The relationship of capitalization period length with market portfolio composition and betas

Beta coefficients are not stable if we modify the observation periods of the returns. The market portfolio composition also varies, whereas changes in the betas are the same, whether they are calculated as regression coefficients or as a ratio of the risk premiums. The instantaneous beta, obtained when the capitalization frequency approaches infinity, may be a useful tool in portfolio selection.

The relationship of capitalization period length with market portfolio composition and betas

Beta coefficients are not stable if we modify the observation periods of the returns. The market portfolio composition also varies, whereas changes in the betas are the same, whether they are calculated as regression coefficients or as a ratio of the risk premiums. The instantaneous beta, obtained when the capitalization frequency approaches infinity, may be a useful tool in portfolio selection.

Sampling Interval and estimated Betas : Implications for the Presence of Transitory Components in Stock Prices

We provide a theoretical framework to explain the empirical finding that the estimated betas are sensitive to the sampling interval even when using continuously compounded returns. We suppose that stock prices have both permanent and transitory components. The permanent component is a standard geometric Brownian motion while the transitory component is a stationary Ornstein-Uhlenbeck process. The discrete time representation of the beta depends on the sampling interval and two components labelled \"permanent and transitory betas\". We show that if no transitory component is present in stock prices, then no sampling interval effect occurs. However, the presence of a transitory component implies that the beta is an increasing (decreasing) function of the sampling interval for more (less) risky assets. In our framework, assets are labelled risky if their \"permanent beta\" is greater than their \"transitory beta\" and vice versa for less risky assets. Simulations show that our theoretical results provide good approximations for the means and standard deviations of estimated betas in small samples. Our results can be perceived as indirect evidence for the presence of a transitory component in stock prices, as proposed by Fama and French (1988) and Poterba and Summers (1988).

Inference for nonparametric high-frequency estimators with an application to time variation in betas

We consider the problem of conducting inference on nonparametric high-frequency estimators without knowing their asymptotic variances. We prove that a multivariate subsampling method achieves this goal under general conditions that were not previously available in the literature. We suggest a procedure for a data-driven choice of the bandwidth parameters. Our simulation study indicates that the subsampling method is much more robust than the plug-in method based on the asymptotic expression for the variance. Importantly, the subsampling method reliably estimates the variability of the Two Scale estimator even when its parameters are chosen to minimize the finite sample Mean Squared Error; in contrast, the plugin estimator substantially underestimates the sampling uncertainty. By construction, the subsampling method delivers estimates of the variance-covariance matrices that are always positive semi-definite. We use the subsampling method to study the dynamics of financial betas of six stocks on the NYSE. We document significant variation in betas within year 2006, and find that tick data captures more variation in betas than the data sampled at moderate frequencies such as every five or twenty minutes. To capture this variation we estimate a simple dynamic model for betas. The variance estimation is also important for the correction of the errors-in-variables bias in such models. We find that the bias corrections are substantial, and that betas are more persistent than the naive estimators would lead one to believe.

Systematic property risk: quantifying UK property betas 1983-2005

The increased frequency in reporting UK property performance figures, coupled with the acceptance of the IPD database as the market standard, has enabled property to be analysed on a comparable level with other more frequently traded assets. The most widely utilised theory for pricing financial assets, the Capital Asset Pricing Model (CAPM), gives market (systematic) risk, beta, centre stage. This paper seeks to measure the level of systematic risk (beta) across various property types, market conditions and investment holding periods. This paper extends the authors’ previous work on investment holding periods and how excess returns (alpha) relate to those holding periods. We draw on the uniquely constructed IPD/Gerald Eve transactions database, containing over 20,000 properties over the period 1983-2005. This research allows us to confirm our initial findings that properties held over longer periods perform in line with overall market performance. One implication of this is that over the long-term performance may be no different from an index tracking approach.

Volatility persistence and time-varying betas in the UK real estate market

This paper investigates the degree of return volatility persistence and the time-varying behaviour of systematic risk (beta) for 31 market segments in the UK real estate market. The findings suggest that different property types exhibit differences in volatility persistence and time variability. There is also evidence that the volatility persistence of each market segment and its systematic risk are significantly positively related. Thus, the systematic risks of different property types tend to move in different directions during periods of increased market volatility. Finally, the market segments with systematic risks less than one tend to show negative time variability, while market segments with systematic risk greater than one generally show positive time variability, indicating a positive relationship between the volatility of the market and the systematic risk of individual market segments. Consequently safer and riskier market segments are affected differently by increases in market volatility.

