Permanent open market operations (POMO)

When the US stock market began to fall in the spring of 2020, the Federal Reserve (FED) announced a stimulus plan of about 2.3 trillion dollars. The press called it a “liquidity injection from the Fed.” Interesting concept, money injection.

But how is liquidity injected into the market? How is all this executed?

Permanent Open Market Operations (POMO)

POMO refers to when the Fed (or any central bank) constantly uses the open market to buy and sell securities in order to adjust the money supply. All these operations go to a portfolio called: “system open market account” (SOMA), which is, in a nutshell, the FED’s portfolio.

This mechanism and these practices have existed for decades, but depending on the moment they become more noticeable or invisible.

When does the Fed buy?

I do not know knows, at least I have not found out, what the FED buys, that is if there is a calendar of purchase days and the estimated quantities that the FED intends to put into circulation. The calendar looks like this:

It is important to understand how much positions they open and finally how much are completed (since not all trades are ccompleted). On this page you can see the data of operations launched and executed:

Several purchases a day

As can be seen in the image below, the situation may arise that there are several shopping packages per day, such as May 27, 2020. During the worse days of the market they were opening 6 or 7 packs of operations per day.

What is happening this spring / summer of 2020?

Well, a lot is happening, but focusing on POMOs, what is happening is that there are many people looking at this data and operating based on these money flows (considered “free” by some specialists).

The general opinion is that there is a correlation between the money that is put into circulation by the FED (the daily injection). With this, on the day before a liquidity injection there are people who operate in certain values ​​seeking the rise of the day of the “big injection”. How do they operate and what do they operate on? … well, I don’t know.

I am trying to get data and draw it to understand if this correlation exists or is a simple bias.

This graph is the only interesting one I found but it is from previous years:

FED money to major traders relative to S&P 500

FED money to major traders relative to S&P 500

Regarding 2020, the only graph I found is this, which doesn’t tell me much:

FED daily purchases August / 2019 - May / 2020

FED daily purchases August / 2019 – May / 2020

 

All this “free” money plugged into the market has made many rich, and at a time when COVID-19 has been affecting the economy in very significant ways, Wall Street is doing its own particular August.

This vignette summarizes very well what has happened:

Is 2.3T $ a lot of money or a just a tip?

Well, I don’t know, the GDP of the US in 2019 was about 21 trillion US dollars (9 zeros).

Another important piece of information is to know the impact of the debt, where Trump is not doing so badly:

If you add Ronald Reagan, the data gets very distorted.

If you add Ronald Reagan, the data gets very distorted.

The immediate questions come to my mind are:

  • How long can the Fed be injecting this huge amount of money?
  • Is it really that much money?
  • What will happen when the numbers of POMO trades drop consistently?

More detail

The data in the green graph above where the Fed purchases in 2020 is visualized is very simple and does not tell me much. I took some time and dumped the data into a spreadsheet, and of course, you see more things.

1.- March 12 was when the serious daily injection of money began.

2.- In the first half of June there was a decrease in purchases by the FED, and it caused a correction. This correction was followed by an increase in the dose.

3.- The number of purchase packages is normally 0 or 1, between March 13 and April 7, it was always 5, 6 or 7 packages released. Then the FED spent a few days with 3-4 packages and returned to 1 package per day.

4.- If we divide the accepted quantities of purchases among the launched ones, it gives you the ratio of accepted purchases. I have also made the average of the last 5 days to see if there is something interesting. And if there is, when the average goes down, in a few days the market goes down (as it happened in June). Now at the end of July it has happened again, with what we see what happens during the first fortnight of August.

5.- On April 9th FED announced the 2.3T$ stimulus program. If we sum up the amount between March 13th, the first day with massive purchases, and August 6th, that is Today, then the total amount injected is 1,71T$, that supposes 75% of the original 2,3T$ budget announced.

Evolution during last 18 years

I have found this table published by Charlie Bilello, where he summarizes the annual changes in the Fed’s balance sheet since 2002. Take into account that 2020 is just till 22/October.

Imagen

My opinion about the POMO

This type of operation is very well known in the US. There are traders doing things with this information. For me it is something that requires data, knowledge and time that I do not have, but I always find it interesting to understand what others do, learn and understand the context where we move.

This is not, in any case, a method of saving or investing in the long term.

If there is something that I have not mentioned or is of interest, let me know!

Financial Accounting Standards Board (FASB)

The FASB Accounting Standards Codification is the source of authoritative
generally accepted accounting principles (GAAP) recognized by the FASB to be
applied by nongovernmental entities.

They provide updates from time to time about different topics.

An example: Archer Daniels Midland

I was reviewing this company and how the free cash flow turned negative in 2017.

I did not liked it, and I did a comment in twitter about this fact on a person that published some fundamental data.

