Category: Maths

artifical intelligence · Big data · Business Culture · decision making · Investment · Learning · Maths · Statistics

The unrules by Igor Tulchinsky, founder and CEO of WorldQuant

Keith GuthrieLeave a comment

Igor’s rules

  1. The UnRule: all theories and all methods have flaws. Nothing can be proved with absolute certainty is, but anything may be disproved, and nothing that can be articulated can be perfect.
  2. You only live once. Your time on earth is the only truly irreplaceable resource. If today was my last day, what would I be doing with it?
  3. Life is unpredictable. There are limits to planning; the key is to act. Foster opportunities, then take advantage of outcomes. If you have to decide and you can’t, flip a coin. If it’s the wrong action, you will feel it and reverse course. Actions have a compounding effect; it’s bad to deliberate for too long.
  4. Establish concrete quantifiable goals and always go from A to B. Concrete things are attainable. Abstract and nebulous wishes are not.
  5. Develop willpower and persist. The most important limit is how much ability and persistence you have. Age means little.
  6. Play to your strengths, don’t compromise. Weaknesses can only be improved marginally, but strength can be improved more.
  7. Obstacles are information. If you can’t get something to work there is a reason. Learn adjust and attack it again.
  8. Aim for the anxious edge, the point of mild anxiety
  9. Arrogance distorts reality. Arrogance makes you perceive the environment in the way that maximises your ego. Environment does not exist for you, so your perceptions turn into fiction. You make bad decisions by chasing illusions. This gets harder after success when hubris slips in.
  10. Make everyone benefit
  11. Opportunity is unlimited, ideas are infinite
  12. Blame no one else. Minimise regrets.
  13. There is a virtue in economy of expression. Efficiency implies clarity and economy of thought. Pretend you have a fixed number of words in your life. The sooner they are all said, the sooner you’ll die.
  14. Value diverse and competing methods. Because all theories are flawed, the best approach is to collect as many of them as possible and use them all, in as optimal a fashion as you can devise, simultaneously.
  15. Value multiple points of view.
  16. Make everyone benefit. Align your endeavours with everyone around you and you will create your own tail wind.

Quotes and other insights

  1. To be successful in this investment business you have to think about it all the time. Thomas Peterffy
  2. Keep losses small. Profits will take care of themselves. Izzy Englander
  1. Don’t get emotional about your trades. React instantly to bad news. If it’s scary run. Take aggressive risks but manage losses. Aggressive behaviour forces your environment to react to you, rather than the other way around. You’re in control; you have the wider array of options in a higher probability of success. You need an exit route if it doesn’t work out.
  2. In systems with a high degree of interactive complexity, multiple and unexpected interactions of failure are inevitable.
  3. A good business runs itself. And create this by choosing the right people. A lot of time should be invested in that activity. Optimal compensation schemes are vital.
  4. Minimise bureaucracy. Time is money; time is scarce. Bureaucracy wastes time and money. If you have the right people, right systems and the right compensation scheme you can scale without adding bureaucracy.
  5. What makes a good trader? Intelligence, focus, action orientation, and the ability to learn from errors; economy of words and thoughts, honesty, and a strong sense of self; the ability to take risks, compartmentalise, and handle setbacks without ego getting crushed.
  6. What makes a good researcher? Creativity, tenacity, attention to detail, intelligence, relentlessness, follow-through, and top-level programming skills.
  7. What makes a good manager? Empathy, intelligence, creativity, relentlessness, and follow through.
  8. In their view, quantity of alphas is far superior to quality. Quality cannot easily be defined. They seek to maximise exponentially the number of Alphas they pursue.
  9. If data increases exponentially, predictability should improve linearly.
  10. They key to testing ideas is to have good simulation software.
  11. As complexity increases so will the number and frequency of non linear events will also increase (ie many std dev events – rogue waves, schrodinger equation)
  12. Power laws very common in nature. In some systems the largest entity often brakes scale invariance, ie. it is even bigger than predicted eg. In network systems, dominant player much bigger.

WorldQuant online university in financial literacy worth checking out.