Conditional alphas and realized betas

This paper proposes a two-step procedure to back out the conditional alpha of a given stock using high-frequency data. We rst estimate the realized factor loadings of the stocks, and then retrieve their conditional alphas by estimating the conditional expectation of their risk-adjusted returns. We start with the underlying continuous-time stochastic process that governs the dynamics of every stock price and then derive the conditions under which we may consistently estimate the daily factor loadings and the resulting conditional alphas. We also contribute empiri-cally to the conditional CAPM literature by examining the main drivers of the conditional alphas of the S&P 100 index constituents from January 2001 to December 2008. In addition, to con rm whether these conditional alphas indeed relate to pricing errors, we assess the performance of both cross-sectional and time-series momentum strategies based on the conditional alpha estimates. The ndings are very promising in that these strategies not only seem to perform pretty well both in absolute and relative terms, but also exhibit virtually no systematic exposure to the usual risk factors (namely, market, size, value and momentum portfolios).

A avaliação do desempenho condicional de fundos de investimento e o problema das regressões espúrias: um estudo empírico para o mercado português

Neste artigo é avaliado e comparado o desempenho de fundos de acções pertencentes ao mercado Português, que investem quer no mercado local quer no mercado Europeu, utilizando modelos de avaliação do desempenho condicionais e não condicionais. Em vez das habituais variáveis locais, este estudo utiliza variáveis de informação pública europeias e analisa detalhadamente o impacto nas estimativas do desempenho da utilização de variáveis condicionais sujeitas a um processo estocástico de remoção da tendência (“detrended”), de modo a evitar os efeitos decorrentes de potenciais regressões espúrias. Os resultados sugerem que os gestores dos fundos não são capazes de “bater” o mercado, apresentando desempenhos negativos ou neutros. Para além disso, é possível observar um efeito distância, na medida em que os gestores que investem no mercado local apresentam um desempenho superior ao dos que investem no mercado Europeu. A introdução da condicionalidade melhora quer as estimativas de desempenho quer o poder explicativo dos modelos, com evidência de betas (mas não de alfas) variáveis ao longo do tempo. No entanto, a utilização de variáveis “detrended” permite concluir que a significância estatística das variáveis de informação se deve à existência de regressões espúrias.

A Avaliação do Desempenho de Fundos de Investimento: Modelos Condicionais vs. Modelos não Condicionais

A eficácia das medidas tradicionais de avaliação do desempenho de fundos de investimento tem sido amplamente posta em causa na literatura, sendo-lhes apontadas importantes limitações de ordem conceptual e econométrica. Uma dessas limitações reside no facto de as mesmas pressuporem a existência de uma medida de risco constante ao longo do período de avaliação. Na tentativa de fazer face a esta limitação e considerando que tanto o risco como as rendibilidades esperadas variam ao longo do tempo, um dos mais recentes desenvolvimentos nesta área está relacionado com a utilização de modelos condicionais, que avaliam os gestores das carteiras levando em consideração a informação pública disponível no momento em que as rendibilidades foram geradas. Neste contexto, depois de feita uma revisão da literatura, leva-se a cabo uma análise empírica, com base numa amostra de fundos pertencentes ao mercado português que investem quer no mercado nacional quer no mercado europeu, com o intuito de se estimarem e compararem as medidas de avaliação tradicionais com as suas versões condicionais, de modo a aferir das potenciais vantagens desta nova abordagem. Para além de utilizar quer modelos parcialmente condicionais quer modelos totalmente condicionais, este estudo empírico utiliza variáveis de informação europeias, em vez das mais usuais variáveis locais, e leva em consideração a utilização de variáveis condicionais detrended, um procedimento que pretende evitar o surgimento de regressões “falsas”. Um outro ponto que é objecto de análise é a avaliação do impacto do enviesamento provocado pela utilização de amostras que contenham apenas fundos que sobreviveram a todo o período da pesquisa (survivorship bias), um problema que afecta a grande maioria dos estudos empíricos. Os resultados da análise efectuada sugerem que os gestores dos fundos não são capazes de “bater” o mercado, evidenciando desempenhos negativos ou neutros. Para além disso, observa-se um distance effect, pois os gestores que investem no mercado local obtêm desempenhos superiores aos que investem no mercado europeu. A introdução da condicionalidade nos modelos fez com que tanto o desempenho dos fundos como o poder explicativo dos modelos melhorasse ligeiramente. Para além disso, há evidência de betas (mas não de alfas) variáveis ao longo do tempo em função das variáveis de informação. Contudo, a significância destas variáveis parece estar relacionada com a existência de regressões “falsas”. No que respeita ao survivorship bias, este tem um impacto pequeno nas estimativas do desempenho.

