Christina Qi on LinkedIn: “Risk is randomness that you can parameterize. Uncertainty is randomness… | 11 comments (2024)

Christina Qi

CEO of Databento, Board of MIT - Modernizing the market data industry.

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“Risk is randomness that you can parameterize. Uncertainty is randomness that you cannot. The best opportunities come from taking on uncertainty, not risk.” - Andrew Lo In any data-heavy industry, you'll hear the terms "risk" and "uncertainty." A classic example of uncertainty in finance is the occurrence of unexpected events or market shocks. COVID-19, wars, sudden regulatory changes, and other events can have a profound impact on financial markets and investment returns. Unlike risk, where probabilities can be assigned based on historical data, uncertainty makes it challenging to quantify the potential outcomes or the likelihood of their occurrence. Usually, if you make an earlier-stage investment, you face less data and more uncertainty. I'd argue that, in general: VC > PE > IB > HF in terms of uncertainty. That's why VCs, when they do score a win, typically win big. Some hedge funds face increased uncertainty too (e.g. emerging market funds), where limited historical data and unpredictable factors make decision-making more challenging.To navigate uncertainty, investors may employ strategies such as diversification, hedging, or incorporating scenario analysis into their decision-making process. These approaches allow for flexibility and adaptation in the face of unknown future outcomes. If you're considering a career as an investor, it's important to think about how much risk vs. uncertainty you're willing to take on.

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Andreas von Hirschhausen, CFA, CAIA

Passionate about Financial Education, Planning, and Technology

11mo

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reminds me of a story Toby Main told me on The Wall Street Lab: what is riskier: jumping of the 3rd or 30th floor of a building?

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Andy Freeman

I do product, technology, business, and help startups figure out and tell their story. What do you need?

11mo

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Not only is it important for an investor to understand how much uncertainty s\he is willing to take on, it is important for folks seeking investment to understand what "lane" a potential investor is in.Two extremes are Venture Capital and Main Street banking. The latter charges 2-10% while the former is looking for 10-100x However, the former insists on "sure things" while the latter's business model can make money with 70% failures.It's sort of obvious why MS doesn't do venture investing, but it is just as true that VCs aren't interested in properly priced "sure things".

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Elliot Haugen

Technical Solutions Engineer at Epic | Mathematics at Mount Holyoke College

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Have you read any of Douglas Hubbard's work? He argues that there is more historical precedent at least within the actuarial science/decision theory/math worlds to speak of measurable uncertainty. He believes its less confusing to refer to the "unknown unknowns" as areas of ignorance. For example, if I'm about to flip a coin, and I ask you if you are uncertain that I will land on tails, you would say yes. However we can clearly measure this uncertainty (50%). So by your definition, we can't call it uncertainty, and that doesn't really make sense to anyone outside of certain schools of economics and finance. I totally agree with the underlying message of your post, just wanted to share a different way of looking at these terms.

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Andy Freeman

I do product, technology, business, and help startups figure out and tell their story. What do you need?

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Risk can be (somewhat) accurately "priced in". Uncertainty can't.

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Shruti Mandaokar

MSCS @Purdue | Project Manager @Laboratory of Data Science | SDE@Vodafone | ML@SCAAI

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Very interesting 💯.

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Julie C.

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Nice one .

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Duane Cousin

11mo

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This risk vs uncertainty post hits home Christina. Very nice breakdown.

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Matthew DeBow

Helping Customers Navigate the World of Copilots - AI - Cloud

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I love that quote!

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    What are some common misconceptions in your industry? Below are some irrelevant sentences that we hear often: 1. "I'm excited to apply my data science skills to Databento." - job candidate 2. "Market data is too small. I'll only invest if you gather the world's data, like satellite data, social media, and healthcare data." - investor 3. "Databento could use our AI services to enhance your offering." - startup 1 doesn't bother us, as it's exhausting applying to job after job, so candidates deserve leniency for not grasping what every company does. 2 indicates a lack of knowledge about market data vs. alternative data, the different audiences they appeal to, and the extreme differences in product, costs, and regulations between the two. 3 just no. The only AI startup I support is the one that eliminates all of the AI spam in my inbox every morning.

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    Sharing my thoughts on data startups since we're quoted in this front-page article today. - It sucks that startups are pitted as rivals when we try our best NOT to compete against each other. If we did, we would all die. Most users switch to Databento from a $10B incumbent. We rarely hear startup names during sales calls - it would suck (& be an omen for all) if we stole significant business away from any startup. - Believe it or not, Databento's enterprise customers don't switch over because of the price (despite having fair pricing: https://lnkd.in/gVMjvZvC). They switch over because our API and web experience are superior to the incumbent vendors. We consistently improve our uptime, latency, and technical support. - I cannot stress enough that targeting retail customers is a formula for failure, unless you get enough user data to sell it to HFT firms, as Robinhood does. That doesn't mean that we should shun retail folks, but rather that startups should think about how to scale from Day 1. Is the answer PLG? Scalable pricing? Better APIs? Better analytics? Cloud or on-prem delivery? - Whatever the innovation is, the answer should NEVER be "cheaper prices." "We're Bloomberg but cheaper," is a formula for failure UNLESS you offer a true technological innovation outside of price.

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  • Christina Qi

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    Random: Someone asked what celebrities I enjoyed meeting, so here's goes nothing. Some are awful, racist crazies, while others are normal and kind. Normal and kind: - Kim Kardashian: Met in Boston. Modest, understanding, low maintenance. (Who would've thought! Ye on the other hand...) - Natalie Portman: Met in Cayman at CAIS. So easy to talk to, was kind enough to say hi to my mom who is a huge Star Wars fan, was introverted on stage, was looking at the floor almost in embarrassment, 100% relatable and real. - David Blaine: Crazy but in a good way. Also met in Cayman at CAIS. Invited me on stage to sew his mouth shut Nightmare Before Christmas style if you know what I mean. There's no "trick" - it was him mutilating himself the entire evening. I almost threw up seeing the blood and guts on the string as he pulled the needle back and forth through his lips. He stayed afterwards and mingled with everyone, even though he could've flown away. He had punctured his hand with an ice pick for a "trick" so it swelled up like a balloon and an EMT had to take a look. I snuck a photo of him getting stopped by Cayman's TSA at the airport. Inspecting his magic up his sleeves? 🤣 One of my core life memories thanks to Anthony Cowell! It's inspiring and refreshing to meet someone down to earth who has every reason not to be. :)

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