Investment · Learning · Psychology · Statistics

Super Forecasting

Keith GuthrieLeave a comment

[Farnam Street Podcast] Philip Tetlock on The Art and Science of Super Forecasting

http://podplayer.net/#/?id=24093071 via @PodcastAddict

Phil Tetlock forms teams of “super forecasters” who are amazing accurate at predicting the probabilites of real world events, in their case often used to predict the likelihoods of complex real world events for the intelligence community.

It has many insights useful to invesmtent management and I am sure other fields that depend on probabilities.

1. Start with the outsiders view. Establish baseline probabilities of how likely something is before you start refining with inside knowledge. Eg in predicting how likely someone specific is to get divorced start with the probabilities of anyone getting divorced.

2. Break the problem down into steps in a decision tree each with their own probability. You can then work on refining each node in the tree. That way you know what the key questions are that you are asking.

3. Focus on accurate statement of the prediction, many of us are managing career risk for fear of being wrong, creating fuzzy statements that could be right under a wide range of outcomes.

4. Being open minded is essential to being a good forecaster. We all like to think we are open minded – we really are usually not. We can be more open minded on things we are not ideological about but where we have ideologies its much more difficult to be open minded

5. A group of people with the same objective and a good debating style but where possible with very independent thought processes can operate far more effectively to get to the right probababilities.

6. There are lots of impediments to making accurate forecasts in organisations where the objective of accuracy may be to further your career, not rock the political boat or not be seen to make a mistake rather than getting to the right answer. Manging that culturally is a challenge that leadership have to undertake: ensuring that the goal is the accuracy, that open mindedness is real and that mistakes are welcomed to learn from.

7. One of the biggest risks is conflating mistakes with probabilistic outcomes. You thought the probabilty of an outcome was 75%, the alternative outcome actually happened. That does not mean your probability was wrong, it could just have been the 1 in 4 chance of the other outcome happening.

Learning · Maths · Psychology

How do we learn? How should we learn?

Keith GuthrieLeave a comment

The fun bit is there are many ways to learn. Books, podcasts, videos, lectures, demonstrations, and doing it yourself. I have learnt that the optimal approach to learning is different for different people. Personally I find my self quite visual and auditory, if I can visualise a problem or listen to an explanation I can often internalise it.

There are also many stages to learning. Head knowledge, heart knowledge, practice, failure until eventually it becomes internalised, muscle memory, and we can be “in the flow…”, operating with unconscious ease.  

There are some guiding principles that I believe are important to remember on our journey to learn:

  • Be open minded: “It is the mark of an educated mind to be able to entertain a thought without accepting it.” ― Aristotle, Metaphysics
  • Seek to truly understand: “Any fool can know. The point is to understand.” ― Albert Einstein
  • Seek simplicity on the other side of complexity: “The simple things are also the most extraordinary things, and only the wise can see them.” ― Paulo Coelho, The Alchemist. (In mathematics you often know you have the cracked a problem and arrived at the right answer when the formulas magically compress to an elegant, beautiful solution)
  • Hold your own beliefs lightly: “Don’t believe everything you think. Thoughts are just that – thoughts.” ― Allan Lokos, Thomas E Kids

Each of these make us more receptive to deep learning.

But most profoundly, are the principle paths to wisdom:

“By three methods we may learn wisdom: First, by reflection, which is noblest; Second, by imitation, which is easiest; and third by experience, which is the bitterest.” ― Confucius

I don’t have time in this life to make all the mistakes myself! So Confucious’s first two paths are to be preferred:

If

  • I can learn through true understanding – often my preferred route, can I come up with an axiomatic explanation or understanding from first principles rather that statistical inference,
  • or learn from other people’s mistakes (or by deconstructing their successes) – the reason that studying history in any field of endeavour is so important is because through that we may potentially understand the reasons for the mistakes and successes of those who came before us

then I can get on with making the mistakes that I need to make myself, Confucius’s bitterest path, to push my own learning further.

And from there flows a further insight, to push the boundaries beyond what others have learnt, we need to be making mistakes. We learn by making mistakes. And you only make mistakes when you go for it.

So don’t be afraid to do, to act. My danger, my demon, is I spend all of my time thinking and not enough of my time doing. So doing is something I have to constantly challenge myself to do more of!