🗞 Executing the Trade

WHILE YOU POUR THE JOE… ☕️

Most people argue that liquidity and credit is still strong…

I would say that quite the opposite is true, no matter how weak the dollar index has been lately or how much the Fed keeps printing today. 📉 

The reason is that the SOFR rate has now jumped over the OIS, and that’s nowhere near being good news. 🐻 

• A SOFR above OIS means that credit and liquidity is tightening, and that doesn’t fare well for EPS and risk-taking moving forward

You can see this at play in the 10Y 2Y yield curve in the United States as well, it shows liquidity is in the early stages of drying up and credit tightening alongside it.

Liquidity and money markets are key to predicting what risk assets (like stocks and crypto) will do in the near future. 👀 

In fact, it is a big focus in the macro section of our flagship program The Sovereign Trader.

But

Covering macro will take you a few hours, so we’ve broken down the entire thing into a free 5-day email crash course, with added Excel models for you to take and use in your keeping up with the narrative

Sign up for your first lesson tomorrow ✅ 

Speaking of what stocks may do, let’s get on with today’s email 📧…

MODELING TIME
Picking Back Up

This long $LSTR and short $CNI trade is about to come into our buy zone.

However, we showed you in our last newsletter that a bit of financial analysis was still needed before pulling the trigger.

So let’s get that done:

Without going into company specifics just yet, here’s where Landstar and Canadian National stand against other trucking and rail peers.

Two things I want you to focus on here:

• Debt

• Capacity

Landstar obviously carries a lot less debt on its balance sheet (13.6%) compared to the much higher 49.3% seen in Canadian National.

However

Both of these generate similar ROIC and ROA figures, 14.8% and 12.8% respectively.

That means that Landstar is a lot more efficient in using what capital they have now compared to Canadian National.

But here’s what I like the most…

It is almost a certainty now that the Fed will cut interest rates, and you know what I have to say about that. 📉 

But that’s not today’s point…

A rate cut will be an amazing thing for Landstar, given how little debt it now carries, as it will enable it to add some cheaper leverage onto its balance sheet.

Something tells me they’re going to need it.
And that’s capacity… 👀 

2.8x for Landstar vs 0.3x for Canadian National.

That confirms where demand is going currently, away from Canadian National (explaining its forward P/E discount and below-average EPS growth).

It also tells you that Landstar is running red hot right now, confirming the reason for the premiums.

Setting Up The Trade

The first thing we look at is correlations, something you’d know being inside our flagship program.

Why correlations? Glad you asked. ⬇️ 

You can’t know how two assets are behaving inside a broader industry move, and whether their relationships are changing one way or another.

Actually, you can, if you understand their correlation seasonality.

It also shows you whether you want to run a long/long or long/short position.

This lesson, which goes much deeper, is at the heart of our portfolio construction chapters inside The Sovereign Trader Program. 🧠 

Knowing this concept alone can not only keep your capital neutral to the S&P 500, but also HALVE the volatility in your entire account.

Stop going in blind and wondering why you’re leaving so much money on the table..

Sign up for The Sovereign Trader Program ✅ 

Given that $LSTR and $CNI have a positive and steady correlation, I feel good about modeling this trade further.

So let’s pair them against each other:

At first glance, our generated hedge ratio (using Python stats models) of 0.5249 gives us this spread above.

That’s $LSTR - 0.5249 * $CNI by the way, you can chart it inside Thinkorswim.

However, we have to test for stationarity in this case, so we know for sure this is going to follow a mean reversion behavior, which is where we make our money.

That’s done through another Python script to test for this statistic.

The result is a P-value of 0.04, and if you failed statistics in school that means we have a 95% confidence interval proving this is mean-reverting. 💡 

In other words…

We can buy at significant deviations, such as $70-$72 to then sell at the mean area of $102-$107.

That’s a setup for approximately 45-48% upside 🔥 

But wait, there’s one more test to be done ⬇️ 

The Z-Score test is just another statistic to smooth out our entries and exits. 🎯 

We actually added this about four months ago on top of our strategy, and that is something that gets its own module and dedicated teaching session inside our program.

Any and all future updates to our code, strategy, or research process will be immediately sent over to you and other alumni to enjoy.

Anyway,

The current Z-Score suggests we are at a crossroads, considering that we’re not entirely in a second deviation, neither are we far enough from it.

So the choice here is to either:

• Wait for further deviations

• Scale in with a much smaller position in case w start reverting back to the mean

Looking at the live chart, I think option #2 is more suitable here. 👍️ 

The reason is that we’re noticing a volume buildup right at this current deviation, which has held for about a month now.

That being said, lots of tails have also been formed on the downside, likely reactive buyers coming in big to load this spread up. 💰️ 

I’ve seen this before, and it’s one of the footprints confirming that other big hedge funds or banks are behind this same idea.

You too could be part of what Wall Street elites hunt for.

Or

Keep relying on chart patterns that anyone has access to (surprise, there’s no edge there)

Your choice,

See you inside our program. ✅ 

To your success,

G 🫰 

GO AND MAKE IT HAPPEN
Together With Augur

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Which is Excel.

Why not cut out the middleman and use the thousands of charts and visualizations made by our friends at Augur Infinity?

Free, quick, useful. ⬇️ 

To your success,

G. 🥃