Naïve Buying Diversification and Narrow Framing by Individual Investors

We provide the first tests to distinguish whether individual investors equally balance their overall portfolios (naïve portfolio diversification, NPD) or, in contrast, equally balance the values of same-day purchases of multiple assets (naïve buying diversification, NBD). We find NBD in purchases of multiple stocks, and in mixed purchases of individual stocks and funds. In contrast, there is little evidence of NPD. Evidence suggests that NBD arises due to stock picking behavior and neglect of diversification. These findings suggest that behavioral finance theory should incorporate transaction, as well as portfolio, framing.     

Disagreement and return predictability of stock portfolios

This paper provides evidence that portfolio disagreement measured bottom-up from individual-stock analyst forecast dispersions has a number of asset pricing implications. For the market portfolio, market disagreement mean-reverts and is negatively related to ex post expected market return. Contemporaneously, an increase in market disagreement manifests as a drop in discount rate. For book-to-market sorted portfolios, the value premium is stronger among high disagreement stocks. The underperformance by high disagreement stocks is stronger among growth stocks. Growth stocks are more sensitive to variations in disagreement relative to value stocks. These findings are consistent with asset pricing theory incorporating belief dispersion.     

Portfolio insurance and prospect theory investors: Popularity and optimal design of capital protected financial products

Portfolio insurance strategies are used on both the institutional and the retail side of the asset management industry. While standard utility theory struggles to provide an explanation, this study justifies the popularity of portfolio insurance strategies in a behavioral finance context. We run Monte Carlo simulations as well as historical simulations for popular portfolio insurance strategies and benchmark strategies in order to evaluate the outcomes using cumulative prospect theory. Our simulation results indicate that most portfolio insurance strategies are the preferred investment strategy for a prospect theory investor. Moreover, the analysis provides insights into how portfolio insurance products should be designed and structured to meet the preferences of prospect theory investors as accurately as possible.     

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.     

The asset allocation decision in retirement: lessons from dollar-cost averaging

How should a retiree allocate his wealth between stocks and bonds? We address this question by studying whether it would have been better to have consumed periodically from stocks than from bonds over the seven decades of U.S. financial markets beginning in 1926 and ending in 1995. We find that retirees would have consistently done better by investing in stocks as opposed to bonds. When we analyze dispersion in consumption around its mean we find that there are greater chances for low consumption from the bond portfolio and greater chances for high consumption from the stock portfolio. Thus, we challenge the conventional wisdom that one should move away from stocks and towards bonds as one ages.     

Portfolio selection: An extreme value approach

We show theoretically that lower tail dependence (χ), a measure of the probability that a portfolio will suffer large losses given that the market does, contains important information for risk-averse investors. We then estimate χ for a sample of DJIA stocks and show that it differs systematically from other risk measures including variance, semi-variance, skewness, kurtosis, beta, and coskewness. In out-of-sample tests, portfolios constructed to have low values of χ outperform the market index, the mean return of the stocks in our sample, and portfolios with high values of χ. Our results indicate that χ is conceptually important for risk-averse investors, differs substantially from other risk measures, and provides useful information for portfolio selection.     

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.     

Fundamental indexation via smoothed cap weights

If prices of individual stocks are unbiased but noisy approximations to fundamental values, there will be a gap in returns between the standard cap-weighted market portfolio and the one based on fundamentals. The discrepancy occurs because, relative to fundamentals, cap-weights are too large (small) for stocks with positive (negative) deviations from fundamental values. It follows that the usual cap-weighted portfolio will underperform relative to the fundamental-based portfolio as long as prices revert to fundamental values. This has led Arnott et al. to propose new market indices based on a firm’s fundamental size as measured by its revenues, number of employees, and so on. In this paper we follow the same principle but propose to estimate fundamental weights using a smoothed average of standard cap-weights. Since the putative excess returns of a fundamentals-weighted portfolio requires reversion to fundamental values, and because fundamental values are likely to change slowly, we can estimate current fundamentals by smoothing the time series of a stock’s noisy prices. The determination of fundamental size in terms of accounting data is thereby replaced by a simple estimate based on price history. We derive expressions for expected returns of the market capitalization-based and fundamentals-based portfolios under various assumptions about (i) the random deviations from fundamental values and (ii) the change in fundamentals over time. We present empirical comparisons between portfolios and find the returns of the fundamentals-based portfolios exceed the standard indices by an amount comparable to the prior estimates that used accounting data to determine size.     

