Genetic algorithms and investment strategies: A global perspective

The profitability of momentum portfolios in the equity markets is derived from the continuation of stock returns over medium time horizons. The empirical evidence of momentum, however, is significantly different across markets around the world. The purpose of this dissertation is to: (1) help global investors determine the optimal selection and holding periods for momentum portfolios, (2) evaluate the profitability of the optimized momentum portfolios in different time periods and market states, (3) assess the investment strategy profits after considering transaction costs, and (4) interpret momentum returns within the framework of prior studies on investors’ behavior. Improving on the traditional practice of selecting arbitrary selection and holding periods, a genetic algorithm (GA) is employed. The GA performs a thorough and structured search to capture the return continuations and reversals patterns of momentum portfolios. Three portfolio formation methods are used: price momentum, earnings momentum, and earnings and price momentum and a non-linear optimization procedure (GA). The focus is on common equity of the U.S. and a select number of countries, including Australia, France, Germany, Japan, the Netherlands, Sweden, Switzerland and the United Kingdom. The findings suggest that the evolutionary algorithm increases the annualized profits of the U.S. momentum portfolios. However, the difference in mean returns is statistically significant only in certain cases. In addition, after considering transaction costs, both price and earnings and price momentum portfolios do not appear to generate abnormal returns. Positive risk-adjusted returns net of trading costs are documented solely during “up” markets for a portfolio long in prior winners only. The results on the international momentum effects indicate that the GA improves the momentum returns by 2 to 5% on an annual basis. In addition, the relation between momentum returns and exchange rate appreciation/depreciation is examined. The currency appreciation does not appear to influence significantly momentum profits. Further, the influence of the market state on momentum returns is not uniform across the countries considered. The implications of the above findings are discussed with a focus on the practical aspects of momentum investing, both in the U.S. and globally.

Genetic Algorithms and Investment Strategies: A Global Perspective

The profitability of momentum portfolios in the equity markets is derived from the continuation of stock returns over medium time horizons. The empirical evidence of momentum, however, is significantly different across markets around the world. The purpose of this dissertation is to: 1) help global investors determine the optimal selection and holding periods for momentum portfolios, 2) evaluate the profitability of the optimized momentum portfolios in different time periods and market states, 3) assess the investment strategy profits after considering transaction costs, and 4) interpret momentum returns within the framework of prior studies on investors’ behavior. Improving on the traditional practice of selecting arbitrary selection and holding periods, a genetic algorithm (GA) is employed. The GA performs a thorough and structured search to capture the return continuations and reversals patterns of momentum portfolios. Three portfolio formation methods are used: price momentum, earnings momentum, and earnings and price momentum and a non-linear optimization procedure (GA). The focus is on common equity of the U.S. and a select number of countries, including Australia, France, Germany, Japan, the Netherlands, Sweden, Switzerland and the United Kingdom. The findings suggest that the evolutionary algorithm increases the annualized profits of the U.S. momentum portfolios. However, the difference in mean returns is statistically significant only in certain cases. In addition, after considering transaction costs, both price and earnings and price momentum portfolios do not appear to generate abnormal returns. Positive risk-adjusted returns net of trading costs are documented solely during “up” markets for a portfolio long in prior winners only. The results on the international momentum effects indicate that the GA improves the momentum returns by 2 to 5% on an annual basis. In addition, the relation between momentum returns and exchange rate appreciation/depreciation is examined. The currency appreciation does not appear to influence significantly momentum profits. Further, the influence of the market state on momentum returns is not uniform across the countries considered. The implications of the above findings are discussed with a focus on the practical aspects of momentum investing, both in the U.S. and globally.

Flexible strategies for association analysis with genomic phenotypes

Thesis (Ph.D.)--University of Washington, 2016-08

Consumer perceived risk, risk reduction strategies and transaction intentions in online marketplaces

