A New Paradigm<\/strong><\/p>\n

Optimization in trading related analytics has always been about finding the <\/em>best case scenario using a single goal criteria. That outdated concept is now shattered by Grid Optimizer.<\/p>\n

With Grid Optimizer, optimization is no longer about a narrow view of the possible scenarios. While conducting your research on potential trading models, you can seek for the best solutions that can handle all kinds of scenarios and environments, faster.<\/p>\n

Optimize Better with Rules beyond Indicator Parameters<\/strong><\/p>\n

Optimization of trading models is about finding the best choice going forward, not curve fitting around the minute changes in the indicator parameter space. Optimizing around just indicator parameters not only limit your thoughts, it also limit your ability to discover better, more stable models.<\/p>\n

Grid Optimizer conducts optimization by rules. Rules that span across all possible elements within a trading model,<\/p>\n

\n
• the potential market to be traded<\/li>\n
• the data series resolution<\/li>\n
• the bar construction style (superposition technology)<\/li>\n
• the timeframe<\/li>\n
• the sensitivity in terms of order fulfillment<\/li>\n
• indicator parameters<\/li>\n<\/ul>\n

  By allowing the model designers to explore and discover the behaviour of the models developed thru such extensive optimization scheme, new ideas and insights can be generated. In turn, better and more robust models can be derived from this knowledge.<\/p>\n

  Optimize Smarter using Smart Search and Post Optimization Filtering<\/strong><\/p>\n

  To get better real-time trading results from trading models, it is not enough to look at just higher winning percentage or any single criteria, not even the famous Sharpe Ratio can do the job, unless you are not given the option.<\/p>\n

  With Grid Optimizer, you can choose to save up all the results your trading models generated, and search for the one that fits your needs. Sometimes, the strongest performing models may not be the right ones for deployment due to many reasons. For example, the best performing models from optimization may not fit the proper risk reward ratio and\/or risk management criteria of your firm. But the same model with the right combination of settings, could very well be a star performer within a portfolio of trading models.<\/p>\n

  The optimization results are saved into a database. This gives the model designers the opportunities to better utilize their research results without wasting time to conduct optimization over cases that has been covered in previous runs. By working on combinations not covered in previous runs only, Grid Optimizer saves time and improves quality of research results for system designers.<\/p>\n

  Optimize Faster thru Grid Computing<\/strong><\/p>\n

  When extensive optmization is called for, what is better than utilizing all the computing power you have to tackle the task as quickly as possible.<\/p>\n

  Grid Optimizer is built from ground up to work with a network of NeoTicker nodes. More NeoTicker you have, the faster your optimization process will get. Results are accessible during the optimization process thus you can check on the intermediate results and analyze the information while the computation nodes are hard at work.<\/p>\n","protected":false},"excerpt":{"rendered":"

  A New Paradigm Optimization in trading related analytics has always been about finding the best case scenario using a single goal criteria. That outdated concept is now shattered by Grid Optimizer. With Grid Optimizer, optimization is no longer about a narrow view of the possible scenarios. While conducting your research on potential trading models, you […]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":9,"menu_order":12,"comment_status":"closed","ping_status":"closed","template":"","meta":{"ngg_post_thumbnail":0,"footnotes":""},"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.tickquest.com\/wp-json\/wp\/v2\/pages\/66"}],"collection":[{"href":"https:\/\/www.tickquest.com\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.tickquest.com\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.tickquest.com\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tickquest.com\/wp-json\/wp\/v2\/comments?post=66"}],"version-history":[{"count":22,"href":"https:\/\/www.tickquest.com\/wp-json\/wp\/v2\/pages\/66\/revisions"}],"predecessor-version":[{"id":2240,"href":"https:\/\/www.tickquest.com\/wp-json\/wp\/v2\/pages\/66\/revisions\/2240"}],"up":[{"embeddable":true,"href":"https:\/\/www.tickquest.com\/wp-json\/wp\/v2\/pages\/9"}],"wp:attachment":[{"href":"https:\/\/www.tickquest.com\/wp-json\/wp\/v2\/media?parent=66"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}