AI & Asset Allocation, Part 3

Third part of an opinion in three parts

Part 1  |  Part 2  |  Part 3  |  Appendix 1  |  Appendix 2  >

image: Fischchen, Breeding Ostrich (May 2007, shared per license)
In Part 1, we considered and opined about:
1. The strenuous life of the beach investor.
2. Artificial intelligence (AI).
3. The appearance of low risk with investments in cash and bonds.

In Part 2, we considered and opined about:
1. Using some of your investment portfolio for investing in cash and bonds.
2. Getting higher rewards by taking risks with investment in stocks.
3. Managing increased risks through diversified stock investments.
4. Managing increased risks through broadly diversified stock index ETFs.
5. Getting higher rewards with broadly diversified growth stock index ETFs.
6. Offsetting personal medical expenses with health-and-pharma sector funds.
7. Metrics for choosing among broad stock index funds.

In this article, Part 3, we will take a close look at making small bets in individual stocks and sector ETFs. Appendix 1 considers another view, investing in actively managed funds. Appendix 2 discusses definitions and formulas for some terms and calculations.

On Placing Small Bets

There are no sure things in sector funds and individual stocks. You MUST be ready to accept some significant (perhaps total) permanent losses on some or many of your choices when you invest in sector funds or individual stocks, for the sake of making extraordinary profits on a few. If you can't do that, then go back to the paragraph on “Sensibility and Prudence”  in Part 2, and choose the 100% solution. By investing in broadly diversified stock index ETFs, you use diversification of holdings to reduce the risk you bear. You avoiding putting all your eggs in one basket. When you buy a S&P500 index ETF, you put your eggs in 500 baskets.

The investor in sector funds and individual stocks makes many small investments so that lightning has many chances to strike somewhere in the portfolio of holdings, and there ignite the next Microsoft or Google or Netflix or Facebook. But most of these hoped-for bolts of lightning never strike, so you want keep your losses small by keeping the initial investment small.

Be skeptical. Don’t rely on “sure things”. Jettison your vanity, and think small. Invest on the order of $1000, $2000, $5000, $10000, definitely no more than 1% of your portfolio in any one stock or sector ETF, and 1% seems too much to me. Smaller is better.

If you rely on your intuition, or reading about hot stocks in the news, or unverified information you heard from a friend, then you won’t find a better motto than “Smaller is Better”, and you should keep your maximum cash investment in any individual stock or sector ETF to $1,000. If you intend to make larger investments in individual stocks or sector ETFs, then to outperform the index ETFs, you MUST read a lot of detail, have some understanding of basic financial statements and their line items, do some calculations, and have the ability and willingness to seek and find information you don’t already have. If you can’t or won’t do these, then save your money, go back to Part 2, forget about individual stocks and sector ETFs, put your money in broad stock index funds and go back to the beach (see Part 1).

You might wonder “How small is too small?” Two disincentives push against smaller holdings. First, the broker’s commission should be small enough to ignore. In days of yore, we would allow 2.5% for the commission. In our modern enlightened era, you can easily find reliable brokers that charge less than $5 per trade. If you pay much more than $5, then change brokers. If your trades are $1000 or more in size, then the commission will be less than 0.5%. You can generally ignore that level of commission, because the price of almost any stock can unsurprisingly vary more than 0.5% in one trading day, making the commission a relatively insigniicant cost for the long term investor on the beach. So keep your buy orders to $1000 or more.

A platoon of assistants
(The Denmark Staff, 1914, Wikimedia, shared per license)
Second, small sizes of investments can, with time, produce a portfolio holding many different stocks. If you have a platoon of assistants, you can instruct them to attend to portfolio operations. But if you manage your portfolio between dips in the sea (see Part 1), then personnel management may crowd your schedule uncomfortably. Then, someday, while doing an end-of-quarter review, you find a stock or fund in your portfolio that you didn’t know you had. This implies either that some other person trades in your account, or more likely that you forgot about it and your chosen investment size is too small. If you are trading $1000, then switch to perhaps $5000 or $10,000. If you are trading $10,000, switch to $50,000 or $100,000, but always an amount well less than 1% of your portfolio.

Sector funds

Sector funds specialize in particular industries. Look for index funds intended to track the performance of all, or of the largest, companies in the industry. Beware of arcanely contrived indexes, synthetic strategies, and leveraged indexes unless you lust for risk injected directly into your central nervous system. Play it safe. Look for long-established indexes managed by long-established firms, including but not limited to MSCI, S&P Dow-Jones and FTSE Russell.

Telecom, Petroleum, Robotics, Biotech and other fairly indexed sector funds can grow less quickly in value than individual stocks, but since the many individual stocks held in these funds will offset the ups and downs of each other, the fund will fluctuate more moderately. While an individual stock can lose nearly all its value in a few months, the fund will probably take decades to decay to oblivion, if it comes to that.

For choosing sector index funds, I have found these metrics relevant:

1. 10-yr price growth (ignore younger funds, prefer more rapid growth, positively correlated),
2. Rate of dividends per share (negatively correlated, a low number is better, as in golf),
3. Beta  (negatively correlated, a low number is better, as in golf),
4. Book value divided by price (negatively correlated, a low number is better, as in golf).

Individual stocks

If investing in stocks bores you, or if you seek certainty, or if you fear losing money more than you look forward to gain, or if you perceive mere randomness governing choices in the madhouse which is the stock exchange, or if it takes more time than you want to spend on it, or if you expect that what you might choose likely won’t beat the S&P500, then stay away from investing in individual stocks.

There are good people who will treat you well, and they are honest, phronetic, well-intentioned, knowledgeable and fair-dealing traders in the market for individual stocks. And you will also find troublesome people, charlatans, hucksters, rogues, chislers, persons with conflicts of interest, ignorant persons, incompetents and the well-intentioned misguided. Think, judge and choose. Seek and work with the good people and abandon the others.

