中国A股市场过度波动之谜——基于日个股回报率的实证研究

本文首次基于方差差(Variance Difference)指标对股票回报率过度波动进行量化,并分别运用组合研究和Fama-Macbeth回归的方法,从过度波动与股票回报率之间关系的角度研究了中国A股市场的过度波动现象。基于1995-2010年A股日回报率的实证结果表明,A股市场日回报率波动中存在投资者过度反应导致的过度波动,过度波动带来的额外风险"驱逐"了风险回避的理性投资者,使得股市出现低估。通过每月买入过度波动最大的20%股票,同时卖出过度波动最小的20%股票,能获得显著为正的超额收益,并且该超额收益不能被市场风险所解释。     

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。     

Non-Gaussian diversification: When size matters

Classical portfolio theory informs investors that they should have a large number of assets in their portfolios in order to diversify risk. We show that the non-Gaussian features of stock return distribution may not allow for this risk protection in times of crisis. Moreover, we demonstrate empirically that, if investors are risk-averse and consider higher order moments, they have numerous incentives not to diversify their portfolios fully. This is caused by the evolution of both large losses and asymmetry of returns when the numbers of assets in a portfolio change.     

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.     

All Guts,No Glory: Trading and Diversification among Online Investors

I explore cross‐sectional portfolio performance in a sample containing 324,736 transactions conducted by 16,831 Swedish investors at an Internet discount brokerage firm during the period May 1999 to March 2002. On average, investors hold undiversified portfolios, show a strong preference for risk, and trade aggressively. I measure performance using a panel data model, and explain the cross‐sectional variation using investors' turnover, portfolio size and degree of diversification. I find that turnover is harmful to performance due to fees, and is therefore more predominant among investors with small portfolios. I argue that the degree of diversification is a proxy for investor skill, and it has a separate and distinct positive effect on performance. Investors underperform the market by about 8.5% per year on average, of which half can be attributed to trading costs.     

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.     

Is gold good for portfolio diversification? A stochastic dominance analysis of the Paris stock exchange

This paper aims to assess the role of gold quoted in Paris in the diversification of French portfolios from 1949 to 2012 using the stochastic dominance (SD) approach. The principal advantage of this method is that there is no restriction on the distribution of the returns. Our results show that stock portfolios including gold stochastically dominate those without gold at the second and third orders. This implies that risk-averse investors would be better off by including gold in their stock portfolios to maximize their expected utilities. The study on sub-periods shows that this result holds especially in unstable or crisis times. However, these results do not hold for bond or risk-free portfolios, for which the portfolios without gold dominate those with gold. To check the robustness of our results, our SD analysis of a mixed portfolio (50% stocks, 30% bonds and 20% the risk-free asset) provides results similar to those for portfolios with stocks only, except from 1971 to 1983. Portfolios including gold quoted in London show results similar to those from Paris. The results of mean–variance performance measures confirm the findings of previous studies that gold is good for the diversification of stock portfolios but not for bond portfolios.     

Is Bitcoin a better portfolio diversifier than gold? A copula and sectoral analysis for China

This paper aims to compare Bitcoin with gold in the diversification of Chinese portfolios using daily data over the 2010–2020 period. We propose a new development of copula-based joint distribution function of returns to simulate the Value-at-Risk and expected shortfall of portfolios including Bitcoin (or gold) and those without it. The stochastic dominance method is also used to compare the return distributions of the three types of portfolios. Empirical results show that gold is a better portfolio diversifier than Bitcoin as it helps better reduce the risk of portfolios. On the other hand, Bitcoin better increases the return but also increases the risk. The stochastic dominance results further show that portfolios diversified by gold dominate those diversified by Bitcoin. Based on these findings, we conclude that in China, gold is a better portfolio diversifier than Bitcoin for risk-averse investors. However, for risk-seeking investors, Bitcoin can be a better choice. This result is found to be robust to the time, frequency and currency effects.     

