Generating long-term trading system rules using a genetic algorithm based on analyzing historical data

2017 ◽  
Author(s):  
Dmitry Iskrich ◽  
Dmitry Grigoriev
Keyword(s):  
Genetic Algorithm ◽  
Historical Data ◽  
Trading System

scholarly journals A GENETIC APPROACH FOR LONG TERM VIRTUAL ORGANIZATION DISTRIBUTION

2011 ◽  
Vol 20 (02) ◽  
pp. 271-295 ◽  
Author(s):  
VÍCTOR SÁNCHEZ-ANGUIX ◽  
SOLEDAD VALERO ◽  
ANA GARCÍA-FORNES
Keyword(s):  
Genetic Algorithm ◽  
Virtual Organization ◽  
Genetic Material ◽  
Multi Agent System ◽  
Crossover Operator ◽  
Agent Based ◽  
Multi Agent ◽  
Global Goal ◽  
Computational Resources

An agent-based Virtual Organization is a complex entity where dynamic collections of agents agree to share resources in order to accomplish a global goal or offer a complex service. An important problem for the performance of the Virtual Organization is the distribution of the agents across the computational resources. The final distribution should provide a good load balancing for the organization. In this article, a genetic algorithm is applied to calculate a proper distribution across hosts in an agent-based Virtual Organization. Additionally, an abstract multi-agent system architecture which provides infrastructure for Virtual Organization distribution is introduced. The developed genetic solution employs an elitist crossover operator where one of the children inherits the most promising genetic material from the parents with higher probability. In order to validate the genetic proposal, the designed genetic algorithm has been successfully compared to several heuristics in different scenarios.

Disparate Entwicklung der Wohnungsmärkte fordert die Politik

2014 ◽  
Vol 63 (1) ◽  
Author(s):  
Oliver Arentz
Keyword(s):  
Housing Policy ◽  
Low Income ◽  
Conflicts Of Interest ◽  
Housing Allowance ◽  
Main Task ◽  
Trading System ◽  
The Public ◽  
Site Development ◽  
High Level

AbstractThe regional differences in the housing markets are enormous and will continue to exacerbate in the future. The main task for the housing policy is to take appropriate long term measures depending on the market structure. A central aspect of future housing policy is the site development. Potential conflicts of interest with other social objectives must be detected and resolved. Creating a trading system for development rights appears to be promising. In order to secure housing for low income households, the housing allowance (Wohngeld) must be promptly adjusted to the market conditions. The public housing sector should be seen as an instrument for the stabilization of neighborhoods. Appropriate market rents secure a housing supply at a high level.

scholarly journals Forecast of Waterway Cargo Turnover Volume Based on Genetic Algorithm to Optimize Neural Network Parameters

2021 ◽  
Vol 2083 (3) ◽  
pp. 032010
Author(s):  
Rong Ma
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Bp Neural Network ◽  
Forecast Model ◽  
Network Parameters ◽  
The Neural Network ◽  
Target Effect ◽  
The Empirical Analysis ◽  
Better Than

Abstract The traditional BP neural network is difficult to achieve the target effect in the prediction of waterway cargo turnover. In order to improve the accuracy of waterway cargo turnover forecast, a waterway cargo turnover forecast model was created based on genetic algorithm to optimize neural network parameters. The genetic algorithm overcomes the trap that the general iterative method easily falls into, that is, the “endless loop” phenomenon that occurs when the local minimum is small, and the calculation time is small, and the robustness is high. Using genetic algorithm optimized BP neural network to predict waterway cargo turnover, and the empirical analysis of the waterway cargo turnover forecast is carried out. The results obtained show that the neural network waterway optimized by genetic algorithm has a higher accuracy than the traditional BP neural network for predicting waterway cargo turnover, and the optimization model can long-term analysis of the characteristics of waterway cargo turnover changes shows that the prediction effect is far better than traditional neural networks.

scholarly journals Shell mineralogy of a foundational marine species, Mytilus californianus, over half a century in a changing ocean

