In mid July, the President went on CNBC and discussed the fed policy. He later tweeted the same things, because he said as a private person I have views. Unfortunately, the President forgets or needs to be reminded he is not a private person, he is public figure and his view is taken very seriously. The President nominates the Chair of the Federal Reserve Bank and with just cause, the President can “fire” the Chair. The trick is the Federal Reserve is suppose to operate independently of the political structure.

The US President similar to all politicians going into the mid term or Presidential elections (in 2 years) wants the economy to be running on all cylinders or full steam ahead, the reason the overwhelming voters number one concern is their source of income. If a person is earning money from working they are likely to be more positive about the existing holders of public office.

The Federal Reserve is suppose to be independent because no politician wishes to raise interest rates, the politicians love to take credit for lower rates. Unfortunately, supply and demand means every once in a while inflation needs to tamed and the closer to full employment means inflation rises. Raising interest rates keeps inflation lower as well the Fed has to do quantitative easing or lowering the amount of debt which was needed to expand the economy after 2008.

In addition, the tax cut to corporations and the wealthiest individuals, most of it permanent helped stimulate the economy. Raising rates should lessen the stimulation as it does not need government assistance to keep going. If you add, the President discussing increasing tariffs on China and other countries around the world, then you have a problem caused by President Trump’s own policies.

The tweets moved the dollar, added uncertainty to the future and everyone said TGIF.

Linking to dividend paying stocks, often politicians who are reasonably new make mistakes because they fail to understand their words means investors need to react to them – both plus and minus. The President is almost 2 years in, there is no excuse for not considering the ramifications of his words. In the summit in Helsinki, the President had to correct his words, the markets will see if history repeats itself again.

There are more questions than answers, till the next time – to raising questions.

In an article in mid July, Ian McGugan wrote about disruption. The poster boys for disruption are Elon Musk and Donald Trump.

Disruption growing appeal is on display in corporate reports. Top executives routinely claim they are planning to disrupt their industries, while fighting off the potential for disruption for new rivals and eyeing the disruptive potential of the latest technology. Media organizations publish lists of the most disruptive companies – venture capitalists are excited.

Mr. McGugan writes about Elon Musk and President Donald Trump.

The overarching lesson is that genuine disruption is hard, risky unpredictable work. Sometimes there are great successes, most of the time there is not.

Investors should be skeptical. Evidence suggests the biggest winners are not self styled disrupters, but simply businesses that simply find smart ways to thrive within an existing sector.

If you bought the same amount of shares of Google’s parent Alphabet or Domino’s Pizza which shares would have given the highest total return? It turns on to be Domino’s.

The idea you can pick out great disrupters early on seems particularly far-fetched. A classic 2001 Study by Louis Chan, Jason Karceski and Josef Lakonishok found there is no persistence in a stock’s long term earnings growth beyond what you expect from chance. Today’s high flier maybe a dud in the near future.

Linking to dividend paying stocks, there is glamor and excitement about stocks that cause disruption, but there are steady earnings and profits for a duller company and in the long run which one do you want to hold most of your investments in. Ensure you have some money in the glamor or hot industry, but be willing to know when to sell if you do. Many individuals and institutions have seen companies go up and come down faster. Institutions remain because by law they have to be reasonably diversified. Individuals the opportunity to rebuilt takes longer. If you invest in profitable stocks that pay a dividend, life will be easier for you.

There are more questions than answers, till the next time – to raising questions.

 

In an article by Eric M Johnson and Tim Hepher of Reuters, Boeing’s Chief Executive Dennis Muilenurg said he is concerned about tariff talks and higher prices in the supply chain. (the author recently bought a hot water heater and prices had gone up because of possible tariffs)  At the end of July, Boeing had not seen any impact with US-Chinese trade.

The supply chain is where the parts of the aircraft are made. The final assembly plants are in  Washington State and South Carolina and maybe China. The parts come from around the world.

Mr. Muilenburg said Aerospace thrives on global trade, free and open trade. Boeing is one of the US biggest contributor to balance of payments, selling planes around the world creating thousands of jobs. Mr. Muilenburg spoke at Britian’s Farnborough Air Show which is an airshow which many purchases of planes signings are announced.

Boeing is in the midst of creating a new plane and has a target date of 2025. The plane would be more economical to run than existing planes. In the airplane world, there are airliners flying 757 and 767 fleets and they are beginning to need replacement.

