Index fund optimization using a hybrid model: genetic algorithm and mixed-integer nonlinear programming

Abstract

Index funds consist of a subset of stocks, an index tracking portfolio, included in the market index. The index tracking portfolio aims to match the performance of the benchmark index. In this paper, we propose a hybrid model for solving the multiperiod index tracking problem, which includes rebalancing concerns, transaction costs, limits on the number of stocks, and diversification by sector, market capitalization, and stock weight. Our hybrid model combines the genetic algorithm (GA) to select stocks of the index tracking portfolio and mixed-integer nonlinear programming (MINLP) to estimate its weights. Finally, we apply our proposed hybrid model to the S&P500 to find an index tracking portfolio that includes those constraints. The results show that our hybrid model is able to create an index fund whose return rate is similar to the market index with significantly lower risk.     

Enhancing spatial ability and mechanical reasoning through a STEM course

There is a clear contemporary interest for developing science, technology, engineering, and mathematics (STEM) at schools. Besides, there exist a lot of research that justify the importance of spatial ability to obtain success in STEM subjects. Nevertheless, the spatial ability is relatively ignored in the general practice of teaching and learning in the K-12 setting. The goal of this paper is to analyse the evolution of spatial abilities of students that assist to a STEM course. Additionally, the evolution of their mechanical reasoning is also analysed. The STEM course was designed and implemented for the first time in a 6th grade class (primary school) and a 7th grade class (secondary school) throughout a whole academic year. First, the spatial ability and the mechanical reasoning of the students were assessed with the corresponding prepared pre-tests. Then, after finishing the STEM course, the students were tested with analogous post-tests. An exhaustive analysis of the obtained results is provided in the paper. It is shown that the spatial ability of the students was definitely improved. Furthermore, this improvement was statistically significant. Results also evidenced that the mechanical reasoning of the participants was also improved, although the improvement was not statistically significant. Moreover, this research showed that, in general, obtained results do not depend significantly on the gender of the participants. Finally, results manifested the statistically significant difference of spatial ability between 6th grade and 7th grade students. The difference between grade levels was not as significant in the mechanical reasoning case.     

Is advertising helpful for organic businesses? Differential effects of packaging claims

What claims should companies use to improve consumer perceptions of their certified organic products and help consumers differentiate them from conventional products? This study focuses on advertising – specifically, on packaging claims that differ in their degree of explicitness and message topic. A laboratory experiment shows that a single claim positively influences perceptions of organic products, though additional claims can cancel out this positive effect. Different claims have distinct impacts on consumer perceptions. This study, thereby, reveals an effect of thematic scope: messages related to the environment have greater scope than those related to health, and they influence both environmental and health perceptions strongly.     

Intensive Horticulture in Almería (Spain): A Counterpoint to Current European Rural Policy Strategies

Much of the recently published literature in Europe on rural development tends to focus on de‐agrarianization and multifunctionality in rural livelihoods as a way to generate employment and incomes. This paper analyses the case of Almería (Spain), an exception to this general rule. Almería, once one of the poorest Spanish provinces, has become the most affluent province in Andalusia and ranks now about average in Spain. This fast growth rate was achieved thanks to the development of intensive horticulture and its processes of change from the 1970s to the present day, due to the factors reviewed in the present study. This success story is a counterpoint to current European rural development strategies that consider the promotion of agriculture a mistake and advocate instead the economic diversification of farms.     

American option valuation using first-passage densities

This paper explores the advantages of pricing American options using the first-passage density of a Brownian motion to a curved barrier. First, we demonstrate that, under this approach, the exact computation of the optimal boundary becomes secondary. Consequently, a simple approximation to the optimal boundary suffices to obtain accurate prices. Moreover, the first-passage approach tends to give more accurate prices than the early-exercise-premium integral representation. We present two ways of implementing the approach. The first is based on an exact representation of the first-passage density. The second exploits the method of images, which gives us a family of barriers with first-passage densities given in closed form. Both methods are very easy to implement and give accurate prices. In particular, the images-based method is extremely accurate.     

ESTIMATION AND INFERENCE BY THE METHOD OF PROJECTION MINIMUM DISTANCE: AN APPLICATION TO THE NEW KEYNESIAN HYBRID PHILLIPS CURVE*

The stability of the solution path in a macroeconomic model implies that it admits a Wold representation. This Wold representation can be estimated semi‐parametrically by local projections and used to estimate the model's parameters by minimum distance techniques even when the stochastic process for the solution path is unknown or unconventional. We name this two‐step estimation procedure “projection minimum distance” and investigate its statistical properties for the broad class of models where the mapping between Wold coefficients and parameters is linear. This includes many situations with likelihood score functions nonlinear in the parameters that would otherwise require numerical optimization routines.     

Devaluating projects and the investment–uncertainty relationship

Sarkar (2000. On the investment–uncertainty relationship in a real options model. Journal of Economic Dynamics and Control, 24, 219–225) analyzes the investment–uncertainty relationship in a real-options model demonstrating that the widely accepted conclusion that uncertainty harms investment can be reversed. Wong (2006. The effect of uncertainty on investment timing in a real options model. Journal of Economic Dynamics and Control, forthcoming) confirms this point showing that more uncertainty can reduce the expected time to exercise the investment option. This paper deals with such an issue and attempts to integrate both Sarkar's and Wong's analysis.For risk-neutral investors, we show that uncertainty can favor investment only if projects devaluate over time. This conclusion does not hold in a CAPM framework, where we demonstrate that the relationship uncertainty/investment can be positive (a) even when the investment threshold increases with uncertainty and (b) in the case of projects negatively correlated with the market portfolio.