# Safe Haven: Investing for financial storms by Mark Spitznagel | Full summary

How many times have you heard the phrase:

**"Higher returns can only be achieved by taking higher risks." **

This is a common belief in the world of investing.

Mark Spitznagel, however, thinks it is a myth. His investment firm, Universa, proves it, outperforming the S&P 500 by over 3% on an annualized net basis thanks to his different approach.

In fact, he believes that to achieve higher returns; **Instead of taking higher risks, investors must reduce their risks**. But how? By adding Safe Havens to their portfolios.

As he explains in his book, "Safe Haven: Investing for financial storms."

*"A safe haven isn't so much a thing or an asset. It is a payoff, one that can take many different forms. It might be a chunk of metal, a stock selection criterion, a cryptocurrency, or even a derivatives portfolio. Whatever forms they may take, it is their function that makes safe havens what they are: They preserve and protect your capital. They are a shelter from financial storms."*

**Why is it crucial to limit losses?**

Before exploring the different types of safe havens, we must understand how adding the right risk-mitigation strategies can deliver higher portfolio returns over time.

To explain this concept, Mark uses the analogy of the St Petersburg Merchant.

The Merchant bought some commodities in Amsterdam for 8,000 rubles, and he wished to ship them over to St Petersburg and sell them there for 10,000 rubles.

Unfortunately, the Baltic sea is infested with pirates, which on average, seize 5% of the shipments from Amsterdam to St Petersburg. The smart merchant thinks that some risk mitigation may be useful and looks to insure his cargo.

The best price he finds for insuring the whole 10,000 rubles cargo is 800 rubles.

Since he is a smart merchant, he takes out some paper and starts doing the math.

Over the course of 100 shipments, he would end up paying the insurance company 80,000 rubles.

Total insurance payments: 100 trips * 800 rubles/trip = 80,000 rubles

However, the insurance company is expected to pay in claims only 50,000 rubles.

Total claims: 5 * 10,000 rubles (value of the shipment) = 50,000 rubles

So he calculates that the insurance company would be profiting 30,000 rubles off of him or about 300 rubles per shipment.

**So what should the merchant do? **

The answer lies in the difference between __Arithmetic and Geometric Mean.__

Now, before you panic, thinking that we are going to need some super complicated math skills, relax. I'll make sure to keep it simple.

Let's assume the following things:

The merchant has an initial net worth of 10,000 rubles, and he decides to keep 20% as savings and use 80% to purchase commodities in Amsterdam.

Once the commodities arrive in St Petersburg, they can be sold for 10,000 rubles.

So at the end of the shipment, his initial net worth would grow from 10,000 rubles (2k savings + 8k spent on goods) to 12,000 rubles (2k in savings + 10k earned in St Petersburg). Which is a return of 20%.

If the pirates seized the shipment, he would lose the 8,000 rubles worth of commodities, and therefore, his net worth would lose 80%.

Additionally, we assume a total of 100 trips; of these, five get seized by pirates.

The cost to insure each trip is 800 rubles.

And finally, we assume that at the end of each shipment, the merchant will always save 20% of his total net worth and reinvest in commodities the remaining 80%.

Now that we have our assumptions let's calculate the Arithmetic average return of both the uninsured and insured strategies.

__UNINSURED:__

In the uninsured scenario, he will achieve a 20% return on 95 trips and a negative 80% return on five trips, resulting in an average return of 15%

average return: ((20% * 95) + (-80% * 5))/100 = 15%

__INSURED: __

In the Insured case, it's much easier to calculate since, each time, the return is the same, and it's 12%.

Average return: (2,000 savings + 10,000 goods sold - 800 insurance) /(10,000 initial net worth) = 11,200 / 10,000 = 1.12 = 12%

So we can clearly see that the arithmetic cost of insuring the goods is 3%, which may lead the merchant to opt for the uninsured strategy.

But there is a big problem that often, even experienced investors tend to forget.

Einstein called it the 8th wonder of the world, but investors should call it the deadliest double-edged sword. We will call it the exponential sword.

**It's the compounding effect.** And it works both ways. After our merchant loses 80% of his net worth, he needs a 400% return just to break even.

Here you can see the returns needed to break even after a certain percentage loss. As you can see, the compounding effect can be very deadly.

As with everything that compounds, it starts slowly, and then it jumps exponentially.

A 1% loss requires only a 1.01% gain to break even. A 10% loss requires an 11.11% gain. A 20% loss requires a 25% gain. a 50% loss requires a 100% gain. And a 95% loss requires a 1900% gain.

Now you probably understand better the famous saying, "At first, you go bankrupt slowly, then all at once."

Unfortunately, most investors focus only on returns, while they should first focus on limiting the losses.