The stock market is where, if you put all your money in one investment, then you can lose all your money. This is the school of hard knocks for people who have more money than they want to spend for the next few years. This is the land of opportunity that can produce millionaires from people who make serendipitous choices. This is the arena in which you see all kinds of ugly and beautiful, wild and crazy, useless and fabulously enriching stuff. This is the midway where you can invest in stodgy insurance companies, or skyrocketing disruptive high tech, or old reliable industrial giants, or lithium mines in Chile, or a breakthrough in next-generation atomic fusion electricity, or small companies currently managed by the third generation of the family that produce profit year after year, or brilliant business models that will turn profitable any day now, or companies that never earned a profit or sold one unit of product, or the next Microsoft.

You won’t be able to choose with certainty, so cast your net widely, and keep your losses small. See "On Placing Small Bets", above.

For choosing individual stocks, I have found these metrics and practices relevant:

1. Ignore any company that reported a loss (negative net income available to common stock including extraordinary items) in any of the last five fiscal years reported in their latest annual report, a publicly available document. (If your broker doesn’t offer this information on their website, then get another broker, seriously.) If you are eager to invest in companies that have lost money in recent years, then expect that you will lose on most of these bets, and keep the amount of your investment utterly minimal.
2. Price change between Oct 9, 2007 and Mar 9, 2009 (ignoring stocks too young to measure, prefer higher growth and less decline, positively correlated).
3. 10-yr growth of price, credibility weighted, giving more credibility to all-stocks average versus specific stock observation for stocks younger than 10 years (prefer higher rates of growth, positively correlated). If you don’t know how to do the credibility calculation, then use the 10-year growth of price, ignoring stocks younger than 10 years.
4. 10-yr growth of price, ignoring stocks younger than 10 years (prefer higher rates of growth, positively correlated).
5. Number of years during the last 5 that the annually reported revenue has increased from the prior year, using the 5 most recently reported years, and ignoring stocks for which you can't find reliable numbers for all 5 years. You will find, at most, 4 increases (a perfect score) in 5 years. (positively correlated).

On Selling

Trim your holdings once every year or two so that no one stock or sector fund is more than 25% of all the individual stocks and sector funds you own. When any one stock or sector fund is more than 25% in value of your stocks-and-sector portfolio (the stocks-and-sector portfolio is all the individual stocks and sector funds you own) then it is too much. Sell it (trade it for cash) down to 10% of all your stocks-and-sector portfolio, and trade the cash for something else.

Otherwise, sell the stocks and sector funds that have lost the most value, but only when metering out steady income in your old age, when paying unusually large medical bills, or when buying a house to live in.

If there is a stock market crash, don't sell. The broadly diversified portfolio, historically, usually recovered fully within two years, rarely more. People who tried to sell to avoid further loss were usually too late or too early. Those who tried to buy just before the upturn were usually too early or too late. Those who tried to time their trades for just the right moments seldom became richer for the experience than those who just held on.

Before investing in individual stocks, re-read the "Sensibility and Prudence" paragraph in Part 2.

Concluding remarks

Almost all investments in our modern era involve the use of computers. Some of the calculations and algorithms might be called AI. Whether it’s AI or not, it helps to have some idea of what services it provides you, and you should definitely seek some understanding of pertinent risks and rewards before investing your money in any bonds or stocks. We think of cash as an investment of low risk, because the price never changes. A dollar is worth one dollar.  A euro is worth one euro. However, cash has no promise of big earnings or investment returns. We think of bonds backed by governments or large, well-managed companies as having little risk, especially when we buy many different bonds aggregated in broadly diversified index ETFs or funds. Generally the bond funds have better return than cash, but bonds fall in value when interest rates rise. We expect that broadly diversified stock index funds will have much larger returns than bond funds in the long (5+ years) run. We also expect the risk of wider fluctuations in price with stocks and stock funds. Sector funds invest in stocks of particular industries. They fluctuate more widely than the broadly-diversified index funds, so we call them riskier, and they can provide bigger returns in the long run. Individual stocks can produce thunderously wonderful returns in the long run, but at risk of partial or total loss. With individual stocks, seek to keep your losses small by never putting more than 1%, at most, of your portfolio (all the stocks, bonds, ETFs, mutual funds, and cash you own) into any one stock. With individual stocks, you give good fortune a chance to visit your portfolio and greatly increase your wealth. If your investments are so risky that you can’t sleep at night, then sell off enough of your riskier holdings so that you can sleep easily. 

Full Disclosure

I own shares of Alphabet (Google, GOOGL), Netflix (NFLX), and Facebook (FB).


Images and Sources

See Part 1.

Michigan, USA, Aug 2019
Image: Daniel Brockman, Public Domain.

AI & Asset Allocation, Appendix 1

History is opaque. You see what comes out, not the script that produces events.
-- Nassim Taleb, "The Black Swan" 2008


A Selection of Actively Managed Funds

Image: Belfius, Scales
(2012, shared per license)
Mr. Rock Brockman, ChFC, CLU, principal of WHB Financial Advisors of Rockville, Maryland, on reading Parts 1 and 2, wrote to me identifying seven mutual funds, with their performance measures, that outperformed the S&P500 over the last 40 years. These are “actively managed” funds, in which the manager chooses investments according to some method that depends on her own principles of good investments. They aren't “passively managed” funds based on an index the manager seeks to match. (Those funds we have discussed in Parts 1, 2 and 3 of this article are “passively managed” funds, for which the method can be duplicated.)

This table shows seven funds that have, from 1976 to 2019, increased in value more than the S&P500. The table shows the cumulative growth of a $10,000 investment, assuming reinvestment of dividends. Mr. Rock Brockman provided these figures from sources he believes to be accurate. (VFINX, a S&P500 index fund, is shown for comparison).

