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Learning how to make smart investments

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

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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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?