Finance

This part of SpearBridge will be mainly dedicated to valuations, company profiles, macroeconomic outlooks and general investment ideas . Additonally, any new concept or idea related to finance that I consider worth writing about will find its place on this page. I anticipate this section of SpearBridge to be the most developed on the site, since I have a genuine passion for reading about financial markets and their key players.

 

Macro effects of automation, inequality and demographics

Our population is getting older and older.
New automation technology will put workers out of their jobs.
Wealth inequality is rising, and the middle class is shrinking.

These three trends are discussed abundantly in various journals and newspapers. However, very few research reports realize that these three trends should not be looked at individually. Rather than being isolated streams evolving on their own path, they are more intertwined and influence each other significantly.

In this article, I aim to show some of the effects that these trends will have on our economy and society and the cause-effect relations they have on each other.

The demographic shift towards an older society is marking the end of an era that was characterized by an abundance of labour. Since the 1950s three forces combined to create the fastest labour force growth in history: The integration of India and China into the global economy, the entry of women into the workforce and the entry of the baby boomers into the workforce. The contributions of these three forces that have fuelled economic growth for the second half of the 20th century is now fading since their contributions have largely been absorbed by the economies and there is not much room for incremental improvement. For example, in 1950 only 35% of the working age women were employed in the US. By 1970 the women participation rate rose to 50% and stands at around 75% today.

The Baby Boomer generation, which includes people born between 1946 to 1964, was born when the full effects of vaccinations and antibiotics led to sinking childhood mortality rates but before the mass introduction of birth control. The baby boomers are now entering the retirement age, which has massive effects on our demographics. Research states, that the population of those above 65 will grow faster than the working age population in the OECD countries. This would lead to a significant decline in our labour force growth rate.

One mitigating effect is that longer and healthier life spans have convinced baby boomers to defer retirement. Life expectancy in the OECD nations in the 1980s was around 73.5 years. By 2015, it had risen to 80.3 years. This has resulted in a rising effective retirement age which would reduce the negative effects on labour force growth.

However, we are not only experiencing a delay in the retirement age but also a delay in the age of entering the workforce. Cohorts in their teens and 20s tend to study longer and enter the workforce later.  The combination of these trends: older workers delaying retirement, young students delaying entry into workforce and baby boomers moving into retirement, does not alleviate much of the global deceleration in workforce growth. Bain & Company projects that the deceleration in labour force growth could result in a $5.4 trillion GDP shortfall by 2030 in the OECD countries.

What other implications could the increase in the number of old households have?

Well, old households, in absolute terms, are spending more due to their longer and healthier life spans. Between 1984 and 2015 US households that were headed by a person aged 75+ increased spending by more than 50%. Old households finance their spending largely through financial savings. As baby boomers begin using assets and pensions, the large-scale liquidation of financial assets could lead to a decline in their value. This could pose a risk to government pensions that relied on financial asset inflation to meet future obligations.

For corporates, talent acquisition will be a major theme in the coming decade. How can they incentivize millennials to work for their companies? Higher wages, flexible work arrangements and attractive corporate cultures (see Silicon Valley Tech companies) will certainly play a part in the incentive programme. Yet, what companies must realize is that the younger generation is looking to have a higher purpose of work, a sense of mission – providing that could be a valuable differentiator for companies in attracting and retaining talent.

Having considered the aspect of labour force growth, we will now look at the other factor that determines overall economic output: labour productivity growth.

Growth in labour productivity, as measured in output per worker, was relatively stable between 1980 to the mid-2000s in developed economies. Since the financial crisis in 2008, it has declined to nearly zero. There are two main forces that will determine the future growth rates of labour productivity.

First, labour productivity declines when workers shift to sectors in which less capital good options are available to improver productivity. The shift to a service focused economy moves workers from high productivity growth industries to low productivity growth industries. For example, between 1993 and 2014, the auto manufacturing industry in the US increased their output per worker by 128% while output per worker in hospitals only increased by 16% in the same period.

The automotive industry had much more options for capital good investments that made the production, assembly etc. much more efficient. The healthcare industry, represented by the hospitals, still requires a high degree of human action with less options of capital good investments making their services more efficient.