As Warren Buffet famously says, "Rule No 1 of investing is: Never lose money. And Rule No. 2 is: Never forget rule No. 1."

Or, as George Soros said, “It's not whether you're right or wrong, but how much money you make when you're right and how much you lose when you're wrong.”

Going back to our merchant,__ in this excel file__, I have plotted the results of 100 uninsured trips. On 95 of them he makes a 20% return, and in 5 out of 100 times, he loses 80% of his net worth.

After 100 trips, his net worth grows to about 106 million rubles.

Now I want to ask you a question: would his ending net worth be lower or higher if the negative 80% losses were all during the first ten trips, or during the last ten trips?

And the answer may shock some of you. His ending net worth will always be about 106 million rubles regardless of when the losses happen.

Which means that all losses count forever. It doesn't matter if you suffer a 20% drawdown now or ten years from now. Your ending wealth will be impacted in the same exact way. And that's why Mark argues that it is crucial to implement risk mitigation strategies.

And to prove it, let's look at the insured scenario. Even though his arithmetical average return is lower by 3% than the uninsured scenario, since the merchant never suffers the cut from the exponential sword, his ending wealth grows to about 835 million rubles. He becomes eight times richer while experiencing less volatility.

We have now proven that the Merchant shouldn't rely on the arithmetic average alone in order to make the best decision. So what should he do instead?

And that's where the geometrical average is needed. It accounts for the effects of compounding, and it gives us the true average compounded return.

The formula is slightly more complicated. If you don't understand it fully, just trust me on the math here, and then __I'll give you a link to a simple video that explains it in detail. __

First, let's calculate the geometrical average of the uninsured scenario.

He achieves a 20% return, which can be expressed as 1.2, in 95 trips.

In 5 trips, however, he loses 80%, which can be expressed as 0.2. We then elevate it to the power of 1 divided by 100 because there is a total of 100 trips. Finally, we subtract one from the results. It gives us 0.097, which can be expressed as 9.7%

So we now know that the geometrical average return for each uninsured trip is 9.7%. That is the compounded growth rate at which our merchant can expect to grow his wealth over time.

And as you can see, it is already far lower than the arithmetic average, which was 15%.

Now let's calculate the geometric average of the insured scenario.

He achieves a 12% return on all 100 trips, which can be expressed

as 1.12 to the power of 100. As we did earlier, we elevate it to the power of 1 divided by 100 trips, and then we subtract one. It gives us 0.12, which can be expressed as 12%.

So, the geometrical average, in this case, is 12%, which shouldn't surprise you since the return was the same for each trip.

And it is far better than the 9.7% geometrical average of the uninsured trip.

If you have followed me so far, you have already discovered the most important secret behind safe havens.

As Mark explains, despite having an arithmetic cost, safe havens have a positive geometric effect on the Portfolio. Therefore improving the compounded annual growth.

In the case of the St Petersburg merchant, despite having a 3% arithmetic cost, the insurance had a positive 2.3% geometric effect on the portfolio. Therefore the insurance was a true safe haven for the merchant.

Now that we have understood the importance of limiting losses and the fundamental difference between arithmetic and geometric averages, we can explore the world of safe havens

**What is a safe haven?**

As Mark says in his book:

*"A safe haven isn't so much a thing or an asset. It is a payoff, one that can take many different forms. It might be a chunk of metal, a stock selection criterion, a cryptocurrency, or even a derivatives portfolio. Whatever forms they may take, it is their function that makes safe havens what they are: They preserve and protect your capital. They are a shelter from financial storms."*

Said differently, safe havens shelter you from the big cuts of the exponential sword. Allowing you to compound your wealth safer and at a higher rate over time.

The goal of safe haven investing should be to reduce the costliness of risk—specifically the costliness of losses—and do so in a way that does not end up costing us even more. In other words, we need a cure that is not worse than the disease. Therefore risk mitigation must be cost-effective.

On this premise, Mark defines a simple condition for safe havens.

If adding a strategy to a portfolio, raises the CAGR over time (so it has a positive geometric effect), then the strategy is mitigating risk cost-effectively. The strategy is, therefore, a safe haven.

If, however, adding a strategy doesn't raise the portfolio's CAGR over time (so it has a negative geometric effect), Then it does not cost‐effectively mitigate the portfolio's risk. Therefore the strategy is not a safe haven.

**Three types of safe havens: **

Armed with this simple condition, we can now explore the world of safe havens.

Mark identifies three types of safe havens.

The first type is the "store-of-value" safe haven which is meant to provide a fixed return over time and is not highly sensitive to systematic risks.

It can provide a cushion and "dry powder" in the event of a crash.

Store-of-value safe havens allow investors to dilute the risk.

