In this video, we dive into two high-performing strategies for the Mini S&P 500, an index featuring the 500 largest US stocks by market capitalization.

The first strategy follows a mean-reversion approach, averaging $144 per trade, while the second capitalizes on a recurring price pattern, with average trades hitting $241.

Combined, these strategies have already earned over $35,000 from January to October 2024!
Watch the video now to learn more! You'll discover:
-How the two strategies work
-All the details about their performance
-Some useful information for trading on the S&P500

Enjoy 😊

Transcription

Introduction

Welcome to this new video where we'll analyze two of the strategies from our trading system database.

In this video, we’ve chosen to examine two strategies focused on the S&P 500 futures, which, as you probably know, is a future that tracks one of the most significant indices in the world, the S&P 500 Index.

In particular, we’ll look at a mean-reverting strategy, shown above, and another strategy that leverages a specific market bias.

One of the coaches at Unger Academy here, and let’s dive in by analyzing the first of these two strategies.

First Strategy: Mean-Reversion Approach on S&P 500 Futures

This strategy has the S&P 500 on Data1, which we can consider the primary series or reference, set on a 5-minute time frame.

On Data2, we use the volatility index, set on a daily time frame.

Let’s go over the entry conditions for this strategy.

First, we start with the initial bar of the session, which is the first 5-minute bar.

I’ve marked the start of each session with a white line, so you can see the first bar right here.

In this setup, we add 0.20% to the high of the first bar and subtract 0.20% from its low.

This creates two levels: an upper level we can call "overbought" and a lower level we’ll refer to as "oversold."

So, what’s the trigger for this strategy? As you might guess, since this is a mean-reverting strategy, the trigger is crossing below or above these levels.

Let’s look at these two trades as examples.

Here, suppose we have the level roughly 0.20% below the low of the first bar.

When the price breaks below this level, we open a long position.

The opposite applies to this short entry.

When the price breaks above the 0.20% level calculated from the first bar’s high, we open a short position, which is then reversed based on the same logic.

You might wonder, what’s the role of the secondary data series—the VIX on a daily time frame?

The VIX on a daily time frame serves solely as a filter for long entries.

We included a rule in the script that prevents trading during VIX expansions.

As you may know, when the VIX—a fear index—expands, it’s often not the best time to open long positions.

But let’s move on to analyzing this strategy’s performance.

Here’s the equity line. It’s worth noting that it’s out of sample roughly starting from early 2018.

As you can see, it has weathered several turbulent phases, like in 2020–2021, yet has continued to perform well over the years, especially in recent months, as shown by this new equity peak.

Now, let’s examine the long and short sides of this equity.

Looking at the long side, it’s generally steady, with a noticeable recent peak.

On the short side, we see a pretty different story.

This difference likely reflects the challenges in finding successful short strategies in markets that have seen substantial upward trends in recent years.

Indeed, the number of trades on the short side is significantly lower than on the long side.

Let’s proceed with the Total Trade Analysis.

About 1,300 trades have been made here, roughly 1,000 on the long side and only 300 on the short side.

This is expected, given that this is a market where we need an asymmetric, or non-mirrored, approach.

For average trade size, we’re seeing around $144, which covers operational costs like slippage and commissions.

It’s notably higher on the long side, at around $166, and much lower on the short side, with just $60.

That $60 average for short trades wouldn’t be enough to cover operational costs, so someone might consider excluding the short side from this strategy.

Even though the short side isn’t performing as impressively, it does help the strategy perform during down markets.

Recently, we’ve been in an overall uptrend, but imagine a phase with a relatively high VIX.

In such cases, the strategy wouldn’t trade long due to the filter but could still profit from short trades.

Now, let’s review annual performance results.

Here they are. Some years, like 2011 and 2015, show negative returns. 2021 was also a down year.

Interestingly, since 2018, when the strategy went out of sample, we’ve had more positive years than in-sample ones.

Also worth noting, 2023 and 2024 have been very profitable years so far, with 2022, a challenging year for stock markets, showing strong results too.

With that, let’s dive into the second strategy.

Second Strategy: Bias-Based Intraday Approach

Here it is—a bias-based strategy.

Let me explain. When a new session starts, as you can see here, there’s a bar counter that begins counting 60-minute bars.

When the count reaches 5, meaning five bars have formed, we open a long position at the next bar's open, as shown here.

Of course, additional conditions, or patterns, were added with the goal of improving the performance of this strategy.

This is strictly an intraday strategy, closing positions on the session’s penultimate bar and trading long only.

But let’s review the performance, starting with the equity line.

As you can see, the equity line shows a steady rise.

It makes fewer trades, but this is obvious since it only works on the long side.

It has had some challenging periods, like 2020, but we can see that year 2022 was an outstanding year.

Moreover, looking at recent results, we see that the strategy is on new equity peaks.

Of course, this is a very satisfying result, especially as this strategy has been out of sample since 2018.

Moving on to the Total Trade Analysis, we see only 345 trades.

However, despite the low trade count, it has a solid win rate of 60% and a high average trade of $241.

That’s impressive, especially given that it’s an intraday-only strategy.

In fact, as we know, spending less time in the market often makes it harder to achieve a substantial average trade.

Finally, let’s look at annual returns for this strategy. Here they are.

As you can see, while 2022 wasn’t a standout year, 2021 generated $10,000, and 2022 hit a net profit of $12,000.

This was particularly remarkable, considering 2022 was very turbulent for stock markets.

Unfortunately 2023 has been a negative year. However, 2024 is performing very well so far, which aligns with the equity line’s recent highs we’ve seen.

Conclusion

These are two potential strategies that could be useful in developing your own trading systems.

As always, click the link in the description if you’re interested in topics like these, and I’ll see you in the next video.

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