Fidelity Magellan
American Funds Growth Fund
T. Rowe Price New Horizons
Fidelity Contrafund
American Funds
Dodge & Cox Stock
Davis NY Venture
Vanguard 500 Index Investor

No one can assure that these funds will perform similarly in the future.



See Part 1.

Image: Daniel Brockman, Public Domain

AI & Asset Allocation, Appendix 2

-- Lord Kelvin, 1883


Guide to Terms and Calculations

Lord Kelvin 1824-1907
Image: Messrs. Dickinson
London, New Bond Street
Here we have an extremely brief look at some arcane but useful terms and simplified useful techniques, and a little guidance toward more information for readers interested in further investigation. Generally, the research pages of your broker’s website are the easiest place to find this information (except what you must calculate yourself). You can readily find most or all of these terms and calculations using your favorite search engine or reading about them in Wikipedia.org.

Find explanations of some additional terms in Part 2.
For additional readings, see the sources list in Part 1.

Assets: All the company’s money, amounts loaned to or invested in others, property, supplies and materials on hand, funds set aside to pay future employee benefits, tax refunds expected but not yet received, and amounts billed to customers but not yet paid.

Bond: A debt owed by a company or government and divided into many uniform shares called “bonds”, having a maturity value (a.k.a. face value) to be paid at a future “maturity” date. Most bonds pay interest, a stated percent of maturity value, though some pay no interest. Some bonds are traded on securities exchanges.

Book value (a.k.a. Equity or Stockholder’s Equity): Assets minus liabilities. For a stock, see the company’s balance sheet, published annually. For stock ETFs for the long term beach investor (see Part 1), book value is the sum of the book values of the stocks held in the ETF, and the ETF has no significant liabilities (ETFs that have significant liabilities are called “leveraged” ETFs, and if you are wary of risk, then know that leveraged funds are playing with fire.).

Book Value Divided by Price: Your broker’s website will probably show the price per share divided by book value per share, or maybe they will show a blank or “N/A”. If the broker shows you price divided by book value, then calculate book value (b) divided by price (p) as

b/p = 1 / (price divided by book value).

If the broker shows you a blank or “n/a” or the like, then they feel challenged by b less than or equal to zero, in which case you should calculate book value manually from the most recently reported quarterly balance sheet (provided by the broker). Then, using market capitalization for the entire company, calculate

b/p = book value divided by market cap

If your broker reports multiple versions of book value, I recommend using "tangible book value (MRQ)", or something like that. "Tangible" means goodwill and intangible assets are excluded, two features of financial accounting that one may easily confuse with hot air. "MRQ" means "Most Recent Quarter" reported by the company.

Positively Correlated.
Image: Wikimedia, "Ordinary Least Squares", Public Domain
Correlated: If the price change usually goes up when the metric goes up, then we say the price change and the metric are “positively correlated”. If the price change goes down when the metric goes up, then we say they are “negatively correlated”. Correlation doesn’t tell us whether one causes the other, or how certain we are, or how intense is the effect. Correlation is a number between -1 and 1. Nearly all spreadsheet apps include the correl() function which calculates correlation, or the equivalent pearson() function. Example: For sector ETFs, we say beta (the metric) and the price change are negatively correlated, the correlation is a negative number, meaning that as beta decreases, we expect the future price change will increase, and as beta increases, the future price change declines.

Credibility: A weighted average of a useful, though not fully believable, measurement and a standard value, though general and non-specific and less relevant, such as the average for all stocks. The credibility calculation allows us to compare a stock like TWTR, which began trading about 5 years ago, with a stock like MA which has been around for decades. If you think an 5-yr price growth metric (g) is a more believable predictor than a 2-yr price growth, but you would need a 10-yr growth of price metric to believe it “completely” and compare it with other stocks, then we can base the weighting on the number of years available (y), divided by 10. Then we calculate the credibility (c) as 

c = square root of the number of years available divided by 10
c = sqrt( y / 10 )
("sqrt()" is the spreadsheet software function for square root) 
Example: TWTR has price history since 2014, so y=5, and then c=0.707.

What we take as the standard (s) could be the average for all stocks for which we have 10 years of information, or the median, or the S&P500, or whatever we are prepared to believe if we don’t know the 10-yr metric for the specific stock, knowing we aren’t exactly right, but knowing the standard is a better estimate than “n/a”. Then we weight the partial growth information (g) we do have by the credibility (c), and for the information we don’t have, we use the standard (s) weighted by (1 - c).

Credibility weighted 10-yr price growth = c * g + ( 1 - c ) * s
Example: if TWTR, y=5, g=1.1, s=3.1, then c=0.707 
credibility-weighted 10-yr growth = 1.7.

Liabilities: Money owed to others, salaries and benefits owed to employees, advance payments from customers, amounts billed to those few customers that probably won’t pay (doubtful accounts), bills for purchases not yet paid, taxes not yet paid, and payments promised to lenders, stockholders and investors.

Market Capitalization (a.k.a. Market Cap or Capitalization): Generally, price multiplied by the number of shares outstanding. If a company has more than one kind of stock, then the market cap of the company (your probable topic of interest) is the sum of the market caps of the various kinds kind of stock.

Price: Unless otherwise indicated, these articles refer to the price of the last trade when the exchange closes for the day, the “closing price” or “last price” on a given day.

Rate of dividend increase (or decline) per share: I take the most recent five years of dividends reported by the company, summarize them by 12-month periods, and apply exponential least squares regression to get the average annual rate of increase. NO, you don’t need to do that. All you need is some way to come up with an unambiguous, repeatable, generally applicable estimate of what rate of increase to expect in the future, so that you can compare one stock with another. If you don’t know exponential least squares regression, and you don’t feel like reading how to do it on Wikipedia https://en.wikipedia.org/wiki/Ordinary_least_squares, or asking a friend, there are satisfactory alternatives.

