行业资产的Black-Litterman模型配置研究——基于社交网络情绪文本挖掘算法

研究目标:构建反映行业股价走势的基于社交网络文本挖掘算法的行业投资者情绪指标，并改善嵌入行业投资者情绪指标的Black-Litterman模型对资产的配置结果。研究方法:基于社交网络文本挖掘算法度量投资者情绪，运用主成分分析法构建行业投资者情绪指标，并嵌入Black-Litterman模型中构建投资者观点矩阵，确定行业资产配置比。研究发现:基于行业投资者情绪的BL模型有效提高了资产配置的日均收益率和夏普比率。实证结果在样本外验证(除受新冠疫情影响阶段)、暴涨暴跌阶段以及经过允许卖空和交易成本调整后仍稳健，进而证实了投资者情绪对资产组合有显著影响。研究创新:基于社交网络文本挖掘算法构建投资者情绪指数，解决了仅依赖于预期收益或历史数据的预测模型无法直观揭示投资者心理认知和行为的局限性问题，从一个崭新的视角科学地解决Black-Litterman模型中投资者观点的生成问题。研究价值:扩展了Black-Litterman模型理论体系研究，并推动了行为金融理论在资产配置中的应用。     

正确的网络舆情立场对营造良好网络环境的影响

高校网络舆情作为高校校园内客观存在的一种社会现象,给大学生思想政治教育带来新的机遇和挑战。关注大学生网络舆情,探究网络对高校思想政治教育的影响,并提出针对高校学生思想政治教育的对策,以维护校园稳定,促进大学生精神生活的健康发展。     

Opinion dynamics and wisdom under conformity

We study a dynamic model of opinion formation in social networks. In our model, boundedly rational agents update opinions by averaging over their neighbors’ expressed opinions, but may misrepresent their own opinion by conforming or counter-conforming with their neighbors. We show that an agent׳s social influence on the long-run group opinion is increasing in network centrality and decreasing in conformity. Concerning efficiency of information aggregation or “wisdom” of the society, it turns out that misrepresentation of opinions need not undermine wisdom, but may even enhance it. Given the network, we provide the optimal distribution of conformity levels in the society and show which agents should be more conforming in order to increase wisdom.     

Impact of network investor sentiment and news arrival on jumps

This paper studied the influence of news announcements and network investor sentiment on Chinese stock index and index futures market jumps. A machine learning text analysis algorithm was employed to measure investor forum sentiment. It was found that news arrivals were an important reason for jump occurrences, jumps were significantly associated with network investor sentiment, and while occasionally the news and network investor sentiment resulted in simultaneous market jumps, they appeared to be relatively independent. The network investor sentiment time-lag and asymmetric effects were also tested, from which it was found that network investor sentiment had a significant asymmetric effect on the jumps, but time-lag effects had little influence. News announcements and the top 25% of the extreme network sentiments were found to explain more than 50% of the jumps, with extreme sentiments tending to increase the volatility of the news-related jumps and persistently influencing returns after the news-related jumps.     

制度条件、机构投资者与上市公司市场价值

上市公司市场价值是投资者获得投资收益的主要来源,公司市场价值的提升是投资者保护的重要体现。本文在制度分析的基础上,通过面板数据模型,实证分析中国机构投资者提升上市公司市场价值的制度条件。结果发现,机构投资者提升上市公司市场价值的作用受到机构持股数量和上市公司所有权性质的影响。较高的持股比例是机构投资者提升上市公司市场价值的重要条件;而上市公司的国有控制特征降低了机构投资者的上市公司价值提升作用,并且国有控制的这种限制作用主要来自地方控制的上市公司。上述研究发现,对理解发展机构投资者的经济后果具有重要意义,有助于更加深入地理解机构投资者提升上市公司市场价值的制度条件,也为投资者保护研究提供了一个有益的视角。     

Knowledge flow and inter-firm networks: The influence of network resources,spatial proximity and firm size

The objective of this paper is to analyse the characteristics and nature of the networks that firms utilize to access knowledge and facilitate innovation. The paper draws on the notion of network resources, distinguishing two types: social capital–consisting of the social relations and networks held by individuals; and network capital–consisting of the strategic and calculative relations and networks held by firms. The methodological approach consists of a quantitative analysis of data from a survey of firms operating in knowledge-intensive sectors of activity. The key findings include: social capital investment is more prevalent among firms frequently interacting with actors from within their own region; social capital investment is related to the size of firms; firm size plays a role in knowledge network patterns; and network dynamism is an important source of innovation. Overall, firms investing more in the development of their inter-firm and other external knowledge networks enjoy higher levels of innovation. It is suggested that an over-reliance on social capital forms of network resource investment may hinder the capability of firms to manage their knowledge networks. It is concluded that the link between a dynamic inter-firm network environment and innovation provides an alternative thesis to that advocating the advantage of network stability.     

