“We define an economic – or competitive – moat as the ability of a portfolio company to create a product or service that is essential to their customer’s strategy or operations. An example of this might be a platform that is essential to capture, analyze and report customer usage data. There are companies like this – Veeva being an example – that are essential to life sciences drug development, promotion, and sales. This in turn generates extraordinary return on capital. Over time, you end up with a holding that is an essential part of their customer’s business that generates extraordinary profits. What’s not to like?”

                                                                                   -        Nintai Investments LLC 

What Makes A Quality Investment?
Over the course of my investment career, I’ve invested in roughly 250 companies. Holding times have ranged from 6 months to 12 years. All of them have met certain criteria which I’ve written about over the years - high returns on capital, equity, assets, high free cash flow margins, and low to no debt. But there are intangible qualities to each of these companies that might create competitive advantages that can’t be simply quantified though a set of ratios.  
 
Importance to Strategy and Operations
A key characteristic we look for at Nintai Investments is a company that produces products or services that are essential in assisting their customers carry out their strategies and operations. This might include everything from creative work (slogans, product jingoes) to building parts essential to making the product operate at peak efficiency. Simply put, their customers wouldn’t be nearly as successful without your portfolio company’s products and services.   
 
Replacement Difficulty
Another sign of quality is the difficulty of a customer in finding a replacement for that specific portfolio holding. An example of this is Fastenal (FAST). The company maintains thousands of vending machines and local shops that supply parts nearly instantaneously keeping manufacturing floor downtime to a minimum. Most companies simply don’t have the scope of product to meet those needs. 
 
Embedded Strength
Any company with a deep and wide moat should have relationship deeply embedded with their costumer’s senior management team. This means a strong web of corporate relationships, a deep sense of trust that the company can meet its promises and deliver product on time, and a long history of quality. These types of intangibles make it hard for any competitor to make inroads in terms of relationships with the customer.    
 
Industrial Expertise
Finally, the portfolio holding should have both a wide and deep knowledge of the industry of their customers. The company should be able to brain storm with middle to senior executives on problem solving potential issues from customer needs to plant operations. This type of knowledge allows a portfolio holding to not only build on existing product lines but develop new solutions unheard or unthought of previously.
 
A Working Example
 
A working example of how Nintai Investments evaluates both existing and potential investment holdings was the purchase of Veeva (VEEV) and Adobe (ADBE) during the market drops in December 2018. Both companies have Pfizer (PFE) as customers and we decided to evaluate the two holdings versus three different vendors who also work with Pfizer - Microsoft (MSFT), ICON Plc (a contract research organization or CRO), and Omnicom (an advertising agency). In Figure 1 is the summary report of the five companies and their respective ratings. 
 
This graphic is typical of the type of work that we generate during research at Nintai Investments LLC. It helps us understand where the strength – and weaknesses – lie with both a potential investment as well as other major vendors at key customers. The goal of course is to isolate the possible weaknesses in our investment case as well as test our knowledge of both a typical customer along with its market. We will generally test these graphics (and the associated ratings) with individuals in the customer we are evaluating (in this case Pfizer) as well as individuals we might know at the competitors listed.   

​In May 2018, Nintai Investments LLC completed an in-depth survey with Pfizer’s middle and senior level executives to discuss the importance the company perceived in two of our portfolio holdings - Veeva (VEEV) and Adobe (ADBE). We then matched these with three other vendors working with Pfizer. The intention of the research was to measure the strength of the intangible qualities of the companies’ moats. In other words, did Veeva and Adobe have stronger (or said differently - “deeper”) roots into their customer Pfizer. 
 
What We Found
 
Over time, Nintai Investments has spent an inordinate amount of time trying to better understand what makes a moat deeper, wider, and increasingly difficult to overcome. What we’ve come to think (and this in no way makes it true) is the previously mentioned intangibles - only found in deep industry and corporate knowledge - are the key components that drive long-term moat duration. Here’s why: 
      
Depth of Relationship Increases Returns
As a portfolio holding company offers an increasing number of products and services, the company should increase returns over time (see “New Markets are Less Capital Intensive” for more thoughts on this). Done successfully, these products and services embed the portfolio company deeper and deeper into their customers’ operations. For instance, Veeva began by offering customer relationship management software for sales and promotion. The company spread its products and services into research site operations, clinical data management, clinical operations, regulatory requirements, etc. As the number of offerings increase, their strength is magnified by their integrative capabilities. At this point, Veeva is so deeply embedded in life sciences it would be extraordinarily difficult to displace them.  
 
Industrial Knowledge Provides A Huge Edge
When a company like Veeva focuses on one particular market (in this case life sciences) and learns what makes the industry really tick (for instance reimbursement is more important that physician prescribing for some drug classes), a company can begin to really dominate a market and provide a great growth story. For instance, Veeva currently dominates Life Sciences CRM and has seen earnings growth of 50% and free cash flow growth of 60% over the past 5 years. Omnicom has no clear dominance in any market and has seen roughly 8% and 5% growth respectively over the same time period. Which company has a potentially greater growth story? Obviously nothing is written in stone, but my money currently is on Veeva.    
 