Here is one. Use the slope() function included with nearly all spreadsheet software. A stock with larger (steeper) slope number has dividends increasing faster.

  s = slope of least squares line
= slope(y1:y5,x1:x5) 

For more information, type “slope function” into your favorite search engine.

Here is a second. Divide the year 5 (most recent) dividend (d5) by the year 1 (earliest) dividend (d1), take the square root of that, then take the square root of that. That is, you can get an estimate of the future rate by either of the following two equivalent calculations.

Estimated rate = sqrt( sqrt( d5 / d1 ) ) = ( d5 / d1 ) ^ ( 1/4 )

Reinvestment of dividends: Using dividends you receive to buy additional shares of the investment that produced them. Many or most brokers will automatically reinvest dividends for you, at no charge, on your request.

Return: The amounts of money you get from an investment, usually compared with what you pay to get it in the first place. That is, how much money do you have when you get out of this investment, compared with how much you put into this investment in the beginning.  Includes the dividends you receive while you hold it, and the price you get when you sell it, less the costs of holding and keeping and selling it, including taxes and broker’s fees and your time. For many purposes, the price you sell for, compared with the price you buy for, gives you a good approximation of the return.

sqrt(), square root. The square root of x is sqrt(x). Nearly every spreadsheet app provides sqrt(), and you probably have a square root function on the calculator app on your phone, and you can type “square root of 0.93” into your favorite search engine to get the calculation, and you can calculate it by hand (ask your favorite search engine).

Ticker (a.k.a. Ticker Symbol): A standardized few letters or numbers representing a stock or bond or ETF or mutual fund or something else traded on an exchange. Examples: AMZN is the ticker for Amazon.com, IYR is the iShares U.S. Real Estate ETF, LUV is Southwest Airlines, VOO is the Vanguard S&P500 ETF, STZ/B is the Constellation Brands Inc. class B shares.

10-yr growth of price: the most recent price divided by the price on this date ten years ago.


Images and Sources

See Part 1.

Alma, Michigan, USA.
Image: Daniel Brockman, Aug 2019, Public Domain


AI & Asset Allocation, Part 2

Second part of an opinion in three parts

Snapshot of Edwin Lefevre in 1907
"You remember Dickson G. Watts' story about the man who was so nervous that a friend asked him what was the matter.
'I can't sleep,' answered the nervous one.
'Why not?' asked the friend.
'I am carrying so much cotton that I can't sleep thinking about it. It is wearing me out. What can I do?'
'Sell down to the sleeping point,' answered the friend."
-- Edwin Lefevre in 1923


In Part 1, we considered and opined about: 
1. The strenuous life on the beach of your kind of long-term investor.
2. It’s hard to consistently beat the investment performance of the S&P 500 in the long term.
3. Questioning the value of AI (artificial intelligence) for tax-loss harvesting, 
4. Doubtful value of AI’s daily portfolio rebalancing.
5. AI portfolio choice, of specific investments, not proven, yet.
6. Costuming assessment of investor’s risk preferences to look like AI.
7. We don’t know AI’s adequacy for the next big crash.
8. Bond values fall when interest rates rise, and vice versa.
9. You probably already own some bond equivalents, like Social Security.

Continuing from Part 1 with our discussion of bonds...

Have a good, clear reason for buying bonds, otherwise you forfeit the higher return available in, say, stocks. Verify your good, clear reason with someone whose financial advice you respect. (If you wouldn’t ask a hairdresser if you need a haircut, then why ask a person who sells bonds if you need to buy bonds? The person who urges you to buy bonds from them may have much wisdom and may be the most honest person you know, but if they get a commission on the sale, then let's bear in mind their conflict of interest.) 

about ETFs…

An ETF (Exchange Traded Fund) is a pool of assets in the care of a manager who issues share certificates in the pool and who buys and sells investments for the pool consistent with the prospectus (every ETF has a prospectus, a document stating the organization of the ETF). Each certificate represents a proportional claim on the assets of the pool. The shares trade on an exchange, such as the NYSE (New York Stock Exchange) or NASDAQ, so you can buy or sell them like stock certificates. In this article, we consider three kinds of ETFs:

Bond index ETFs - The manager buys and sells bonds for the pool to match the performance of an independently determined index. There exist many indexes, but we are interested in indexes of broad classes of government or high grade corporate bonds.

Sector index ETFs - The pools contain common stocks managed to match the performance of an independently determined index of a particular industry, country or other narrow category. For instance, you can buy sector index ETFs to match the performance of the health care, telecommunications, real estate, and petroleum industries, and of the publicly traded companies in Switzerland, China, Japan, United Kingdom, Eurozone, and Chile, and of many other countries and industries.

Broad Stock index ETFs - The pools contain common stocks managed to match the performance of an index reasonably defined to specify “the entire market”. The classic, oldest examples are S&P500 index funds VOO and SPY, which match the 500 largest companies traded in the US. There are broad stock index ETFs that attempt to match all the publicly traded companies in the world, and more specialized in the largest companies of particular countries (indistinguishable from country sector index ETFs), and in large-capitalization (big) companies, small-capitalization (little) companies, and mid-cap (medium sized) companies. Also, we find “growth” stock variations, which contain the cross-section of companies with low book-to-price ratios, and “vaue” index ETFs, which contain companies with high book-to-price ratios.

On the other hand, as long-term investors, we have little interest in ETFs which aren’t managed to match the performance of an index, but which are managed according to the manager’s judgement, also called “actively-managed” or sometimes “hedge” funds.

