Machines are Catalysts, but can Machines Predict Catalysts?

The answer is …not yet!

I love and hate machines.

It’s probably why I love and hate Venture Capitalists.

We need machines and venture capitalists as both are catalysts for growth.

No doubt some venture capitalist and firms have insane track records. I follow them as closely as possible. The miracle of the social web. Unlike the machines that the great angels and venture capitalist’s use, the great investors are in it for more than nickels, dimes and points.

Everything about machines until a few years back was about shaving pennies.

Wall Street has been fascinated with high frequency trading and the machines that make it possible. The financial industry has probably been the least respectful of the machines and benefitted the most. The banks used money, influence and machines to get their noses up as close to the pipe as possible. Now the pipe is all the way in their greasy pie holes and back out their asses. Times infinity. Good for them. They have forced the smart ones to think out further. While the machines fought for fractions of a penny every second trading Netflix, it rallied 400 points. The machines should have been hoarding…be grateful they were not.

Bitcoin may just be the poster child for the new age of machines, markets, finance AND hoarding. Time will tell.

The markets will change again soon because the machines are getting smarter and people…are just people. If you don’t believe me and or want to bet against me, you can probably short some $GOOG. Either way…take the time and read this fascinating article on Ray Kurzweil.

Thanks Niv for watching my long videos and culling some insights that got me thinking about this topic a little more.


  1. MarketShot says:

    That’s a great point on NFLX. I was just asked the other day about what indicators I follow as in Bollinger bands etc etc, just replied with macro, company leadership, and some light technicals. At the end of the day the machines try to predict human behavior which works fine until the next crash, then the algos blow up (see random 1k drop whenever that was last, feels too soon).

    I agree that HFT’s can’t yet see into the distance the forest from the trees and are scraping pennies, but they seem to be gaining steam at least from what I’ve seen in the institutional space. Then again the equity business margins are shrinking industry wide so this is a way for firms to differentiate in the space and not get killed on razor thin margins.

    Ok maybe that was a bit of a diverted point, but yeah turn the machines off and just freaking buy Netflix and Tesla. All you need to do is hear either CEO once and see that they “get it”.

    Leave the quants at home ;)

  2. Vconomics says:

    Kind of makes you wonder if the boom/bust cycle is going to get shorter and shorter the more machines we add to equity/currency markets. It’s very possible that recessions become deeper while recoveries are shallow with very little to no growth. A little worrisome.

  3. Niv Dror says:

    I believe in market efficiency and high frequency trading takes that to the limit (or fraction of a penny). When the infrastructure is ready; it will be interesting to see machines grind BTC down to the 8th decimal place of a Bitcoin). 

    With that being said… There is more money to be made by thinking of what the future will look like in 10 years, seeing which companies today are best positioned to make that future a reality, and investing (or creating) those companies. Bonus points: enter the position without looking at the price.

    Example 1: no one under 25 pays for cable, “cutting the cord” is a thing, we are in a golden age of TV; maybe the current *cable* providers are not best positioned to lead an industry with no cables. Long $NFLX

    Example 2: if Tesla or Tesla-inspired technology will be in every new car on the road 10 years from now, will the stock be worth more than it trades for today? Can a machine calculate the probability of the Gigafactory solving an externality in lithium-ion batteries; where only Gigafactory scale can create the economies of scale to reduce the cost of a mass production car – which is the only price point low enough to warrant mass production demand – but only one company is in a position to be so unequivocally (non-fuel cells) bullish on the success of electric cars to make a Gigafactory sized investment. Long way of saying long $TSLA.

    Thanks for the shout out :-) 

  4. ivanhoff says:

    The machines are just disciplined humans. They look at what has worked in the past and assume that it will work in the future. Since what worked in the past is based on market inefficiencies, the machines have made the market even more inefficient and therefore increased the opportunities for other machines and smart humans.

    The main factor that has been a huge drag for the market is legislation. Sarbanes Oxley is basically one of the major catalysts behind the huge increase in liquidity for private markets.

Comments are closed.