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Learning how to make smart investments
Chris Carrion
edited Nov 28, 2017
Seeking Help Getting Started Portfolio Optimization Risk Management Stat Arb

I'm a fairly inexperienced trader, but I've just finished Ernest Chan's Quantitative Trading: How to Build Your Own Algorithmic Trading Business. Being that mean-reversion is one of the primary tools for use in statistical arbitrage, I'd like to build a basis from which i can conduct my own research using logic and financial news outlets. My question(s) is/are, what's a good way to implement a mean-reversion strategy, where beta is close to 0 (i believe beta is basically safety from market volatility? correct me if I'm wrong please) and maximizing alpha (risk-adjusted return based on an index, or the jensen alpha?). I've read posts and lectures on choosing across multiple sectors and weighing choices as to reduce beta, is this correct? Does this include going beyond just equities (picking some bonds, real estate, etc)?

I guess the biggest question is: would there be a video or guide on how to do all of this, or is this type of strategy a natural combination of learning these pieces separately and morphing them together?

2 responses
Dan Dunn
Nov 28, 2017

You've got a bunch of great questions in there, and they need to be untangled a bit.

Having a beta to SPY that is close to zero means that your algorithm doesn't track with the SPY - that's it. You still can have an algo with a lot of volatility, or very little volatility. Your algorithm could still be exposed to the market and suffer up and down swings - you're just swinging differently than the SPY. You want to manage volatility (up or down) and your market exposure (up or down) in addition.

Have you taken a look at the Long/Short Equity lecture (and video)? And the pre-reqs to it? They will be very good at grounding you in these concepts.

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Chris Carrion
Dec 3, 2017

So I've delved into the videos a bit more, and I'm starting to understand these concepts and how they come together (thank you). My next question is, how does the flow of creating an algorithm go? Do i start by finding my own factor to base a strategy on, or pick a test to then research specific factors for, and go from there? Is there a general workflow for creating an all-around profitable and hedged algo?

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian.

In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.