Linking to dividend paying stocks, as a leading aircraft manufacturer, Boeing has to look into the future to determine what planes will be needed. As India and China develop a middle class able to travel by plane, thousands of planes are needed. Trade wars and tariffs ruin short term planning. Similar to large manufacturers based in the US, while the main product may be finished in the US, most of the parts come from somewhere else. Politicians or at least the President may feel trade wars are winnable, but if China decided to buy more from Airbus, then no matter how great Boeings are, fewer planes would be sold.

There are more questions than answers, till the next time – to raising questions.

 

Artificial Intelligence is and continues to change the way we see things and the way we do things. For much of our lives there has been conventional wisdom, there are strong elements why conventional wisdom has lasted, but is it the best approach? In a recent book written by Nick Polson and James Scott titled AIQ published by St. Martin’s Press, NY, 2018, the authors examine artificial intelligence – what it is, how it works, where it comes from and how to harness its power for a better world. Note the optimism in the authors expectation, AI can help make the world a better place.

It is not unusual for 2 different published research findings to look at different data sets and find different answers to the same questions. This is often how science works. Only overtime does the evidence accumulate convincingly in a single direction.

AI has limitations, one can use the same data and come up with different conclusions and reports have done that. The lesson is simple, algorithms do exactly what they are told, there are biases or assumptions in the program. In reviewing data, find out about the assumptions to see if you agree or not. The assumptions are made more important because the consequences of a bad one can be amplified over and over again. What do you look for:

Rage to conclude

Model rust

Bias in, bias out.

Most calculations in data science require assumptions of one kind or another. The first was constant probability and the second is independence. Why are they related?

Data scientists have a favorite saying: all models are wrong, but some models are more useful. No model is perfect.

Linking to dividend paying stocks, over the course of investing you will see many projections. Some are right and some are wrong, learn from the ones that are wrong. What was the assumptions and why did it go wrong that you can easily notice. Start with the basics and build on them, why was a projection rate used? why are people going to buy the goods and services? by approaching the reports with a bit of cynicism you will save money, which means you will earn more.

There are more questions than answers, till the next time – to raising questions.

 

 

Artificial Intelligence is and continues to change the way we see things and the way we do things. For much of our lives there has been conventional wisdom, there are strong elements why conventional wisdom has lasted, but is it the best approach? In a recent book written by Nick Polson and James Scott titled AIQ published by St. Martin’s Press, NY, 2018, the authors examine artificial intelligence – what it is, how it works, where it comes from and how to harness its power for a better world. Note the optimism in the authors expectation, AI can help make the world a better place.

One of the things the examination of large data can do is to look for variability or anomalies. As computers have speeded up and we look to 5G on the phone, the ability to find differences can make decision making easier.  The basic elements are:

data collection: several measurements are taken of some underlying process

averaging: all the measurements are average to provide a snapshot of the process

decision-making: is the average close what you expect and what is outside the bounds of normal variability?

The basics over the centuries has remain the same: to detect an anomaly you have to understand variability.

The author’s use  credit card companies as an example. There has always been some element of fraud in the system. However with the help of modern algorithms and modern supercomputing infrastructure, PayPal has lowered its fraud rate to 0.32% of revenue. The system uses deep learning to compare every transaction with your own past behavior, as well as the behavior of other users similar to you. On the basis of that comparison which uses other features, the system produces a fraud score  to accept or decline the transaction all within a fraction of a second.

Linking to dividend paying stocks, as systems improve so does detecting fraud. If you own companies that offer credit you need to use the fraud write offs as a comparison to find the best alternative. Fraud is money lost, if a company can lessen the fraud more revenue flows to the company and the shareholder.

There are more questions than answers, till the next time – to raising questions.

 

Artificial Intelligence is and continues to change the way we see things and the way we do things. For much of our lives there has been conventional wisdom, there are strong elements why conventional wisdom has lasted, but is it the best approach? In a recent book written by Nick Polson and James Scott titled AIQ published by St. Martin’s Press, NY, 2018, the authors examine artificial intelligence – what it is, how it works, where it comes from and how to harness its power for a better world. Note the optimism in the authors expectation, AI can help make the world a better place.

Finding lost objects in deep water is a challenge and the leading expert for the Navy is Dr. John Craven. Their are multiple methods – ideally machines that go in the water have GPS type signals, however Dr. Craven’s preferred strategy is Bayesian search.

the essence is Prior Beliefs + Data = Revised Beliefs.

Start with what you know through plotting on a grid.

Add data – what is known to your search and you have narrowed your field.

