A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Periodic strategies in optimal execution with multiplicative price impact

We study the optimal execution problem with multiplicative price impact in algorithmic trading, when an agent holds an initial position of shares of a financial asset. The interselling decision times are modeled by the arrival times of a Poisson process. The criterion to be optimized consists in maximizing the expected net present value of the gains of the agent, and it is proved that an optimal strategy has a barrier form, depending only on the number of shares left and the level of the asset price.     

When Do Qualitative Risk Disclosures Backfire? The Effects of a Mismatch in Hedge Disclosure Formats on Investors' Judgments

Disclosure standards mandate the quantitative disclosure of hedging‐instrument‐related risks but not the disclosure of hedged‐item‐related risks. We examine how a match (mismatch) in formats, caused by making quantitative (qualitative) hedged item disclosures alongside quantitative hedging instrument disclosures, affects investors' integration of information from these two related disclosures. Our first experiment varies the hedged item disclosure format (quantitative or qualitative) and the portion of risk hedged (small or large). We find that when disclosure formats are mismatched, the less comparable nature of the two disclosures caused investors to neglect the offsetting relationship when assessing net risks. As a result, risk and investment judgments were influenced by the more prominent quantitative hedging instrument disclosures. Our second experiment finds that the use of a qualitative debiaser that clarifies the relationship between the two disclosures led to the integration of information and mitigated this effect.     

Do pensions foster education? An empirical perspective

The paper examines the effect of population ageing on public education spending. On the one hand, ageing is expected to have a negative effect on education, as an increasing number of retirees results in ‘intergenerational conflict’ and, hence, the condemnation of education expenditure. On the other hand, ageing, in combination with pay-as-you-go pension systems, offers incentives for the working-age generation to invest in the public education of the young in order to ‘reap’ the benefits (that is, higher income tax/contributions) of their greater future productivity. Empirical evidence derived from the application of a fixed effects approach to panel data for OECD countries shows that the increasing share of elderly people has a non-linear effect on education spending. This indicates a certain degree of intergenerational conflict. Nevertheless, we find that future population ageing, which reinforces the mechanism linking public education and pensions, reflects positively on education expenditure. Furthermore, by disaggregating total education expenditure by educational levels, we observe that this effect is led by levels of non-compulsory education, probably as a reflection of the direct connection to labor productivity.     

Easing the assessment of emerging technologies in technology observatories. Findings about patterns of dissemination of emerging technologies on the internet

This paper considers the Web as a big data container that can be used by Technology Observatories and administrations to track emerging issues and more specifically emerging technologies. It considers information that is available on the Internet for free from different sources, and proposes a framework that can be useful to characterise them and to detect patterns of dissemination. This framework is made up of 30 metrics obtained from different kinds of sources (general web, patents, scholars?…). Some of them are obtained directly as the number of hits retrieved by queries on a search engine, and other ones calculated by means of ratios. This paper contains the development of a complete case that utilises this framework to characterise emerging technologies included in the well-known Hype Cycle for Emerging Technologies, in this case the 2015 release¹ and to analyze patterns of dissemination of these technologies on the Internet.     

The Impact of Employment on Parental Coresidence

We examine the extent to which parents use housing and shared living arrangements as a form of risk‐sharing for their adult children, using detailed data on children and parents in the Health and Retirement Study for 1998–2012. On average, a young man moving from full‐time to nonemployment raises the likelihood of coresiding with a parent by 1.5 percentage points; moving from full‐time employment to being part‐time employed raises the likelihood of coresiding with a parent by 2 percentage points. The implied elasticity of parental coresidence with respect to the son's income is ‐1.1; for daughters, the elasticity is ‐0.5.     

Further Mining the Predictability of Moving Averages: Evidence from the US Stock Market

Most studies on the predictability of moving average (MA) technical analysis use the discrete (buy/sell) trading recommendations. However, it is possibly incomplete or unreliable to explore the predictability of MA by only employing its generated trading signals. To further explore the forecastability of MA, we study its measurable impact on the stock market returns by using a conventional predictive regression framework. Our empirical study on the US stock market with respect to more detailed price information finds, (i) that the proposed predictor, MADP (MA based on daily prices) shows significant predictability in‐ and out‐of‐sample, and significantly outperforms the historical average (HA) benchmark as well as the MA based on monthly prices, (ii) that the predictability of MADP centers on the short‐term lags (within the most recent 10 days) and disappears when lags are beyond 20 days, and (iii) that the economic evaluation of the portfolios based on trading strategies confirms the superior performance of MADP with short‐term lags against the benchmark even though considering transaction costs.     

Balancing social and political strategies in emerging markets: Evidence from India

This article explores the substitution and complementary effects between political and social strategies on firm performance in the context of an emerging market (EM). Using in‐depth, historical case‐study approach, the article investigates how companies integrate political and social resources in this market. Corporate performance includes traditional measures, such as accounting performance and nonfinancial measures like the ease of doing business. The study finds that social strategies are stronger enablers of firm long‐term performance than political strategies. The latter have a short‐term impact on performance, but their success over time is limited. The main drawback of reliance on political resources in EMs is the lack of political stability, fragmented polity, and weak political coalitions. We identify rather limited evidence of firms using these two strategies as complements. Thus, we suggest that firms should employ both these strategies in the EM.     

Effects of aid for trade on extensive and intensive margins of greenfield FDI

Using a panel dataset of 105 developing countries for the period 2003–15, this paper assesses the effects of Aid for Trade (AfT) on greenfield FDI flows to the aid‐recipient countries. Particularly, this paper classifies the total dollar value of greenfield FDI flows to each recipient country in terms of four different layers: the extensive and intensive margins of projects as well as the extensive and intensive margins of source countries. Applying the system GMM estimator, this paper finds that AfT not only increases the dollar value of FDI flows to the recipient countries but also helps diversify the greenfield projects and source countries. In addition, this paper finds that AfT has a greater effect for greenfield FDI from donor (developed) countries than from non‐donor (developing) countries. Among the three components of AfT, aid for trade‐related infrastructure and aid for trade policy regulations are found to have positive links with greenfield FDI, irrespective of source‐country groups, yet their effects are larger for developed source countries. In contrast, aid for building productive capacity hinders greenfield FDI flows from non‐donor countries, while it promotes greenfield FDI from donor countries. We offer some explanations for this finding.