A note on the returns from minimum variance investing

Disappointed with the performance of market weighted benchmark portfolios yet skeptical about the merits of active portfolio management, investors in recent years turned to alternative index definitions. Minimum variance investing is one of these popular concepts. I show in this paper that the portfolio construction process behind minimum variance investing implicitly picks up risk-based pricing anomalies. In other words the minimum variance tends to hold low beta and low residual risk stocks. Long/short portfolios based on these characteristics have been associated in the empirical literature with risk adjusted outperformance. This paper shows that 83% of the variation of the minimum variance portfolio excess returns (relative to a capitalization weighted alternative) can be attributed to the FAMA/FRENCH factors as well as to the returns on two characteristic anomaly portfolios. All regression coefficients (factor exposures) are highly significant, stable over the estimation period and correspond remarkably well with our economic intuition. The paper also shows that a direct combination of market weighted benchmark portfolio and risk based characteristic portfolios will provide a statistically significant improvement over the indirect pickup via the minimum variance portfolio.     

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.     

Ambiguous Information,Portfolio Inertia,and Excess Volatility

I study the effects of risk and ambiguity (Knightian uncertainty) on optimal portfolios and equilibrium asset prices when investors receive information that is difficult to link to fundamentals. I show that the desire of investors to hedge ambiguity leads to portfolio inertia and excess volatility. Specifically, when news is surprising, investors may not react to price changes even if there are no transaction costs or other market frictions. Moreover, I show that small shocks to cash flow news, asset betas, or market risk premia may lead to drastic changes in the stock price and hence to excess volatility.     

An analysis of the impact of timberland, farmland and commercial real estate in the asset allocation decisions of institutional investors

We examine the effects of including timberland, farmland and commercial real estate in a mixed asset portfolio with stocks, government bonds and T-Bills. Using both smoothed and unsmoothed returns (as per Geltner [Geltner, D. (1993). Estimating market values from appraised values without assuming an efficient market. Journal of Real Estate Research, 8, 25-345.]) and both constrained and unconstrained allocation assumptions (as per Eichhorn, Gupta and Stubbs [Eichhorn, D., Gupta, F., & Stubbs, E. (1998). Using constraints to improve the robustness of asset allocation. Journal of Portfolio Management, Spring, 41-48.]), we employ Markowitz portfolio optimization and find widely varying allocation outcomes. However, timberland entered nearly all portfolios, accounting for large percentages in several scenarios, while farmland entered only low-risk portfolios. At lower risk levels, commercial real estate dominates the real estate allocation but as acceptable risk levels rise, timberland supplants commercial real estate as the primary component of the portfolio's real estate allocation.     

Performance Attribution of US Institutional Investors

Institutional investors play a prominent role in today's markets. Quarterly reported portfolio holdings make it possible to evaluate the risk-adjusted equity investment performance of all institutional investors in the United States during 1981–2002. The results indicate that institutional investors have been successful in managing client assets; they have added significant value by generating excess returns after controlling for underlying portfolio risk factors. Style choice is the main factor in determining overall portfolio performance, but institutional investors also displayed significant stock selection skills during the period. The stocks they choose for their portfolios have outperformed the stocks they exclude.     

Capital market equilibrium with heterogeneous investors

As a two-parameter model that satisfies stochastic dominance, the mean-extended Gini model is used to build efficient portfolios. The model quantifies risk aversion heterogeneity in capital markets. In a simple Edgeworth box framework, we show how capital market equilibrium is achieved for risky assets. This approach provides a richer basis for analysing the pricing of risky assets under heterogeneous preferences. Our main results are: (1) identical investors, who use the same statistic to represent risk, hold identical portfolios of risky assets equal to the market portfolio; and (2) heterogeneous investors as expressed by the variance or the extended Gini hold different risky assets in portfolios, and therefore no one holds the market portfolio.     

Leverage constraints and asset prices: Insights from mutual fund risk taking

Prior theory suggests that time variation in the degree to which leverage constraints bind affects the pricing kernel. We propose a measure for this leverage constraint tightness by inverting the argument that constrained investors tilt their portfolios to riskier assets. We show that the average market beta of actively managed mutual funds—intermediaries facing leverage restrictions—captures their desire for leverage and thus the tightness of constraints. Consistent with theory, it strongly predicts returns of the betting-against-beta portfolio, and is a priced risk factor in the cross-section of mutual funds and stocks. Funds with low exposure to the factor outperform high-exposure funds by 5% annually, and for stocks this difference reaches 7%. Our results show that the tightness of leverage constraints has important implications for asset prices.     