See more definitions in Appendix 2.
If you decide to buy bonds, then buy bond index ETFs (Exchange Traded Funds), plain vanilla bond index funds invested in US govt securities or high-grade US corporate bonds, such as ticker symbols SCHZ, ILTB, SPTL or VTIP. Use ETFs, because selecting individual bonds is tedious and arcane, requires frequent attention to your holdings to reinvest on maturity of a bond, and because only those who trade hundreds of thousands of dollars in each trade can justify the time spent on this work. With ETFs, you avoid those concerns. 
If your concern about whether you have enough invested in bonds and cash keeps you awake at night, then buy enough bond ETFs that you can sleep at night. Cash has nearly no investment return, but it won’t lose its face value, so many regard it as extremely low risk. If you are more than 30 years old, then keep enough cash to pay your living expenses for 3 to 6 months, and invest the rest of your cash in something.

That leaves us with stocks...

A definition ... when talking about stocks, "cap" is "capitalization", which is the number of shares multiplied by the price.

To get significant rewards, you must take risks. Use diversification of investments and long-term holding periods to moderate the risks you must take.

For investments outside of the US: Mr. Mark Hulbert has found that returns on US versus ex-US stock indexes ran, historically, in long 5+ year episodes where one is higher than the other. Generally, there is no reason to buy ex-US stock ETFs at this time.

Your portfolio should consist of ETFs of broadly diversified stock index funds and perhaps some bond funds (see warning about bonds above), unless you want to invest in some individual stocks (see Part 3), in which case, reduce the stock ETFs to 95% of your stock investments, or to 90%, if you must. 

If you are shy about risking fluctuating prices, then buy a S&P500-indexed large cap fund like VOO or SPY to avoid extreme fluctuations. If getting as much increase in value as you can reasonably expect interests you more, then get a large cap growth index fund like VUG or a small cap growth index fund like SLYG. Higher rates of growth come with increasingly large expectations of fluctuations of prices over the next 2 or 3 years, but if you are going for the long 5+ years horizon, then your long 5+ years holding period mitigates the price fluctuation risk. The relative return advantage of a growth fund, such as VUG, is significant over a ten-year period, compared with its vanilla siblings, such as VOO. Small cap growth funds show only small return advantage versus large cap growth variants.

So, for broadly diversified stock index ETFs, in order from higher rates of value increase (return) to lower:
1. Small cap growth -- expect highest price fluctuations, highest rates of growth in value.
2. Mid cap growth.
3. Large cap growth. 
4. Large cap S&P 500 -- expect lower price fluctuations, lower rate of growth in value.

You can also buy value index ETFs, instead of "blend" growth+value (plain vanilla like the S&P500) index ETFs or growth index ETFs. I don't think the value index ETFs are worth the price fluctuation risk forgone, but if you are worried, put 2%-points of your stock portfolio in bond ETFs and buy growth index ETFs.

My recommendation for stock index ETFs: Go for growth. 

Exception: if you expect high (a large part of your personal budget) and rising medical expenses, then you might like to have an investment that would increase in value with your medical expenses, and then you might substitute health-and-pharma sector funds (for example XBI, IHF or VHT) for a large portion (up to 1/4) of your investment in broad stock index funds.

For choosing broad stock index funds, I have found these metrics relevant: 

sleep for the chance of extra profits.” -- Warren Buffett
1a. 10-yr growth of price (credibility weighted, giving more credibility to all-funds average versus specific fund observation for funds younger than 10 years, and if you can't do that calculation, then ignore this metric, and ignore funds younger than 10 years),
1b. 10-yr growth of price (ignore funds younger than 10 years),

2. Book value divided by price (inverse of price divided by book). Book value divided by price correlates negatively with future performance, that is, a low score is better, as in golf.

Sensibility and Prudence: It's sensible and prudent and low in effort to put 100% of your stock portfolio into ETFs of broadly diversified stock index funds. You may give up a percent point or two of returns in many years, but the 100% solution is a lot easier and a lot less labor than trying to get just a little more return. If you choose this 100% solution, then you can make your portfolio choices, order your trades, and never sell. (And if it allows you sleep better, put a portion of it in bond funds, but see warning about bonds above). Then go outside and play, and stop reading here.

On placing small bets on sector funds and individual stocks… see Part 3.


I own shares of VTIP, XBI, VOO, VUG, SLYG and VHT.

I want to thank my proofreader, 
whose corrections and comments were 


Images, notes and sources

See complete list in Part 1.

Wild foxglove. Gig Harbor, Washington, USA, June 2019.
Image by Daniel Brockman.


AI & Asset Allocation, Part 1

First part of an opinion in three parts


The Turk marvelously won at chess
Imagine the sun warming you on the beach. You check the financial headlines on your mobile phone. A down day. You put the phone under the umbrella and take a dip in the sea. Returning to the umbrella, you ask the waiter to bring another cold one for you and your companion. This feels good. The next day, you check the financial headlines on your mobile phone. Stocks gained on the exchange. You log in to your brokerage. A few down and a few up, and a respectable increase overall for the last few years. You put the phone under the umbrella and take a dip in the sea. Returning to the umbrella, you ask the waiter to bring another cold one for you and your companion. This feels good. Just another couple of days for your kind of investor.

This triplet of articles is about the roles of AI (Artificial Intelligence), cash, pensions and Social Security, bond funds, stock funds, and individual stocks in your personal investment portfolio, that is, asset allocation.

Ample research shows almost no humans can consistently beat the S&P500 in the long term, when adjusted for risk (price fluctuation). Those humans who seem to do so (Warren Buffet, George Soros, a few others) can be explained by the luck of the draw.

I'm skeptical about the value of AI investing.

Parijat Garg asks good questions about AI investing. Considering the Turing Test, the message I take away is that when robots choose stocks like humans choose stocks, then we should expect similar results.

