Algorithmic trading concepts
I believe free white papers are an invaluableresource when written by a niche expert, and this is one of thoseinstances where I think knowledge has to be shared when it isdiscovered. NetConcepts has written a wonderful (and free) white paper worthbringing attention to. As much as I use writing as a platform to freelyexpress my thoughts and ideas, often I find myself blogging as a way ofspeaking to individuals in my life (somewhat anonymously) such as acolleague, thinking this indirect form of communication is a moresubtle way of taking leadership initiative.
Perhaps I am trying to help my partners, employeesand colleagues discover their core skill sets’ application to searchengines. In other words, what are you very good at doing and how canthis be directly applied to implementing a successful marketingcampaign or building a successful business? Many companies still do notunderstand the concepts of “direct to consumer” (D2C) marketing. Manyare timid to even broach the subject for fear of looking prehistoric infront of their colleagues when most members of the executive floor arealso quite uninformed.
In the trading community, there are many proprietaryquantitative traders that became obsessed with cracking the long tailriddle and focused their energy on search engine algorithmic researchrather than building trading algorithms. Thisnatural transition for these talented programmers is an obvious choicebecause no matter how good of a programmer you are, you must still be agood trader and market analyst in order to monetize your programmingskills. With online marketing, one must be a good programmer andunderstand how search engine algorithms function.
Making the connections between an observation ofsearch behavior and functioning code that seeks to accomplish aspecific marketing objective is a much gentler mental exercise thandealing with the market’s never ending stream of non-linear data.And therein lies the edge that an individual schooled in algorithmictrading has in the world of internet marketing. Your work will beprimarily within the more rational world of linear data analysis so no chaos theory to drive you crazy.
As the cliche suggests in financial trading, “trendfollowing” is about finding and staying with a trend for a bulk of thatmove. The ‘chaos’ factor kicks in when there is some systemic marketshock that triggers behavior the models aren’t built to predict. As thealgorithmic trading article highlights, even Renaissance Capital, the famed quant shop, got short circuited by a 30 sigma event. Trend predicting in consumer behavior for search engine marketing purposes is not susceptible to central bank sovereign debt defaults!
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