A simulation-based valuation of Alliance Data Systems Corporation (ADS): December 2020

Summary

- Alliance Data Systems Corporation (ADS) is a marketing and loyalty programs provider headquartered in Columbus, Ohio ().

- In this post we provide a simulation-based (sim-based) valuation () of ADS.

- Our results suggest the following fair values – stock price: $156.13, and price-to-earnings ratio: 18.16.

- ADS trades at $77 at the time of this writing, so it appears to be undervalued, with a potential upside of a little more than 100%.

Alliance Data Systems Corporation (ADS)

Alliance Data Systems Corporation (ADS) is a marketing and loyalty programs provider headquartered in Columbus, Ohio. Among other things, the company provides private label credit and debit cards, which allows them to also add value to their clients by developing and executing data-driven marketing initiatives. Recently ADS announced the upcoming acquisition of Bread, a digital payments company.

The company operates in two main segments: Card Services and LoyaltyOne. Card Services makes up about 80% of the company’s revenues; it involves transaction processing and customer collections services. LoyaltyOne generates approximately 20% of the revenues, and involves data-driven marketing initiatives. Financial services providers, grocers, drug stores, and specialty retailers are among the company’s main clients.

Estimating a fair value for the stock

In this post we provide a simulation-based (sim-based) valuation () of ADS.

At the time of this writing the company had a trailing twelve months price-to-earnings ratio of 11.63. The trailing twelve months price-to-cash flow ratio was 5.57. Earnings growth trends have been remarkably positive recently. We will set our sim-based estimated earnings growth rate for the next 5 years to be the group average, at 18.39% - to be somewhat conservative.

The table below summarize our sim-based results.

Since our sim-based analysis uses a S&P 500 return as a basis, our results summarized on the table above suggest the following fair values – stock price: $156.13, and price-to-earnings ratio: 18.16. ADS trades at about $77 at the time of this writing, so it appears to be undervalued, with a potential upside of a little more than 100%.

Final thoughts

Like many companies that extend credit to customers (e.g., car and equipment manufacturers), ADS is often presented as having a very high debt load. This can be misleading, because the company does not have to pay interest on debt that others owe to it. In fact, this type of debt generates a significant amount of interest income. The problem is the risk of default, which is countered by data-driven credit analyses prior to lending approval.

The expectation of growth in the short term is way above the group average of 18.39%. Still, the company is currently valued as if there will be little to no growth going forward. The reason for this is that some of the retailers that ADS works with are having serious problems, even though ADS also has partnerships with retailers that are doing quite well. With the synergistic acquisition of Bread, it is quite possible that ADS will experience above-average growth in the next 5 years.

Disclosure

The author owns ADS shares at the time of this writing.

Understanding the price of bitcoin: Data from early 2019 to mid-2020

Summary

- We conducted a multivariate analysis of the price of bitcoin with financial data from early 2019 to mid-2020.

- Our main conclusion is that bitcoin should do well in what we could call a “nervous bull market”.

- In this scenario, we would see the market generally going up, with some expectation of inflation in the future, all of this against a bearish backdrop.

The analysis

We used WarpPLS () to create several second-order indices (as composites of first-order index funds) and link them in an exploratory model to help us understand what has been driving the price of bitcoin from early 2019 to mid-2020.

The period from early 2019 to mid-2020 was used because prior to it bitcoin was generally perceived as a cash-like currency that could be used for day-to-day transactions among individuals and organizations. From early 2019 onwards, the perception shifted to one of a store of value; something akin to “digital gold”.

We collected and analyzed daily data from various funds. More specifically, the price of one share of each fund at each day’s close was used. In terms of WarpPLS settings, the outer model analysis algorithm used was “PLS Regression”, and the default inner model analysis algorithm was “Linear”. The composite variables were made up of the following funds.

- FIN, reflecting a bullish view of financial institutions, was made up of the iShares U.S. Regional Banks ETF (IAT), and the Financial Select Sector SPDR Fund (XLF).

- HDG, reflecting a bearish view of the market (intention to hedge), was made up of the iShares Silver Trust (SLV), the SPDR Gold Shares (GLD), and the iShares 20+ Year Treasury Bond ETF (TLT).

- MKT, reflecting a bullish view of the market, was made up of the SPDR S&P 500 ETF Trust (SPY), and the Invesco QQQ Trust (QQQ).

- GBTC, reflecting the price of bitcoin, was measured through a single indicator, namely the Grayscale Bitcoin Trust (GBTC).

The Grayscale Bitcoin Trust (GBTC) provides one of the most straightforward ways for investors to own bitcoin. It is generally available to retail investors through various online brokers.