I received an answer. And it was that a change in the US GAAP accounting classification made $ADM to reclassify the early collection of revenue that $ADM receives in advance,

The note that follows:

So this change in 2016 is impacting so many companies and I was thinking that it was a deterioration of the business itself. 🙁

Statement of Cash Flow Topic 230

This Statement of Cash Flows (Topic 230), contains all the data related to the different classifications that need to be done. It’s a large document for accountants.

 

 

 

Simplywall.st Share Price vs. Fair Value

SimplyWall.st have an indicator called: Share Price vs. Fair Value

I love it, it allows me to simplify so many things. It’s shown as (stock used Allianz (ALV)):

The important thing is how the Fair value is calculated.

Below are the data sources, inputs and calculation used to determine the intrinsic value for Allianz.

XTRA:ALV Discounted Cash Flow Data Sources
Data PointSourceValue
Valuation ModelExcess Returns Model
Stable EPSWeighted future Return on Equity estimates from 16 analysts.
= Stable Book Value * Return on Equity
= €183.66 * 0.1%
€23.33
Book Value of Equity per ShareWeighted future Book Value estimates from 10 analysts.€183.66
Discount Rate (Cost of Equity)See below5.7%
Perpetual Growth Rate10-Year DE Government Bond Rate0.2%

An important part of a discounted cash flow is the discount rate, below we explain how it has been calculated.

Calculation of Discount Rate/ Cost of Equity for XTRA:ALV
Data PointCalculation/ SourceResult
Risk-Free Rate10-Year DE Govt Bond Rate0.2%
Equity Risk Premium S&P Global6.0%
Insurance Unlevered BetaSimply Wall St/ S&P Global0.67
Re-levered Beta= Unlevered beta (1 + (1- tax rate) (Debt/Equity))
= 0.667 (1 + (1 – 30.0%) (43.19%))
0.912
Levered BetaLevered Beta limited to 0.8 to 2.0
(practical range for a stable firm)
0.91
Discount Rate/ Cost of Equity= Cost of Equity = Risk Free Rate + (Levered Beta * Equity Risk Premium)
= 0.23% + (0.912 * 5.96%)
5.66%

Discounted Cash Flow Calculation for XTRA:ALV using Excess Returns Model Model

The calculations below outline how an intrinsic value for Allianz is arrived at using the Excess Return Model. This approach is used for finance firms where free cash flow is difficult to estimate.

In the Excess Return Model the value of a firm can be written as the sum of capital invested currently in the firm and the present value of excess returns that the firm expects to make in the future.

The model is sensitive to the Return on Equity of the company versus the Cost of Equity, how these are calculated is detailed below the main calculation.

Note the calculations below are per share.

XTRA:ALV Value of Excess Returns
CalculationResult
Excess Returns= (Stable Return on equity – Cost of equity) x (Book Value of Equity per share)
= (0.1% – 5.66%) x €183.66
€12.93
Terminal Value of Excess Returns= Excess Returns / (Cost of Equity – Expected Growth Rate)
= €12.93 / (5.66% – 0.23%)
€237.89
Value of Equity = Book Value per share + Terminal Value of Excess Returns
EUR183.66 + €237.89
€421.55
XTRA:ALV Discount to Share Price
CalculationResult
Value per share (EUR)From above.€421.55
Current discountDiscount to share price of €218.8
= -1 x (€218.8 – €421.55) / €421.55
48.1%

 

Seedocumentationto learn about this calculation.

Fundsmith annual shareholder meeting

This video: https://www.youtube.com/watch?v=d3cRr318ve4, is the annual shareholder meeting of Fundsmith. Apart of presenting the results of the year, they review a set of economic fundamentals and behaviors that are communicated in a very didactic way.

Basic strategy principles

The investment strategy has three pillars that are summed up by the acronym ODD:

  • Only invest in good companies.
  • Don’t overpay.
  • Do nothing.

“We limit it to a few sectors which have the characteristics we seek: consumer staples, some consumer discretionary products, healthcare, and technology being the main sectors.”

About Brexit: Better A Painful Ending, than An Endless Pain.

When there is not the perfect company in a sector, we pick two to look for that perfection.

Licenses, what you purchase vs what you use

You go through a procurement process and you buy licenses for the whole corporation to enable it to use the services/products linked to it.

After a while you figure out how much of these licenses you are using in reality:

  • How many people is really using it?
  • How many new joiners are accessing to it?
  • How many servers are using them?

A good asset management process linked to the original contract signed with the vendor needs to be in place, or just a person reviewing it periodically.

Well, you will not imagine how many organizations are losing money with over estimated license contracts that finally are not used.

It’s not easy to convince to an organization to invest money to analyze the gap between the signed license agreement and the real use of these licenses. To do it sometimes is like to recognize that they did not signed the right contract, so it’s like to recognize an mistake.

  • How much we can save if we re-negotiate the license agreement?
  • What is the real forecast we have with respect the use of these services?
  • Can we move to a “as a service” agreement model?