In 2012 I was on my noncompete (a paid vacation common in trading), and everyone expected me to go back into HFT after the year was up. When I started a tech company instead, people were surprised. The common response was, “Wait, your company’s not trading related at all?”
I traded in my East Village apartment, with its ambitious but empty yard where I never got around to having barbecues, for a Palo Alto Eichler, where we had many barbecues. My Ralph Lauren and Burberry dresses were replaced by Lululemon, so at any moment I could break into a jog or a 7 minute workout. My Stella McCartney vegan bags decayed at my dad’s house while I got my first car (electric) and started rock climbing. Instead of trading scandals on Squawk Box, I followed Elon Musk on Twitter.
High frequency trading is an exotic, shadowed land within the gated world of finance, and is the strangest place you can be, except for Silicon Valley. I was entering a complex tribe with unspoken castes and rites of passage – but I am from another secret tribe, with its own inscrutable numerology and hieroglyphics.
Silicon Valley surprised me:
1) Everyone is open.
Algorithmic trading works through intense secrecy. When an interviewer tries to evaluate you, they fully expect vague responses:
“How do your models work?”
“We capture edge using signals.”
“Do you add or remove liquidity?”
“It depends.”
After a few hours, they say, “Thanks for talking with us. We love what we learned about your approach,” and they mean it. You know that they know that you know the first rule of fight club. The best trading companies never let anyone know what they do, trade, or think – an algorithm sufficiently secret is indistinguishable from magic.
In contrast, everyone in the valley is amazingly open and helpful. People email me to ask for advice or intro’s, and we’ll talk about everything. Because two companies are rarely in direct competition, and the advantage your circle gains by sharing trumps whatever you could gain by hiding, Silicon Valley has developed an amazing culture of paying it forward. Everybody’s trying to conquer the same markets, and knows roughly what the space of ideas looks like, so sharing helps everyone. Around here, it’s execution over IP.
2) Valuation math is not intuitive.
When my friend asked me to invest, I asked, “What’s your company worth, like $100K?”
“No, it’s $6M.”
“Can’t I pay 3 developers $50K to make your product in a month?”
“That’s not how it works…”
I could build Snapchat in a week, but if I did, I would not have the user base of Snapchat. Same with WhatsApp – it’s worth an enormous multiple of what the app and architecture cost to build.
3) Money != success.
In trading, life was simple: PNL was all we talked about. Increasing this number was the goal. If we saw PNL underperforming, or the money eroding from a model that used to be our bread and butter, we knew we had to step it up to survive. In startups, the metrics for success are less clear, which makes it hazier to tell the difference between success and failure. One month, a startup has Hint in the refrigerator, dogs in the halls, and Friday hot tub parties. The next month, it’s selling all its Aeron chairs on Craigslist. Did the company suddenly tank? In HFT, yes- it would mean they were making money but then suddenly lost a ton of money in a few minutes due to a bug in its software. In SV, no- it probably means someone finally realized the company had died a year ago.
Lessons from algorithmic trading that have helped me in building Apptimize:
1) Today’s future is not yesterday’s future.
While I was in trading from May 2007 to Jan 2012, several events happened that had never happened before: the collapse of the housing market, the financial crisis, the Fed’s repeated rounds of QE, etc. How are you going to backtest that? You know you’re in a scary regime that’s never been seen, which means there’s incredible opportunity, and the models have to handle it. Stuff changes under your feet and you have to run like the red queen just to stay put. You stay up at night adapting the models, because otherwise they’ll lose money in the morning. Predicting the future correctly is the first step to success; the next is making the right bet on your predictions.
Startups are the same way. Technology changes so fast that you have to work every advantage to its limit to compete. Innovate as fast as possible, invent things others believe to be impossible, and think what others haven’t thought of yet, because you’ll be swallowed by the current the moment it catches up.
2) Accept reality.
In trading, if the market tells you you’re wrong, you listen. No matter how smart you are, you can’t argue your way to victory: the market will take your money. If you’re underperforming, sometimes it means your connections are slow, but usually it means your models suck and you need to make new ones. You can lie to yourself, but you can’t lie to the market. All you can do is accept reality, and update your models to match.
For startups, it’s human to invent excuses for everything. Even the most literal people suddenly get creative when confronted by unpleasant realities:
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“Our users need our product; they’re not just doing it because they’re our friends.”
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“We can’t show live demos, not because our demo is jury-rigged to work only on our special setup, but because we want to show a build of our SDK we haven’t released yet but will soon.”
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“We’re going to beat the competition despite { an inferior product; an unimpressive team; a lack of funding; having no user base } because { we’ll out-execute on something else; we’re differentiated; the market is huge }.
This is not accepting reality. In order to win, you have to be honest and ruthless in admitting every weakness, because you can only correct the flaws you know you have.
3) Make your own bets.
Never believe what people say without examining it, especially if it’s about the future. People are wrong all the time. The ones who are right are too busy succeeding to tell you what to do. By the time the world knows where the market’s going, the money’s gone.
Nobody knows exactly where the prize is, but if you have a good idea, you need to make big bets, and you need to obsess about the future – the future’s where everything happens. If you copy the people who have already done the legwork for you, you’ll always be eating their scraps. You can’t afford to follow. Ask questions. Bet your beliefs. Test your hypotheses. Rely on yourself.
There’s one thing that holds true across HFT and tech startups: it’s all about the talent. At Apptimize, our investors have often remarked we have one of the strongest teams they’ve ever seen. That lets me be confident no matter what: in trading or tech, NYC or SV, it’s about betting on the right people, and I’m all in on us.
Thanks to Lucas Baker for editing this and vetoing the boring post I was considering publishing instead.