The results

The figure below shows our model with the main results. The iGBTC variable is an instrumental variable that controls for the effect of “time” on the results; to account for autoregression, or the fact that the variable GBTC is influenced by its own values back in time. The instrument used was a numeric variable generated based on the date associated with each data point. In a previous analysis published on this blog, based on the same data, we did not employ this type of control, which led to slightly different results.

The path coefficients (indicated as beta coefficients) reflect the strength of the relationships; they are a bit like standard univariate (or Pearson) correlation coefficients, except that they take into consideration multivariate relationships (they control for competing effects). A positive beta means that an increase in a variable is associated with an increase in the variable that it points to.

The P values indicate the statistical significance of the relationship; a P lower than 0.05 means a significant relationship (95 percent or higher likelihood that the relationship is “real”). The R-squared value reflects the percentage of explained variance for the variable in question; the higher it is, the better the model fit with the data.

I should note that the P values have been calculated using a nonparametric technique, which does not require the assumption that the data is normally distributed to be met. This is good, because I checked the data, and it does not look like it is normally distributed. 

So, what does the model above tell us? It tells us that: 

- As a bullish view of financial institutions (FIN) increases, the price of bitcoin (GBTC) also increases, in a statistically significant way (beta=0.13; P below .01). This is not normally what one would expect, if we assume that bitcoin’s success means the failure of financial institutions.

- As a bearish view of the market (HDG) increases, the price of bitcoin (GBTC) also increases, in a statistically significant way (beta=0.42; P below .01). This is what one would expect, if we assume that bitcoin is used as a hedge against a drop in the market. Note that this effect is the strongest in the model, by far.

- As a bullish view of the market (MKT) increases, the price of bitcoin (GBTC) also increases, in a statistically significant way (beta=0.17; P below .01). Again, this is not normally what one would expect, if we assume that bitcoin’s success means that a bear market is under way.

The three predictors above (i.e., FIN, HDG, and MKT) explain 33 percent of the variance in the variable GBTC (R-squared=0.33). This essentially means that the model is incomplete, although it does explain enough of the variance in GBTC to be useful in an exploration of major influences on the price of bitcoin.

Main conclusion

While the results above may look contradictory, they in fact suggest that bitcoin should do well in what we could call a “nervous bull market”. Here we would see the market generally going up, with some expectation of inflation in the future (which tends to be good for financials), all of this against a generally bearish backdrop.

Disclosure

The author does not own bitcoin at the time of this writing.

Does yield curve flattening hurt US bank stocks?

Summary

- US banks derive part of their income from borrowing funds and investing them, with interest rates paid and earned being correlated with the short and long ends of the Treasuries yield curve.

- Since the short end yields (for Treasuries) tend to be lower than the long end yields, usually US banks benefit financially from the difference.

- Given this, one would expect bank stocks to be strongly and positively correlated with yield curve steepening; i.e., the opposite of flattening.

- If we look at data from the past 5 years, however, the opposite has happened. As the yield curve has flattened, bank stocks have gone up.

Yield curve flattening and US bank stocks

US banks derive part of their income from borrowing funds and investing them, with interest rates paid and earned by the banks being correlated with the short and long end of the yield curve. Since the short end yields (for Treasuries) tend to be lower than the long end yields, usually US banks benefit from the difference. Given this, one would expect bank stocks to be strongly and positively correlated with yield curve steepening; i.e., the opposite of flattening.

The figure below shows, at the top, the difference in yields for 10-year and 3-month Treasuries for the past 5 years. The two graphs at the bottom show the stock prices for two banks: JPMorgan Chase, representing multinational investment banks; and U.S. Bancorp, representing regional banks. The sources for the graphs are Yahoo Finance and the US Federal Reserve Economic Data (FRED) (, ).

As you can see, prior to COVID there seems indeed to be a correlation between US bank stocks and yield curve flattening. However, it is the opposite of what we would expect. The correlation is negative. As the curve flattens, bank stocks go up. In other words, US banks tend to do well in response to what could be seen as a major obstacle to profitability.

What is happening? Compensatory adaptation

As the yield curve flattens, US banks react in a compensatory way – e.g., by resorting to other sources of income. This is compensatory adaption theory at work (, ).

Compensatory adaptation of this type is facilitated by the size and flexibility of the US economy. This makes the environment in which US banks operate significantly different from those of Japan and Europe, where arguably banks have fared worse.

Cold weather and COVID: Compensatory adaptation may lead to unexpected results

Summary

- If COVID cases necessarily spike in cold weather, it would be reasonable to expect more lockdowns in countries, like the US, which are about to transition from warm to cold weather.

