//Web 2.0 - Investment Capitalist

Archive for the 'Web 2.0' Category

Invitation to Join Proprietary Traders Wordlwide

Try Match.com – One Week Free With all of the clutter and insanity due to groups turning into recruiting grounds and advertising forums for esoteric and mindless products, I was compelled to launch my own LinkedIn Group which is being emphatically embraced by the systematic and discretionary proprietary trading universe, to my delight. I know [...]

Algorithmic Trading Concepts in Search Engine Optimization (SEO) and Marketing (SEM)

As the open source platform has shown us, by providing an open sharing of software code, we are in fact enhancing economic opportunities for the masses by taking away from the intellectual property value of the few

Advice for New Companies and Entrepreneurs

Free 10GB Photo Storage in the Cloud I was recently asked about the role of Angel Investors in this brave new world of capital markets post “D-Day”, which I refer to when talking about the collapse of 2008 in capital markets and the ongoing rewriting of the new rules. We can call it BD for [...]

Microsoft + Skype = Netscape Redux?

Magazineline.com Let’s look at Skype’s acquisition by Microsoft 10, 20, even 50 years from now. The first thing I noticed was the cancellation of: “Skype Me Now” Moreover, Skype remains downloadable for Android regardless of the acquisition and iPhone is still on the boards as well. No proprietary moves thus far but it’s the top [...]

Help Investment Capitalist Cover Costs

Try Match.com – One Week Free It’s not free running a free blog, much less something like a Proprietary Trading site based on Global Macro financial research. Every reader knows that they get something out of the site and for each reader it’s unique. Some like the geo-political twists, some purview based on Quantitative Global [...]

An Epic Battle for Individual Eyeballs Starring: Google, Yahoo, Apple, MSN and Facebook

Although behavioral targeting has thrived by allowing marketers to offer ads that are customized based on the web surfer’s age, gender, location and online activities, in the immediate future not only will those variables be considered, but also the items the user may have been shopping for recently. For example, imagine you have searched for a specific bottle of wine from a shopping web site in the past couple of weeks, and were now on your favorite news site reading an article about foreign affairs. At the end of your article, you might see an ad from a wine merchant suggesting you take a look at their inventory and pricing. To go one step further in our example, the merchant that is serving you the ad has agreed to pay the advertising network a generous fee if that user clicks through and ends up purchasing a product. So the advertising network will be incentivized to track every single web user going through their network in a way that continually allows them to “guide” users to products that meet their real time interests. The convenience factor lies in that last term, “real time interests”.