Effects of common factors on stock correlation networks and portfolio diversification

This study empirically investigates the effects of common factors on the connectivity of the network among stocks and on the distribution of the investment weights for stocks. The network is defined as a stock correlation network from the minimal spanning tree (MST), and portfolio is defined as an efficient portfolio from the Markowitz mean-variance (MV) optimization function (MVOF). For these research goals, we devise a method using the comparative correlation matrix (C-CM), which does not have the property of a single common factor included in the sample correlation matrix (S-CM). The results reveal that common factors clearly affect the changes of connectivity among stocks in the networks, and that their influence is much greater on stocks with many links to other stocks in the network. Further, common factors significantly affect the determination of the investment weight's distribution for stocks from the MVOF. In particular, among the common factors, a market factor plays a dominant role in both structuring the network among stocks and in constructing the well-diversified portfolio. In addition, the devised method of the C-CM without the property of the market factor in the S-CM plays a crucial role in constructing a more diversified portfolio with better out-of-sample performance in the future period. These results are robust in both the Korean and the U.S. stocks markets.     

基于小波神经网络的高阶CAPM实证研究

本文在传统CAPM的基础上,引入了一个高阶的CAPM。借助小波神经网络在非线性函数逼近方面的优势,使用上海证券交易所股票数据分别对二阶至四阶CAPM进行了实证分析。最终的研究结果表明:就上海股市而言,12只大盘股组合已经能够有效分散非系统风险,而12只小盘股不能充分化解非系统风险,存在所谓的规模效应;训练后的网络预测显示,高阶CAPM无论是在预测精度还是预测稳定性上都要明显优于传统的CAPM,在一个非系统风险得到充分分散的证券组合中,加入三阶矩的CAPM已经能够比较准确地把握风险资产的市场定价。     

TIME-VARYING FACTORS AND CROSS-AUTOCORRELATIONS IN SHORT-HORIZON STOCK RETURNS

In this paper I show that the lead-lag pattern between large and small market value portfolio returns is consistent with differential variations in their expected return components. I find that the larger predictability of returns on the portfolio of small stocks may be due to a higher exposure of these firms to persistent (time-varying) latent factors. Additional evidence suggests that the asymmetric predictability cannot be fully explained by lagged price adjustments to common factor shocks: (i) lagged returns on large stocks do not have a strong causal effect on returns on small stocks; (ii) trading volume is positively related to own- and cross-autocorrelations in weekly portfolio returns; and (iii) significant cross-autocorrelation exists between current returns on large stocks and lagged returns on small stocks when trading volume is high.     

Idiosyncratic Volatility Covariance and Expected Stock Returns

Given that the idiosyncratic volatility (IDVOL) of individual stocks co‐varies, we develop a model to determine how aggregate idiosyncratic volatility (AIV) may affect the volatility of a portfolio with a finite number of stocks. In portfolio and cross‐sectional tests, we find that stocks whose returns are more correlated with AIV innovations have lower returns than those that are less correlated with AIV innovations. These results are robust to controlling for the stock's own IDVOL and market volatility. We conclude that risk‐averse investors pay a premium for stocks that pay well when AIV is high, consistent with our model.     

Risk aversion vs. individualism: what drives risk taking in household finance?

Despite a considerable premium on equity with respect to risk-free assets, many households do not own stocks. We ask why the prevalence of stockholding is so limited. We focus on individuals’ attitudes toward risk and identify relevant factors that affect the willingness to take financial risks. Our empirical evidence contradicts standard portfolio theory, as it does not indicate a significant relationship between risk aversion and financial risk taking. However, our analysis supports the behavioral view that psychological factors rooted in national culture affect portfolio choice. Individualism, which is linked to overconfidence and overoptimism, has a significantly positive effect on financial risk taking. In microdata from Germany and Singapore, as well as in cross-country data, we find evidence consistent with low levels of individualism being an important factor in explaining the limited participation puzzle.     

