporate tax avoidance policies has a “local preference” in the same industry. Finally, because of the inherent difficulty of credibly identifying direct strategic reactions (e.g., Angrist, 2014), we conduct a “falsification test” to assess the robustness of our inferences to alternative explanations (Cohen-Cole and Fletcher, 2008). We repeat our first set of tests using firms’ pre-tax financial performance, which should not exhibit strategic reactions if the firms do not alter their pre-tax performance in response to that of their industry competitors, rather than their tax avoidance. If our results are a product of the endogenous relation between the idiosyncratic stock returns and tax avoidance of industry competitors, then we should find evidence of spurious strategic reactions to firms’ pre-tax performance. However, we find no evidence of strategic reactions to pre-tax net income, which strengthens our results.
Our findings contribute to the research on the determinants of tax avoidance, which has almost exclusively focused on firm- and manager-level characteristics, and has not formally considered whether the strategic interactions among firms influence their tax avoidance. We also draw on the literature on geographic distance and regional industrial concentration (Krugman and Obstfeld, 2000; Bai et al., 2004; Fu, 2009; Ayers et al., 2011), and examine the strategic reactions to corporate tax avoidance in relation to geographical distance. The observed effects of the strategic complementarities expand the potential application of this theoretical mechanism to domestic and foreign markets. Finally, we contribute to the literature by providing evidence that competitors’ (or peers’) decisions can affect firms’ decisions not only through social interaction (e.g., Beck et al., 2014; Leary and Robert, 2014; Bird et al., 2018), but also by influencing the monetary costs and benefits of the firms’ strategic interactions. This finding has potential policy implications because it suggests that policies that seek to limit or curtail the tax avoidance of a subset of firms could inadvertently affect the tax avoidance of their otherwise unaffected competitors through the strategic reactions that we document.

The availability of value investments on the Chinese market is a controversial issue. The Chinese stock market has attracted a large number of retail investors who prefer to speculate and tend to make irrational investments. In this respect, the speculative nature of the Chinese market is likely to induce more mispricing and question the idea of value investments. However, the question remains as to whether value investment strategies really do not work in the Chinese A-share market. Can investing firms with good fundamentals earn significant excess returns? How do we quantify the concept of value investment? These questions have rarely been examined in the literature.
The traditional value investment strategies are based solely on valuation indicators. However, these indicators may not correctly identify the intrinsic value of a company. Warren Buffett extended the traditional concept of value investment by arguing that holding “brilliant” companies is more important than holding companies with cheap prices. Recently, Frazzini et al. (2018) used a quantitative investment method to analyze Buffett’s performance, and concluded that the key to seeking “brilliant” companies can be specifically quantified as investing in high “quality” firms, which is regarded as a new feasible pricing factor.
Considering the differences in the market microstructure and degree of development of the Chinese and U.S. markets, we wish to determine whether the quality premium exists in China. Following Asness et al. (2019), we quantify a firm’s quality using a composite indicator comprising four dimensions, namely, profitability, growth opportunity, safety, and payout. We conduct one-way sorting and two-way sorting analyses to investigate whether a firm’s quality provides incremental predictive information about future stock returns. We then test whether a firm’s quality still has predictability using Fama-Macbeth regressions after controlling some of the firm characteristics in the cross-section. Our empirical results show that high quality firms in the Chinese market have higher returns than low quality firms, and the quality premium remains stable after controlling other relevant variables. Furthermore, the relatively high quality firms exhibit larger market capitalizations and lower B/M ratios than the relatively low quality firms. Next, we explore the effectiveness of a quality strategy using different sample sub-intervals in time-varying tests, and find that the quality premium is stable across all periods, which is inconsistent with the evidence from the U.S. (Asness et al., 2019). Finally, to test whether this predictive power is a manifestation of rational pricing based on compensation for the risk or irrational mispricing, we conduct empirical tests to explore the rational risk and behavioral mispricing explanations. We find that the results do not support the argument based on the compensation for rational risk. With respect to the quality effect arising from irrational mispricing, we find that positive feedback trading, gambling preferences and the limits of arbitrage are the main sources of the mispricing in the quality premium.
