基于余弦相似度(CS)和最小生成树(MST)的基金市场复杂网络研究

以中国基金市场中123家基金公司持有的投资组合为样本,综合运用余弦相似度(CS)和最小生成树(MST)方法,考量基金市场复杂网络。结果显示：各家基金公司持有股票组合的相似程度比持有债券组合的相似程度更高,表明他们持有的债券组合较之股票组合更加多元化,基金公司持有的股票相对集中于市值大、成长性高的公司。同时,全部资产投资组合、股票投资组合和债券投资组合等三类基金MST网络的节点度均服从幂律分布,表明大多数基金公司以少数强影响力基金公司为中心聚集起来,彼此之间具有较强的业务关联。此种网络结构特征可能导致市场风险向基金聚集团体集中,其抵御系统性风险的能力偏弱,也不利于满足投资者的理财多元化需求。     

中国股市个股非流动性、换手率和短期反转的关系

本文在排除买卖报价反弹、周末效应等干扰因素的前提下,利用分组构建逆势投资组合及Fama-Macbeth回归方法,研究周期下我国股市中的短期收益反转现象。实证结果表明：我国股市中存在短期收益反转现象,短期反转在股票输家中表现更为明显;股票收益的短期反转随着非流动性的增强而增强;我国股市具有极高换手率的投资组合表现出特殊性,极高换手率对股票输家的短期收益反转具有抑制作用,而对股票赢家的短期收益反转具有促进作用。     

刻意卖空投资策略在对冲基金中的运用及投资收益对比分析

本文分析了刻意卖空对冲基金中的主要投资策略、投资风险及其防范措施,并通过实证分析,比较了刻意卖空对冲基金与股票、债券市场指数的整体收益率、收益率分布特征及其联动关系,指出利用刻意卖空投资策略构建的投资组合具有很高风险,其收益表现落后于股票、债券市场指数,且收益分布具有很大的不确定性.整体来说,这类基金的投资策略和时机选择是失败的.     

银行财务信息对价值股票是否具有甄别效应?

基于资产定价理论,构建财务信息基本面分析模型,考量商业银行财务报表信息所构建的投资组合是否能获得超额收益。结果表明,从盈利性、稳健性和增长性三个维度构建的基本面分析指标B-scoreChina,对当期银行股票收益和未来股票收益具有较强的解释能力,且该能力主要来自商业银行的稳健性。进一步分析表明,B-scoreChina策略对规模较大、分析师跟踪较少、换手率更低的银行具有更强的甄别效应。     

指数基金在中国的实践和发展

指数基金是基金的一种特殊形式,在投资理念上有其独特之处,即根据股票综合指数的构成组织投资组合,投资对象的选择主要依据构成股票综合指数的股票所占权数,以使其收益与大盘的收益尽可能相同.这种投资方法相对较为简单,所以该类基金的管理费用也较低.在相当一段时间里,美国积极管理的平衡型基金的业绩被具有广泛代表性的Wilshire5000股票指数击败了.从平均水平来看,在一年之中,具有代表性的积极管理的基金业绩水平与指数水平相差约为2%.因而,在美国,指数基金越来越受到投资者的普遍关注和青睐;与此同时,中国也设立了优化指数基金进行证券市场投资.但是,中国目前3只优化指数基金的投资业绩却落后于所追踪的指数和其他类型的证券投资基金,本文拟就其原因和今后的发展进行探讨.     

贷款利率市场化前后商业银行股票网络拓扑性质分析

运用复杂网络方法,构建商业银行股票收益率网络,考量贷款利率市场化前后商业银行股票网络的拓扑性质变化.结果表明:贷款利率市场化前后,16家商业银行股票收益率相关系数没有发生显著变化,网络的平均路径长度及聚集系数也未发生明显变化,但贷款利率市场化后国有五大行股票收益距离更近,彼此相关性更强,网络中心节点变化较大.     

商品期货可以提供潜在组合多样化收益吗?北大核心CSSCISSCI

本文使用动态Skewed-t Copula模型实证证明我国股票、债券和商品期货回报率之间存在时变的非对称相关。无论是Copula相关还是尾部相关,不同市场的资产间相关明显低于相同市场不同资产间相关。将商品期货指数纳入投资组合可以降低尾部风险,获取多样化收益;在最小尾部风险组合中,农产品期货指数占有相对较高的权重。本研究意味着监管部门对金融机构放开商品期货市场投资准入不仅有利于金融机构对冲持有组合的尾部风险,也有利于商品期货市场风险管理功能的实现。     

中国居民储蓄与上证指数关系的实证检验

居民储蓄和股票作为两种重要的金融资产,已有研究对二者是否存在联动性存在较大分歧.本文从投资者行为角度分析居民储蓄与股市间可能的作用机制,利用2000-2011年的居民储蓄余额和上证综合指数月度数据,构建VAR模型进行实证分析.结果表明我国居民储蓄和股市波动之间存在联动性,储蓄有向股市分流的趋势,同时居民储蓄的增加会促进股指上升.     

