So we look at successful trading approaches of the past.
And we find that the reason they tended to work was because one was being paid to:
1. do something useful
2. take on risk or unattractive work
3. do the job well.
Like any other business you might believe in.
11/n
We want trades where there's some obvious cause/effect.
We want "stonkingly obvious edges".
We'll look at Risk Premia Harvesting. Where we look to be rewarded for taking on risks others are keen to avoid.
12/n
We find that assets that are sensitive to certain risks tend to be less attractive.
Risks such as:
- rising interest rates
- rising inflation
- credit risk
- lower economic growth
- political risk
make assets like stock indexes less attractive than less risky assets.
13/n
Cos losing money ain't fun.
So when we hold risky assets, we're actually doing something useful.
It's a win-win situation.
You - as person prepared to take the risk - expect to get paid in excess returns.
And the risk-averse person is happy to avoid the risk.
14/n
Or "Stonks. They Go." Well, the index tends to. If you're patient enough.
And it tends to go up BECAUSE of their inherent risk.
So the job is to:
1. get exposed to the risks that pay
2. minimizing the ones that don't.
15/n
So we put together a simple 3 asset risk premia harvesting strategy, which dynamically manages the risks we're not paid for through:
- diversifying in 3 dissimilar assets
- dynamic sizing and rebalancing to target equal risk contribution.
16/n
And we discuss how not to screw up good edges by overcomplicating them.
So these games are less stable but probably worth going after as long as you have more high probability ideas covered first
But where do we find opportunities?
And how do we get the opportunity to trade them - given there are more sophisticated players competing with us?
20/n
We discover we need two things to be true.
First - you need to find a time when a large group is willing or forced to trade at inopportune prices. You'll need to understand the constraints and incentives of the big "end users" in the market.
21/n
Second, you need inefficiencies that aren't fully "gobbled up" by other players.
Inefficiencies can "leak out" because they are:
- too big or random
- too small, too noisy, too capital intensive or too awkward to harness.
22/n
This leads us to being able to identify inefficiencies YOU can exploit.
You'll learn how to make simple testable "elevator pitches" for these inefficiences.
These are simple statements of:
- why the inefficiency exists
- why you think YOU can exploit it.
23/n
A 5-year-old should buy your elevator pitch and understand why you might expect to get paid for doing that thing.
1. What would cause the inefficiency 2. Why it wouldn't be fully "gobbled up" by others who are quicker or better informed 3. How you might harness it, on average.
25/n
If doing this sounds intimidating, it's probably because it is. At least a little.
You probably aren't used to thinking like this. And don't trust your instincts yet.
But through a lot of discussions and examples, I'll make sure you get it.
Practically, you'll learn it is crucial to understand the effect you are harnessing.
You'll set up simple analytics to track the drivers of those effects. This helps you not to be dependent on noisy decaying P&L to know when to adapt or pull a strategy.
34/n
Emotionally, you'll explore random data and simulations to start to "feel the randomness in your bones".
You don't want to be "Fooled by Randomness" into making rash decisions.
35/n
By this point, you should have:
1. a good understanding of what inefficiencies you can exploit look like
2. a good process for finding them and exploiting them
3. realistic expectations of the experience of trading a systematic strategy.
36/n
Next, we'll look at time-varying variance risk premia harvesting strategy, based on the concepts in this thread on VIX and VIX futures:
Now, with a bunch of different systematic strategies, what do you do?
You'll learn a sensible, quantitative approach to putting them together, including:
- a system for thinking about portfolio construction, both practically and emotionally
39/n
- how to set portfolio management objectives
- how to set strategy-level volatility targets
- how to size strategies in a portfolio
- how to track and adjust strategy contributions
- what to do when things get weird
- how to chill out and "Trade More S**t"
40/n
This time around, I've also added a new module on Cryptocurrency trading.
We look at the market and discuss the process for weighing up the decision on whether to enter a new market.
At any point, there are many other things you could be spending your time on.
And it’s important to choose activities that are expected to have a good payoff.
You must be especially aware of this when you are considering entering a new market.
42/n
We'll take you through the process we went through before deciding to enter the crypto market, building up a business case by:
- Finding out what other traders are doing
- Reading published research
- Doing simple quant analysis
- Doing some trading.
43/n
And we'll outline some simple high-probability trading strategies harnessing basis and momentum effects.
All that in 5 weeks.
And most important of all, we'll leave you with the confidence that There Will Always Be More Trades.
Cos market movements change asset prices, which causes our actual exposures to deviate from the ones we want.
Also, our views on asset returns and (co)risk might change and need to be updated.
1/n
The trading problem (ignoring txn cost) is to:
- forecast expected returns (alpha) over some forward horizon
- model risk (including the relationship between assets)
- find a set of asset weights we think maximizes our objective (risk-adjusted returns) subject to some stuff
2/n
Rebalancing is really just shunting weights back in line when the market moves them away from where we want them.
In practice, rebalancing can look a bit more complicated because your alphas and risk estimates are changing too.
In the original thread we noted:
- you can't trade VIX
- so there's no market mechanism to stop it from being predictable
- but VIX futures do trade and their price incorporates where the market thinks VIX is likely to go
2/n
If the market thinks VIX is going to go up, the futures will likely already be trading at a premium.
Sellers won't sell low if it's likely to go up.
Buyers will be happy to buy higher if it's likely to go up.
If you're an experienced trader, you'll recognize immediately that this is not a thing you can trade.
Why?
Cos it wouldn't look like that if people could trade it.
2/n
Cos, just by eyeballing the time series chart, you can tell VIX is very predictable:
- It stays about the same in the short term
- But if it's low it's more likely to go up
- And if it's high it's more likely to go down
- It has a floor under which it's unlikely to go lower