In this brilliant article, Kris talks about the importance of trying to "shorten the feedback loop"?

How does a fundamental manager "shorten the feedback loop"?

I don't do anything that looks like "fundamental investing" but I couldn't stop thinking about the problem...

I think of the returns from "fundamental investing" coming from two sources...

1. Risk Premium - The tendency of risky assets to be relatively cheap vs their expected cashflows. This leads them to "carry" more than they would if their real cashflows were riskless

2. Mispricing - For behavioural/structural reasons, some assets are under/over-priced vs a reasonable estimate of their ex-ante "fair value".

On average, we expect them to converge towards fair value over some long time horizon.

This is "alpha" in fundamental investing

As @KrisAbdelmessih explains, it's hard to tell if you have any skill in this mispricing game because the "time to convergence" ("the feedback loop") is soooo long.

So most of us avoid the game most of the time because we can.

Easier games available. Too hard basket.

In some domains, it is easy to see how you might shorten a long feedback loop.

If I want to predict the winner of the English Premier League I can get good shorter feedback from my predictions vs the outcomes of individual matches.

I can get even shorter feedback by looking at the rate of goal scoring within a game.

I can get different feedback from *other factors which are highly correlated with match result*, such as "shots on goal", or "number of corners".

It is hard to find analogs in trading convergence on fundamental asset mispricing.

If we lower the time period we're looking at we tend to simply observe noise.

In investing, there are no easily-idenitiable "matches" for us to test our ability against.

And the market tends to be so efficient that any fast-converging factor we can identify will only be *very noisily related* to our objective (long-run expected convergence.)

In investing, our "corners" and "shots on goal" are only very weakly correlated to our result.

I tend to avoid these games for these reasons - and because I can.

There are easier games to play: risk premia and quicker flow-based mispricings.

But I'm interested in how a good fundamental investor would try to navigate the challenge of "shortening the feedback loop".

If you are a fundamental manager you don't have the option of the "Too Hard Basket"

How do you approach this?


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More from @therobotjames

3 Dec
Trading is a game of repeatedly asking:

1. What exposures do I want?
2. What exposures do I have?
3. How do I get closer to 1 from 2, given that:
a) it costs to switch positions
b) my estimates are noisy
c) co-movements of assets are somewhat predictable

Concepts like "open trades" and "unrealized p&l" tend to be unhelpful in this paradigm.

If you don't like the exposures you have, then move them closer to the ones you want.

It makes no difference if you're underwater or in profit in your "position accounting"

There is no difference between a position that you have kept on the book for a while and one you just opened. It's exactly the same exposure either way.

Let's run through these 3 questions using a simple toy trading approach...

Read 21 tweets
2 Dec
Traders often implicitly assume recent conditions will persist - without checking whether that's likely to be true.

You need to understand the assumptions you are making, and whether they are reasonable.

Here are some examples and a simple analytical approach 👇👇👇

"I want to find an asset with characteristics X

"So I'm going to look for stuff which showed these characteristics in the recent past - and I'll hope it carries on having them for a while."

Sometimes this is reasonable. Sometimes it is wishful thinking.

How do we tell?

Here's an example of something we know is persistent - volatility.

"I want to find a low volatility stock - so I'm going to look for stocks which have been low vol this year"

Is this reasonable, or wishful thinking? Let's see...

3/n Image
Read 17 tweets
27 Nov
You think you've identified a new, useful predictive factor for trading...

But is it really new? Or just another way of looking at something you already know about?

How might you tell? Here are some simple ways...

A research thread 👇👇👇
First, put aside any expectation that you can isolate and quantify effects with great precision.

The market is a highly efficient beast - why means that any non-random effects we observe tend to be extremely noisy.

But just cos something is hard, doesn't mean we shouldn't try.
In fact, it's essential that we try to understand and isolate effects as best we can.

The best tools for the job (at least to start) are:
- economic intuition
- very simple data analysis (the kind of thing you could do in an excel pivot table)
Read 21 tweets
12 Nov
Shall we do some analysis on a *really dumb* factor which might predict relative returns in stocks?

"Are cheap stocks expensive?"

A research thread 👇👇👇
Options on stocks with a low share price tend to be overpriced.

Equity options (at 100 shares a pop) are quite big for a small retail trader. So we might say there is excess retail demand for options on cheap stocks - which would result in them being overpriced.
But are low priced stocks also expensive?

The AMZN share price is $3k+. There are Robinhooders who can't afford a single stock.

Do we see the same effect in Stocks as we do in the options?
Read 25 tweets

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