Early Stage Finance Institutional Investors Social Network 
Both Sides of the Table
JULY 23, 2014
Just 3 years ago there was talk of institutional investors “not being able to write small enough checks.” The “big boom” in startup financing started around March 2009? Public-company tech investors creates competition in late-stage financings and these investors can afford to be less price sensitive if they choose.
David Teten
SEPTEMBER 5, 2014
Professional expert networks allow you to efficiently convert your financial capital into relationship capital. Like many established finance & media companies, GLG knows that the tech startup sector is a growing part of the economy. Or, you can go straight to the source. Previously posted at Forbes.
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Both Sides of the Table
OCTOBER 1, 2009
There’s no doubt (at least anecdotally) that the pace of VC investments in early-stage technology companies has picked up in the past few months. I hear from several sources that Sequoia is very active in the market aggressively chasing several deals and even driving up prices on some early-stage deals.
Both Sides of the Table
MAY 23, 2012
The movie, “The Social Network” might have had more of an impact on creating future entrepreneurs than any other event of the past 5 years. Yes, it’s true that FOMO (fear of missing out) is driving some irrational behavior and valuations amongst uber competitive deals and well-financed VCs. Thank you, Aaron Sorkin!
David Teten
JANUARY 10, 2012
The first panel will focus on public markets and will discuss the use and effectiveness of social media tools and data mining technologies in harnessing the wisdom of crowds to generate investment ideas. Howard Lindzon is Co-Founder and CEO of StockTwits, a social network for traders and investors to share real-time ideas and information.
David Teten
DECEMBER 3, 2019
Excel and Google simply aren’t going to cut it if you expect to build a high quality institutional investor base.”. Boardex and Relationship Science make it easier to understand and map social networks into potential limited partners. This is a great example of why data businesses have substantial moats.
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