Thursday, 11 May 2017

What advice would you give to a beginner quantitative trader?



Timothy Gouskov
Timothy Gouskov, I write trade orders on paper, then throw them at an exchange really fast
Here are a few things I learnt when I was starting out.
  • Understand that price can only behave in these two ways: Mean Reversion and Trending.
  • You don’t need to know exactly what your strategy is at the start. One of the best things you have in the beginning is an open and un-biased learning about all the types of trading.
  • Don’t be afraid of mathematics. This is a huge one I realised. Go and jump right into reading research papers and textbooks that are both directly to do with trading (statistics, algorithms etc), and also ones that aren’t (game theory, agent-based modelling, machine learning etc). Even if your mathematics is not that strong, you will still capture so many interesting ideas.
  • Understand the difference/relation between simplicity and complexity. Your strategy/algorithm should follow this type of process: Simple question at the start (should I buy/sell now)…then onto complexity used in your model (to determine an answer)…then back onto a simple answer (buy now). Simplicity should always surround the complexity.
  • Understand that a lot of people talk about a lot things. It doesn’t mean they’re correct. Trading is such a unique field and profession. You can succeed and fail through so many paths.
  • Be cautious about “successful” traders, who give advice/resources at a price. Think about why they would rationally/pragmatically/morally and you’ll probably find some contradiction in the reasoning.
  • Understand that the market is these two things at the same time: A social interaction between beliefs about a fundamental value, and, a complex system.
  • Learn risk management in your portfolio.
  • You will take losses. Think of them as an expensive lesson you just paid tuition for.
  • In the beginning, backtesting is useless for you. It will only be useful, when you start to properly study about data sets. You’ll then appreciate why people have professions specialised in data.

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