Do work, if you come up with nothing, start again by moving to another square in the grid. Repeat until you are successful.

Dr. Craven was tasked at finding a submarine which went missing somewhere between Spain and the US without a single clue. He caught a break, the government had spent $17 billion on listening devices in the Atlantic. He examined the records and found an unusual series of sounds. He had the ability to narrow down the scope of the task. Next came adding multiple scenario and running simulations to see how the submarine should have responded. After the research they put together a grid and while no one publicly knows what happen to the submarine – it was found within 260 yards of Dr. Craven’s team best estimate.

The author’s examine whether it is better to do index investing or be influenced by great marketing? The authors use Bayes’ rules and determine while great managers do exist, they are very rare. If you try to follow Warren Buffett remember he is buying profitable companies with a near monopoly position which implies they will remain profitable for a number of years. Through his insurance holdings cash position he is able to leverage his purchases and he loves cash generating companies.

Linking to dividend paying stocks, you may not call what you do Bayes’ rules but it is always important to continually educate yourself or add data to what you know and do not know. Try to understand how companies earn their income and can leverage the data they collect to continually earn profits. The more you understand, then you can find a price the stock looks attractive to you. If you buy dividends you are thinking long term which allows patience in your decision making.

There are more questions than answers, till the next time – to raising questions.

Artificial Intelligence is and continues to change the way we see things and the way we do things. For much of our lives there has been conventional wisdom, there are strong elements why conventional wisdom has lasted, but is it the best approach? In a recent book written by Nick Polson and James Scott titled AIQ published by St. Martin’s Press, NY, 2018, the authors examine artificial intelligence – what it is, how it works, where it comes from and how to harness its power for a better world. Note the optimism in the authors expectation, AI can help make the world a better place.

Within the book are some great and compelling stories which lead to the conviction, AI although there should be and will be concerns, on balance it is good for society. The issue remains how to interpret data for solutions. For generations and generations or through out history, governments and corporations have collected information. What they do with most of the information has been limited, now it is possible and probable there will be interconnectivity of the information. This can be very good for society.

To begin with you need to learn and understand a key concept called personalization or conditional probability. In math, conditional probability is the chance that one thing happens, given that some other event has already happened. The classic example is the weather forecast, if the forecast on your phone says rain 60%. Data scientists write this as P(rain this afternoon | cloud this morning) = 60%. P is probability;  the bar | in the brackets means given or conditional upon. To the left of the | is the event we are interest in. To the right of the | is our knowledge, also called conditioning event or what we believe or assume to be true.

Personalization run on conditional probabilities, all of which must be estimated from massive data sets in which you are the conditioning event.

The core idea behind personalization came from Abraham Wald who worked in Columbia’s Statistical Research Group and one of the clients was the military’s Office of Scientific Research and Development. Wald came up with a solution known as sequential sampling which show how factories could produce fewer defective tanks and planes just by implementing smarter inspection protocols.

Another project Wald worked on was devising personalized survivability recommendations for aircraft. In WW II, the military sent planes to drop bombs on the other side, many of them did not return. How do you improve the chances more would come back? Wald came up with an algorithm to improve the survivability of any model plane using data on combat damage. His task knowing the conditional probability that a plane has taken damage on the fuselage, given that it returns safely. The question to be answered was what is the conditional probability that a plane returns safely given that is has taken damage on the fuselage?

It is important to note conditional probabilities are not symmetric. It is very important to be clear about which event is on the left side of the bar, and which side is on the right side of the bar.

Wald needed to estimate how many planes had damage to the fuselage and never made it home? Wald’s model after examining most of the possibilities of how a plane could be shot down to have reasonably accurate assumptions solved the problem from any of the navy’s planes. Conditional probability plus careful modeling of missing data proved to be a lifesaving combination.

Linking to dividend producing stocks, there will always be information you do not know, it is possible to do analysis to estimate, but there are numbers of the company you do not know. Fortunately there are things we do know, in general profitable companies will trade at higher multiples than non profitable companies; if there is a downturn in the economy dividend producing companies lose less than the general market and bounce back sooner. If you pick stocks from dividend companies your total return will often beat the market index.

There are more questions than answers, till the next time – to raising questions.

 

In mid July, Ian Tam of Morningstar Research examined the top S&P 500 companies paying reasonable dividends with enough cash to pay them.