Even though online commerce has garnered vast academic interest during the recent years, theoretical grounds for consumer behavior online still remains ambiguous. Despite the globally rapid growth of online commerce, only a fraction of Internet browsers end up purchasing goods online. This is argued to be caused by the intangible and distant nature of the Internet, causing overwhelming perceived risks for consumers and negatively affecting transaction intentions. To combat perceived risks, consumers may actively or passively seek to relieve those risks to tolerable level. These risk reduction strategies refer to both institutional mechanisms as well as consumer risk reduction strategies. The objective of this thesis is to provide further understanding upon the relationships between consumer perceived risk, risk reduction strategies and transaction intentions in online marketplaces. To serve the objectives of the present thesis, a quantitative approach was chosen as the method for conducting empirical research. The data was collected with an online survey through discussion board, using a random sample approach. The proposed research model was examined with a set of hierarchical regression analyses. Results revealed several direct relationships as well as moderating interaction effects. The key finding of this thesis is that institutional risk reduction mechanisms significantly contribute to consumer perceived risks. These mechanisms have the potential to reduce perceived risks, and therefore may stimulate transaction intentions. Additionally, it was observed that risk reduction strategies moderate the relationship between intermediary provided risk relievers, consumer perceived risks and transaction intentions. Retailer related risk reduction strategies were also shown to enforce the effectiveness of payment methods; however feedback and monitoring mechanism was shown to have a diminishing effect of perceived risk only when consumers did not rely on product related risk reduction strategies. The present thesis also illustrates the importance of effective information search, as those consumers are more willing to transact as the perceived risks become less significant. For managerial purposes, the importance of well-functioning institutional mechanisms cannot be emphasized enough.

Partnering Strategies for Fitness Evaluation in a Pyramidal Evolutionary Algorithm

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes for (sub-)fitness evaluation purposes are examined for two multiple-choice optimisation problems. It is shown that random partnering strategies perform best by providing better sampling and more diversity.

A Pyramidal Evolutionary Algorithm with Different Inter-Agent Partnering Strategies for Scheduling Problems

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

Partnering Strategies for Fitness Evaluation in a Pyramidal Evolutionary Algorithm

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes for (sub-)fitness evaluation purposes are examined for two multiple-choice optimisation problems. It is shown that random partnering strategies perform best by providing better sampling and more diversity.

A Pyramidal Evolutionary Algorithm with Different Inter-Agent Partnering Strategies for Scheduling Problems

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

Self-regulated learning in higher education : strategies adopted by computer programming students

Trabalho apresentado em PAEE/ALE’2016, 8th International Symposium on Project Approaches in Engineering Education (PAEE) and 14th Active Learning in Engineering Education Workshop (ALE)

The use of motivational interviews by nurses to promote health behaviors in adolescents: developing a search strategy for this review

Introduction: The developmental changes during adolescence may affect subsequent risk for diseases and health-related behaviors. Motivational Interview (MI) may be taken as an essential tool in the provision of nursing care to adolescents, being itself a workspace with possible therapeutic effects. At this context, it is important to examine and map the use of MI by nurses in their clinical practice with adolescents to promote health behaviors. Objectives: A scoping review has been undertaking to find out what is the current extent of the use of nurse-led MI; which adolescents were included; in which contexts nurses use MI; which MI techniques/strategies are used and what outcomes have been reported. The first task was to develop a search strategy to identify relevant studies for this review. It is described here the experience in constructing the search strategy review. Methodology: This scoping review will be informed by JBI methodology. An initial search of MEDLINE and CINAHL was undertaken. An analysis of the text words contained in the title and abstract, and of the index terms used to describe the searched articles were retrieved and these were then used to construct a search strategy for use in Medline and Cinahl. Results: Analysis of the text words and the index terms generated 19 keywords: It was identified 5 synonyms for "Adolescents", 12 for "MI" and 2 for "nurse". A new research formula was designed using the text words identified. Adolescen*[Title/Abstract]) OR Younger*[Title/Abstract]) OR Youth*[Title/Abstract]) OR Teen*[Title/Abstract]) OR Adolescent[MeSH Terms])) AND (((((((((((("Motivational interview"[Title/Abstract]) OR "Motivational intervention"[Title/Abstract]) OR "Motivational interviews"[Title/Abstract]) OR "Motivational interventions"[Title/Abstract]) OR "motivational interviewing"[Title/Abstract]) OR "motivational counseling"[Title/Abstract]) OR "motivational support"[Title/Abstract]) OR "Motivational enhancement"[Title/Abstract]) OR "Brief intervention"[Title/Abstract]) OR "Brief interventions"[Title/Abstract]) OR Motivational Interviewing[MeSH Terms]) OR Directive Counseling[MeSH Terms])) AND ((nurs*[Text Word]) OR Nurses[MeSH Terms]). Limiters - Language: English, Portuguese, Spanish. In MEDLINE this research formula generated 125 results. Other 16 databases referenced at the protocol will be searched to identify additional studies. Articles identified from the final search will be assessed for relevance to the review, based on information provided in the title and abstract. The full article will be retrieved for all studies that meet the inclusion criteria of the review. Conclusions: It was presented here the initial results of this search. Next steps of this study will be to develop and refine the search strategy for use in other databases. It is expected that findings from this Scoping Review provide needed information to nurses related to the use of MI to promote health behaviors in adolescents and inform opportunities for future development in nursing practice.