Our contributions can be summarized as follows. First, our analysis mostly contributes to the research on the anomalies associated with quality premium. Instead of focusing on developed markets, we explore the existence of a quality premium in the Chinese market, which is growing rapidly and has become an important part of the global capital market. We also focus on the Chinese market because the anomalies observed in mature markets may not exist in emerging markets owing to their typical characteristics, such as over-speculation and unsophisticated investors. Second, our quality indicator contains comprehensive information because we measure four different dimensions of firm performance, whereas the literature tends to only focus on some of these factors. Third, in contrast with results from the U.S. market showing that the predictability of quality is time varying, we find that the quality premium in China exists stably across all periods. Fourth, we provide evidence that the quality effect is more likely attributable to behavioral mispricing than to the rational risk-based explanations.

Institutional investors often share information with and learn from others in the market. This information interaction promotes the dissemination of private information among investors, and can directly affect their decision-making and asset pricing. Thus, research on the impact and mechanism of the information interaction among investors can help explain the behavior of institutional investors and some of the anomalies in asset pricing. Based on social network theory, this paper empirically analyzes how the information interaction between funds influences their decision-making and stock pricing.
First, this paper uses Pareek’s (2009) method to establish the fund information networks. Specifically, if two funds are heavy holders of the same shares, they are deemed to be “connected.” In this way, all of the funds connected to a fund constitute its information network. An information network is a typical social network based on the exchange of information, which can be regarded as the scope and medium of the information interaction. Second, we examine the relationship between the position decision-making of funds and that of the members of their information networks. This relationship can be considered to reflect the influence of the information interaction in controlling public information. We further consider whether the effects of the information interaction under different decision-making scenarios and market situations are significant and different. We then divide the effects of the information interaction into the effects in the same city and different cities, and test whether there are any significant differences. Finally, we test whether the effects of the information interaction vary in terms gender, length of service of fund managers, and size of the information networks. In addition, we build a stock information network based on the fund information network to study how the information interaction affects the stock pricing. A stock’s information network is composed of all of the funds that are heavy holders of this stock and their information network members. The structural characteristics of the network determine the efficiency of the information sharing among the funds. We verify the impact of the information sharing on stock prices and its mechanism by examining the relationships between the structural characteristics, pricing efficiency, and stock prices.
Our sample comprises all of the A-share listed companies on the Shanghai and Shenzhen Stock Exchanges from the first quarter of 2005 to the fourth quarter of 2018 and the equity and mixed open-ended funds. The data on the positions of the funds are from the Wind database. The financial data on the listed companies, the stock transaction data, and the basic information about the funds are all from the CSMAR database.
The results show that information interaction has a significant impact on the funds’ position decision-making, and the impact is significantly different under different decision-making scenarios and market situations. In addition, the subjective factors (fund managers’ gender and length of service) and objective factors (size of the information networks) influence the effect of the information interaction. In Beijing, Guangzhou, and Shenzhen, the effects of other cities are significantly greater than those of the same city, while the case is the opposite in Shanghai.Moreover, information sharing reduces the long-term idiosyncratic volatility of the stock prices, and the pricing efficiency of the stock market plays a mediating role.
This paper extends the application of social network theory to research on financial markets by exploring the relationship between decision-making on individual investments and the corresponding market performance. Our findings contribute to our understanding of the decision-making of institutional investors and means of controlling the market risk caused by herding behavior. Our quantitative findings regarding the information interaction among institutional investors can help regulators identify the “head sheep” of funds in the market and avoid irrational and excessive behavioral synergies. We also discuss the factors that influence the information interaction of funds, which can help the regulators to track the transmission of public and private information among institutional investors, prevent and monitor insider trading and stock price operations, and establish fair competition in the market.