The criteria he used was:

S&P 500 stocks

Dividend yield

Quarterly and Annual Cash Flow Momentum ( past 4 quarters of operating cash flow compared with the same figure one quarter and 4 quarters ago)

5 year variability of earnings ( a measure which shows how steady a company’s earnings have been over the past 5 years – what a low number)

Payout ratio on earnings less than 80%

payout on operating cash flow less than 60%

companies show positive earnings in their latest reported quarter

dividend yield of greater than 1.33%

Company              Mkt Cap   Earnings  Div Yield  Ann CF  Qtrly CF   Payout on   Payout on

($ Bil)       Deviation  %            Mo           Mo              Earnings %  Oper CF

Wells Fargo           275.902     1.9            3.0          80.9          18.8              37.2                n/c

Altria Group          111.212    2.7             4.8           79.2           5.1              72.9               67.7

Southern Co            47.890     2.9            5.3            65.3           2.4               71.6              30.9

UPS                            93.501    2.4            3.4              18.9         94.7             54.4              52.0

Newell Brands         13.424    4.2           3.3              44.1         20.2              33.5             35.5

Regency Realty        10.450    6.4            3.6             47.7         18.8            146.1             57.0

Bank of America    292.317    10.1         2.1               75.2       24.7              22.0               9.5

PPL                              21.580    4.6           5.8                9.4       13.9               67.3             38.5

AT&T                         199.582    2.7           6.2                4.9          2.8              62.3              28.6

Prudential Fin           40.744    7.4           3.7               61.9         0.8             29.0              15.5

The other companies in the chart were Kimco Realty, Ameriprise Financial, Verizon Communications, Omicom Group and Johnson Controls

Linking to dividend paying stocks, one never knows when the market goes down but being defensive with dividend paying companies means you will loose less. In 2008, if you own these types of stocks the market went down 37%, these went down 19.9% and came back faster. The above are a mixture of banks, utilizes, and consumer services. If you do not own one, the price will move up and down – put them on your list to buy at a good price and remember dividends count as total return.

There are more questions than answers, till the next time – to raising questions.

In mid July David Milstead wrote a column about banks using information from Bloomberg. President Trump in his first year and a half asked the banks which regulations they do not like and try to eliminate them, this plus the corporate tax sent bank shares higher. The result in the past was according to Chris Kotowski, an analyst with Oppenheimer & Co resulted in the banks becoming highly leveraged, heavily regulated, cyclical commodity companies with a history of blowing up every decade or so. Earning reports were beginning to come out in mid July and that is why the topic was chosen to be written about.

Mr. Kotowski noted bank stocks historically trade at 735 to 78% of the market P/E and at July 4th they were at 64%.  Bank balance sheets are probably less risky that any time in the past 30 years which should lead the shares upwards to their historical P/E ratios.

The problems include a new found focus on deposit beta or the proportion of changes in interest rates that banks pass along to their customers in the form of higher interest rates on deposits. Conventional wisdom is  banks can pass higher costs from the federal reserve raising interest rates, but the deposit beta tries to answer how well do they do it?In a June report, analysts at S&P Global Market Intelligence said the number averaged 19.6% in 2017, but it was 72.5% in the 4th quarter. They forecast 45% for the full year. Thus it seems the conventional wisdom is not fact.

Another concern is the yield curve between the 10-year Treasury and the 2-year Treasury is flattening. Peter Winter of Wedbush Securities says the yield curve has narrowed to its lowest level since before the financial crisis. It is note able that every recession in the past 60 years has been preceded by an inverted yield curve, which is why investors are focused on the shape of the yield curve.

RBC analyst Gerald Cassidy says investors should continue to own 3 types of bank stocks – Return on Capital (those that raise dividends and buy back shares); Risk On stocks (a more aggressive belief in the sector’s potential) and Multiple Revaluation (banks that should be favored as investors warm to their prospects.

examples Return on Capital – Bank of America, Regions Financial, Citigroup, M&T Bank, PNC Financial and SunTrust Banks

Risk On – Bank of America, Citigroup, JPMorgan Chase and Key Corp

Multiple Revaluation  PNC and BB&T

Linking to dividend paying stocks, it is very hard not to own bank shares in  your portfolio because as credit goes so does the economy. The previous administration put in regulations to keep the ability to leverage joined to earning the money back or with the money be repaid. Often times when banks have blown up, it is because many of the borrowers can not repay their loans or the risky part of the portfolio became too large. If a sector is trading below its historical average it may be a good time to buy, just do not use too much margin.

There are more questions than answers, till the next time – to raising questions.