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.

 

 

 

 

 

President Trump is under the illusion that it is easy to win a trade war and it is projected that in the steel and aluminum industry 30,000 jobs will be created, while in the steel and aluminum manufacturing industry where most of the jobs come from 600,000 jobs will  be lost. One of the reasons is there was a practical reason why companies were buying non American made steel and aluminum – many of the companies making the steel or aluminum has American ownership or healthy American investors using the natural resources of another company. US Steel has plants in Canada, Mexico and the US, if a manufacturer bought steel outside the US but from a US producer is the product American or non American? As of mid July the President continues to issues more tariffs.

In the auto industry, German owned plants in the US exported vehicles to China, now German companies will be shifting production to China with joint ventures. BMW is doing a joint venture with Great Wall Motor Co to produce electric vehicles. BMW also announced it will be making more vehicles with partner Brilliance China Automotive Holdings. BMW sold 560,000 units in China which is more than the US and German markets combined.

Tesla announced in will begin construction of a new plant in China which will produce 500,000 electric vehicles a year within the next 2 or 3 years. Currently China exports the vehicles from its Freemont, California plant. Tariffs have added $30,000 to the price of the vehicles in China. Last year Tesla sold about 15,000 units or 3% of the market for electric vehicles. In terms of ranking that is 10th in the market but 17% of Tesla’s revenue.

Linking to dividend paying stocks, Presidents come and go, but corporate America makes decisions in the best interests of the company. If the interest of the company and the interests of the government are the same, so much the better. Manufacturers similar to every organization like to have options, there are more preferred options but options never the less. Political types can make silly policies, but  as long as companies are not buying into it and maximizing their returns, they are worth holding. If companies buy into the political musing of the day, find alternatives for eventually there will be change.

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

In every industry, people look to the leaders and try to copy them for it is normal thing to do for a person as well as in corporate strategy. In the world of movie production involving HBO and Netflix, according to Johanna Schneller, recently AT&T bought Time Warner and one of the media properties is HBO. The New York Times reported John Stankey who oversees Warner Media told a town hall meeting of 150 people that they will have to radically step up production this year. Mr. Stankey discussed the hours a day because we are competing with devices that sit in people’s hands that capture their attention every 15 minutes.

Ms Schneller disagrees with the idea because to her HBO has built a priceless alternative; a brand so reliable that people will try anything the service puts out, because they have that much faith in the network’s taste. Ms. Schneller sees Netflix as a generous throw it at the wall and see what sticks attitude. There has been some shows which are great but most are pleasantly good, not loyalty oath pledging fantastic.

The reason Netflix can produce more is highlighted in a book called AIQ by Nick Polson and James Scott, published by St. Martins Press, NY, 2018. In the book Netflix started out as a machine learning by mail. The company sent out red envelopes with DVDs and no late fees. Each envelope as the person to rate the movie between 1 and 5. As time went on, Netflix algorithms would look for patterns.

House of Cards was Netflix first try at producing a series rather than distributing it. When the production team pitched Netflix, after having been turned down by other studio who wanted to see a pilot to see how people reacted to it. Netflix said essentially we have run our data, and we do not need a pilot. To put that into perspective, in the year House of Cards premiered, the major TV networks commissioned 113 pilots costing $400 million. Of those only 35 went to be a series and only 13 ran in season 2. What did  Netflix know that the networks did not?

The pat answer is that Netflix had data on its subscriber base. (the networks had plenty of data to). Netflix had two things going for it: (1) the deep knowledge of probability required to ask the right questions of their data and (2) the courage to rebuild their entire business around the answers they received. Now days Netflix is where data scientists and artists come together to make awesome television.  Few organizations use AI for personalization better than Netflix. Personalization means conditional probability.