To take one example, some of the benefits identified by Schwab, a highly reputable firm, for their “Intelligent Portfolios” product include these (enhanced by my opinion):

1. Tax-loss harvesting: it's probably good during relatively stable markets, but I doubt what value this provides, compared with waiting till the end of the year, selling your losers, waiting long enough to avoid IRS wash-sale rules, then buying them back. I wonder what effect tax-loss harvesting will have on your net worth during a crash and recovery.

2. Daily portfolio rebalancing: Rebalancing assures portfolio allocation to avoid excessive concentrations of relatively risky assets. I question whether there's significant value produced, compared with quarterly rebalancing, and I doubt the value of quarterly versus annually, and even if you miss a year, there's not much to gain by remembering it instead. An advanced researcher at Mellon, Mr. Jeff Ricker, studied the effect of rebalancing and asset reallocation on taxable accounts and found negative effects on portfolio value. That is, the implicit advice is: Make the best decision available to you when you buy, then don't sell (unless you have major personal need for cash or major change in investment strategy). If you think rebalancing gets more valuable with increasing frequency, then rebalance daily, or perhaps hourly, and AI robotic methods do rebalance correctly with little cost.

3. Portfolio content selection: Using AI has no value compared with human choices or buying a copy of Barron's and throwing darts at the stock list pages. There is some dispute about the value of choosing investments by throwing darts (Mr. Ricker, when at Wells Fargo Investment Advisors, preferred a professional competition grade blowgun) or taking financial advice from blindfolded chimpanzees. Rick Ferri writes in Forbes that the monkeys easily beat the Dow Jones Industrials, time after time. Alex Mayyasi writes that the professionals beat the monkeys, though maybe by having their picks published in the Wall Street Journal or by taking risks or by cheating.

I skeptically want to see how AI portfolio management does in a crash before I do anything more than a minimal exploratory speculative investment.

Before putting you into their AI product or any other investment product, your broker, with some prudence and regulatory compliance, puts you through a risk preference interview or checklist. If called "AI", that is pure marketing nonsense. Some one or some computer looks up your answers in a table or chart or calculates a simple linear formula or merely applies human judgement to the risk and reward preferences of a person “like you”. Very like putting a small person inside an "automaton" that marvelously wins at chess.

My own advice for fortunes under $10m in the USA, taking a long 5+ years view:

Bonds and cash...

Your Social Security (national pension in the United States) and other pension payments provide the effect of a long-term government bond with the present value of the future payments. You already own these future payments. An investment in bonds will do no better for you. Bond prices fall when interest rates rise, a mathematical equivalence. Currently we remain at generational low levels of interest rates. The rate on a 30-year US Treasury bond is about 3% at April 30, 2019. Expect bond values to fall as interest rates rise in the future. Even if there is no change in rates and value, you may want a higher return on your invested money. If your social security payment is $1,000 per month, and if you want 5% per year or more from your investments, then your future social security payments are about equal to a bond that pays $12,000 per year forever (or until your death, whichever comes first), and the value of your forever bond is about $240,000 (=$1,000*12/.05), or very slightly less for the probability of death in 30 years or so. If you aren’t old enough to collect Social Security, then the forever bond is worth somewhat less, and will grow as you approach the qualifying age.

In Part 2, we will consider using Bond ETFs (Exchange Traded Funds) and Stock ETFs.



Fischchen, Breeding Ostrich in Berlin Zoo (May 27, 2007, shared with attribution under GNU Free Documentation License, Wikimedia.org, https://commons.wikimedia.org/wiki/File:Breeding_Ostrich_Berlin.jpg)

Mark Hirschey, Warren Buffett portrait (2005, used with permission, retrieved Jun 14, 2019 from https://en.wikipedia.org/wiki/Warren_Buffett#/media/File:Warren_Buffett_KU_Visit.jpg)

Lord Kelvin (circa 1900, Messrs. Dickinson, London, New Bond Street, Public Domain, https://en.wikiquote.org/wiki/William_Thomson)

Edwin Lefevre snapshot (published in “The Bookman”, v.25, 1907, Public Domain, retrieved Jun 14, 2019 from http://babel.hathitrust.org/cgi/pt?id=uc1.$b623112;view=1up;seq=137;size=200)

Maersk Line, The Denmark Staff (1914, Wikimedia.org, shared with attribution under Creative Commons Attribution-Share Alike 2.0 Generic licensehttps://commons.wikimedia.org/wiki/File:The_staff_(1914)_(7312784848).jpg)

"The Turk:, engraving, published in Gottlieb von Windisch, "Inanimate Reason" (1784, Wikipedia, https://en.wikipedia.org/wiki/The_Turk, retrieved May 24, 2019, Public Domain)

Images in Appendix 2 are from Wikipedia.org and in the Public Domain or made available via Wikipedia's Creative Commons Attribution-ShareAlike License


Warren Buffett, Chairman’s Letter to Sharelholders, Feb 27, 2009 (published in Berkshire Hathaway, Inc., “2008 Annual Report”, letter copyright 2009 by Warren Buffett, retrieved Jun 14, 2019 from http://www.berkshirehathaway.com/2008ar/2008ar.pdf)

Department of the Treasury, “Daily Treasury Yield Curve Rates”, (https://www.treasury.gov/resource-center/data-chart-center/interest-rates/Pages/TextView.aspx?data=yield, retrieved Apr 30, 2019)

Rick Ferri, “Any Monkey Can Beat The Market” (Dec 20, 2012, Forbes, https://www.forbes.com/sites/rickferri/2012/12/20/any-monkey-can-beat-the-market/#4acf7191630a, retrieved Apr 29, 2019)

Parjat Garg, “Discretionary Investing in the Age of Artificial Intelligence” (retrieved Apr 29, 2019, CFA Institute, https://www.the-right-question.org/en/discretionary-investing-in-the-age-of-artificial-intelligence/)

