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Quant Trading 101

Session held at the London Big Data and Machine Learning Revolution event in April 2018.You can also access the full slides (video pending compliance approval).

Abstract

Nitish focuss on the similarities and differences between quantitative and discretionary investing with an emphasis on the importance of data. Watch as he hosts a demonstration of quantitative alpha using a web based simulator.

Three main questions are addressed:

  • What do Quants do and how have they grown overtime?
  • Space of Alpha in the quantitative world
  • What is the systematic approach to building a diversified quantitative portfolio?

  • access slides
    Quant Trading

    Quant vs. Discretionary Traders

    Discretionary Trading: is an approach that seeks to choose investments based on human decision-making & develops over time.

    Quantitative Trading: is a rule-based strategy that utilizes computer models to identify investments and to execute most of the trades.

    World of Quants

    Backtesting: By testing against historical data, Quants can set leverage based on the worst drawdown a given strategy has endured.

    Diversification: Quants identify, trade and monitor multiple strategies across many markets for a large number of instruments.

    Data: Quants can take advantage of the big data revolution

    Efficient: Because of the minimal human involvement required, burnout and execution mistakes can be reduced for Quants.

    World of Quant Trading

    Volumes Traded: Quants have nearly doubled their share of stock trades from 14% in 2013 to 27% in Q2 2017.

    Average Returns: In the past five years (as in Q2 2017), quant strategies gained about 5.1% a year, while the average hedge fund rose 4.3%.

    Capital Growth: Quant strategies account for more than 30% ($932 billion) of all hedge fund assets in Q2 2017, up from 25% ($408 billion) in 2009.

    World of Alphas

    An alpha is a mathematical, predictive model of the performance of financial instruments.

    Triple Axis Plan (TAP) of Diversification

    • Provides a systematic approach to exploring the gigantic world of alphas.
    • By freezing a target on one axis, gives Quants the flexibility to explore the other two axes.
    • Helps new Quants gather knowledge, develop relevant skills and provides alpha ideas.
    • Helps experienced Quants identify untouched sources of alphas, add diversity and increase efficiency.

    Alpha Diversification Plan: TAP of Diversification

    • Provides a systematic approach to exploring the gigantic world of alphas.
    • By freezing a target on one axis, gives quantitative trading the flexibility to explore the other two axes.
    • Helps new quantitative traders gather knowledge, develop relevant skills and provides alpha ideas.
    • Helps experienced quantitative traders identify untouched sources of alphas, add diversity and increase efficiency.

    Ideas and Datasets

    On the ideas axis, they can be very simple ideas, or there can be a lot of individual complex ideas to generate.

    There are a lot of datasets to generate alphas and there are alot of datasets available in the marketplace that can be used.

    Quant Trading

    Regions and Universe Axis

    One must identify where you want to focus on in order to build the alpha. This decision is based on the capitalization of the stock market in that particular country or region or it depends on the rules or regulations govern by that country.

    In terms of universes, a Quant may want to trade the stocks based on liquidity, a particular sector, industry or they might want to build their own groups depending on their objective statement.

    In terms of the last axis and the most interesting, is the performance parameters of this strategy. We can think that the sharp returns can be used to analyse the results and are used of analysing the results, but for me it's a big source of alpha ideas and a big source of identification.

    Quant Trading

    Linear Regression Alpha - A Demonstration

    First we put in a very basic expression using mathematical techniques which have already been coded into the platform, then we will identify the data and then we will execute our strategy.

    Quant Trading
    access slides
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