Also, the number of workers in the US automotive industry declined by 28% during 1993 and 2014, while the number of workers in US hospitals increased by the same number in the same time frame. This shift to lower productivity growth industries will likely continue for the foreseeable future.

Second, common consensus is that the new era of technological innovation will result in a strong increase in productivity as automation replaces or frees up human labour. Research states, that automation could put 20 -25% of the workers in the US out of a job in the US. The gap between the majority of the workers who will suffer from the negative impacts of automation and the few highly skilled who will benefit from it is likely to increase income inequality significantly.

Income and wealth inequality have been steadily increasing. The GINI Index for most of the OECD economies has been rising in the past 30 years. The GINI index measures the extent to which the distribution of income within an economy deviates from the perfect equal distribution. Consequently, a GINI index of zero represents perfect equality and 100 represents perfect inequality.

As mentioned in the beginning, the three forces – shifting demographics, automation and rising inequality are strongly linked. So how does the demographic shift effect income inequality?

First, an aging population typically increases inequality as older households tend to have higher levels of accumulated wealth compared to younger households at a similar socioeconomical level.

Furthermore, high income workers are more likely to be in occupations that do not require heavy physical work. Therefore, age related physical decline, is less of a restriction. Those in the bottom three income quintiles have a 64% chance of suffering age-related decline in the ability to work compared to 25% of those in the top quintile. As a result, high income workers work 77% more hours in 2006 compared to 1979 while those in the bottom 20% of income earners work 39% less hours in the same time frame. Adding to that, is the fact that people with higher incomes enjoy longer and healthier lives which enables them to sustain their period of wealth accumulation for a longer time.

Finally, we will look at how the increase in automation will affect inequality.

Experts analysis states that workers earning between 30 and 60k per year in the US will experience the greatest disruption from automation (disruption could mean displacement and depressed wage growth). The deployment of automation technologies is likely going to exceed the pace at which economies can re-educate and redeploy the millions of workers who will lose their jobs to automation. A study by the Federal Reserve Bank showed that a longer period of unemployment reduced earnings by 67% immediately and 32% 10 years down the road. Also, as automation spreads throughout the economy, occupations that are not easily automated, i.e. jobs requiring high social skills will experience strong wage growth. And since these are the jobs that are already well paid today, income inequality will be adversely affected.

Another aspect of how automation may increase income inequality is by increasing the share of income going to profits rather than wages. With increased automation, the share of income being produced by labour will fall. This means that labour will effectively also be entitled to a smaller share of the cash flows and the increased profitability, achieved by automation, would largely flow to capital providers (equity and debt investors). Generally speaking, capital providers tend to be in the higher income brackets, therefore the income gap will widen further.

As a final thought, the macroeconomic consequence of an increasingly unequal society seems to be a bit disturbing. If the higher income brackets of our society earn more income, they are most likely not going to spend that extra income. They are more likely to save the additional money than consume it. This would result in declining demand. Assuming automation will continue to increase the supply of goods and services, we would very likely be living in a demand constrained economy. This, in turn, will have big implications on what kind of monetary and fiscal policies and measures will work.

 

Source: Bain & Company’s Research Report:Labor 2030: The Collision of Demographics, Automation and Inequality

Andeavor – Comparable Company Analysis

Andeavor, previously known as Tesoro, is one of the largest independent petroleum refining, logistics and marketing companies in the US. Having been incorporated in Delaware in 1968, it is currently headquartered in San Antonio, Texas – where it is the only Fortune 500 company that has its headquarters there.
Andeavor’s business is organized into three main operating segments: Refining, Logistics and Marketing.

Andeavor’s refining segment refines crude oil into transportation fuels, such as gasoline, jet fuel and diesel fuel as well as other products including liquified petroleum gas. Oil Refining is the process in which crude oil (the unprocessed oil from beneath the ground) is processed into more useful products, such as diesel fuel or heating oil. This process consists of fractional distillation, where you heat the crude oil up, let it vaporize and then condense the vapor. By doing so, one is exploiting the difference in the boiling temperatures of the various hydrocarbons that make up crude oil.