New Markets are Less Capital Intensive
When an investor looks at a Veeva or Adobe, it becomes apparent their strategy is to move into adjacent industries where capital outlays are limited by the existence of current products and similarities between industries. For instance, Veeva’s move into cosmetics makes sense in the fact the industry faces very similar operations as life sciences - design and testing of human-usage products, federal regulatory requirements, product safety, etc. The ability to remain asset and capital light in its research and development, product manufacturing, etc. continues to push margins and returns on capital higher. 
 
Conclusions
 
Finding an investment with high quality characteristics is both a numbers driven and industry/company specific process. Running a screen that gives you a list of companies with high returns on capital and equity, no debt, and high free cash flow margins is only 15 - 20% of the research process. The ability to define why and how a company achieves those numbers and how it can maintain them for the next two decades requires an enormous amount of contacts, industry journal reading, and interviews (both potential investment management, customers, industry leaders, etc.). At Nintai Investments, we believe we have enough knowledge in perhaps 50 - 75 companies and 2 - 3 industries to invest in over the next decade. Understanding the quality of those companies - both numbers wise and in a broader business sense can give you an edge that not many players on Wall Street can compete with over a 10 year period. 
 
As always, I look forward to your thoughts and comments. 
 
DISCOSURES: Nintai Investments owns positions in Veeva and Adobe in individual privately managed accounts. 
    

“The greater the fear, the greater the chance that correlations between different asset classes will begin to merge closer to 1. Overtime, this makes the investment universe less and less protected against risk. Theoretically, the correlation between corporate debt with a BBB rating issued by a company with a $10B in debt, $50M in cash, and negative free cash flow should be drastically different than corporate debt issued by a company with an AA credit rating, no debt, and high free cash margins. Yet in October 2008, we found over 50 cases where such disparate corporate debt traded at a nearly perfect 1.0 correlative factor. Go figure."           
                                                                             -     Simon R. Bellows

Asset correlation is a measure of how investments move in relation to one another and when those movements happen. When assets move in the same direction at the same time, they are considered to be highly correlated. When one asset tends to move up when the another goes down, the two assets are considered to be negatively correlated. Fidelity describes correlation from 100% to -100%. In their “The Pros Guide to Diversification” they state:

“Correlation is a number from -100% to 100% that is computed using historical returns. A correlation of 50% between two stocks, for example, means that in the past when the return on one stock was going up, then about 50% of the time they return on the other stock was going up, too. A correlation of -70% tells you that historically, 70% of the time they were moving in opposite directions—one stock was going up, and the other was going down. A correlation of 0 means that the returns of assets are completely uncorrelated. If two assets are considered to be non-correlated, the price movement of one asset has no effect on the price movement of the other asset. 

In a great article by Mark Maggiulli of Marker[1], he pointed out the difference between correlation of returns between assets during the credit asset market crash in 2008 - 2009 and the market crash in February - March 2020 brought on by the coronavirus. In the former crash (see Figure 1), the red lines show a positive correlation between the higher risk assets such as US stocks, international stocks, REITs, and emerging markets equities. Conversely, the blue lines show a negative correlation between lower risk assets (such as 20 year treasuries) versus the entire higher risk category of equites. In the coronavirus crash of 2020, it’s easy to see the nearly complete panic setting in as nearly every asset correlation showed a positive correlation with every other asset class (see Figure 2). 

​Figure 1: +/- Correlation Between Risky and Non-Risky Assets: Credit Asset Market Crash 2008-2009 Source: Marker.com

​Figure 2: + Correlation Between Risky and Non-Risky Assets: Corona Virus Market Crash 2020 Source: Marker.com

​What This Means
Two clear differences between the credit asset market crash in 2008 - 2009 and the coronavirus crash in February - March 2020 was both the speed in which the crashes took place and the drastic differences in correlations between “risky” and “safe” asset classes. 

Time and Correlation in the Credit Asset Market Crash
In the credit asset market collapse, the bear market took a series of cascading events that brought the market to its final lows. Events such as Bear Stearns’ collapse, Lehman Brothers’ bankruptcy, the AIG/Freddie and Fannie bail outs - all led to a slow draw down in the markets followed by a relatively classic recession. The only difference was the length and duration of the recovery with some industries disappearing entirely. However, unemployment peaked at roughly 10.5% or less than half of the Great Depression from 1929 - 1940. During this crash and ensuing recession, Figure 1 shows that there was both positive and negative correlations between asset classes. There was a positive correlation between risky assets (meaning domestic and US-stocks moved in a similar fashion (usually down!) but there was a negative correlation between higher risk (stocks, real estate, etc.) and lower risk assets (bonds, treasuries, etc.) As stocks went down, bonds remained flat or increased in value.
      