With Friends Like These: Endogenous Labor Market Segregation with Homogeneous, Nonprejudiced Agents

In the economics literature, labor market segregation is typically assumed to arise either from prejudice ( Becker 1971 ) or from group differences in human capital accumulation ( Benabou 1993 ; Durlauf 2006 ; Fryer 2006 ). Many sociological studies, by contrast, consider social network structure as an embodiment of various forms of social capital, including the creation of obligations, information channels, and enforceable trust ( Coleman 1988 ; Portes and Sensenbrenner 1993 ). When firms hire by referral, social network segregation can lead to labor market segregation ( Tilly 1998 ). Various social network structures may arise from the actions of self-interested individuals ( Watts and Strogatz 1998 ; Jackson 2006 ); by incorporating concepts of social capital into an economic framework of profit-maximizing firms, this article develops a model of labor markets in which segregation arises endogenously even though agents are homogeneous and have no dislike for each other. Firms hire through referrals, and can enforce discipline by bribing a referrer to prevent a hiree from getting any outside job offers from other friends if he or she shirks. This is possible only if social networks are reasonably closed, so that the referee knows a majority of his or her friends' friends. By segregating into small communities, workers can more effectively create closed social networks. Social networks with different reservation wages will receive different wages; firms can induce such segregation and wage discrimination in the interest of profit. Workers may not benefit from such segregation, except as a best response to being in a society where it already exists; the "friends" in these social networks act as a worker discipline device, and in this way treat each other inimically.     

How much should an investor trust the startup entrepreneur? A network model

Trust is an important determinant of start-up financing. In a simple agent-based model it is determined what the best trusting strategy is for a collective of investors and whether it is rational for an individual investor to deviate from this collective optimum. Trust depends on a measure of social distance and is the precondition for investment. Trust increases and decreases based on whether an investor is satisfied with the interest payments received from an entrepreneur. If an investor is dissatisfied, he terminates the relation with the entrepreneur. For assessing the quality of their own investments, investors communicate with other investors in a network-like structure. I find that, as a collective, it is best for investors to compare their returns critically in order to identify unproductive entrepreneurs, but to be tolerant regarding existing links to entrepreneurs in order not to terminate profitable relations because of minor productivity drops. However, it is optimal for an individual investor to deviate from this strategy and to be less easily disappointed, but to decrease trust in larger steps. In a sense, an individual investor can free ride on the others’ critical assessment. If all investors behave according to this latter strategy, too many unproductive firms remain in the market and the average investor’s return is lower than in the collective optimum.     

网络舆情发展规律与处理研究

当前,我国正处于转型时期,网络舆情缺乏有效的监管,使得各种言论、思想充斥网络,导致信息不对称的普通民众极易受到一些偏激言论的吸引而忽略了真正的事实真相,引发更多的社会矛盾和冲突。因此如何构建起高效的网络舆情处理机制对于更好的利用网络舆情反映现实民意、缓和社会矛盾、维护社会稳定有着重要的意义。     

Social networks,mass media and public opinions

Our opinions and ideas are shaped by what our friends said and what we read or watched on mass media. In this paper, we propose a concise and analyzable model to study the effects of mass media modeled as an applied external field, and social networks on public opinions based on the multi-state voter model, and a tuned parameter can control the relative intensity of the effects of mass media and social networks. We consider a generalized scenario where there exist committed or stubborn agents in the networks whose opinions are not affected by their friends or mass media. We find that the fraction of each opinion will converge to a value which only relates to the fractions and degrees of stubborn agents, and the relative intensity between media and network effects. The final agents with media opinion, except the stubborn agents, also include the increment produced by the internal impact of social networks and that caused by the external impact of media. Interestingly the second increment is composed of two parts, one is from the media effect when there are no interactions between agents and the other is from the influence of media on agent opinions caused by social network structure. That is the interactions among agents within social networks can amplify media influence. Finally we also discuss several extensions to the dynamics model which consider more realistic scenarios.     