Household portfolio optimization with XTFs? An empirical study using the SHS-base

XTFs are plain-vanilla Exchange Traded Funds (ETFs) which replicate a broad, internationally diversified market index. We question, if XTFs can optimize the performance of households’ portfolios when taking multiple relevant asset classes into account, not only stocks. As opposed to most existing studies, we apply representative household portfolio data to estimate households’ portfolios. Households’ portfolios in our sample show similar compositions and can be grouped into one of three stylized portfolio compositions which exhibit asset class concentrations on cash/savings, mutual funds and individual stocks. For each stylized portfolio, we first investigate if an easily investable 60/40 stock/bond XTF portfolio which is risk-adjusted (including (de-)leverage costs) to the risk of the stylized portfolios, achieves higher returns than the stylized portfolios. This is the case for all stylized portfolios, even those with concentrations on cash/savings or mutual funds. Second, we examine risk/return-changes when replacing the entire risky assets of the stylized portfolios with the 60/40 stock/bond XTF portfolio including transaction costs. This leads to return enhancements in all stylized portfolios and particularly in the portfolio with high stock concentrations to risk reductions. Overall, we find that XTFs are generally suitable to optimize the performance of households’ portfolios under consideration of multiple relevant asset classes.     

Individual investors’ information use,subjective expectations,and portfolio risk and return

What information do individual investors use when making their financial decisions and how is it related to their stock market expectations, their confidence in these expectations, and the risk and return of their stock portfolios? I study these questions by combining survey data on the information usage among individual investors in Sweden with detailed registry data on their stock portfolios. I find that investors use filtered financial information (e.g. information packaged by a professional intermediary) more frequently than they use unfiltered financial information (e.g. information from annual reports and financial statements). Investors who frequently use filtered financial information are, however, more confident in their stock market expectations and take larger risks in their stock portfolios. Investors that instead use unfiltered financial information take lower portfolio risks and obtain higher portfolio returns. The findings in this paper thus suggest that investors can improve their financial decisions by using more unfiltered financial information rather than filtered financial information when they make their financial decisions.     

Liquidity risk and stock returns around the world

The recent global financial crisis demonstrates that market liquidity is a prominent systematic risk globally. We find that local liquidity risk, in addition to the local market, value and size factors, demands a systematic premium across stocks in 11 developed markets. This local pricing premium is smaller in countries where the country-level corporate boards are more effective and where there are less insider trading activities. We also discover that global liquidity risk is a significant pricing factor across all developed country market portfolios after controlling for global market, value, and size factors. The contribution of this risk to the return on a country market portfolio is economically and statistically significant within and across regions.     

Preferred risk habitat of individual investors

The preferred risk habitat hypothesis, introduced here, is that individual investors select stocks whose volatilities are commensurate with their risk aversion. The data, 1995–2000 holdings of over 20,000 clients at a large German broker, are consistent with the predictions of the hypothesis: the returns of stocks within each portfolio have remarkably similar volatilities, when stocks are sold they are replaced by stocks of similar volatilities, and the more risk-averse customers indeed hold less volatile stocks. Greater volatility specialization is associated with lower Sharpe ratios, primarily because more specialized investors hold fewer stocks and thereby expose themselves to more unsystematic risk.     

Nonlinearly weighted convex risk measure and its application

We propose a new class of risk measures which satisfy convexity and monotonicity, two well-accepted axioms a reasonable and realistic risk measure should satisfy. Through a nonlinear weight function, the new measure can flexibly reflect the investor’s degree of risk aversion, and can control the fat-tail phenomenon of the loss distribution. A realistic portfolio selection model with typical market frictions taken into account is established based on the new measure. Real data from the Chinese stock markets and American stock markets are used for empirical comparison of the new risk measure with the expected shortfall risk measure. The in-sample and out-of-sample empirical results show that the new risk measure and the corresponding portfolio selection model can not only reflect the investor’s risk-averse attitude and the impact of different trading constraints, but can find robust optimal portfolios, which are superior to the corresponding optimal portfolios obtained under the expected shortfall risk measure.