Johnathan Hoenig, “Find Your Stock Market 'Sleeping Point'” (May 9, 2011, Marketwatch, retrieved Jun 16, 2019 from https://www.marketwatch.com/story/find-your-stock-market-sleeping-point-1304958203774)

Mark Hulbert, "Almost all retirees make this mistake" (Jul 27, 2019, Marketwatch, retrieve Jun 26, 2019 from https://www.marketwatch.com/story/almost-all-retirees-make-this-mistake-2019-07-26?siteid=nbch)

Edwin Lefevre, “Reminiscences of a Stock Operator” (1923, https://www.amazon.com/Reminiscences-Stock-Operator-Edwin-Lefèvre/dp/0471770884/ retrieved Jun 14, 2019)

Burton G. Malkiel, “A Random Walk Down Wall Street” (1973-2019, https://smile.amazon.com/Random-Walk-Down-Wall-Street/dp/1324002182)

Alex Mayyasi, “How Well Do Blindfolded Monkeys Play the Stock Market” (Jan 31, 2014, https://priceonomics.com/how-well-do-blindfolded-monkeys-play-the-stock/, retrieved Apr 29, 2019)

Charles Schwab & Co., "Intelligent Portfolios" (2019, https://intelligent.schwab.com/)

Alan Turing, pp. 3-5 (1951, transcript, BBC broadcast 1952, conversation with M.H.A. Newman, AMT, Sir Geoffrey Jefferson and R.B. Braithwaite, The Turing Archive, http://www.turingarchive.org/viewer/?id=460&title=5)

Dickson G. Watts, “Speculation as a Fine Art (, https://www.amazon.com/dp/1607962659, retrieved Jun 14, 2019) ; nb. The story has been retold many times, of course, and attributed to various persons, no doubt apocryphally, and may predate Watts by centuries. As Watts told it, it's much more terse: "One man told another that he could not sleep on account of his position in the market; his friend judiciously and laconically replied: 'Sell down to a sleeping point.'" As the legend came down to me, a man approached J.P. Morgan on Wall Street, saying "I worry I am overinvested in bonds. Is the market going down? Should I sell it all and hold the cash? Please tell me what to do, Mr. Morgan. I can't sleep at night!". Morgan replied "Sell until you can sleep at night." And Mr. Hoenig, writing in Marketwatch, seems to have heard the same attribution, but a slightly different story than I. 

Wikipedia, “The Turk” (retrieved Apr 29, 2019, https://en.wikipedia.org/wiki/The_Turk)

Image by Daniel Brockman, May 2019


The Fairy Tale of Capitalism: Growth and Income Disparity

FTC is a dramatization and a comedy. 

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“Income disparity is something we must address.” 
-- Nancy Pelosi, Speaker of the United States House of Representatives 

“The income disparity deal is real in our country, and the question is, 
‘What are we going to do about it?’” 
-- Bill Haslam, Governor of Tennessee 

“The rapid rise of oligarchy and wealth and income inequality 
is the great moral, economic, and political issue of our time.” 
-- Bernie Sanders, United States Senator

GDP approximates the income of the Society. The amount of GDP, average or per capita GDP, and  rate of increase of GDP tell us nothing about the disparity of income in the Society.

When we hear the news announcer say something like “GDP grew at an annual rate of 3.4% during the 3rd quarter of 2018”, it seems good news. The Professors sing “Growth of GDP”, a perennial hit. Politicians brag about it. GDP is “the economy”. GDP growth is good. 

GDP is Gross Domestic Product. People who measure GDP collaborated on the SNA System of National Accounts, 664 pages defining GDP and its components.

GDP equals GNI Gross National Income, all the income of a national subset of the Society, plus the depreciation of capital equipment, usually about 16% of GDP, plus all the stuff sold to foreigners, less all the stuff bought from foreigners (these foreign transactions adjustments net +/- 1% or 2% of GDP for the larger countries). When we consider the things that will make a big change in GDP or GNI, the main idea is

GDP = GNI + depreciation = the value of all the stuff produced in a country

GNI = GDP - depreciation = about 84% of GDP

The remaining value of a large asset is, for accountants, the purchase price less prior depreciation. Accountants deduct from income a fraction of the purchase price each year as depreciation. Accountants put appreciation in income when and if the owner sells the asset. But that’s another story.

GNP Gross National Product includes the worldwide income of citizens and excludes the local income of foreigners. GNP differs a little bit from GDP, but that’s another story.

The news announcer seldom mentions how we distribute GDP unevenly. According to the World Inequality Lab, in the United States, the average real after-tax income of the 50 Percent grew 21% during the 35-year period from 1980 to 2014. For the 40 Percent it grew 49%, for the Ten Percent it doubled, for the One Percent it tripled, and for the top 0.001 Percent, average real post-tax income increased 616%.

Some people get much more income than others. We call this “income disparity”. The OWS Occupy Wall Street movement circa 2011-2 called it “income inequality”, a phrase that caught on. Some dictionary definitions of “inequality” connote unfairness, leading to conversational confusion over small, insignificant differences. Both “income inequality” and “income disparity” mean about the same thing, that is, a possibly unfair difference in incomes, with “disparity” connoting a large difference and a disregard for fair insignificant differences. 

From birth, individuals have differing talents, life experiences, and desires. As adult participants in the Society, their incomes aren’t mathematically equal. 

The differences among incomes are consistent, we may suppose, with the condition of our ancestors when they descended from the trees. If we can imagine ourselves there with them, one member of the tribe is good at hunting antelope, while another is good at sharpening arrows. Then the sharpener trades some arrows to the hunter for antelope meat. The sharpener gets food, and the hunter gets good arrows with which to kill more antelope. Together, they have more food to eat, and they are better equipped, than before they traded, but they aren’t equally provisioned with meat and arrows. 

