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。     

The shrouded business of style drift in active mutual funds

This study investigates the motivation and performance consequence of intentional style drift in an exclusively in-house fund management industry in China. With style drift, fund investors are exposed to investment portfolio outside their risk-return preference but are generally unaware that their risk and return expectations are disrupted, and the functioning of the fund market undermined. Our study provides evidence for the first time about the incentive that motivates style drift behavior. We find that style drift increases a fund's subsequent net inflows, thus affirming the maximization of AUM-linked compensation as the motivation for fund manager's style drift behavior. We also find that larger funds have greater incentive to drift. We demonstrate that style drift behavior interferes with the picking of quality stocks to deliver fund performance for fund investors. Style drift as an unobserved risk behavior harms fund investor interest and undermines market integrity.     

我国基金重仓股选股偏好的时期似无关回归分析

基于基金重仓股季度面板数据,本文采用时期似无关回归模型分析了四大类共28个指标对基金持股比例的影响,并利用基金重仓股的统计值特点发现基金筛选股票的标准。研究结果表明,基金确实在寻求价值型投资,扩大基金规模可减轻股市投机行为;基金在调研阶段和操盘阶段对风险有不同的偏好,调研阶段规避风险,操盘阶段偏好高风险高回报;基金偏爱长期流动性好的股票;开放式基金的选股要求高于封闭式基金,牛市时基金的选股要求高于熊市;基金偏爱关注率高、信息丰富的股票;基金对行业的偏好基于行业的业绩表现;基金重仓股持股比例基本上与指数有相似的变化趋势。     

Should investors include Bitcoin in their portfolios? A portfolio theory approach

Many papers in recent years have examined the benefits of adding alternative assets to traditional portfolios containing stocks and bonds. Bitcoin has emerged as a new alternative investment for investors which has attracted much attention from the media and investors alike. However relatively little is known about the investment benefits of Bitcoin and therefore this paper examines the benefit of including Bitcoin in a traditional benchmark portfolio of stocks and bonds. Specially, we employ data up to June 2018 and analyse the potential out-of-sample portfolio benefits resulting from including Bitcoin in a stock-bond portfolio for a range of eight popular asset allocation strategies. The out-of-sample analysis shows that, across all different asset allocation strategies and risk aversions, the benefits of Bitcoin are quite considerable with substantially higher risk-adjusted returns. Our results are robust to rolling estimation windows, the incorporation of transaction costs, the inclusion of a commodity portfolio, alternative indices, short-selling as well as two additional optimization techniques including higher moments with (and without) variance-based constraints (VBCs). Therefore, our results suggest that investors should include Bitcoin in their portfolio as it generates substantial higher risk-adjusted returns.     

Equilibrium with investors using a diversity of deviation measures

It has been argued that investors who optimize their portfolios with attention paid only to mean and standard deviation will all end up choosing some multiple of a certain master fund portfolio. Justification for the capital asset pricing model of classical portfolio theory, which relates individual assets to such a master fund, has come from this direction in particular. Attempts have been made to provide solid mathematical support by showing that the imputed behavior of investors is a consequence of price equilibrium in a market in which assets are traded subject to budget constraints, and optimization is carried out with respect to utility functions that depend only on mean and standard deviation.     

Institutional investors: Arbitrageurs or rational trend chasers

This paper studies the relationship between institutional investor holdings and stock misvaluation in the U.S. between 1980 and 2010. I find that institutional investors overweigh overvalued and underweigh undervalued stocks in their portfolio, taking the market portfolio as a benchmark. Cross-sectionally, institutional investors hold more overvalued stocks than undervalued stocks. The time-series studies also show that institutional ownership of overvalued portfolios increases as the portfolios' degree of overvaluation. As an investment strategy, institutional investors' ride of stock misvaluation is neither driven by the fund flows from individual investors into institutions, nor industry-specific. Consistent with the agency problem explanation, investment companies and independent investment advisors have a higher tendency to ride stock misvaluation than other institutions. There is weak evidence that institutional investors make a profit by riding stock misvaluation. My findings challenge the models that view individual investors as noise traders and disregard the role of institutional investors in stock market misvaluation.     