The success and failure of policy-implanted inter-firm network initiatives: motivations,processes and structure

This paper examines the processes and causes of inter-firm network success and failure, defined in terms of the ability of networks to become a sustained and valued form of business activity for their members. The paper examines four different case study network initiatives: (1) a failed informal ‘new entrepreneurs' network’ (2) a successful informal ‘local cluster group’ (3) a failed formal ‘defence contractors' network’ and (4) a successful formal ‘small-firm technology group’. It is shown that networks in business are often consciously developed and maintained by those managing directors who have recognized the importance of cooperative activities for achieving competitive advantage for their companies. The best network support consisted of brokers who are able to mix and overlap the ‘hard’ business and ‘softer’ social interests of participants. The case studies indicate that it is formal groups that are the most potent form of inter-firm network, but that it is through an initially informal structure that they are best facilitated. It is concluded that both economic and social rationalities are at play in the motivation of firms to join networks, and that their success is closely connected to pre-existing commonality between members.     

Swedish BioTech SMEs: The veiled values in online networks

For many years, sociologists have conceptualized and debated the value of ‘social capital’, the resources embedded in an actor's social network. The notions of network organizations and strategic alliances have become important forms of entrepreneurial venture, yet often the value in these networks is veiled by network complexity. These associations of individuals and organizations are typically undocumented, difficult to identify by third parties, and even pass unrecognized by their constituent members. They consist of informal Internet networks that are extremely valuable because of the strategic social capital embedded in them.Drawing on social network theory, this paper outlines a methodology for viewing and valuing informal Internet networks, using small-to-medium sized enterprises in the Swedish biotechnology arena as a backdrop. It demonstrates that networks can be constructed from the links between the web sites of actor firms, and that it is possible to use social network theory to identify the most prominent actors. Then, using structural hole analysis, the entrepreneurial opportunities surrounding these actors can be unveiled.     

The Naming Game in social networks: community formation and consensus engineering

We study the dynamics of the Naming Game (Baronchelli et al. in J Stat Mech Theory Exp P06014, 2006b) in empirical social networks. This stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.     

Topological properties of reconstructed credit networks and banking systemic risk

Financial bipartite networks provide channels for contagion risks and their topological properties determine financial stability. We enrich the bipartite network reconstruction methods proposed by Ramadiah et al. (2020) and extend them to the Chinese banking system. By comparing the reproducibility of the real credit market and the corresponding systemic risk, the impact of topological properties for different reconstructed bipartite networks on financial stability is analyzed. The empirical evidence shows that network reconstruction methods based on maximum entropy ensembles capture more properties in the real credit network. It also highlights that the different systemic risk level is mainly contributed by the topological properties based on common exposures. These analyses for topological properties provide regulatory insights for systemic risk prevention. It shows that reducing credit similarity across banks while increasing credit diversification in different sectors helps to control systemic risk. The results imply the possibility of increasing financial stability through the macro-regulation of the credit market structure.     

Does investor sentiment impact the returns and volatility of Islamic equities?

In this paper, we estimate generalized autoregressive conditional heteroskedasticity (GARCH) and vector autoregressive (VAR) models to examine whether investor sentiment impacts the returns and volatility of various U.S. Dow Jones Islamic equity indices. The results from GARCH estimations show that changes in investor sentiment are positively correlated with the returns of the Shari’ah-compliant market portfolio. In addition, we find similar results for the three Shari’ah-compliant firm-size portfolios (i.e., large-, medium-, and small-cap). However, this relationship is stronger for harder to arbitrage Shari’ah-compliant stocks; that is, investor sentiment has a greater influence on small-cap equities. Additionally, estimations from the vector autoregressive model confirm the aforementioned results. In terms of volatility, GARCH estimations suggest that bullish shifts in investor sentiment in the current period are accompanied by lower conditional volatility in the ensuing period. In general, our findings suggest that as noise traders create more risk the market seems to reward them with higher expected returns.     