中国共享单车市场的投资者情绪测评——基于网络文本挖掘的研究

随着互联网技术的不断渗透,共享单车、共享汽车等共享经济形态机遇与挑战并存。网络社交媒体作为目前投资者交流与传递投资信息的重要渠道,能够成为量化投资者情绪的数据来源。以2017年1月1日至2017年6月30日东方财富网共享单车概念股的股吧信息为研究对象,通过网络文本挖掘技术构造投资者情绪、投资者关注度、投资者互动程度三个指标,并与股票收益进行相关性分析和混合回归分析。结果发现,共享单车市场中投资者情绪高涨、关注度增强能够提升概念股的股票收益水平,而投资者互动度与股票收益负相关。此外,积极情绪、消极情绪对股票收益的影响存在差异。     

中国开放式股票型基金定期投资策略比较分析

本文将市场中常见的定期投资策略——固定份额策略、定期定额策略、价值平均策略与一次性投资进行比较,发现对于开放式股票型基金,收益最高的是定期定额策略,但绩效最好的是一次性投资策略;将股票型基金分成不同类型后,发现最适合积极成长型基金、稳健成长型的投资策略变为定期定额投资策略,最适合指数型基金的是价值平均交易策略。     

Analysing and forecasting co-movement between innovative and traditional financial assets based on complex network and machine learning

We study the co-movement between innovative financial assets (i.e., FinTech-related stocks, green bonds and cryptocurrencies) and traditional assets. We construct a co-movement mode transmission network and discuss the network topology during the pre-COVID-19 and COVID-19 periods. We extract network topology information to predict the co-movement mode by machine learning algorithms. We further propose dynamic trading strategies based on the co-movement mode prediction. The empirical results show that (i) the evolution of co-movement is dominated by some key modes, and the mode transmission relies on intermediate modes and shows certain periodicity; (ii) the co-movement relationships are influenced by the ongoing COVID-19 outbreak; and (iii) the novel approach, which combines complex network and machine learning, is superior in co-movement mode prediction and can effectively bring diversification benefits. Our work provides valuable insights for market participants.     

Co-movement between commodity and equity markets revisited—An application of the Thick Pen method

This paper analyses interdependence between the returns of specific energy and non-energy commodities and equities using (i) Thick Pen Measure of Association (TPMA) and (ii) Multi-Thickness Thick Pen Measure of Association (MTTPMA). We capture time-varying co-movement and co-movement across different time scales to analyse the short-term and long-term features of the time series using stationary data. Energy index futures show an increase in co-movement with equities since the start of the financialisation period. There are asymmetric effects in cross-scale co-movement between various commodities and equities. Weak co-movement between equity and specific commodity futures indicates diversification benefits for short-term and long-term investors.     

Stock price synchronicity and liquidity

We argue and provide evidence that stock price synchronicity affects stock liquidity. Under the relative synchronicity hypothesis, higher return co-movement (i.e., higher systematic volatility relative to total volatility) improves liquidity. Under the absolute synchronicity hypothesis, stocks with higher systematic volatility or beta are more liquid. Our results support both hypotheses. We find all three illiquidity measures (effective proportional bid-ask spread, price impact measure, and Amihud's illiquidity measure) are negatively related to stock return co-movement and systematic volatility. Our analysis also shows that larger industry-wide component in returns improves liquidity. We find that improvement in liquidity following additions to the S&P 500 Index is related to the stock's increase in return co-movement.     

Financial contagion and the real economy

This paper studies the spread of the Global Financial Crisis of 2007–2009 from the financial sector to the real economy by examining ten sectors in 25 major developed and emerging stock markets. The analysis tests different channels of financial contagion across countries and sectors and finds that the crisis led to an increased co-movement of returns among financial sector stocks across countries and between financial sector stocks and real economy stocks. The results demonstrate that no country and sector was immune to the adverse effects of the crisis limiting the effectiveness of portfolio diversification. However, there is clear evidence that some sectors in particular Healthcare, Telecommunications and Technology were less severely affected by the crisis.     

Foreign Ownership of Stocks and Long-run Interdependence Between National Housing and Stock Markets—Evidence from Finnish Data

Globalization of the financial markets may have undermined co-movement between stock and housing markets, at least in small open economies. This paper provides an empirical study on the long-term dynamic interrelation between stock and housing markets in a small open economy with special attention to the effect of foreign investors on the dynamics. The empirical findings, based on a quarterly dataset from Finland over 1970-2006, do not support the hypothesis of diminished co-movement between Finnish stock and housing markets after the abolishment of the foreign ownership restrictions of stocks in 1993. The markets still appear to be tightly interdependent in the long run. Nevertheless, the results suggest that the substantial growth in the foreign ownership of Finnish stocks induced a large and long-lasting deviation from the cointegrating long-run relation between stock and housing prices. The results also imply that diversification between stock and housing markets works the worse the longer the investment horizon is.     

