Exploring discipline, risk and getting started in trading

Bob Iaccino, Chief Market Strategist and Co-Founder of Path Trading Partners, joins us live every Friday from 11am EST, as our risk management educator.

With 30 years’ experience working as an active investor in equities, commodities, futures and FX there are few better to talk on the subject of risk management.

Bob has developed a method for breaking down his key fundamentals of risk management, in a way that he thinks retail traders can understand and use to get actionable insights to bring into their own trading.

Below are some excerpts of Bob’s thoughts from a recent live session. If you’d like to save your seat to watch and participate in the next session, register here.

Let’s move into questions:

What is Monte Carlo simulation?

Monte Carlo Simulation is basically a mathematical technique that allows you to quantify risk in a random exercise as opposed to a deterministic exercise.

I’ve mentioned before that when I was at my hedge fund of funds for 9 years, my job was to be on a two-person investment committee, analyzing emerging managers (managers with three years of track record or less).

People might say: ‘three years? I’ve back tested my strategy for a year, and it works great”.

The reason why we ask for three years, for example, is if you started a back test with Apple in January in 2019 and ended it in January 2022, all Apple did was go up with a few rotations.

If you did your back test and your strategy was long only on Apple; can I believe those returns? Of course not, because I have no idea what your strategy does if it turns lower.

This is the type of situation in which we would run a Monte Carlo Simulation.

How does Monte Carlo simulation work?

Monte Carlo basically takes individual sessions and takes the return level of the individual sessions and randomizes them.

Have you ever played any of those puzzle games on your phone; whether it’s Candy Crush or Royal Match where you have to line up things in a row for them to disappear? When you run out of things you can line up there’s usually a button that says: ‘Shuffle’ and it takes everything and shuffles it in a random order: that’s what Monte Carlo does.

Monte Carlo could take three years of Apple (for example) and shuffle it, so the stock isn’t going straight up. What does that do?

It takes away the deterministic outcome of your strategy – the curve fitting. Curve fitting is when people take a strategy and they set it to a certain block of data and say: “Wow, my strategy worked really well here, therefore it will work in the future”.

We all know that is not necessarily the case.

So, in essence, a Monte Carlo simulation incorporates randomness into your trading to actually analyze the potential risk of loss and the robustness of your strategy.

When should I use a Monte Carlo simulation?

One of the most important reasons to attempt a Monte Carlo simulation is because you don’t have enough data to gauge your trading.

For example, say I’ve been live trading for 2.5 years and it’s been going great, but I just don’t know if that’s going to continue.

Then, you’d run a Monte Carlo simulation on 20 years of data – or just the last 2.5 years is useful. You can say: “I’ve been positive for 2.5 years but let me randomize this data and see what happens”.

The Monte Carlo simulators that are out there will take the last two years (of data) and distribute the returns in a way that is possible. You can look at it and say: “This is something that could possibly happen with my strategy, so I need to be prepared for it”.

This snaps people out of the fantasy that their particular strategy can’t lose money or can’t go into a losing streak, and that’s the most important part of it.

Since you’ve made it to the end of the article you may want to join Bob live during his next education session. Save your seat here.

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