2021 ◽  
Vol 118 (3) ◽  
pp. e2004769118
Author(s):  
Elizabeth M. Bullard ◽  
Ivan Torres ◽  
Tianqi Ren ◽  
Olivia A. Graeve ◽  
Kaustuv Roy
Keyword(s):  
Ocean Acidification ◽  
Historical Data ◽  
Mineralogical Composition ◽  
Marine Species ◽  
Mytilus Californianus ◽  
Negative Effects ◽  
Saturation State ◽  
Long Term Changes ◽  
Time Periods

Anthropogenic warming and ocean acidification are predicted to negatively affect marine calcifiers. While negative effects of these stressors on physiology and shell calcification have been documented in many species, their effects on shell mineralogical composition remains poorly known, especially over longer time periods. Here, we quantify changes in the shell mineralogy of a foundation species, Mytilus californianus, under 60 y of ocean warming and acidification. Using historical data as a baseline and a resampling of present-day populations, we document a substantial increase in shell calcite and decrease in aragonite. These results indicate that ocean pH and saturation state, not temperature or salinity, play a strong role in mediating the shell mineralogy of this species and reveal long-term changes in this trait under ocean acidification.

Periodical Waves in the Evolution of Art: Methods of Study

2010 ◽  
Vol 437 ◽  
pp. 530-534
Author(s):  
Alexander V. Kharuto
Keyword(s):  
Social Relations ◽  
Art History ◽  
Historical Data ◽  
Oscillation Period ◽  
Time Interval ◽  
Historical Time ◽  
Stylistic Evolution ◽  
Long Term Trend ◽  
Temporal Segment

Studies of periodical processes in the evolution of art became rather widespread. P. Sorokin described cycles of about several centuries; periods close to 50 years have been observed in social relations by S. Maslov; numerous cycles in the stylistic evolution of art became well known due to C. Martindale. One of important characteristics of art history is the ‘intensity of artistic creativity’, which can be measured as the total (summary) volume of encyclopedic descriptions devoted to artists of appropriate creative sphere during every temporal segment of 1..10 years. These rows of ‘experimental data’ form evolutionary curves on historical time interval of several centuries. Such curves contain two components: a long-term trend and an ‘oscillating part’, which have time constants of about decades of years. In the row of historical data, these oscillations may be represented with only 2..10 ‘waves’ including 2 to 10 sampling points pro oscillation period. The goal of investigation is, to measure parameters of such oscillating components.

Testing Technical Trading Rules: Evidence from SAARC Countries

2018 ◽  
Vol 1 ◽  
pp. 1-36
Author(s):  
Faisal Anees ◽  
Shujahat Haider Hashmi ◽  
Muhammad Asad
Keyword(s):  
Historical Data ◽  
Moving Average ◽  
Technical Analysis ◽  
Moving Averages ◽  
Short Term ◽  
Technical Trading Rules ◽  
Average Rule ◽  
Data Representative ◽  
Simple Average

Technical analysis is widely accepted tool in professional place which is frequently used for investment decisions. Technical analysis beliefs that there exist patterns and trends and by capturing trends and patterns one can bless with above average profits. We test two technical strategies: Moving averages and Trading Range to question, either these techniques can yield profitable returns with the help of historical data. Representative daily indices of Four countries namely Pakistan, India, Srilanka, Bangladesh ranging from 1997 to 2011 have been examined. In case of Moving Average Rule, both simple and exponential averages have been examined to test eleven different short term and long term rules with and without band condition. Our results delivered that buy signals generate consistent above average returns for the all sub periods and sell signals generate lower returns than the normal returns. Intriguing observation is that Exponential average generates higher returns than the Simple Average. The results of Trading Range Break strategy are parallel with Moving average Method. However, Trading Range Strategy found not to give higher average higher return when compared with Moving Averages Rules and degree of volatility in returns is higher when compared with moving Average rule. In attempt to conclude, there exist patterns and trends that yield above average and below average returns which justify the validity of technical analysis.

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