Linking entrepreneurial and market orientation to the SME’s performance growth: the moderating role of entrepreneurial experience and networks

Entrepreneurial orientation and market orientation (EO and MO, respectively) have received extensive research attention in the past several decades. Although scholars widely agree that both MO and EO are critical to firms’ performances, a better understanding is still needed about how market and entrepreneurial orientation develop over time as well as their relative impact on the growth of the SME’s performance. This study does not consider MO and EO as generic resources that always positively influence firms’ performances; instead, it tries to explore contingent elements, such as social and business networks and accumulated entrepreneurial experience. The hypotheses were tested on 191 small and medium-sized electronic firms located in an Italian geographical cluster during two periods: 2005 and 2016. This study suggests that SMEs, which develop social networks, may enjoy considerable advantages from entrepreneurial and market orientation, improving their performance benefits. Moreover, our results show that previous entrepreneurial experience, when specific, can reinforce the impact of entrepreneurial and market orientation on firms’ performance growth. This analysis makes several important contributions to the management literature on the strategic orientation of firms, the entrepreneurial experience and network development.

     

The fluctuation correlation between investor sentiment and stock index using VMD-LSTM: Evidence from China stock market

The impact of the investor sentiment on China’s capital market price volatility is concerned under the perspective of the behavioral finance. Firstly, in terms of the existing methods of establishing the investor sentiment index, the composite investor sentiment index which include six indicators (five objective indicators and a subjective indicator) are obtained. Secondly, VMD-LSTM (Variational Mode Decomposition and Long Short Term Memory) hybrid neural network model is used to decompose and restructure the investor sentiment index and the Shanghai Security Exchange Composite Index (SSEC) into the short-term, medium-term and long-term trend. Each trend is trained to obtain the forecasting results in three different time scales, and then to achieve the final predicting results by superimposing the output of each trend. Furthermore, compare with other prediction methods, the model can indeed improve the overall predicting accuracy. Finally, GARCH model and the co-integration error regression model are used to discuss the fluctuation correlation and VAR (Vector Auto-regression) models are established to analyze the causality between the stock market indices and the investor sentiment index.     

Assessing the reversal of investor sentiment

Assessing the reversal of sentiment in stock markets is needed because, according to the social mood cycle, the change of social mood over time is an antecedent of price movements. The purpose of this study is to empirically assess reversal of investor sentiment, to show the phases of social mood cycle from increasing mood to decreasing mood, and to explain the dynamic change in market inefficiency from increasing to decreasing. Growth modeling, developed particularly for dealing with the change over time, is used in this study for assessing the reversal of investor sentiment. The autocovariance structure of errors and the variances/covariances of the random coefficients are all taken into account in the model. The results have indicated that the change in investor sentiment over time is inverted U-shaped for the entire market. Moreover, arbitrage constraint and stock characteristics exert a joint moderating effect on sentiment reversal. Less arbitrage constraint can strengthen sentiment reversal only when the market for individual stocks is dominated by noise traders. Based on the results obtained, we discuss asset pricing, liquidity management, and market intervention.     

Social networks,employment and worker discouragement: Evidence from South Africa

Social networks are increasingly being recognized as having an important influence on labour market outcomes, since they facilitate the exchange of job related information. Access to information about job opportunities as well as perceptions about the buoyancy of the labour market depend critically on the social structures and the social networks to which labour market participants belong. In this paper, we examine the impact of information externalities generated through network membership on labour market status. Using Census data from South Africa, a country characterized by high levels of unemployment and worker discouragement, we adopt an econometric approach that aims to minimise the problems of omitted variable bias that have plagued many previous studies of the impact of social networks. Our results suggest that social networks may enhance employment probabilities by an additional 3–12%, and that failure to adequately control for omitted variables would lead to substantial over-estimates of the network co-efficient. In contrast, the impact of social networks on reducing worker discouragement is much smaller, at between 1 and 2%.     

Analysing network partnerships

Support for the notion of networks is growing rapidly across Europe, especially in the public sector where faith in market and hierarchy is diminishing. However, the concept is still loosely interpreted and variably applied. This article unpacks the concept of network and goes on to suggest that a useful model for application to a ‘whole systems’ approach is Ken Benson's neglected framework of an ‘inter-organisational network’. It urges application of the framework to specific contexts and issues.