An example could be short-term treasury bills, which provide a safe, guaranteed return and can act as useful liquidity in the event of a market crash.

The second type is the Alpha safe haven. It is similar to the store-of-value payoff but is expected to have a negative correlation and generate a greater positive return during a crash, similar to a flight-to-quality scenario.

The US dollar, the Swiss Franc, and gold could be examples of Alpha safe havens. They tend to have a negative correlation to the stock market, and investors usually buy them during crises.

Finally, the third type is the insurance safe haven. It is the most extreme type of safe haven and is highly convex to crashes, meaning it generates a large profit in the event of a crash relative to its small expected losses the rest of the time. It is described as an explosive payout in return for an insurance premium.

An example could be a put option, which loses money when the market is flat or trending upwards but has an exponential payoff in the event of a crash.

The St. Petersburg merchant was effectively using an insurance safe haven, which lost him 800 rubles for each successful trip but paid him back the whole 10,000 rubles when the Pirates seized his ship.

Apart from these three types of safe havens, Mark also identifies three safe haven imposters.

The first one is the hopeful safe haven. Something that might protect you or not during a crash. Mark uses the metaphor of a parachute that sometimes deploys and sometimes it doesn't.

An example could be long-term treasury bonds. While during many past bear markets, long-term treasuries have acted as safe havens, they don't always protect investors. Just look at how badly TLT performed during 2022.

Investors fall into the hopeful haven trap based on the presumption that the next crash will have similar characteristics and internal market relationships (or “cross‐correlations”) to past crashes. However, the next crash rarely does—or it does just enough to catch those committing the retrospective safe haven fallacy in its trap.

The second impostor is the unsafe haven. Mark describes it as:

*"An asset or strategy that has so far always gone up, so it likely has a good story for why that should always be the case. The logic is then extended to their performance in a crash. But they are often as vulnerable in a crash (or even more so) as that which they are intended to protect. Perhaps they have even shown some evidence of that vulnerability. But that doesn't change the optimism around their presumed safe haven status. This complacency—particularly around their use as risk mitigation—is most unsafe. (To continue the metaphor, an unsafe haven is like jumping out of an airplane with the conviction that you can fly)."*

And the third impostor is the most common. The diworsifier haven is an investment strategy named after Peter Lynch's concept of diworsification. It involves filling a portfolio with assets that don't move in the same direction, in order to lower portfolio volatility and have a better performance during a crash. However, this diversification comes at the cost of underperformance during non-crash periods, and over time it ends up costing more than it saves.

As we said earlier, safe havens must improve the portfolio CAGR over time. The Diworsifier haven is the perfect example of a cure that is worst than the disease.

Mark calls diworsification "a confession that investors don't care about cost‐effectiveness in their risk mitigation. They just want less risk, no matter the cost."

**Universa risk-mitigation strategy:**

In the last part of the book, Mark goes on to analyze the most common assets used in risk-mitigation strategies.

His focus is to find an asset or strategy that, with the smallest arithmetic cost, can have a positive geometric effect on the portfolio. Therefore improving the CAGR over time.

His study finds that, historically, an allocation to 3-month treasury bills, 10-year treasury bonds, or 20-year treasury bonds, doesn't improve the CAGR over time. And so he dismisses these assets as potential safe havens.

The only two safe havens that come out of his study are gold and the insurance-type payoff.

However, he then analyses gold using different time frames, and concludes by saying:

*"When inflation was higher in the 1970s, gold's payoff profile made it very cost effective as a safe haven protecting against crashes. Outside of that, gold has been much less cost-effective. Gold has required a tactical call regarding these regimes— be they inflation, or real rates regimes—in order to be a cost effective safe haven.*

*It means that we need certain things to go right for gold to even be effective in mitigating systematic risk (of a crash). And this is an internal contradiction, and a problem for gold as a strategic safe haven."*

So what safe haven has Mark implemented to allow Universa to outperform the S&P 500 consistently over the years?

While we can't know for sure, it appears that Mark uses a strategy that involves buying several put options that act as insurance during market crashes.

Unfortunately, he doesn't disclose his strategy in the book, and for the average investor who doesn't understand volatility and time decay, buying put options can be risky and damaging to the overall portfolio.

As Mark states at the beginning of the book:

*"This is not a “how-to” book, but it is a “why-to” as well as a “why-not-to” book. If the only things readers get out of this book are a more realistic and rational premise of safe haven investing and a foundation from which to assess and tackle it—and thus avoid its traps—then the book will have achieved its purpose"*

**I hope you have enjoyed my review summary.**

I think every investor should read this book and use it as a starting base in their quest to grow their wealth over time.

__Here you can find the link to purchase the book on Amazon __