Evolutionary approaches for portfolio optimization

Portfolio optimization involves the optimal assignment of limited capital to different available financial assets to achieve a reasonable trade-off between profit and risk objectives. Markowitz’s mean variance (MV) model is widely regarded as the foundation of modern portfolio theory and provides a quantitative framework for portfolio optimization problems. In real market, investors commonly face real-world trading restrictions and it requires that the constructed portfolios have to meet trading constraints. When additional constraints are added to the basic MV model, the problem thus becomes more complex and the exact optimization approaches run into difficulties to deliver solutions within reasonable time for large problem size. By introducing the cardinality constraint alone already transformed the classic quadratic optimization model into a mixed-integer quadratic programming problem which is an NP-hard problem. Evolutionary algorithms, a class of metaheuristics, are one of the known alternatives for optimization problems that are too complex to be solved using deterministic techniques. This thesis focuses on single-period portfolio optimization problems with practical trading constraints and two different risk measures. Four hybrid evolutionary algorithms are presented to efficiently solve these problems with gradually more complex real world constraints. In the first part of the thesis, the mean variance portfolio model is investigated by taking into account real-world constraints. A hybrid evolutionary algorithm (PBILDE) for portfolio optimization with cardinality and quantity constraints is presented. The proposed PBILDE is able to achieve a strong synergetic effect through hybridization of PBIL and DE. A partially guided mutation and an elitist update strategy are proposed in order to promote the efficient convergence of PBILDE. Its effectiveness is evaluated and compared with other existing algorithms over a number of datasets. A multi-objective scatter search with archive (MOSSwA) algorithm for portfolio optimization with cardinality, quantity and pre-assignment constraints is then presented. New subset generations and solution combination methods are proposed to generate efficient and diverse portfolios. A learning-guided multi-objective evolutionary (MODEwAwL) algorithm for the portfolio optimization problems with cardinality, quantity, pre-assignment and round lot constraints is presented. A learning mechanism is introduced in order to extract important features from the set of elite solutions. Problem-specific selection heuristics are introduced in order to identify high-quality solutions with a reduced computational cost. An efficient and effective candidate generation scheme utilizing a learning mechanism, problem specific heuristics and effective direction-based search methods is proposed to guide the search towards the promising regions of the search space. In the second part of the thesis, an alternative risk measure, VaR, is considered. A non-parametric mean-VaR model with six practical trading constraints is investigated. A multi-objective evolutionary algorithm with guided learning (MODE-GL) is presented for the mean-VaR model. Two different variants of DE mutation schemes in the solution generation scheme are proposed in order to promote the exploration of the search towards the least crowded region of the solution space. Experimental results using historical daily financial market data from S &P 100 and S & P 500 indices are presented. When the cardinality constraints are considered, incorporating a learning mechanism significantly promotes the efficient convergence of the search

Evolutionary approaches for portfolio optimization

Portfolio optimization involves the optimal assignment of limited capital to different available financial assets to achieve a reasonable trade-off between profit and risk objectives. Markowitz’s mean variance (MV) model is widely regarded as the foundation of modern portfolio theory and provides a quantitative framework for portfolio optimization problems. In real market, investors commonly face real-world trading restrictions and it requires that the constructed portfolios have to meet trading constraints. When additional constraints are added to the basic MV model, the problem thus becomes more complex and the exact optimization approaches run into difficulties to deliver solutions within reasonable time for large problem size. By introducing the cardinality constraint alone already transformed the classic quadratic optimization model into a mixed-integer quadratic programming problem which is an NP-hard problem. Evolutionary algorithms, a class of metaheuristics, are one of the known alternatives for optimization problems that are too complex to be solved using deterministic techniques. This thesis focuses on single-period portfolio optimization problems with practical trading constraints and two different risk measures. Four hybrid evolutionary algorithms are presented to efficiently solve these problems with gradually more complex real world constraints. In the first part of the thesis, the mean variance portfolio model is investigated by taking into account real-world constraints. A hybrid evolutionary algorithm (PBILDE) for portfolio optimization with cardinality and quantity constraints is presented. The proposed PBILDE is able to achieve a strong synergetic effect through hybridization of PBIL and DE. A partially guided mutation and an elitist update strategy are proposed in order to promote the efficient convergence of PBILDE. Its effectiveness is evaluated and compared with other existing algorithms over a number of datasets. A multi-objective scatter search with archive (MOSSwA) algorithm for portfolio optimization with cardinality, quantity and pre-assignment constraints is then presented. New subset generations and solution combination methods are proposed to generate efficient and diverse portfolios. A learning-guided multi-objective evolutionary (MODEwAwL) algorithm for the portfolio optimization problems with cardinality, quantity, pre-assignment and round lot constraints is presented. A learning mechanism is introduced in order to extract important features from the set of elite solutions. Problem-specific selection heuristics are introduced in order to identify high-quality solutions with a reduced computational cost. An efficient and effective candidate generation scheme utilizing a learning mechanism, problem specific heuristics and effective direction-based search methods is proposed to guide the search towards the promising regions of the search space. In the second part of the thesis, an alternative risk measure, VaR, is considered. A non-parametric mean-VaR model with six practical trading constraints is investigated. A multi-objective evolutionary algorithm with guided learning (MODE-GL) is presented for the mean-VaR model. Two different variants of DE mutation schemes in the solution generation scheme are proposed in order to promote the exploration of the search towards the least crowded region of the solution space. Experimental results using historical daily financial market data from S &P 100 and S & P 500 indices are presented. When the cardinality constraints are considered, incorporating a learning mechanism significantly promotes the efficient convergence of the search