Trading strategies with partial access to the derivatives market

This research analyzes trading strategies with derivatives when there are several assets and risk factors. We investigate portfolio improvement if investors have full and partial access to the derivatives markets, i.e. situations in which derivatives are written on some but not all stocks or risk factors traded on the market. The focus is on markets with jump risk. In these markets the choice of optimal exposures to jump and diffusion risk is linked. In a numerical application we study the potential benefit from adding derivatives to the market. It turns out that e.g. diffusion correlation and volatility or jump sizes may have a significant impact on the benefit of a new derivative product even if market prices of risk remain unchanged. Given the structure of risk investors may have different preferences for making risk factors tradable. Utility gains provided by new derivatives may be both increasing or decreasing depending on the type of contract added.     

Which past returns affect trading volume?

Anecdotal evidence suggests and recent theoretical models argue that past stock returns affect subsequent stock trading volume. We study 3,000 individual investors over a 51 month period to test this apparent link between past returns and volume using several different panel regression models (linear panel regressions, negative binomial panel regressions, Tobit panel regressions). We find that both past market returns as well as past portfolio returns affect trading activity of individual investors (as measured by stock portfolio turnover, the number of stock transactions, and the propensity to trade stocks in a given month). After high portfolio returns, investors buy high risk stocks and reduce the number of stocks in their portfolio. High past market returns do not lead to higher risk taking or underdiversification. We argue that the only explanations for our findings are overconfidence theories based on biased self-attribution and differences of opinion explanations for high levels of trading activity.     

What Matters to Individual Investors? Evidence from the Horse's Mouth

We survey a representative sample of U.S. individuals about how well leading academic theories describe their financial beliefs and decisions. We find substantial support for many factors hypothesized to affect portfolio equity share, particularly background risk, investment horizon, rare disasters, transactional factors, and fixed costs of stock market participation. Individuals tend to believe that past mutual fund performance is a good signal of stock-picking skill, actively managed funds do not suffer from diseconomies of scale, value stocks are safer and do not have higher expected returns, and high-momentum stocks are riskier and do have higher expected returns.     

Can utility optimization explain the demand for structured investment products?

In this paper, we first show that for classical rational investors with correct beliefs and constant absolute or constant relative risk aversion, the utility gains from structured products over and above a portfolio consisting of the risk-free asset and the market portfolio are typically much smaller than their fees. This result holds irrespectively of whether the investors can continuously trade the risk-free asset and the market portfolio at no costs or whether they can just buy the assets and hold them to maturity of the structured product. However, when considering behavioural utility functions, such as prospect theory, or investors with incorrect beliefs (arising from probability weighting or probability misestimation), the utility gain can be sizable.     

Portfolio Selection and Optimization with Higher Moments: Evidence from the Indian Stock Market

The Markowitz portfolio optimization model, popularly known as the Mean-Variance model, assumes that stockreturns follow normal distribution. But when stock returns do not follow normal distribution, this model wouldbe inadequate as it would prescribe sub-optimal portfolios. Stock market literature often deliberates that stock returns are non-normal. In such context the Markowitz model would not be sufficient to estimate the portfolio risks. The purpose of this paper is to expand the original Markowitz portfolio theory (mean-variance) via adding the higher order moments like skewness (third moment about the mean) and kurtosis (fourth moment about the mean) in the return characteristics. The research paper investigates the impact of including higher moments using multi-objective programming model for portfolio stock selection and optimization. The empirical results indicate that the inclusion of higher moments had a considerable impact in estimating the returns behavior of portfolios. The portfolios optimized using all the four moments, generated higher returns for the given level of risk in comparison to the returns of the Markowitz model during the study period 2000–2011. The results of this study would be immensely useful to fund managers, portfolio managers and investors as it would help them in understanding the Indian stock market behavior better and also in selecting alternative portfolio selection models.     

Cash demand,liquidation costs and capital market equilibrium under uncertainty

In this paper, the portfolio and the liquidity planning problems are unified and analyzed in one model. Stochastic cash demands have a significant impact on both the composition of an individual's optimal portfolio and the pricing of capital assets in market equilibrium. The derived capital asset pricing model with cash demands and liquidation costs shows that both the market price of risk and the systematic risk of an asset are affected by the aggregate cash demands and liquidity risk. The modified model does not require that all investors hold an identical risky portfolio as implied by the Sharpe-Lintner-Mossin model. Furthermore, it provides a possible explanation for the noted discrepancies between the empirical evidence and the prediction of the traditional capital asset pricing model.     

Trading Volume: Implications of an Intertemporal Capital Asset Pricing Model

We derive an intertemporal asset pricing model and explore its implications for trading volume and asset returns. We show that investors trade in only two portfolios: the market portfolio, and a hedging portfolio that is used to hedge the risk of changing market conditions. We empirically identify the hedging portfolio using weekly volume and returns data for U.S. stocks, and then test two of its properties implied by the theory: Its return should be an additional risk factor in explaining the cross section of asset returns, and should also be the best predictor of future market returns.     