Andeavor currently owns seven petroleum refineries in the US (2x California, 2x Pacific Northwest, 3x Mid-Continent) with a collective crude oil capacity of 895 million barrels per day. Andeavor purchases its crude oil from domestic markets such as North Dakota, Alaska and California as well as from foreign sources such as South America, the Middle East and western Africa. It transports the purchased oil to its local refineries through several pipelines and tanks, to which Andeavor is leasing access.

Andeavor also owns and operates several transporting facilities under its logistic segment Tesoro Logistics LP (TLLP). TLLP owns and operates several oil pipelines, trucking fleets, rail facilities and terminals with storage capacity for refined products. TLLP generates revenues by charging fees to third parties that require transportation or storage facilities of their oil products.

Finally, Andeavor’s Marketing segment sells diesel fuel and gasoline in the western area of the United States through various channels. Andeavor sells transportation fuels through third party distributors and retail stations that include brands such as Shell, Exxon and Arco.

I found the operating business of Andeavor extremely interesting and therefore decided to perform a comparable companies analysis of Andeavor and its peer group. I obtained the peer group from the “Competition” section of Andeavor’s 10-K form and sourced all of the relevant financial information for the valuation from the respective companies’ annual reports and Yahoo! Finance.

Immediately noticeable is that Andeavor and its peer group are trading extremely close to their 52 week high, which confirms the omnipresent topic of all-time high equity valuations due to the current low interest rate environment. Andeavor, as of the first of January, had the highest stock price among its peers and the second lowest market capitalization with around $18bn.

Also, Andeavor has seen a recent 23% increase in its stock price since Hurricane Harvey hit the Gulf coast on 17th August 2017. Andeavor doesn’t own or operate any refineries on the Gulf coast and therefore benefited from the subsequent spike in gas prices. This sharp increase in the  stock price seems to have been overly optimistic – which is why common sentiment is that a minor correction is due in Andeavors share price.

After this minor correction, however, Andeavor is going to be a solid investment. Given it’s highly diversified and integrated portfolio of assets and operations, Andeavor can provide strong growth opportunities across their value chains and is not completely exposed to adverse movements in the oil price. Its Marketing segment has added 544 stations to its branded Network through the acquisition of Western Refining that will further capture margin downstream within the value chain. The Logistics segment maximizes Andeavors overall performance by focusing on fee-based and stable business. This segment effectively acts as a hedge against adverse oil price movements. The Refining segment is efficient, reliable, strategically located and geographically diverse. Andeavor plans to enhance growth in this segment by capturing the synergies associated with the Western Refining acquisition, which are estimated to be around $350 to $425 million annually, investing in major capital projects and maintaining high utilization of its refineries.

While past performance is not necessary indicative for future performance, there seems to be no apparent reason why Andeavor should not continue to outperform the S&P 500 and its peers in the years to come. Andeavors portfolio is highly diversified, their Management team is experienced and strong and they are operating a very shareholder-centric business, which can only be beneficial for investors.

Tesla - Valuation and Profile

My first discounted cash flow valuation model attempts to determine the intrinsic value of Tesla. Tesla is one of the creations of serial entrepreneur Elon Musk and has been disrupting the automotive industry for years by eliminating the prejudice that owning an electric vehicle means compromising on speed, power or appearance of the car.
I felt that a DCF model was an appropriate measure to value Tesla, since in a DCF model most of the value is attributable to the terminal value. Since Tesla is projected to generate profits only after 3-5 years and has negative free cash flow before that time, a DCF valuation approach seemed plausible.
All my assumptions regarding growth and expenses are derived from company filings or Elon Musk’s statements. Since this is one of my first valuation models, there are some inputs that could have been calculated more precisely. For example: I obtained the Beta by regressing the weekly returns of Tesla on the weekly returns of the S&P 500 for the past 5 years. Since a simple regression is subject to variances, a more sound calculation of Tesla’s Beta would have been to calculate the average unlevered beta of comparable companies and then re-lever this Beta regarding Teslas targeted capital structure. However, I aim to try different methodologies in calculating inputs to see the effects of using different approaches.

See the following link for the valuation spreadsheet, and feel free to give any suggestions/feedback or improvements.
Tesla DCF Valuation                                                           

For a more holistic approach I have also created a company profile of Tesla, outlining the company’s historical performance as well as analysing the industry Tesla operates in.