Estimating the Spot Covariation of Asset Prices—Statistical Theory and Empirical Evidence

ABSTRACT

We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semimartingale log asset price process, which is subject to noise and nonsynchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance estimates. The latter originate from a local method of moments (LMM), which recently has been introduced by Bibinger et al.. We prove consistency and a point-wise stable central limit theorem for the proposed spot covariance estimator in a very general setup with stochastic volatility, leverage effects, and general noise distributions. Moreover, we extend the LMM estimator to be robust against autocorrelated noise and propose a method to adaptively infer the autocorrelations from the data. Based on simulations we provide empirical guidance on the effective implementation of the estimator and apply it to high-frequency data of a cross-section of Nasdaq blue chip stocks. Employing the estimator to estimate spot covariances, correlations, and volatilities in normal but also unusual periods yields novel insights into intraday covariance and correlation dynamics. We show that intraday (co-)variations (i) follow underlying periodicity patterns, (ii) reveal substantial intraday variability associated with (co-)variation risk, and (iii) can increase strongly and nearly instantaneously if new information arrives. Supplementary materials for this article are available online.     

Institutions and Policies for Pro‐poor Agricultural Growth

Global experience with pro‐poor growth and empirical work spanning India, Malawi and Zimbabwe demonstrates the importance of agricultural growth for poverty reduction in poor rural areas, while also pointing to the need for complementary non‐farm sector growth. Theoretical arguments, historical evidence and livelihoods modelling in poor medium‐potential rural economies suggest that, contrary to thinking dominating much of current development policy, subsidies to relieve critical seasonal credit and cash restraints and reduce market and input supply uncertainties need to help in ‘kick‐starting’ agricultural markets if increased smallholder productivity in food‐grains is to drive rural non‐farm growth. Establishing the base conditions for these to work, designing and implementing them to be effective, and then phasing them out are major challenges facing policymakers.     

Characteristics of Older Adults with Written Wills

Using data from the Study of Aging and Health Dynamics of the Oldest Old (AHEAD), an empirical model was tested to examine and explain the presence of a will among older adults. This study investigated the influence of the following multiple factors on the presence of a written will: demographic characteristics, socioeconomic status, physical health problems, negative psychological functioning, sense of control, and financial assessments. Two-thirds of the sample (N = 521) indicated they had a written will. Logistic regression analysis of the empirical model revealed there were four significant predictors of an older adult having a will: race, education, net worth, and the respondent's assessment regarding the chances of leaving a financial bequest.     

Open Data in Science

Open Data (OD) is an emerging term in the process of defining how scientific data may be published and re-used without price or permission barriers. Scientists generally see published data as belonging to the scientific community, but many publishers claim copyright over data and will not allow its re-use without permission. This is a major impediment to the progress of scholarship in the digital age. This article reviews the need for Open Data, shows examples of why Open Data are valuable, and summarizes some early initiatives in formalizing the right of access to and re-use of scientific data.