This paper finds statistically and economically significant out-of-sample portfolio benefits for an investor who uses models of return predictability when forming optimal portfolios. Investors must ...account for estimation risk, and incorporate an ensemble of important features, including time-varying volatility, and time-varying expected returns driven by payout yield measures that include share repurchase and issuance. Prior research documents a lack of benefits to return predictability, and our results suggest that this is largely due to omitting time-varying volatility and estimation risk. We also document the sequential process of investors learning about parameters, state variables, and models as new data arrive.
Using panel regression estimates from the IMF's CPIS survey of foreign debt and equity portfolios across 174 originating and 50 destination countries from 2001 to 2007, we clarify the role of culture ...and extend the set of cultural variables that have been investigated in gravity models of foreign portfolio investment (FPI). Incorporating Hofstede's cultural dimensions of individualism, masculinity, power distance and uncertainty avoidance, we show how cultural traits in both originating and destination countries, as well as the cultural distances that separate them, interact with geographic distance and other gravity variables to determine global FPI patterns. We find hitherto unreported effects and show that while gravity always deters FPI, aspects of culture and cultural distance can offset this by supporting FPI. PUBLICATION ABSTRACT
We examine whether the concern about insurers selling similar assets due to an overlap in holdings is justified. We measure this overlap using cosine similarity and find that insurers with more ...similar portfolios have larger subsequent common sales. When faced with a shock to assets or liabilities, exposed insurers with greater portfolio similarity have larger common sales that impact prices. Our portfolio similarity measure can be used by regulators to predict the common selling of any institution that reports security or asset class holdings, making the measure a useful ex ante predictor of divestment behavior in times of market stress.
Using a novel database that tracks web traffic on the Security Exchange Commission's EDGAR server between 2004 and 2015, we show that institutional investors gather information on a very particular ...subset of firms and insiders, and their surveillance is very persistent over time. This tracking behavior has powerful implications for their portfolio choice and its information content. An institution that downloaded an insider trading filing by a given firm last quarter increases its likelihood of downloading an insider trading filing on the same firm by more than 41.3 percentage points this quarter. Moreover, the average tracked stock that an institution buys generates annualized alphas of over 12% relative to the purchase of an average non tracked stock. We find that institutional managers tend to track top executives and to share educational and locational commonalities with the specific insiders they choose to follow. Collectively, our results suggest that the information in tracked trades is important for fundamental firm value and is only revealed following the information-rich dual trading by insiders and linked institutions.
Window Dressing in Mutual Funds Agarwal, Vikas; Gay, Gerald D.; Ling, Leng
The Review of financial studies,
11/2014, Letnik:
27, Številka:
11
Journal Article
Recenzirano
Odprti dostop
We provide a rationale for window dressing wherein investors respond to conflicting signals of managerial ability inferred from a fund's performance and disclosed portfolio holdings. We contend that ...window dressers make a risky bet on their performance during a reporting delay period, which affects investors' interpretation of the conflicting signals and hence their capital allocations. Conditional on good (bad) performance, window dressers benefit (suffer) from higher (lower) investor flows compared with non–window dressers. Window dressers also show poor past performance, possess little skill, and incur high portfolio turnover and trade costs, characteristics which in turn result in worse future performance.
The Effect of Housing on Portfolio Choice CHETTY, RAJ; SÁNDOR, LÁSZLÓ; SZEIDL, ADAM
The Journal of finance (New York),
June 2017, Letnik:
72, Številka:
3
Journal Article
Recenzirano
Odprti dostop
We show that characterizing the effects of housing on portfolios requires distinguishing between the effects of home equity and mortgage debt. We isolate exogenous variation in home equity and ...mortgages by using differences across housing markets in house prices and housing supply elasticities as instruments. Increases in property value (holding home equity constant) reduce stockholdings, while increases in home equity wealth (holding property value constant) raise stockholdings. The stock share of liquid wealth would rise by 1 percentage point—6% of the mean stock share—if a household were to spend 10% less on its house, holding fixed wealth.
Stock Options as Lotteries BOYER, BRIAN H.; VORKINK, KEITH
The Journal of finance (New York),
August 2014, Letnik:
69, Številka:
4
Journal Article
Recenzirano
We investigate the relationship between ex ante total skewness and holding returns on individual equity options. Recent theoretical developments predict a negative relationship between total skewness ...and average returns, in contrast to the traditional view that only coskewness is priced. We find, consistent with recent theory, that total skewness exhibits a strong negative relationship with average option returns. Differences in average returns for option portfolios sorted on ex ante skewness range from 10% to 50% per week, even after controlling for risk. Our findings suggest that these large premiums compensate intermediaries for bearing unhedgeable risk when accommodating investor demand for lottery-like options.
Correlation Risk and Optimal Portfolio Choice BURASCHI, ANDREA; PORCHIA, PAOLO; TROJANI, FABIO
The Journal of finance (New York),
February 2010, Letnik:
65, Številka:
1
Journal Article
Recenzirano
Odprti dostop
We develop a new framework for multivariate intertemporal portfolio choice that allows us to derive optimal portfolio implications for economies in which the degree of correlation across industries, ...countries, or asset classes is stochastic. Optimal portfolios include distinct hedging components against both stochastic volatility and correlation risk. We find that the hedging demand is typically larger than in univariate models, and it includes an economically significant covariance hedging component, which tends to increase with the persistence of variance—covariance shocks, the strength of leverage effects, the dimension of the investment opportunity set, and the presence of portfolio constraints.
This paper contributes to the literature on cryptocurrencies, portfolio management and estimation risk by comparing the performance of naïve diversification, Markowitz diversification and the ...advanced Black–Litterman model with VBCs that controls for estimation errors in a portfolio of cryptocurrencies. We show that the advanced Black–Litterman model with VBCs yields superior out-of-sample risk-adjusted returns as well as lower risks. Our results are robust to the inclusion of transaction costs and short-selling, indicating that sophisticated portfolio techniques that control for estimation errors are preferred when managing cryptocurrency portfolios.
•We compare different portfolio construction methods using cryptocurrencies.•Black–Litterman with VBCs that controls for estimation errors is superior.•It provides superior out-of-sample risk-adjusted returns and lower risk.•Our results are robust to transaction costs and short-selling.
Mean-variance portfolios constructed using the sample mean and covariance matrix of asset returns perform poorly out of sample due to estimation error. Moreover, it is commonly accepted that ...estimation error in the sample mean is much larger than in the sample covariance matrix. For this reason, researchers have recently focused on the minimum-variance portfolio, which relies solely on estimates of the covariance matrix, and thus usually performs better out of sample. However, even the minimum-variance portfolios are quite sensitive to estimation error and have unstable weights that fluctuate substantially over time. In this paper, we propose a class of portfolios that have better stability properties than the traditional minimum-variance portfolios. The proposed portfolios are constructed using certain robust estimators and can be computed by solving a single nonlinear program, where robust estimation and portfolio optimization are performed in a single step. We show analytically that the resulting portfolio weights are less sensitive to changes in the asset-return distribution than those of the traditional portfolios. Moreover, our numerical results on simulated and empirical data confirm that the proposed portfolios are more stable than the traditional minimum-variance portfolios, while preserving (or slightly improving) their relatively good out-of-sample performance.
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