The edge in trading IPOs: 18% annual return

[quantitativo]

Hi,

Some weeks ago, I listened to a great strategy shared by Marsten Parker in a podcast interview. I backtested it and was surprised at the results: 18% annual returns over the past 23 years. The strategy beats the S&P 500 with 3x its return and 1/3 of its drawdown. I'm writing here to share what I found.

Marsten Parker is a self-taught programmer and systematic trader with over 20 years of experience in the trading world. He is best known for being featured in Jack Schwager's book, "Unknown Market Wizards," where he is highlighted as the only purely systematic trader in the series.

His strategies have delivered an average annual compounded return of 20%, significantly outperforming the S&P 500.

Marsten's IPO strategy consists of frequently buying and selling IPOs, holding the positions for just a few days. The rules, as he explained:

• Define an IPO as any company recently listed (e.g., in the past 90 days);
  
  
• Whenever the stock closes at a new all-time high, buy;
  
  
• Put a profit target order and a stop-loss order on the day you buy.
  

This is the equity curve and the strategy stats for a profit target of 20%, a stop loss of 10%, and a maximum number of positions of 20:

Equity and drawdown curves for the strategy for P = 20%, L = 10% and N = 20

Summary of the backtest statistics

Summary of the backtest trades

Monthly and annual returns since 2001

The strategy delivers 17.8% annual returns, a 1.42 Sharpe, and a 17.3% max. drawdown.

If we had traded this strategy in the last 23 years:

• We would have had only 2 down years (2008 and 2011);
• We would have seen 66% of the months positive, with the best at +46.7% (Oct '21: this above-average return was driven by DJT, which the strategy bought 8 days after its IPO and held for 37 days);
• We would have seen 34% of the months negative, with the worst at -9.0% (Nov' 21);
• The longest positive streak would have been 13 months, from Aug '02 to Aug '03;
• The longest negative streak would have been for 5 months, from Jun '08 to Sep '08.
  

Given the high number of trades / year (~100), it would only make sense to trade a strategy like this with 100% automation.

I also investigated the statistical significance of the average return of buying all-high IPOs vs. non-IPOs. Buying an IPO at an all-time high and holding for 20 days has an expected return of 3.98% vs. 1.14% non-IPOs: it's 4x better, and the difference is statistically significant (p-value well below 0.05).

This strategy is a bit more complex than the previous ones I've shared... there are several details... I created a full write-up with all the details here.

I'd love to hear what you guys think...

Cheers!

 

[gkishot]

Hi,

Some weeks ago, I listened to a great strategy shared by Marsten Parker in a podcast interview. I backtested it and was surprised at the results: 18% annual returns over the past 23 years. The strategy beats the S&P 500 with 3x its return and 1/3 of its drawdown. I'm writing here to share what I found.

Marsten Parker is a self-taught programmer and systematic trader with over 20 years of experience in the trading world. He is best known for being featured in Jack Schwager's book, "Unknown Market Wizards," where he is highlighted as the only purely systematic trader in the series.

His strategies have delivered an average annual compounded return of 20%, significantly outperforming the S&P 500.

Marsten's IPO strategy consists of frequently buying and selling IPOs, holding the positions for just a few days. The rules, as he explained:

• Define an IPO as any company recently listed (e.g., in the past 90 days);
  
  
• Whenever the stock closes at a new all-time high, buy;
  
  
• Put a profit target order and a stop-loss order on the day you buy.

This is the equity curve and the strategy stats for a profit target of 20%, a stop loss of 10%, and a maximum number of positions of 20:

Equity and drawdown curves for the strategy for P = 20%, L = 10% and N = 20

Summary of the backtest statistics

Summary of the backtest trades

Monthly and annual returns since 2001

The strategy delivers 17.8% annual returns, a 1.42 Sharpe, and a 17.3% max. drawdown.

If we had traded this strategy in the last 23 years:

• We would have had only 2 down years (2008 and 2011);
• We would have seen 66% of the months positive, with the best at +46.7% (Oct '21: this above-average return was driven by DJT, which the strategy bought 8 days after its IPO and held for 37 days);
• We would have seen 34% of the months negative, with the worst at -9.0% (Nov' 21);
• The longest positive streak would have been 13 months, from Aug '02 to Aug '03;
• The longest negative streak would have been for 5 months, from Jun '08 to Sep '08.