Evaluation on dry forage yields and nutritional characteristics of introduced herbaceous legumes in Myanmar

The study was carried out to evaluate the forage yields, nutritive values and in vitro fermentation parameters of herbaceous legumes. Five varieties of introduced herbaceous legumes; Stylosanthes guianensis cv. Ubon stylo, Macrotyloma axillare cv. Archer, Centrosema brasilianum cv. Ooloo, Stylosanthes guianensis cv. Stylo 184 and Macroptilum bracteatum cv. Cadarga were evaluated at the research farm, University of Veterinary Science, Yezin, Myanmar. No fertilizer and no irrigation were applied for cultivation to test drought resistance. Dry forage yield, nutritive values and gas production at four harvesting times were measured with 4×5 factorial arrangement (5 legumes and 4 harvesting time) in randomized complete block design. There was no interaction between legumes and harvesting time on forage yield, nutritive values and fermentation parameters but they were affected by the main effects of legume types and harvesting time. Among the legume forages, the highest dry forage yields were found in Ooloo, Ubon stylo, and Stylo 184, and followed by the DM yield of Archer and Cadarga. The DM yield of the second harvest was significantly higher (p<0.05) than those of the first, third and fourth harvest which were not significantly different from each other. As a chemical composition, the DM content of Archer was lower (p<0.05) than those of other varieties. Among the legumes forages, the lower CP content was found in Cadarga. The higher NDF was observed in Ooloo. Ooloo, Ubon stylo and Cadarga showed higher ADF in comparison with the other two varieties. Among the harvesting time, the lowest DM content was found at the first harvest. The highest CP content was found at third harvest. The NDF content was not significantly different. The lowest ADF content was found in fourth harvest. According to the dry forage yield, Ubon stylo and Ooloo had the highest dry forage yield and in term of nutritive values, Stylo 184 and Archer had higher nutritive values. As the main effect of forages, Stylo 184 and Archer had higher gas production in comparison with the other varieties. As the main effect of harvesting time, the fourth harvest had the highest gas production in comparison with other harvesting time. It could be better for cultivation by application of fertilizer and irrigation to get more forage yield and quality. &nbsp

Comparisons on the nutritive values of local and introduced forages and feed mixture for ruminant feed in central dry zone of Myanmar

This study aimed to compare nutritive values of local (Sorghum) and introduced (Mombasa) forages and their feed mixtures for ruminant feed in central dry zone of Myanmar. Sorghum based feed mixtures (FeedMix-1, 2 and 3) were the commonly used feed mixtures for cattle in dry zone of Myanmar and other feed mixtures (FeedMix-4, 5 and 6) were based on Mombasa. The lower CP and higher fibre contents (P<0.05) were observed in sorghum and its feed mixtures. The highest gas volumes (P<0.05) were observed in the FeedMix-4 and 6, and then the lowest gas volume (P<0.05) was observed in FeedMix-3. The gas production from quickly soluble fraction (a) of sorghum was significantly higher (P<0.05) than that of Mombasa, inversely the gas production from insoluble fraction (b) of sorghum was significantly lower (P<0.05) than that of Mombasa. Moreover, potential gas production (a+b), ME, OMD and SCFA of sorghum were also significantly lower (P<0.05) than those of Mombasa. The value of “a” was lowest (P<0.05) in FeedMix-1, whereas the highest value was found in FeedMix-6. The lowest values (P<0.05) of “b”, “a+b”, ME, OMD and SCFA were observed in FeedMix-3 and the highest values (P<0.05) of those parameters were found in FeedMix-4. Thus, the higher nutritive values observed in the introduced forage, Mombasa and its feed mixtures were indicating that Mombasa should be used instead of sorghum for the feed of cattle in dry zone of Myanmar.&nbsp

Risk Level Prediction for Heart Disease using Decision Tree Induction

Heart Disease was the major cause of causalitiesin most of the countries. According to the medicalrecords, heart disease kills one person in very sorttime. Classification and prediction are the forms ofdata analysis that can be used to extract models forimportant classes or to predict future data trends. Inthis paper, decision tree induction algorithm is usedto classify the risk level for heart disease. Decisiontree is a flow-chart-like tree structure, where eachinternal node denotes a test on an attributes, eachbranch represents an outcome of the test, and theleaf nodes represent classes or class distributions.This system generates the understandable rules foruser and estimates the accuracy for classifier.Depending on the attribute values of the data set,this system can classify the risk level of heartdisease whether it is in serious or normal conditionsfor patients. Thus, the user can test his or hermedical check concerned with their heart.Moreover, the system can provide the classifieraccuracy by using Holdout Method

