Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

The USSR property law: Possible forms of development

Conclusions Up to now, specific historical development is reflected in ideological views predominant in the USSR. Many people continue to place their hopes mainly in the activity of the bodies of state power and administration, not in private initiative. An interrelated implementation of political and economic reforms will contribute to the development of new theory and ideology. It will then be possible to combine a pragmatic and theoretical approach, and to accelerate the reform of the Soviet economy [theoretical, practical and historical aspects connected with the problem of property are considered in more detail by the author in his bookEconomics and the Law soon to be published by the Economics publishing house in Moscow].     

Globalization and Outward Foreign Direct Investment

While recent research into foreign direct investment (FDI) has focused on examining the importance of institutions, corruption, money laundering, and tax havens, the role of globalization on FDI has not yet been explored. This research investigates the impacts of globalization on outward FDI. We find that both overall globalization and its economic and social dimensions significantly positively influence outward FDI flows. We also demonstrate that beyond the level of globalization, corruption, money laundering, and the status of a country as a tax haven, cross-country similarity also plays an important role. Accordingly, policies specifically designed to increase the transparency of outward FDI flows should be required to address money laundering and the existence of tax havens.     

Creation of models for calculation of coefficients of terrain passability

Quality & Quantity - The content of this article is a paper about a complex mathematical model of terrain passability which respects geographical and meteorological conditions in terrain and...     

New development: Can ‘public’ market-based solutions restore the banking system? The case of non-performing loans (NPLs)

The authors discuss how policy-makers could use new market-based solutions to dismantle NPLs. They examine viable solutions for NPLs and then study the Italian State Guarantee Scheme for NPL Securitization (GACS) to highlight how public actors could efficiently use public resources to solve the NPL problem.     

Is there a profit premium for market-oriented firms? A panel data investigation

ABSTRACT

This paper provides an empirical investigation of the impact of market orientation on firms' economic performance during the period 1998–2012 using a panel of Italian manufacturing firms. We introduce a dynamic concept of market orientation, in that we define a market-oriented firm as one that persistently undertakes product and marketing innovation, while at the same time introducing organizational changes and training efforts to manage and improve its knowledge assets over the long term. This notion of market orientation is therefore crucially related to the so-called dynamic capability approach. The related empirical model shows that being a market-oriented firm significantly affects profitability, in a framework in which this latter is simultaneously estimated with productivity, thus allowing for more precise estimates of the profit premium which is earned accordingly.     

Who Convinces Whom? Parent and Child Perceptions of Children's Engagement in Parental Purchase Decisions

Do children overestimate their engagement in parental purchase decisions? A systematic analysis of the articles enabled us to create a database of 149 cases where child and parent perceptions of children's engagement in parental purchase decisions were measured. The findings proved that there is congruence between children's and parents' perception of a child's engagement in most cases. Children's overestimation of their engagement in a parental decision to purchase products is likely the exception rather than the rule. The cases characterized as overestimations are related to product category and type of measured domain. (Children tend to overestimate their engagement more when the measures track participation or influence rather than decision independence.)     

Sales forecasting in financial distribution: a comparison of quantitative forecasting methods

This paper deals with the issue of forecastability of sales activities of independent financial advisers (agents). Employing the most common quantitative methods on a diverse sample of timelines from multiple advisory companies, we have found that under most settings, these methods offer sub-par performance with high relative errors and no statistical differences between them. When a more granular approach is applied (reflecting sales unit size), ARIMA and the simple moving average emerge as significantly less accurate. This outcome is true for all sales units regardless of their size, when relative error is concerned. Thus, our analysis confirms the difficult forecastability of financial sales, speaking against the utilisation of more sophisticated forecasting methods, which mostly fail when compared to their much simpler and less costly counterparts.