Linking to dividend paying stocks, Netflix and Warner Video are competing and both will churn out many hours to watch on TV or the tablet or smart phone. If the production company is correct more people will watch and advertisers will pay. If the show is being made to essentially fill up time slots rather than consider who is watching at what time and are they willing to buy a subscription? Turning out mediocre movies may keep an executive’s job, but if it does not draw the expected audience, perhaps the strategy of HBO will produce movies that were similar to the Hollywood era with a movie a week. and maybe one or two will be great. However the odds are against HBO becoming better than Netflix and Netflix and HBO reversing positions.

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

If you are focused on buying stocks which pay a dividend, unless the company has a monopoly and from an operation point of view the company is well run, then it will have multiple small competitors. Most of them will not challenge the company but some can and you need to be aware of what is happening in the marketplace. Recently Merge Gupta-Sunderji founder of Turning Managers into Leaders wrote an opinion piece in the newspaper titled How to spot warning signs of disruptive innovations.

When a young company outperforms an industry titan it is called disruptive innovation. The company often introduces new products or services to gain advantage over established competitors. If the new company is successful, the new company can replace the old one.

The issue for investors is no matter how much you “love” the established company, once the new one takes hold it is game over. The time can be still months away but the new company has gained traction that any efforts to reverse the tide is futile.

The signs needed to nip or see the potential threats:

Identify Potential Disruptions – Ensure the SWOT (Strengths, Weaknesses, Opportunities, Threats) Analysis is correct. LISTEN to your customers when your customers tell you their pain pints and who is stepping into relieving the ache. (It is easier to start with are there any little concerns you have with the company? listen and then ask about big ones). Companies that are addressing your customers’ complaints are the ones that pull ahead to disrupt your business. How does the company listen to complaints?

Determine Your Competitive Advantage – How does the company make profits? Why is better than the others?

Evaluate Your Disruptors’ Barriers – Look beyond the present. What barriers does your competitors have to go over to wipe out your existing differentiators?

Momentum – are customers there because they are used to status quo? Remember status quo can change.

Tech Implementation – will changes in the use of technology change your customers. As the world moves to the connectivity of everything how does that change your business.

Ecosystem– can the business environment shift?

New Technology – what has to be invented for disruption to occur?

Business Model – is the competitor following your business model or a different one?

Linking to dividend paying stocks, these are the companies that can be disrupted because they are profitable. The issue for you is to ensure you know how your company makes its profits and how secure they are. What has to change and how likely will it change while you own the stock. Many companies have a monopoly or monopoly like environment and that has worked very well for the companies. Will it continue and why would it continue?

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

 

If you invest in raw materials world or the minerals, quickly the companies you invest in will go beyond the reasonably stable democratic country where you live. Minerals are found around the world and in some countries due to the person in power, essentially bribes or royalty fees to the ruling cabinet must be paid. It is very hard to be in the mining industry only dealing with saints, invariably by any definition of the word companies have to deal with sinners. Recently Eric Reguly examined Glencore’s dealings with some sinners.

Glencore is one the world’s biggest commodities traders and miners. The example in the article deals with Glenore’s operations in Africa but with minerals it could be multiple countries around the world. Africa is blessed with endless resources to be tapped – cobalt, copper, diamonds, oil. In the more regulated countries, some of the dealings with the unregulated countries keeps the lawyers files filled and invariably companies pay a fine without admitting breaking the law. Recently the US Department of Justice filed a suit against Glencore alleging it had broke the law regarding the Foreign Corruptions Act. Glencore in the Republic of Congo used the services of Dan Gerler (who has ties to the President) with great success. The background is the mining of cobalt in which the Congo is home to 60% of the world’s known reserves.

Linking to dividend paying stocks, we all have choices in terms of investments and some companies are easily removed from seemingly wrong doing. For example, if you invested in ExxonMobil for the most part it tries to the right thing at healthy margins, however the history of how the Rockefeller’s gained a monopoly and controlled the oil industry at the beginning of the 19th century while healthy for investors was not in keeping with the ethics of Mr. Rockefeller’s seemingly personal ethics.  At some stage many companies prior to gaining a dominance did something to lessen the competition. It is after they gain a dominance that from an ethical standard they are more easily invested in.

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

 

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