In the "win-lose" games of active trading, your "edge" comes from:
- Buying from someone too cheap
- Selling to someone too expensive

At least on average.

To do this, you need to know who you are playing against.

🧵on "edge", where to find it, and how you can compete 👇

If you are a market maker, it is relatively clear to understand who you are trading against.

If you're a positional trader, it is perhaps less clear.

On a trivial level, you're probably trading with a market maker.

But understand that "the market line" is set by the supply/demand pressures of other aggressive traders.
- End users (wealth mgmt, retail)
- Aggressive prop traders doing short term risky arbs
- Informed positional traders with pricing models + (maybe) info advantages

It is easy to understand why "end users" would be prepared to trade at inopportune prices.

- perhaps they don't know any better.
- perhaps they are operating under *constraints* (they HAVE to sell/rebalance even though they don't WANT to)

- perhaps they need to get an investment committee together before they can make a trading decision
- perhaps they are * incentivized* to do things that don't maximize their expected returns (window-dressing, return chasing, defensive posnig around the reporting cycle)

In an uncompetitive trading environment, it would be easy for you to get an edge in the markets by understanding the above.

You could get paid for selling to these traders when they were FORCED to buy, due to their constraints.

You could get paid for buying trash from fund managers that were interested in "tidying the book" for window-dressing around exposure reporting dates.

And also from selling them the "respectable-looking" stuff they want to rotate into.

You could get paid for fading short-term supply/demand imbalances caused by impatient noise traders.

You get the idea...

It's clear that in an uncompetitive market, we could make good money trading.

There's plenty of uninformed money out there!

HOWEVER... (big however)... we don't trade in an uncompetitive market!

We trade in a highly competitive one!

There are highly sophisticated, fast, trading firms like Citadel competing to trade the short-term inefficiencies.

And there are sophisticated analysts running pricing models at hedge funds and banks making it difficult to get an edge on pricing/valuation with public knowledge.

The intense competition means that prices tend to be extremely efficient.

I don't necessarily mean that everything trades at the "right" price (if we could know such a thing)

I mean that it's hard to make money trading both in the short term and the long term.

The aggressive competition for P&L is what *causes* this:

It's essential to identify the inefficient behaviour of "end users" players.

But it's not enough!

We're in massive competition with aggressive trading firms to exploit it. And it's a game most of us can't compete in.

So you need to find places where competition is low.

There's a reason Citadel buys order flow from Robinhood.

Because they know it's noise trading.

So they're confident they can "eat all the edge" so no tradeable inefficiencies escape.

You can think of it as a big net around all the inefficiencies

You could sit outside the net with your mouth open like pacman here...

But all the good stuff will have been kept in the net and eaten by the big boys.

You'd just be eating noise.

Noise is not tasty.

But not everything is always so neatly contained.

Sometimes inefficiency leaks out because exploiting it is relatively unattractive.

Maybe the flows are just too massive to be fully contained.

Maybe the opportunities are too small, too capital intensive, too awkward...

If it's not worth the big boys getting out of bed for, then opportunity can leak through...

So, if you know where and when to sit with your mouth open, you can feed yourself on noisy alpha scraps like this happy pacman here.

Now you know what needs to be true to identify inefficiencies you can exploit.

You need:
1. A group of traders willing or forced to trade at inopportune prices
2. Exploiting this to be unattractive to aggressive players.

Both of these pieces need to be in place.

To help you with this, I teach you to think of "business cases" or "elevator pitches" for trades.

These are simple descriptions of what, why, and how you could make money from a market effect.

A 5 yo should understand it and find it reasonable.…

These "elevator pitches" are simple statements of:

WHAT would cause the inefficiency
WHY it wouldn't be fully "gobbled up" by other aggressive traders who are faster or better informed
HOW you might harness it, on average.

Sometimes, if this is compelling enough, this is enough to start designing a strategy to exploit the effect.

But if you have enough data, you'll want to look for evidence in the past data that you could have exploited the effect.

Simple data analysis is your friend.

You start thinking about HOW you're going to trade an effect, once you have:
- An "elevator pitch" for why YOU can exploit the effect
- Significant evidence of it in the past data.

Then you want the simplest trading rules to exploit the effect.

Cos every time you add a new rule, you add a new way to screw up.

Once you have a simple set of rules, you might do some simulation (backtesting) to validate your assumptions.

Then, trade it with discipline.