Given the high number of trades / year (~100), it would only make sense to trade a strategy like this with 100% automation.

I also investigated the statistical significance of the average return of buying all-high IPOs vs. non-IPOs. Buying an IPO at an all-time high and holding for 20 days has an expected return of 3.98% vs. 1.14% non-IPOs: it's 4x better, and the difference is statistically significant (p-value well below 0.05).

This strategy is a bit more complex than the previous ones I've shared... there are several details... I created a full write-up with all the details here.

I'd love to hear what you guys think...

Cheers!

What source did use for historical listing of IPOs?

 

[quantitativo]

Nasdaq Sharadar US Equity Bundle dataset.

great vendor

 

[Slow Learning Elf]

It’s a well know source of alpha, which has been gradually disappearing over the last 5 years or so despite a high number of IPOs (SPACs are partly to blame). You, obviously, have curve-fit the parameters quite a bit, I’d expect it perform much worse in real life but you know this already.

 

[quantitativo]

It’s a well know source of alpha, which has been gradually disappearing over the last 5 years or so despite a high number of IPOs (SPACs are partly to blame). You, obviously, have curve-fit the parameters quite a bit, I’d expect it perform much worse in real life but you know this already.

The strategy worked well in 2020 and 2021 (both years returned over 40%).

When we look at 2022, 2023, and 2024, the returns were below expected, but I don't know if that's because the alpha is gradually disappearing, as you mentioned, or if it is just because of a lower number of IPOs (as shown in the chart above).

The current # of IPOs is similar to what we saw in the aftermath of the 2008 crisis. Maybe the strategy will perform again once the # of IPOs comes back to the historical average... let's see...

 

[Slow Learning Elf]

The strategy worked well in 2020 and 2021 (both years returned over 40%).

It's a long-only strategy, so you want to think in terms of market-adjusted returns (which is especially true since everything rallied like crazy from the bottom of the COVID crash). Instead of doing outright returns, see what the the returns look like if you subtract performance of SPX for every day you carry a position (this would make it dollar-neutral returns, which is still pretty aggressive since all IPO stocks are high beta by definition).

 

[d08]

Define an IPO as any company recently listed (e.g., in the past 90 days);

Technically those wouldn't be just IPOs but new listings. Often from other markets, SPACs etc.

When we look at 2022, 2023, and 2024, the returns were below expected, but I don't know if that's because the alpha is gradually disappearing, as you mentioned, or if it is just because of a lower number of IPOs (as shown in the chart above).

Around late 2022 the IPO numbers severely dwindled.

What's good about these is there's an inherent filter - IPOs won't be filed or are withdrawn during bear markets. You'll notice it's very hard to find strategies that work on the short side on IPOs.
The problem with this strategy is that a lot the names have anemic volume and I didn't see any liquidity filter applied. Almost certainly with a filter the ROR goes down significantly.

 

[quantitativo]

Technically those wouldn't be just IPOs but new listings. Often from other markets, SPACs etc.



Around late 2022 the IPO numbers severely dwindled.

What's good about these is there's an inherent filter - IPOs won't be filed or are withdrawn during bear markets. You'll notice it's very hard to find strategies that work on the short side on IPOs.
The problem with this strategy is that a lot the names have anemic volume and I didn't see any liquidity filter applied. Almost certainly with a filter the ROR goes down significantly.

Oh, I applied a filter. We only trade mid-, large-, and mega-cap IPOs; we dont trade small-cap IPOs.

(I described all details in the write-up… this strategy is a bit more complex than the others… I didn’t put all the details here to not make the post too long…)

And I would love to be able to trade the short side of it as well. But it is impractical as you mentioned… so, I left it out…

 

[Maverick2608]

Is it a backtest? Are data free of survivorship bias?

 

[quantitativo]

Yes, this is a backtest using a survivorship bias free dataset (Nasdaq Sharadar Core US Equity Bundle)