- These lockdowns would presumably have a negative economic effect, and likely a severe negative effect on equity prices.

- This post looks at data from Brazil and the US, and concludes that COVID infections may not be significantly influenced by the weather.

- The reason may be a compensatory adaption feedback loop – people adapt in a compensatory way.

- In fact, if compensatory adaptation theory is any guide, it would not be surprising to see COVID infections actually go down, as a country with growing COVID infections transitions from warm to cold weather.

Do COVID cases spike in cold weather?

If COVID cases necessarily spike in cold weather, it would be reasonable to expect more lockdowns in countries, like the US, which are about to transition from warm to cold weather. These lockdowns would have a negative economic effect, and likely a severe negative effect on equity prices. But is it inevitable that COVID cases spike in cold weather?

To answer this question, it may be instructive to look at COVID figures for Brazil and the US, because these two countries have had similar responses to the pandemic (); and have opposite weather patterns – when it is hot in the US, it is cold in Brazil, and vice-versa. This applies particularly to the most populous areas of the two countries.

COVID figures for Brazil and the US

At the time of this writing, we had the following approximate numbers for Brazil and the US. Brazil – population: 209.5 million, COVID cases: 4.12 million, and COVID deaths: 126 thousand. US – population: 328.2 million, COVID cases: 6.26 million, and COVID deaths: 188 thousand. The two graphs below show the two following ratios: cases-to-population, and deaths-to-population.

The ratios are too close to support the “spike hypothesis”

In the last several months since the pandemic hit both countries, it has been generally cold in Brazil and hot in the US. Given this, these ratios are too close to support the assumption that COVID cases spike in cold weather. So, what would be a reasonable answer to the question posed earlier: do COVID cases spike in cold weather? The answer is: probably not.

What is happening? Compensatory adaptation

This brings to mind another question: would indoor activities, such as restaurant dining and movie theater attendance, lead to spikes in COVID cases?

Well, the idea was that cold weather would lead to more indoor activities ...

While risk of infection may go up with cold weather and more indoor activities, people react in a compensatory way – e.g., by wearing masks, resorting to social distancing etc. This is compensatory adaption theory at work (,). This feedback loop may lead to unexpected results.

If we use compensatory adaptation theory as a guide here, it would not be surprising if COVID infections were to go down, as a country with growing COVID infections transitions from warm to cold weather.

Interest rates and PE ratio expansion: S&P 500 going above 4100 before the end of 2020?

Summary

- Most professional investors see price/earnings (PE) ratios as inversely proportional to interest rates.

- Mathematically, this would be expressed as: PE = k / IR.

- Assuming that the interest rate on 10-year Treasuries could rise to 1%, and the k multiplier to rise to the pre-COVID level of 0.39, the expected S&P 500 PE ratio would then be 38.66.

- This would bring the S&P 500 up to 4,148. Still, not as expensive, in PE ratio terms, as in either the 2000s dot-com bubble or the Great Recession.

Interest rates and PE ratios

Most professional investors, including the late Benjamin Graham (), see PE ratios as inversely proportional to interest rates for Treasuries. Mathematically, this would be expressed as follows, where PE = the PE ratio of an equity security, IR = a relevant interest rate, and k = a multiplier.

PE = k / IR

There are a couple of key reasons for this relationship. One is that Treasuries become less attractive as an investment when interest rates go down. Since the Treasuries market is very large, a little over $21 trillion at the time of this writing, even a fraction of it moving to equities would push their PE ratios up significant.

Another key reason for the relationship above is that investing in Treasuries when interest rates are low becomes risky in terms of principal preservation. Treasury prices are inversely related to the interest they pay, or their yields. When yields are very low, the tendency is for them to go up.

Interest rates on 10-year Treasuries

The figure below shows the interest rates for the 10-year Treasury notes from January 2007 to July 2020. Those rates, which influence a number of other consumer-relevant rates (e.g., those for mortgages), go from 4.76% to 0.55% during the period.

While the interest rates have been going down over the years, they went up significantly during the recovery from the Great Recession. The same may happen during the recovery from the COVID recession. A move from 0.55% to 1% would be significant.

S&P 500 PE ratios

The figure below shows the PE ratios for the S&P 500 from January 2007 to July 2020. Note that the PE ratio for July 2020 is nowhere near the peak during the Great Recession.

The k multipliers

Finally, the figure below shows the k multipliers for the relationship between the S&P 500 PE ratios and interest rates on 10-year Treasuries from January 2007 to July 2020. An all-time low was reached for the multiplier in July 2020.