Time and Correlation in the Coronavirus Market Crash
The coronavirus crash was like nothing I’ve seen in my investing career. Compared to the credit asset market crash, the coronavirus crash exploded onto the world stage in roughly 60 days. By March 18th, the S&P 500 was down 27% YTD, the German DAX was down 38%, and the Japanese Nikkei was down 29%. These drops mostly happened in just 45 days or less. The credit markets came under enormous strain and even US Treasuries were sold in droves. In a mere month, the entire global economy seemed to have suffered a massive cardiac event. Combine this with a global pandemic that went from roughly 100 cases in January 2020 to over 4,000,000 by May 2020, with over 300,000 confirmed deaths worldwide and nearly 90,000 in the US by May 2020. Unemployment in the US jumped by roughly 30,000,000 cases in just 6 weeks reaching unemployment rates we haven’t seen since the Great Depression. The speed and scope of the crash was like nothing we’ve seen in nearly 90 years. Equally important - as Figure 2 shows - there was absolutely no place to hide (save cash) as nearly every asset cash’s correlation factor went to 1.    
 
Looking Forward
You often hear that investors get caught fighting the current war with the last war’s weapons. That was certainly the case in this year’s crash. While investors worried about asset prices, debt levels, and valuations (which all mattered), no one could possibly have guessed a global pandemic would close down the entire global economy and suddenly having us face a global depression. As always, I think there are several key takeaways from such debacles in the market place. 

Cash Will Always Be King. All Hail the King
During downturns like we saw in February, March, and April, cash is the only asset with liquidity, value, and stability that can save investors from truly awful losses. At Nintai Investments LLC, our average investment partner portfolio had somewhere between 15 – 30% of assets under management in cash. We didn’t have any special crystal ball which foresaw with a market crash or a global pandemic. Rather we saw nearly every asset class was (and still is) overvalued. This could mean only one thing – during a crash nearly every asset would be equally correlated to its neighbor – US stocks to emerging market stocks to global debt. Nearly every overpriced asset would see a dramatic drop in value – with the exception of cash.   

Panic Leads to Matching Correlation……..
When a real panic sets in – and a pandemic that effects 400,000,000 people, killing 313,000, and shuts down nearly the entire global economy – can create such a scenario, then you will see investors selling nearly every investment they can lay their hands on. Whether it be municipal bond mutual funds to triple leveraged oil futures funds, outright panic impacts everything from the credit markets, to the real estate market, to precious metals and other commodities. Figure 2 shows that the latest crash – combined with the economic cardio infarction – brings nearly every asset class into perfect correlative alignment.   

And Matching Correlations Provide no Hiding Place
I’ll be the first to admit that I’m very old fashioned when it comes to creating portfolios. I don’t like to try any type of new sexy “triple negative/positive absolute return exceptional fund” that nearly (but not always of course) states that you won’t lose money in such a fund. I’ve found that the more words in the name of a mutual fund the lesser chance an investor a.) understands the funds strategy or b.) it remotely hits its target returns over time. At Nintai Investments we tend to purchase only two 
things - publicly traded equities and a money market sweep account that holds assets as close to cash as possible. Very rarely do these two have positive correlations. Generally stocks either go up or down and the money market fund goes nowhere. In this model a generous percentage of our client AUM does nothing – it remains as an anchor preventing exorbitant losses (and exorbitant gains). This yin and yang of correlative values has allowed my portfolios at Nintai Partners and Nintai Investments to reap significant gains in market crashes. The past few months have been no different. If I lose several points to the upside while saving double digit losses on the downside, I am very comfortable with this model.     
 
Conclusions
The past quarter gave investors that rare insight when assets across the spectrum all near perfect correlation with each other. When this happens it mean one (or more) of several things. First, all assets are equally overvalued and the markets recognize them as such. Second, investors have reached a stage of complete and utter panic where they sell all assets regardless of type, their portfolio role, or their valuation. At Nintai Investments, we believe the sudden correlation of so many assets was a mix of both reasons. Investors have been part of a bull market that – with several exceptions – has seen markets (both equities and bonds) rise for nearly 10 straight years. In addition, in a very short three month period, the entire global economy collapsed under the weight of a novel coronavirus. Finally, many investors were fighting the last war looking for issues related to credit issues or real estate. 

​A rather simple lesson to learn from this recent crash has been to keep your portfolio design and selection as simple as possible. This doesn’t mean use only three index funds or two asset classes. But rather create a model that can easily adjust for rapid changes in the marketplace and the outside geopolitical and economic conditions. It might be as simple as moving 2% of your AUM into cash for every point above the markets’ fair value as calculated by Morningstar. Whatever you choose, make sure to keep it simple and that it allows you to sleep at night. 
 
As always, I look forward to your thoughts and comments 
DISCLOSURES: None

​[1] “How the Coronavirus Crash Is Different From the 2008 Financial Crisis”, Marker.com Mark Maggiulli, March 31, 2020. The article can be found here.