Lesson #3 of 7:

"RUNNING THE GAUNTLET: How to Remove Yourself From the Equation and Make Your Trading System Foolproof"

PLUS: A sneak peek into Dynamic Time Warping, the jaw-dropping “weird math” equation that can transform the way you trade.

From: Dan Murphy

Corona Del Mar, CA

(Missed any of the prior lessons? Go here for Lesson #1 and here for Lesson #2.)

Now, after a brief strategy call with my business partner Ruud, things were really starting to heat up.

All the strategies have been separated into rough buckets, and you can already see improvements.

On the phone, I said, “We know we’ve got great strategies, we’ve got the Meta ML deciding the optimal time to trade each strategy, and now we have these buckets making sure we’re using all of our cash.”

I continued …

“What I’m wondering is, what’s the number one factor that could get in the way … What could keep us from realizing the seriously impressive results it looks like we could have?”

Without a second’s hesitation, Ruud gave me his reply.

“Doubt,” he said confidently.

I paused for a second and thought …

“You’re right. Emotions like doubt, pride, and greed are the main things that could mess this up for someone.”

That conversation set the tone for the next portion of my research.

It makes perfect sense …

A number of studies have proven, time and time again, that actively managed funds can’t beat the market in the long term.

In fact, actively managed funds perform worse than the market more than 50% of the time.

That means they have a worse chance of working out than a random coin flip.

But still, there are “quantitative funds” out there that manage to crush the market year after year.

So what’s the main difference between the successful “Quant Funds” and the majority of actively managed funds that lose money?

The defining trait that sets “Quant Funds” ahead of the pack is this rule.

When you find a system that works, don’t question it.

For them, it isn’t about emotions or opinions.

It’s about hard numbers.

That means for this system to be foolproof, it needs to be proven beyond anything that you could reasonably doubt.

You need to be confident enough in your system that you can follow it without question.

After all, what’s the point of starting a “one-man hedge fund” and then making the same mistakes that actively managed funds make?

For this, I put together a set of tests I called “the Gauntlet.”

“The Gauntlet” is not a specific series of tests.

Instead, it’s about removing yourself from the equation …

By giving yourself absolute peace of mind …

And rigorously testing every single aspect of your system …

Until all of your doubts are satisfied.

After running my version of the Gauntlet I’m fully confident in my “one-man hedge fund.”

A falling knife is a stock that’s plunging with no end in sight

If I got an order to “catch a falling knife,” as a stock dropped towards zero, I would have no hesitations.

Recovery after “Catching a falling knife”

Because I know that my system gave me that signal for a reason.

That’s the kind of trust you need to have in your system, and that’s the kind of trust the Gauntlet can give you.

I don’t have time or space to cover all of the tests I ran to satisfy my own sense of doubt …

And it’s important that its customized to soothe your doubts …

But here are three of the biggest takeaways from my Gauntlet of tests.

1. What Not To Do

2. Make Sure Your Strategies Aren’t “Too Good”

3. Cut Without Mercy

First things first, this is what you shouldn’t bother trying.

1. What NOT to do

If you have any background in statistics, your first bet will likely be to run something called a “correlation matrix” between the strategies in your different buckets.

A correlation matrix is a standard way to measure how closely related a series of variables are.

You check every member of the set against every other member.

In our case, that means checking all of our strategies (at least 100 of them) against all the others.

Correlation data for our Josh 100 pack of strategies.

So 100*100 means checking — at a bare minimum — 10,000 points of data.

You then assign each point of data a value between -1 (not related) and 1 (very related).

Seems like a good idea, right?

I thought so, too, at first …

But a standard correlation matrix will only work for data that’s linear …

And stock market gains are anything but.

This meant all the time spent checking every one of those 10,000 points of data was WASTED.

(There is a way to check this data for correlation… that’s how I got that fancy table up above. But it’s a lot of work and too in-depth to explain here. To get a peek into this method, watch the video at the end of this article.)

Don’t repeat my mistakes … instead, try this.

2. Make Sure Your Strategies Aren’t “Too Good”

What do I mean by too good?

Often when backtesting using AI tools like Portfolio Boss, we can play around and come up with strategies that look amazingly impressive.

With yearly gains of 60%, 150%, 1000% or more.

These strategies are fun to find, but they aren’t great to trade.

A well-made Meta ML realizes this. Most of the time, it just ignores them.

(Keep reading to see why you should get rid of them anyways.)

If you try to trade it directly, you’ll realize that the strategy is what I call “overfit to the past.”

I’ll explain exactly what “overfitting to the past” means in this video AND how to avoid it using the same technique hedge funds use when crafting strategies:

3. Cut Without Mercy

If you want to get hedge fund level results you can’t have any dead weight lying around your portfolio.

In Lesson 2, we learned how to turn the “dead weight” of our cash reserves into an asset. Actively growing our portfolio.

But sometimes, there are parts of our overall system that can’t be repurposed or put to work.

The answer when this problem arises is to cut it.

Any strategy in our system that isn’t helping us is hurting us.

Even if the Meta ML is ignoring it, because it’s an obviously bad strategy, it needs to be cut.

It’s just another variable where something could go wrong, and we’re striving for clinical precision. The kind of precision that inspires the confidence to never second guess the system.

So if a strategy is overfitted to the past … CUT IT!

If a strategy is highly correlated to another strategy … CUT IT!

If a strategy has a low “profit ratio” … CUT IT!

If a strategy has a high drawdown … that … actually might not be a bad thing. I’ll explain why strategies like this can help your portfolio flourish in a later part of this series.

In the meantime, I think you get the idea. If a strategy isn’t helping you, it has to go.

If you’re interested in learning more about the “weird math” I had to do to make a correlation matrix for my strategies, watch the video below.

Otherwise, check your inbox tomorrow to see the next strategy we’re offering for free.

In the next lesson I’ll explain how top hedge funds utilize “True Diversification” to beat the market with extreme consistency.

Bonus Video Clip

Watch below to learn about “Dynamic Time Warping.” This physics equation is used in language processing, AI technology, and by DJs to match live samples with recordings.

It’s also used to analyze stock pricing data, which is where you’ll find the most use for it in setting up your “one-man hedge fund.”

The video is very technical, and the speaker is a literal robot, but the benefits of using Dynamic Time Warping are absolutely PRICELESS! (I felt giddy when I got it to work as one of my Gauntlet tests)

Play Video