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Robot James Profile picture
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19 Mar, 4 tweets, 1 min read
Examples of "elevator pitches" for retail-friendly trades, that I would find reasonable 👇👇👇

1/4
"Wealth management equity/bond rebalance flows are massive and, due to their size, may not be fully dispersed when performance differences (and therefore rebalance trades) are very large.

We might get paid for buying what they're selling around month-end"
"Institutional yield enhancement programs are massive and tend to be info-insensitive sellers of volatility on an up-tick in vol.

This may keep IVs depressed in the short-term, leading to trend effects in IV on significant bad news, which we could profitably trend-follow"
Your pitch should include:

1. what would cause the inefficiency
2. why it wouldn't be fully dispersed by others who are quicker/better informed
3. a simple robust way to trade it

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More from @therobotjames

Robot James Profile picture
20 Mar
Risk and Reward: A Quant Tragedy

Through careful research, you have assembled a collection of alphas that are correlated with future asset returns.

There's some conventional stuff (momentum, ST reversal, valuation, quality, short interest etc)...

1/7
There's some totally unique stuff (you think)...

And there's some stuff you're still clinging onto because you don't want to admit you wasted all that time and money on alternative data.

You take these alphas and you combine them into an expected return for each asset.

2/7
You run some simple sense checks. Each period you sort the assets by expected return, long the top and short the bottom.

It looks good. You are encouraged.

But you wouldn't trade it like that.

Some assets are more volatile than others, many are driven by similar risks

3/7
Read 7 tweets
Robot James Profile picture
18 Mar
How do I know if I have an edge?

A thread... 👇👇👇👇

I've been helping a family friend with his trading. I've given him a simple systematic strategy to trade by hand.

We can plot the distribution of historic trade returns from past trading or a backtest as a histogram.

1/n
The trade P&L is on the x-axis and the frequency (# of trades with that P&L) on the y-axis.

This is useful because it gives us a hint as to what the "edge" of our strategy might be - if we could ever truly *know* such a thing.

2/n
In this case, our strategy had positive mean and negative skew.

We saw winning trades about 58% of the time but losers were bigger, on average, than winners.

(As many things that make money tend do, regrettably)

3/n
Read 15 tweets
Robot James Profile picture
9 Mar
On "stationarity"...

When we talk about something being "stationary" we mean that the observations look like they could be drawn from the same "bag of observations" (distribution), regardless of what time we choose to look at.

1/5
You can observe this by eyeballing charts.

VIX (blue) stays within a range the whole time. If it gets to extreme values, it's likely to revert back to moderate values.

By contrast, the SPX price (orange) just seems to drift away. It doesn't appear anchored to any range.

2/5
We can also see this by sampling from the distributions at different times.

Let's divide our sample roughly in half (2004-2012 vs 2013-2021).

From the histogram, it's clear that SPX prices are not drawn from the same distribution in the first and second periods

3/5
Read 6 tweets
Robot James Profile picture
9 Mar
Let me try to be helpful.

If you have some kind of factor that you think predicts future stock returns (or similar) and you are making charts like below, then here are some tips...

We'll go through an example of trying to "time" SPX with the level of VIX.

A thread 👇👇👇👇
You get daily SPX index prices and daily VIX close data

You align them by date and plot them on dual axes, in true RealVision style.

"SPX tends to go down when VIX is high. I can therefore time an SPX allocation based on VIX. Let me share this on twitter" you say.

No. Very no.
There are two main problems with what you did:

1. The SPX price drifts. We can't directly compare the price of SPX in 2004 with its price in 2021

2. As traders, we are more interested in whether high VIX is *followed by* decreasing SPX prices, not *coincident with* them.
Read 23 tweets
Robot James Profile picture
28 Feb
This is a fantastic initiative from @KrisAbdelmessih.

It is hard for a beginner to know what effective trading "looks like", and where to concentrate efforts.

This will help bring the best of pro trading training programs to the masses.

Some thoughts on trader training... 1/n
The path to profitable trading is straight and narrow.

Having a theory on inflation, or memetics, or an in-depth knowledge of the VIX expiration, is a waste of time if I'm quoting corn options.

So good training concentrates the trader on things that matter.

2/n
You need to concentrate on micro things (information, motivations, constraints, game theory) when you're playing micro games.

And you need to concentrate on macro things (stats, broad behavioural tendencies) when you're playing macro games.

3/n
Read 12 tweets
Robot James Profile picture
10 Feb
Broadly, there are 3 types of systematic trading strategy that can "work".

In order of increasing turnover:
1. Risk premia harvesting
2. Economically-sensible, statistically-quantifiable slow-converging inefficiencies
3. Trading fast-converging supply/demand imbalances

👇👇👇
1. Risk Premia Harvesting - is typically the domain of wealth management, but it's important to any trader who likes money.

A "risk premium" is the excess return you might expect over and above risk-free cashflows for taking on certain unattractive risks
"Equity Risk Premium", for example, is how you say "Stonks, they go up" if you work for Blackrock

(Though, they're really referring to the extent to which they "go up" more than an equivalent less risky thing)
Read 20 tweets

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