Evaluation of Myanmar Rice Germplasms for Resistance to Bacterial Blight

Pathogenic diversity of Xanthomonas oryzae pv. oryzae from four major rice growing divisions of Myanmar was investigated. One hundred and thirty two isolates: 28 isolates from Ayeyarwady Division, 17 from Yangon Division, 42 from Bago Division and 45 from Mandalay Division, collected during 2004 and 2005 rice growing seasons were very diverse in virulence on 12 near-isogenic lines each of which carrying a specific resistance gene, Xa 1, Xa 2, Xa 3, Xa 4, xa 5, Xa 7, xa 8, Xa 10, Xa 11, xa 13, Xa 14, or Xa 21. The isolates were classified into 19 races based on their virulence. Among 19 races, Race 17 which consisted of 21.97% of the test isolates, was not only the most predominant race but also prevalent in 4 major rice growing divisions of Myanmar. It was also virulent on most of the differentials except IRBB 13 and IRBB 21. Race 7 and Race 11 fell into the second and third position in terms of predominance, respectively. However, Race 11 was found in four major rice growing divisions except Yangon Division, and Race 7 was detected in Bago and Mandalay Divisions only. Similarly, most of the other races found in one or two divisions were not detected in other divisions. The most predominant race in one division was also different from that of other divisions. Pathogenic diversity of four selected isolates collected from Hmawbi, Bogale, Paukkhaung and Kyaukse was confirmed by computer-assisted image analysis method in quantifying disease severity. The virulence of each of the four isolates on three near-isogenic lines, IRBB 3, IRBB 7 and IRBB 13 each carrying a specific resistance gene Xa 3, Xa 7, and xa 13, respectively, was qualitatively different from that of other isolates. One hundred and thirty-four Myanmar rice germplasms obtained from Seed Bank, Department of Agricultural Research, Yezin, were evaluated for their resistance to the representative isolates of four races. The test rice germplasms were divided into four groups, Group A, B, C and D, based on their reaction to four isolates. Two rice germplasms namely Mya Wut Yi and Talay were belonged to Group D and resistant to three representative isolates of the three most predominant races detected in four major rice growing divisions of Myanmar

Proactive Software Rejuvenation Solution with Enhanced VM Migration Decision in IT Infrastructure

The availability of IT infrastructures is stilla huge challenge nowadays. As servervirtualization is used as an essential softwareinfrastructure of various software services in ITenvironment and it is emerging as a technique toincrease system reliability and availability. Toprevent system failures caused by softwareaging, software rejuvenation can be applied invirtualized environment. Software aging ofvirtual machine monitors (VMMs) is becomingcritical because performance degradation orcrash failure of a VMM affects all virtualmachines (VMs) on it. Live VM migrationenables a running VM on a host server to moveonto the other host server with very smallinterruption of the execution. VM migrationdepends on a variety of criteria and efficientdecision support is required. The work presentedin this paper aims to offer the high availabilityagainst software aging of virtualized serversystem by providing VM migration based VMMsoftware rejuvenation solution. First, we presentthe resource usage as accepting as manyservices as in virtualized environment whichsupport of VM migration. Second, we presentmigration based VMM rejuvenation analyticmodel and evaluate the steady-state systemavailability based on familiar Markoviananalysis through the use of numerical analysis

A Study on Some Myanmar Ornamental Fish Species in Inlay Lake

The taxonomical studies of ornamental fishes of Inlay Lake were carried out. This study has recorded the occurrence of 12 species of ornamental fishes belonging to three orders and six families representing ten genera. Five species were recorded as endemic to Inlay Lake and its environments. About four of exported species were described in detail. The status of the studied species in the lake were discussed

Occurrence of Root and Stem Rot of Durian in Mon State and its Control by Trunk Injection with Phosphorous Acid

Durian (Durio Zibethinus Murr) orchards in Thahton, Pauung, Mudon and Thanphyuzayat Townships. Mon State, were visited during 2000-2001. Root and stem rot disease caused by Phytophthora palmivora was found to be serious and widespread in those durian growing areas. Disease incidence ranged from 16% to 100%. The investigation was undertaken at Kangalay orchard (Mudon Township) and Kyonka orchard (Paung Township), Myanma Agriculture Service, to evaluate the effect of trunk injection of Phosphorous acid and some chemical application in controlling of root and stem rot of durian. Effective control of the disease on 4-year-old durian trees was achieved by injecting 20% Phosphorous acid twice a year. Phosphorous acid injection in combination with Ridomil 25 WP bark paint and Ridomil 5G soil treatment was also found to be effective