Conditioning information in mutual fund performance evaluation: Portuguese evidence

We estimate and compare the performance of Portuguese-based mutual funds that invest in the domestic market and in the European market using unconditional and conditional models of performance evaluation. Besides applying both partial and full conditional models, we use European information variables, instead of the most common local ones, and consider stochastically detrended conditional variables in order to avoid spurious regressions. The results suggest that mutual fund managers are not able to outperform the market, presenting negative or neutral performance. The incorporation of conditioning information in performance evaluation models is supported by our findings, as it improves the explanatory power of the models and there is evidence of both time-varying betas and alphas related to the public information variables. It is also shown that the number of lags to be used in the stochastic detrending procedure is a critical choice, as it will impact the significance of the conditioning information. In addition, we observe a distance effect, since managers who invest locally seem to outperform those who invest in the European market. However, after controlling for public information, this effect is slightly reduced. Furthermore, the results suggest that survivorship bias has a small impact on performance estimates.

Measuring fund performance using multi-factor models: evidence for the Portuguese market

This paper examines the performance of Portuguese equity funds investing in the domestic and in the European Union market, using several unconditional and conditional multi-factor models. In terms of overall performance, we find that National funds are neutral performers, while European Union funds under-perform the market significantly. These results do not seem to be a consequence of management fees. Overall, our findings are supportive of the robustness of conditional multi-factor models. In fact, Portuguese equity funds seem to be relatively more exposed to smallcaps and more value-oriented. Also, they present strong evidence of time-varying betas and, in the case of the European Union funds, of time-varying alphas too. Finally, in terms of market timing, our tests suggest that mutual fund managers in our sample do not exhibit any market timing abilities. Nevertheless, we find some evidence of timevarying conditional market timing abilities but only at the individual fund level.

Style and performance of international socially responsible funds in Europe

This paper analyses the performance and investment styles of internationally oriented Socially Responsible Investment (SRI)funds, domiciled in eight European markets, in comparison with characteristics-matched conventional funds. To the best of our knowledge, this is the first multi-country study, focused on international SRI funds (investing in Global and in European equities), to combine the matched-pairs approach with the use of robust conditional multi-factor performance evaluation models, which allow for both time-varying alphas and betas and also control for home biases and spurious regression biases.In general, the results show that differences in the performance of international SRI funds and their conventional peers are not statistically significant. Regarding investment styles, SRI and conventional funds exhibit similar factor exposures in most cases. In addition,conventional benchmarks present a higher explaining power of SRI fund returns than SRI benchmarks. Our results also show significant differences in the investment styles of SRI funds according to whether they use “best-in-class” screening strategies or not. When compared to SRI funds that employ simple negative and/or positive screens, SRI “best-in-class” funds present significantly lower exposures to small caps and momentum strategies and significantly higher exposures to local stocks.

An Extension of Gompertzian Growth Dynamics Weibull and Frechet Models

In this work a new probabilistic and dynamical approach to an extension of the Gompertz law is proposed. A generalized family of probability density functions, designated by Beta* (p, q), which is proportional to the right hand side of the Tsoularis-Wallace model, is studied. In particular, for p = 2, the investigation is extended to the extreme value models of Weibull and Frechet type. These models, described by differential equations, are proportional to the hyper-Gompertz growth model. It is proved that the Beta* (2, q) densities are a power of betas mixture, and that its dynamics are determined by a non-linear coupling of probabilities. The dynamical analysis is performed using techniques of symbolic dynamics and the system complexity is measured using topological entropy. Generally, the natural history of a malignant tumour is reflected through bifurcation diagrams, in which are identified regions of regression, stability, bifurcation, chaos and terminus.