{"title":"Algorithmic Decision-Making Framework","authors":"R. Kissell, R. Malamut","doi":"10.3905/jot.2006.609171","DOIUrl":"https://doi.org/10.3905/jot.2006.609171","url":null,"abstract":"The emergence of algorithmic trading as a viable and often preferred execution mechanism has created a need for new suites of trading analytics to assist investors compare, evaluate, and select appropriate algorithms. Unfortunately, many of the existing algorithms do not provide necessary transparency to make informed trading decisions. In this paper we provide a dynamic algorithmic decision making framework to assist investors determine the most appropriate algorithm given overall trading goals and investment objectives. The approach is based on a three step process where investors choose their price benchmark, select trading style (risk aversion), and specify adaptation tactic. The framework makes extensive use of the Almgren & Chriss (1999, 2000) efficient trading frontier.","PeriodicalId":322824,"journal":{"name":"Algorithmic Trading Methods","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134021735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Algorithmic Trading","authors":"R. Kissell","doi":"10.1002/9780470061602.eqf20007","DOIUrl":"https://doi.org/10.1002/9780470061602.eqf20007","url":null,"abstract":"Research, no doubt, plays an important role in formulating any policy. Algorithmic Trading and, in particular, High Frequency Trading and Colocation, are some of the most controversial issues affecting how global security transactions are conducted. Rapid execution, accuracy, reduced costs, and avoidance of human emotions are some of the reasons for the increase. At the same time, the development of these technologies raises many regulatory challenges, especially with regard to market exploitation and ensuring market equity and integrity. And since these high-frequency sales are in the low-income category in India, research is in the survival category This paper provides the first direct evidence of the impact of AT and HFT on the Indian Stock market. There is no strong evidence that AT is damaging the markets. Problems such as market fraud have been around for a long time. Technology has changed the way financial markets operate and the way financial assets are marketed. Two important parallel technological changes are investors using computers to make their trading processes and markets redesigned so almost all markets now have electronic ordering books on Twitter, Facebook and other social networking sites. In this paper, we have discussed the methods used to perform large quantities of trading analysis and our ability to obtain `data 'technically. Algorithmic algorithms and terrifying systems for data integration and predictability, analysis, versatility, complexity, and great size. Potential developments include new algorithms, methods, systems and applications in algorithmic trading that derive useful and hidden information from trading effectively.","PeriodicalId":322824,"journal":{"name":"Algorithmic Trading Methods","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116734095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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