When do improved covariance matrix estimators enhance portfolio optimization? An empirical comparative study of nine estimators

The use of improved covariance matrix estimators as an alternative to the sample estimator is considered an important approach for enhancing portfolio optimization. Here we empirically compare the performance of nine improved covariance estimation procedures using daily returns of 90 highly capitalized US stocks for the period 1997–2007. We find that the usefulness of covariance matrix estimators strongly depends on the ratio between the estimation period T and the number of stocks N, on the presence or absence of short selling, and on the performance metric considered. When short selling is allowed, several estimation methods achieve a realized risk that is significantly smaller than that obtained with the sample covariance method. This is particularly true when T/N is close to one. Moreover, many estimators reduce the fraction of negative portfolio weights, while little improvement is achieved in the degree of diversification. On the contrary, when short selling is not allowed and T?>?N, the considered methods are unable to outperform the sample covariance in terms of realized risk, but can give much more diversified portfolios than that obtained with the sample covariance. When T?<?N, the use of the sample covariance matrix and of the pseudo-inverse gives portfolios with very poor performance.     

Does the recent success of some OECD countries in lowering their unemployment rates lie in the clever design of their labor market reforms?

In recent years some OECD countries were successful in loweringthe unemployment rate substantially while other countries werenot. In this paper we investigate to what extent successfulcountries implemented a comprehensive set of institutional reforms.We present a theoretical framework to investigate the relationshipbetween unemployment and labor market institutions (LMI) suchas labor taxes, unemployment benefits, employment protection,union bargaining power and (de)centralization of bargaining.In our empirical analysis of data over the period 1960–99of 17 OECD countries we show that particular combinations ofLMI are responsible for low unemployment rates.     

Precautionary savings of agents with heterogeneous risk aversion

This article focuses on the estimation of the importance of the precautionary motive in the wealth accumulation decision. We use the micro data set of the De Nederlandsche Bank (DNB) Household Survey (DHS) (CentERdata, Tilburg University), a Dutch household survey containing information on wealth, a subjective measure of income uncertainty and subjective qualitative measures of risk aversion. We find that only a small share of wealth is accumulated for the precautionary motive by the Dutch households. This share of wealth is constant across assets with different degrees of liquidity. The economic downturn of the period 2008 to 2010 seems to affect risk attitudes and precautionary saving. Our findings also suggest that the more risk-averse individuals are those who hold less savings.     

Regularity and Pareto improving on financial equilibria with price-dependent borrowing restrictions

We consider a pure exchange, general equilibrium model, with two periods and a finite number of states, commodities, numeraire assets, and households. Participation in the asset markets is restricted in a household specific manner, imposing upper bounds on the amounts of borrowing which can be obtained using assets. Those bounds are assumed to depend on asset and commodity prices. After establishing existence of equilibria, we show that, generically in the set of the economies, equilibria are finite and regular. Then, we restrict our attention to the significant set of economies in which some associated equilibria exhibit a sufficiently high number of strictly binding participation constraints. We prove that, generically in that set, those equilibria are Pareto improvable through a local change of the participation constraints.     

Highway to (Digital) Surveillance: When Are Clients Coerced to Share Their Data with Insurers?

Journal of Business Ethics - Clients may feel trapped into sharing their private digital data with insurance companies to get a desired insurance product or premium. However, private insurance must...     

How capital markets assess the credibility and accuracy of CSR reporting: Exploring the effects of assurance quality and CSR restatement issuance

This research examines how the credibility and accuracy of corporate social responsibility (CSR) disclosures enhance market confidence by exploring their effect on the cost of capital. How do capital markets react to higher-quality assurance of CSR reporting? Can the hypothetical reduction in the cost of capital that assurance quality produces be explained by restatements of previous information given in these CSR reports? We explore the relationship between assurance quality, as a proxy for credibility and market confidence, and the mediating effect of CSR restatements as indicators of accuracy. We propose regression models with a sample of CSR reports issued by European companies. Building upon the signalling and legitimacy theories, the results support the positive effect of higher assurance quality statements on market confidence by confirming a decrease in the cost of capital; assurance quality gives an indication of credibility to the capital market and restatements related to methodological updates signal accuracy. The reduction in the cost of capital brought on by higher assurance quality appears to be determined by the issuance of CSR restatements, which create legitimacy for both client companies and assurance providers. CSR reporting and assurance have reached a greater level of maturity as demonstrated by the evolution of these practices and financial market perceptions.     

Machine learning,artificial neural networks and social research

Quality & Quantity - Machine learning (ML), and particularly algorithms based on artificial neural networks (ANNs), constitute a field of research lying at the intersection of different...     

Time,space and accounting at Nonantola Abbey (1350–1449)

Accounting historians have provided several accounts of monastic life and accounting's role in it, considering important settings such as Montecassino and San Pietro abbeys in Italy and Durham Cathedral Priory in England. Research has shown how their governance arrangements and common values enabled the Benedictines to manage their monasteries in an efficient manner which was essential in tackling the misappropriation of resources by organisational actors, including abbots. Other studies have shed light on the use of practical and effective accounting practices by the Benedictines to manage their considerable wealth and pursue their spiritual and temporal goals. Nevertheless, this body of literature is yet to explicitly consider the dimensions of time and space and their relationship with accounting practices. This study begins to address this oversight by analysing the surviving accounting records of the Benedictine abbey of Nonantola in northern Italy from 1350 to 1449. In the accounting books of Nonantola Abbey linear and cyclical conceptions of time coexisted and had an impact on the way in which transactions were reflected in the accounts. At the same time, the abbey was at the centre of a complex network of accountabilities which included lay accountants, farmers and the lessees of the abbey's properties. The main characteristic of this system was not the accuracy of the records in detailing the assets, liabilities, expenses and revenue of the abbey but the maintenance of a control system to administer an extensive agricultural network and the identification of the relationships between the abbey and the stakeholders inhabiting its space.     

Insurance fraud detection: A statistically validated network approach

Fraud is a social phenomenon, and fraudsters often collaborate with other fraudsters, taking on different roles. The challenge for insurance companies is to implement claim assessment and improve fraud detection accuracy. We developed an investigative system based on bipartite networks, highlighting the relationships between subjects and accidents or vehicles and accidents. We formalize filtering rules through probability models and test specific methods to assess the existence of communities in extensive networks and propose new alert metrics for suspicious structures. We apply the methodology to a real database—the Italian Antifraud Integrated Archive—and compare the results to out-of-sample fraud scams under investigation by the judicial authorities.