The Dynamic Extreme Co-Movement between Chinese Stock Market and Global Stock Markets

ABSTRACT

We use time-varying Symmetrized Joe-Clayton Copula model to study the extreme co-movement (boom or crash together) between the Chinese stock market and major stock markets in the world from 2007 to 2017, including developed markets and stock markets on “Belt and Road Initiative” (hereafter B.R.I.). We find that the extreme co-movement probability between Chinese market and “Belt and Road Initiative” markets is higher than developed markets at both tails. Then we study important “real” and “non-fundamental” factors affecting the excess co-movement probability, including bilateral trade openness, financial integration, and economic policy uncertainty. The results of panel regression analysis show that: the bilateral financial integration has significant effects over the lower tail dependence between Chinese and developed markets, but does not affect the extreme co-movement between Chinese and B.R.I. markets. And the bilateral trade openness is an important factor for the extreme co-movement at both tail between Chinese and global markets. The economic policy uncertainty index, especially China’s economic policy uncertainty, plays a key role in the extreme co-movement between Chinese and developed markets at both tails. However, it has sizable effects only at the upper tail co-movement between Chinese and B.R.I. markets.     

Geopolitical risk and the returns and volatility of global defense companies: A new race to arms?

The ongoing war in Ukraine and rising geopolitical tensions between Russia and western countries have led several European countries to increase defense spending to historic levels. Under such intense circumstances, we examine the co-movements between the daily geopolitical risk (GPR) index and the daily returns and volatility of 36 global defense and aerospace companies covering ten countries and three continents. Using the wavelet coherence approach, we find significant co-movement concentrated around the eruption of the war in Ukraine, mostly for medium and longer scales, indicating a flight-to-arms phenomenon. The strong co-movement is significant for most of US and European companies. Specifically, the GPR index leads the return and volatility of several US and European companies at medium and longer scales throughout the war period, and its impact is mostly positive. Our findings offer new and interesting implications for multi-horizon market participants such as traders and investors.     

Stock returns,order imbalances,and commonality: Evidence on individual,institutional, and proprietary investors in China

Using a unique dataset from the Shanghai Stock Exchange, we study the relation between daily open-to-close stock returns and order imbalances, and the commonality in order imbalances across individual, institutional, and proprietary investors. We find that institutional (proprietary) order imbalances have a larger price impact, but account for a significantly smaller proportion of daily price fluctuations. Commonality is much stronger for individual, rather than institutional (proprietary), order imbalances. Institutional (proprietary) investors favor large capitalization stocks, and co-movement in institutional (proprietary) order imbalances is stronger for these stocks.     

Asymmetric causality of economic policy uncertainty and oil volatility index on time-varying nexus of the clean energy,carbon and green bond

Vigorously developing the clean energy industry, improving the carbon allowance trading scheme, and issuing green bonds can effectively reduce emissions. To this end, this study aims to investigate the time-varying connections among clean energy, carbon, and green bonds through the DCC-MIDAS model, thus providing a bird's-eye view of their dynamic nexus. A non-parametric causality-in-quantile method is also employed to adequately capture the asymmetric causation of economic policy uncertainty (EPU) and the oil volatility index (OVX) on cross-asset correlations under different market conditions. The primary results imply complicated links among these three assets, with alternating positive and negative trends throughout the sample period. Notably, turbulence in financial markets can exacerbate network connectivity, particularly during the COVID-19 pandemic. Moreover, EPU and OVX can serve as strong predictors across various distributions of cross-market connections, which indicates that co-movement between assets is vulnerable to exogenous risks, especially under normal market conditions. Our findings have broader implications for market participants and policymakers.     

A network perspective of the stock market

Complex networks are constructed to study correlations between the closing prices for all US stocks that were traded over two periods of time (from July 2005 to August 2007; and from June 2007 to May 2009). The nodes are the stocks, and the connections are determined by cross correlations of the variations of the stock prices, price returns and trading volumes within a chosen period of time. Specifically, a winner-take-all approach is used to determine if two nodes are connected by an edge. So far, no previous work has attempted to construct a full network of US stock prices that gives full information about their interdependence. We report that all networks based on connecting stocks of highly correlated stock prices, price returns and trading volumes, display a scalefree degree distribution. The results from this work clearly suggest that the variation of stock prices are strongly influenced by a relatively small number of stocks. We propose a new approach for selecting stocks for inclusion in a stock index and compare it with existing indexes. From the composition of the highly connected stocks, it can be concluded that the market is heavily dominated by stocks in the financial sector.