Hacker News Reader

Comment by nshinabarger | Hacker News Reader

I think you bring up an excellent point. With traffic, content certainly tends to deteriorate, or at least change. Like you've noted, most things are their best at the beginning. This being said, how do you try and stay on the cutting edge of the best sites in their early stages?

I'm honestly too young to have an experience with this myself, and don't expect finding out the best new sites to be easy or quick, but what tips from your experience can you offer?

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As someone who's spent most of their career in professional finance, my strong advice would be to avoid the proliferation of "contributor" sourced sites.

These sites typically allow anyone to write financial articles, trading recommendations etc. and get paid for page views. There is little to no verification of the content, let alone diligence on the credibility of the authors, and the quality of the discussion is extremely poor.

Unfortunately, given the volume of content they can produce through crowd sourcing, they are also extremely popular. Examples include Forbes, Seeking Alpha, The Motley Fool.

EDIT: Assuming your question was in relation to financial news.

Agreed. Also, in the name of "understand your market" - what did early HN readers get from reading HN that they wouldn't elsewhere and how does that translate to finance? Would HN be successful if some random dude had started it instead of PG? I admittedly wasn't around in the early days, but back then I would imagine that the expectation was "wow, generally people who post on here are legit" as a direct consequence of that association.

I'm not familiar with the author - is he/she someone baller enough in the finance world to draw quality discussion? Are people going to break away from WallStreetOasis and minesweeper for this? Is there useful industry-relevant information? (My impression from friends who've gone into finance is that technical skills matter for jack shit as long as you're competent, and relationships, positioning, and sounding like you know what you're talking about rule the day. Is that something you can vaguely convince yourself you're getting better at at while wasting office time on a finance hacker news clone?)

Unrelated, I've always thought it would be fun to hem up a corpus of SeekingAlpha articles, use some rudimentary NLP to look for clear short-term bullishness or bearishness on some specific security, and see if you can either (a)find anyone who's demonstrably worth reading and following (and maybe trading based on them), or (b) more likely point out that everyone is full if s, most of them are convinced of their own s, and in the end it's all clickbait with charts and important-sounding finance words.

The problem with this approach is that given a sufficient population of contributors, a random distribution is going to give you individuals that consistently out/under perform purely by chance. This can be seen in the professional asset management industry, where:

there is strong evidence that chasing managers with strong 3 and 5 year track records is actually harmful to your portfolio health [1]

[1] http://advisorperspectives.com/dshort/guest/BP-130108-Track-...

So you should short-sell managers with strong 3 and 5 year track records, then?

On the flip side, though, Seeking Alpha is extremely handy for stock alerts and earnings call transcripts.

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