In a low interest rate environment, a high k multiplier would typically be associated with a high PE ratio. The multiplier increase, if it happens, should lag the interest rate reduction. Investors need time to be convinced that interest rates will remain subdued. 

S&P 500 above 4,100 soon?

Assuming that the interest rate on 10-year Treasuries could rise to 1%, and the k multiplier to rise to the pre-COVID level of 0.39 (which is below its historical average), the expected S&P 500 PE ratio would then be 38.66. This would bring the S&P 500 up to 4,148. Still, not as expensive, in PE ratio terms, as in either the 2000s dot-com bubble or the Great Recession.

This PE ratio expansion for the S&P 500 is already happening at the time of this writing, with the S&P 500 hitting an all-time high. Our main point in this post is that, if interest rates on Treasuries remain low, we may see more of that - even with bankruptcies among small businesses, significant  unemployment, and high volatility (including downward corrections).

The business media is missing this: The rise of the immune

Summary

- The fastest growing “demographic” in the world today are those who are immune to COVID-19.

- This is bullish for equities, because those who are immune to COVID-19 are likely less hindered as consumers than those who are not.

- The equities that should benefit the most are those for companies at the epicenter of the pandemic.

- Why is the non-immune view the prevalent one in the business media? Probably because of the average age of those speaking and writing.

- The rising immune population so far is predominantly young.

The fastest growing demographic

The fastest growing “demographic” in the world today are those who are immune to COVID-19. At the time of this writing, there were 3.3 million confirmed cases in the US alone. Assuming that the actual cases are around 10 times the confirmed cases, we have 33 million cases in US.

If we consider the death rate to be 1 percent, this means that we will have about 30 million people with immunity to COVID-19 in the US very soon. Many are already immune. Even without a vaccine and some mitigation (e.g., masks), by the end of the year the number of immune people in the US could be 100 million. In the world, this number could be 500 million.

People want the immune around them

Herd immunity is seen as a desirable goal because of the idea that the immune form a protective barrier around the non-immune (). In this sense, immune people are a better barrier than social distance. For example, if you have an immune person in between two non-immune people, that may be better than six feet of empty space. The immune person is much more lethal to the virus.

High-risk individuals, such as the elderly, are advised to isolate themselves. However, social and physical isolation could negatively affect their health in various ways unrelated to COVID-19. The real problem is interaction with the non-immune, because of the risk of infection. Interaction with the immune is fine. Maybe more than fine, because of the benefits of social interaction, not to mention needed care. People will want the immune around them.

Media naturalness theory

With current commercial technology, virtual meetings are simply not a viable alternative for a species that evolved over millions of years communicating face-to-face. The naturalness of a communication medium (i.e., how similar it is to the face-to-face medium) leads to a number of effects. For example, low naturalness reduces physiological arousal. Also, low naturalness leads to more confusion, particularly when knowledge is being communicated ().

So, face-to-face meetings will be needed, particularly when knowledge-intensive tasks must be carried out. Imagine a non-immune person being asked to attend a face-to-face meeting with 5 other people, all using masks. Would that person like the idea of the meeting more if she knows that all of the 5 other people are immune? Probably yes. Maybe not 5, but 3. The more the better. Again, people will want the immune around them.

Businesses will want the immune

Airlines are being asked to keep middle seats empty. Imagine you getting on an airplane and going to your window seat, just to find out that someone is sitting next to you, in the middle seat. You do not like it, even though the person is wearing a mask. He tells you that he is immune, and shows you the results of an immunity test. Will that make you feel better? Probably yes.

Companies that are at the epicenter of the pandemic are airlines, bars, restaurants, amusement parks, and ride-sharing companies. All of these companies have a strong incentive to have the immune as their employees, partners, and customers. Would a non-immune person favor a bar where most customers are immune? Probably yes.

Is this bullish for equities? If yes, what equities?

Arguably this is bullish for equities, because those who are immune to COVID-19 will probably be less hindered as consumers than those who are not. It stands to reason that the equities that should benefit the most from this are those for companies at the epicenter of the pandemic. Essentially, the ones that suffered the most so far.

Virtually all of the discussion in the business media nowadays is from the standpoint of the non-immune. One hears things like: “… the consumer will be cautious going forward … the risk of infection …”, “… parks will never have the same sales again …”, “… the economy will never be the same …” etc. Think about these statements assuming that you are immune – they make little sense.

And the numbers of the immune are growing fast, even without a vaccine. They will grow a lot faster with one or more effective vaccines. Also, keep in mind that the immune are not only consumers themselves, but also enablers of consumption. For the economic recovery, they are worth their weight in gold!