Downside risk aversion,fixed-income exposure,and the value premium puzzle

The value premium is relatively small for investors with a material fixed-income exposure, such as insurance companies and pension funds, especially when they are downside-risk-averse. Value stocks are less attractive to these investors because they offer a relatively poor hedge against poor bond returns. This result arises for plausible, medium-term evaluation horizons of around one year. Our findings cast doubt on the practical relevance of the value premium for these investors and reiterate the importance of the choice of the relevant test portfolio, risk measure and investment horizon in empirical tests of market portfolio efficiency.     

Coskewness timing ability in the mutual fund industry

The ability of mutual fund managers to time coskewness successfully can help them manage their portfolio’s exposure to potential losses and improve their fund’s performance. This study assesses whether mutual fund managers are able to manage the market exposure of their investment portfolios given a change in coskewness. We demonstrate that fund managers investing in Small Blend and Small Growth stocks possess the ability to time coskewness. On average, the fund managers of these two investment objectives increase the market exposures of their portfolios about 2.749 % and 1.340 %, respectively, based on their anticipations on future coskewness. Superiority is driven from the fact that the fund managers in small capitalization stocks are successfully able to manage the tail risk of their funds’ portfolios. The fund-by-fund results confirm that the number of individual funds succeeding in timing market skewness of the Small Blend and Small Growth investment objectives is larger than the remaining types. The main findings are robust when controlling for other types of timing ability, the periods of financial turbulence, and the construction of coskewness.     

The high-volume return premium: evidence from the Chinese stock market

Extreme trading activity contains valuable information about the future evolution of stock prices in the Chinese stock market. Over the next 30 trading days after the initial volume shocks, a high-low volume portfolio earns a net average cumulate return of 2.08% and a high-low volume and size portfolio earns 3.37%, suggesting that there exists a high-volume return premium and that Chinese investors favor high-volume small-size stocks. However, a volume momentum portfolio earns a −1.65% net average cumulative return, indicating that Chinese stocks exhibit a short-run reversal. Portfolio construction, market risk, and firm size do not seem to explain the results.     

基于VaR的开放式股票型基金市场风险的测量与评价

通过采用半参数法计算投资组合VaR,得到相应VaR的近似置信区间,并结合成分VaR、边际VaR对投资组合vaR进行分解,结果发现,VaR作为风险管理工具同样可以有效应用于开放式股票型基金市场风险的测量与评价.     

Climate change news sensitivity and mutual fund performance

In the presence of rising concern about climate change that potentially affects risk and return of investors' portfolio companies, active investors might have dispersed climate change risk exposures. We compute mutual fund covariance with market-wide climate change news index and find that high (positive) climate news beta funds outperform low (negative) climate news beta funds by 0.24% per month on a risk-adjusted basis. High climate news beta funds tilt their holdings toward stocks with high potential to hedge against climate change news risk. In the cross section, such stocks yield higher excess returns, which are driven by greater pricing pressure and superior financial performance over our sample period.     

Are paper winners gamblers? Evidence from Australian retail investors

This study examines stock market gambling using a comprehensive set of investor characteristics and past portfolio performance measures. We find that retail investors overinvest in ‘lottery stocks’, stocks with gambling‐like properties. Significant portfolio underperformance is the result of gambling through lottery stocks. Investors are more likely to gamble following recent portfolio paper gains, regardless of realised performance, providing new evidence that paper gains trigger a house money effect. Investors trading greater values or holding more stocks, and older and female investors, are less likely to invest in lottery stocks.     

中国公募基金挖掘了股票市场异象吗？

公募基金是我国重要的机构投资者之一,分析其投资逻辑对理解机构投资者行为和公募基金的选择至关重要。基于2005年至2019年主动管理偏股型开放式基金数据,本文检验了公募基金对A股市场87个异象因子的挖掘。为解决因子维度过大问题,本文采用非参方法从87个异象因子中提取有效信息的综合指标A-Score,并根据基金持仓构建基金的异象投资指标AIM(Anomalies Investing Measure)。结果显示:(1)中国公募基金挖掘了市场异象;(2)利用AIM可以选择表现更好的基金,并能获得0.45%的月度多空组合收益;(3)基金经理的选股能力、风格选择能力和风控能力是其挖掘异象收益的主要来源;(4)异象挖掘可以为基金带来长期资金流,同时也缓和了市场的错误定价。