The motif of trade recurs ubiquitously in FTC. The participants in a trade each exchange something they have for something else they want more. After the trade, each has more of that they valued more highly. 

A trade changes the distribution of goods in the Society. The Society can’t maintain equality of incomes, if ever achieved. We haven’t good reason to expect mathematical equality. Individuals will find things to trade

GDP and GNI in the United States being roughly the same thing, we can map out fuzzily how GDP and GNI apportion disparately in the Society... 

…, figures +/-5%, depending on the year. Thus, we can see there are significant subdivisions of GDP by who receives it, and in FTC we call them GDP01, GDP10 (= GDP09 + GDP01), GDP90 (= GDP40 + GDP50), the 2-digit number indicating the income stratum that gets the subdivision of GDP. See “The Fairy Tale of Capitalism: Workers, GDP and Economists” for details.

When GDP grows, who gets the benefits? During the 38 years from 1980 to 2018, in the United States, about one-half of growth was captured by the Ten Percent, and the other half by the 40 Percent, together the half of the people with the higher incomes. The bottom 50 percent got about zero, and some less than that. In her book “The Divine Right of Capital”, journalist Ms. Marjorie Kelly calculated that some groups’ slow-growing slices of the pie enabled the corporate profits slice to grow three times as fast as GDP in the United States in the late 20th century. 

The Staffs of the Ingenious Innovative Job Creators and the Aristocracy asserted that GDP growth brings a bright future. They urged lowering levels of taxes to cause growth of GDP, enabling the Downward Trickle (the waste stream of the Aristocracy) to distribute abundance to all. There were significant income tax reductions in the time of Reagan and thereafter through 2017. Moderate GDP growth occurred, though at gradually lower rates than earlier in the period that followed the Great Wars. Ordinary fluctuations accompanied the moderate growth, plus two booms and three big crashes. In the early period of the Great Wars, in the time of Harding, the United States Congress lowered taxes markedly. A boom ensued, then the Crash of 1929, and then the Great Depression.

In our enlightened modern era, GDP growth enlarges the pie, but about a fifth of the people get less pie ultimately, only half the people get any additional pie at all, only one tenth get significantly much, and one percent get abundance.

Professor Younkins didn’t mention Growth of GDP, nor its distribution, in his hymnbook “Commerce and Capitalism”, although FTC benefits from his many contributions. But that’s another story.

As evening turns to night, in our current Society, the Aristocracy lullabies their babies with “Competition among Workers makes certain that no one is underpaid” and other lines from the song “No One is Underpaid”, included in Professor Younkins’ hymnbook.  

FTC Ring: <Previous | Next>

I am indebted to my kind family members and friends who provided comments, guidance and critiques that shaped this article. 


“Cumulative Growth in Average Incomes” (Congressional Budget Office, https://www.cbo.gov/)

“Share of growth captured by income groups, 1980-2016” (WID.world 2017, World Inequality Lab, wir2018.wid.world

“Top 10% National Income Share across the world, 2016” (2018, World Inequality Report, https://wir2018.wid.world/files/download/wir2018-full-report-english.pdf)

“US GDP in billions of chained 2012 dollars” (US Dept of Commerce, bea.gov)

Notes and Sources

Definitions of “inequality” and “disparity”:

Daniel Brockman, “The Fairy Tale of Capitalism”, topics addressed in other articles:

Bureau of Economic Analysis, Department of Commerce, “Measuring the Economy” (2015, Public Domain, https://www.bea.gov/sites/default/files/methodologies/nipa_primer.pdf)

Bureau of Economic Analysis, Department of Commerce, “News Release, Gross Domestic Product” (Dec 21, 2018, Public Domain, https://www.bea.gov/system/files/2018-12/gdp3q18_3rd_1.pdf)

Jose DelReal, “Pelosi defends income equality push” (Jan 8, 2014, Politico, Fair Use, https://www.politico.com/story/2014/01/nancy-pelosi-income-inequality-101899, retrieved Mar 1, 2019) 

European Commission, et al, “System of National Accounts 2008” (2009, https://unstats.un.org/unsd/nationalaccount/docs/SNA2008.pdf)

Marjorie Kelly, “The Divine Right of Capital” (2003, Berrett-Koehler, Fair Use, https://www.amazon.com/Divine-Right-Capital-Dethroning-Aristocracy/dp/1576752372)

Bernie Sanders, United States Senator (Mar 16, 2018, The Guardian, https://www.theguardian.com/commentisfree/2018/mar/16/corporate-media-oligarchy-bernie-sanders, retrieved Mar 1, 2019)

Shobhit Seth, "GDP vs. GNP: What's the Difference?" (Mar 10, 2019, Investopedia, https://www.investopedia.com/ask/answers/030415/what-functional-difference-between-gdp-and-gnp.asp)

Benjamin Wermund, “The red state that loves free college” (Jan 16, 2019, Politico, Fair Use, https://www.politico.com/agenda/story/2019/01/16/tennessee-free-college-000867, retrieved Mar 1, 2019)

The World Bank, GDP & GNI data series (retrieved Jan 28, 2019, https://databank.worldbank.org/data/reports.aspx?source=2&series=NY.GNS.ICTR.ZS#)

World Inequality Lab, “World Inequality Report 2018” (Non-commercial use by CC license  https://creativecommons.org/licenses/by-nc-sa/4.0/https://wir2018.wid.world/files/download/wir2018-full-report-english.pdf)

Edward Y. Younkins, “Capitalism and Commerce” (2002, Lexington Books, Fair Use, https://www.amazon.com/dp/0739103814)

Mt. Rainier, 2019, image: Daniel Brockman