Understand the things underlying the effect, and check that they're still valid (so you're not dependent on poor P&L to turn off).

And chill out, and find some more stuff to trade.


To find an inefficiency you can exploit you need to understand market structure, the players, and their constraints and incentives.

You need:
1. many traders willing or forced to trade at inopportune prices
2. exploiting this to be unattractive to the best players


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More from @therobotjames

27 Apr
A simple thread about position sizing and volatility targeting 👇

You have $1,000
You buy $1,000 of SPY
You leave it alone
The volatility of SPY over the period was 18%

What is the volatility of your portfolio?

Not a trick question. It's 18%

Imagine instead you buy $500 of SPY in your $1000 account.

At the start, you have half your money in cash and half in SPY.

What is the volatility of your portfolio now?

It's 9%: half what it was before.

Now, let's say you could buy $2000 of SPY in your $1000 account (and don't pay anything to borrow)

What is the volatility of your portfolio now?

It's 36%: twice the figure when you were fully invested.

This is a useful result. You can prove it to yourself easily in Excel

Read 22 tweets
22 Apr
Tips for doing financial analysis with OHLC bar data.

Many of you doing quanty analysis with OHLC bar data.

Here's some boring but crucial stuff you need to understand if you're doing that. 👇👇👇

An OHLC bar represents a summary of trades that happened in a certain period.

Open -the price of the first trade in the period
High - the highest price traded in the period
Low - the lowest price traded in the period
Close - the price of the final trade in the period

For daily stock data, the Close price will be the price arrived at in the closing auction.

This is set by balancing the supply and demand of MOO (market on close) and LOO (limit on close) orders to maximize the amount of stock traded.

Read 17 tweets
20 Apr
In Australia, if you're serious about getting the job done effectively and efficiently, you might say:

"I'm not here to f*** spiders"

Many traders act like they are, indeed, here to f*** spiders.

A thread about getting serious about making money trading 👇👇👇

If you're making soup, you first need a good stock.

Stock isn't exciting. Everyone has stock.

Garnish is exciting, but you can't make soup from just garnish.

You need some stock in your trading portfolio

You need at least one reliable, stonkingly obvious way to get paid

Here's a non-soup analogy...

If you start a business venture, it's clear that you need an obvious, reliable way to make money.

You wouldn't just try to blag it.

"I am smart and hard-working" is not a business case.

You need a stonkingly obvious way to get paid.

Read 31 tweets
19 Apr
In my 20 years of trading I have noticed this cycle play out again and again with traders that "make it":

1. Overconfidently reach for returns
2. Get humbled by the market
3. Simplify + concentrate on clear, high probability edges.

Nearly everyone starts with a lack of respect for how hard it is to consistently make money trading.

That leads them to pass over high-probability sources of returns in favor of more marginal ideas.

Or they overcomplicate the trading of a good edge.

Here's an example...

It is 2015. You look at a simple strategy.

You hold an equal dollar exposure to:
- Cap Weighted US Stocks (VTI)
- 20+ Yr US Treasury Bonds (TLT)
- Gold (GLD)

And rebalance each month.

(I've extended back a bit with mutual fund prices.)

Read 22 tweets
14 Apr
A common mistake is to make implementation decisions or parameter choices based on "what improves the summary performance of a backtest".

Quant research is not "changing random stuff and picking the best performing backtest"

A backtest is a very complicated thing.

In the best case, the cause -> effect relationship between what you are changing and the performance of the backtest (say) is highly non-linear.

More likely there is no clear relationship.

Quant trading is not "changing stuff until you get a backtest you're happy with".

You need to split what you're doing into small component chunks and model those chunks as best you can.

Read 5 tweets
11 Apr
It's easy to lose money trading if you:
1. Trade too much (paying fees + impact on each txn)
2. Size positions too big (high vol hurts compounding ability + gets u rekt)
3. Shorting positive drift/risk premia

It's hard to lose money consistently if you avoid these things.
However clueless you are, you get to trade at market prices.

Imagine we can know that an asset has a fair value of $100.

You might think it's worth $150.

But if it's quoted $99 / $101, you can buy now at $101.

You were totally wrong but you still bought close to fair value.
The same mechanisms that make it hard to get an edge also make it hard for you to trade at really bad prices.

In a simple model, you might say that prices are set by:
- (risky) arbitrage and relative value in the short term
- pricing/valuation models in the long term
Read 15 tweets

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