Hedging, Familiarity and Portfolio Choice

We exploit the restrictions of intertemporal portfolio choicein the presence of nonfinancial income risk to test hedgingusing the information contained in the actual portfolio of theinvestor. We use a unique data set of Swedish investors withinformation broken down at the investor level and into variouscomponents of investor wealth, income, and demographic characteristics.Portfolio holdings are identified at the stock level. We showthat investors do not hedge but invest in stocks closely relatedto their nonfinancial income. We explain this with familiarity,that is, the tendency to concentrate holdings in stocks to whichthe investor is geographically or professionally close or thathe has held for a long period. We show that familiarity is nota behavioral bias, but is information driven. Familiarity-basedinvestment allows investors to earn higher returns than theywould have otherwise earned if they had hedged.     

Speculative trading preferences of retail investor birth cohorts

This study examines the effect of investor birth cohorts on speculative investment preferences. Using retail trading and portfolio data from Finland over two decades, we find that individuals who have experienced desirable macro-economic and social conditions during adolescence, such as high gross domestic product (GDP) growth and low divorce rates, are more likely to invest in speculative stocks. A positive relation is found between the proportion of speculative-prone cohorts in the stock market and returns of stocks of lottery nature. We provide new evidence on the adverse effect of speculative investments, finding that cohorts with higher speculative investment weights on their portfolios achieve lower absolute and risk-adjusted returns. We also provide support for earlier research that identifies a positive association between recent portfolio performance and the propensity to invest in speculative stocks.     

Returns,volatility and investor sentiment: Evidence from European stock markets

In this study, we show that patterns in returns behave as if investors, influenced by their level of optimism, selected stocks according to their volatility. Our goal is to confirm the contribution of behavioral finance while showing that investor sentiment can be profitably used by practitioners. We incorporate volatility in the relationship between investor sentiment and future returns, this is the main originality of our approach. Our methodology consists in comparing returns, volatility and higher-order moments of portfolios managed with investor sentiment against those obtained either with passive (buy and hold) portfolio management or with a minimum variance portfolio. Portfolios managed with investor sentiment have better returns and involve less risk under certain conditions.     

Portfolio Distortions Among Institutional Investors: Evidence from China

The behavior of institutional investors often deviates from established personal or social norms; this deviation may reflect either an informational advantage or a psychological bias. In this paper, we investigate the reasons Chinese mutual funds hold lottery-type stocks, which are characterized by low average returns and high risk. We find that funds at the aggregate level do not exhibit a propensity to gamble, but when they do gamble, they earn abnormal returns on lottery-type investments. Gambling-related outperformance is greater among held firms with characteristics that enable fund managers to obtain more informational advantages. Our results suggest that portfolio distortion is driven by the ability of managers to capitalize private information rather than by behavioral bias.     

What determines mutual fund trading in foreign stocks?

We examine the portfolio rebalancing, measured by the equity churn rate, of mutual funds from 29 countries based on annual stockholdings over the 1999–2006 period. We find that funds more often trade the stocks of companies located in countries with higher degree of information asymmetry and are less familiar to fund managers, after we control for the effects of stock market development and investor protection. Consistent with the behavioral bias, fund managers more often rebalance stocks in foreign markets that perform well. This bias is exacerbated when fund managers are less familiar with and less informed about those markets.     

我国基金规模对业绩及其投资行为的影响分析

本文从实证角度出发,采用面板数据分析法研究基金规模与业绩及其投资行为之间的关系。结果显示:随着基金规模的扩大,基金经理先是倾向于提高投资组合内股票的持股比例,然后才是增加股票的数目,提高投资的分散化程度。大型基金随规模变大其投资分散化程度提高较显著;而大盘股基金随规模扩大其持股比例提高的程度较显著。     

Earnings and price momentum

This paper examines whether earnings momentum and price momentum are related. Both in time-series as well as in cross-sectional asset pricing tests, we find that price momentum is captured by the systematic component of earnings momentum. The predictive power of past returns is subsumed by a zero-investment portfolio that is long on stocks with high earnings surprises and short on stocks with low earnings surprises. Further, returns to the earnings-based zero-investment portfolio are significantly related to future macroeconomic activities, including growth in GDP, industrial production, consumption, labor income, inflation, and T-bill returns.