Why is the non-immune view the prevalent one in the business media? This may be due to the average age of those speaking and writing.

The rising immune population now is predominantly young.

How could the March-June 2020 stock market rally have happened if $1T moved to the sidelines?

Summary

- As the rally in the S&P 500 happened, approximately $1T of money moved to the “sidelines”; that is, into money market funds.

- Of that $1T, about 20% was from retail investors and 80% from institutional investors.

- This is not what we have seen in previous recessions. Normally when money moves to the sidelines the S&P 500 goes down.

- One could argue that the money that is on the sidelines would be coming in to take advantage of pullbacks, as the new money that came in earlier is taken out to fuel consumption. Some of these pullbacks could be severe.

The March-June 2020 rally in the S&P 500

The figure below shows the rally in the S&P 500 during the March-June 2020 period. The index has gone from approximately 2,237 to 3,055; up about 36%.

We used the charting feature of Yahoo Finance (). The slow-moving line is the 52-day moving average.

About $1T moved to the sidelines

As the rally in the S&P 500 happened, approximately $1T of money moved to the “sidelines”; that is, into money market funds. This is illustrated by the figure below, with charts from FRED (). Of that $1T, about 20% was from retail investors and 80% from institutional investors.

The top chart shows the growth in money market funds from retail investors. For example, if an individual investor with an account on E-Trade (i.e., a “retail” investor) sells a stock position, that money typically will go into a sweep account tied to a money market fund. The bottom chart shows the growth in money market funds from institutional investors.

So, both retail and institutional investors moved a lot of money to the sidelines. This is not what we have seen in previous recessions. Normally when money moves to the sidelines the S&P 500 goes down.

Many people would interpret this as money leaving the financial markets, in absolute terms. This is not what happened. For each stock sale there must be a corresponding purchase. If investors on the sidelines are buying, and sellers are moving to the sidelines, there should be no significant change the in the total amount held by money market funds.

If investors are selling to raise cash, and stock prices are going up, there must be “new” money coming into the stock market at a higher rate than the rate at which investors are selling.

The Fed’s balance sheet grew by $2T during the rally

As you can see in the figure below, the Fed’s balance sheet grew by about $2T during the rally. It grew $3T from February. That is partly what fueled the rally.

This new money that has been “created” by the Fed takes some time to make its way into the hands of people who can buy stocks. So, what we are seeing here is the beginning of something interesting; a rather rare occurrence.

What does this mean? The bull case

One could argue that the money that is on the sidelines would be coming in to take advantage of pullbacks, as the new money that came in earlier is taken out to fuel consumption. Some of these pullbacks could be severe, because newcomers may be parking money in stocks as they would with a bank account - with money that they need to pay for recurring expenses.

This should propel the stock market higher after each pullback. The increase in consumption caused by the money coming out of the stock market may give the impression that the economy is recovering by itself. The ensuing optimism would push stocks even higher.

But the impression that the economy is recovering would be a mirage, at least early on. This highly volatile bull market would be largely driven by the liquidity injected by the Fed. The volatility would be triggered by mixed headlines; e.g., consumer confidence is up, but so is the government deficit.

We could see something like the S&P 500 reaching 4,000 amid a wave of bankruptcies! Not all companies will go bankrupt, of course. For each local “Supa Burger” that goes bankrupt, there will be a bit more market share for the local McDonald’s and Burger King competitors.

Active investing may shine brighter than passive (index funds) in this scenario. Active investors have to think about a number of issues, such as how failures in one industry can benefit leaders in another. As a Hertz goes bankrupt, Uber may benefit. (Disclosure: the author owns shares of UBER at the time of this writing; and also of MCD and QSR, for the references above.)

What does this mean? The bear case

It is hard to see a scenario where this new money printed by the Fed, the portion available for stock purchases, will all go to the sidelines due to pessimism. Money market accounts are paying very little, because Treasury yields are so low. Investors are compelled to put the money somewhere. The stock market is one of the only options.

It is not hard to see a scenario where inflation will grow due to an increase in money supply, even as GDP contracts. Inflation is bad for fixed-income investing, making Treasuries even less attractive, but inflation is not necessarily bad for stock investing. At least not while inflation is growing but is still relatively low (e.g., low single digits).

This creates a positive feedback loop for stocks!

However, this is a bad scenario if maintained for too long, which could bring about severe economic strain, and another major drop in the stock market. High inflation would eventually prompt the Fed to increase interest rates, without a robust economy to compensate for that tightening if GDP is contracting.

But this bad scenario may take a few years to materialize.