AI

Foreword

The world is ablaze with talk and speculation on Artificial Intelligence (AI), with untold billions of dollars poured into AI related companies.

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Words

Before we delve into the topic, a very brief history of AI and its related fields in the form of a mini glossary:

Artificial Intelligence (AI)

The term AI was originally used to mean intelligence that rivals that of the average human, and which was created by humans (i.e. not natural). The formal study of reasoning and how it can be applied via computer science began in the 1940’s, and over the decades, many have herald the imminent emergence of AI. Over the decades, many have been wrong about the imminent emergence of AI.

Machine Learning (ML)

ML is a term specific to computer science, and describes a field of study that encompasses many different technologies. ML is differentiated from AI in that while it aspires to human-level intelligence, it is mostly concerned with how to make machines (specifically computers) “smarter”, to learn and to improve.

Artificial Neural Network (ANN)

ANNs are an application of ML, i.e. a technology created as part of the study of ML. First invented in the 1970’s, ANN seeks to mimic the human brain by defining computing nodes akin to human neurons. These “neurons” are then connected to each other via a hierarchical layer structure. Each “neuron” operate independently of the others in the same layer, and all “neurons” in the same layer get input either directly or transitively from “neurons” of prior layers, with the final “neuron(s)” being the output of the entire network.

ANNs, and a close cousin Hidden Markov Models (HMMs), have been used very successfully over the decades in various applications, providing impressive results.

There are various specializations of ANNs, such as Deep Neural Networks (DNNs, aka Deep Learning), Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), with each preferred for their own niches of ML.

Large Language Model (LLM)

Large Language Models (LLMs) encapsulate many of the features of the above, and a lot more not discussed, and have been extremely successful in producing almost human-levels of prose. Recent (circa 2023) developments in LLMs have resulted in the ability to generate not just text, but also other contents such as graphics and video. These latest developments are coined Large Multimodal Models (LMMs), and today, the terms LLM and LMM both generally refer to the latter.

The simplest (and somewhat crude) way of describing a LLM is that it is a statistical prediction model — given a stream of input such as words, what would be the most likely output (such as words of a prose, or pixels in a picture).

Grade inflation

Today, the term AI is used interchangeably with ML, or more specifically LLMs. This is despite the fact that most practitioners agree LLMs are not quite on par with human-level intelligence. To differentiate human-level intelligence and what LLMs are capable of today, a new term Artificial General Intelligence (AGI) was coined to refer to what AI used to mean.

I’m more of a traditionalist when it comes to definitions, and am not a fan of this marketing gibberish and rampant grade inflation, so for the rest of this post, I will be using AI to mean the original definition above.

State of the art

As mentioned above, as of this article, LLMs are extremely capable of producing prose and visual content that is at almost human level. In particular, many have found great success with using LLMs to produce code (also called Vibe Coding), where the user uses spoken English as input to the LLM in order to get it to produce (hopefully) useful source code, such as in C++ or Python.

However, as LLMs are not really thinking models, but rather statistical prediction models, they are prone to errors, sometimes called hallucinations. Nobody really understands what causes hallucinations or what they mean, but my personal take is that it is an artefact of the LLM being fed inputs that it simply hasn’t encountered in training before, and in such a way that its interpolation or extrapolation of the input results in output that is simply garbage.

There are techniques to working around hallucinations, such as feeding the output back into the LLM and asking it to rework or rethink through its response, effectively a mulligan. However, this is generally only applicable when the user can recognize that the output is wrong — if the user simply does not have the ability to evaluate the correctness of the output, then chances are the user will just end up believing the garbage.

Practical concerns

Despite the hype of the imminent emergence of AI, I am less optimistic. But even without AI, ML (and LLMs) can be of practical use. There are many areas where it is fairly easy for the user to verify the correctness of LLM output, such as when vibe coding (if the code compiles, and if the code does what the user wants), prose generation (user can read the prose) and graphics/video generation (look and see!), and in these respects, LLMs have proven to be huge time savers and productivity boosters.

Central to these use cases is the cost benefits analysis — if it is more cost effective to have a human produce the content, then it doesn’t make sense to have LLMs do it. Today, the cost to end-users of using LLMs is pretty cheap, with pricing around single to low double digit dollars per million tokens, where you can think of a token as somewhat like a “sub word” (some words cost one token, others may cost more). With the Lord of the Rings trilogy being less than 500k words, a million tokens is plenty!

And this is where hallucinations come in. The problem with the above paragraph is that while in the ideal scenario, you can almost produce the Lord of the Rings trilogy with a million tokens (~$10!), the reality is that you’ll likely end up with garbage — hallucinations tend to creep in pretty quickly, and without constant human supervision to read the output and force the LLM to redo/rework parts of the output, it simply won’t be very good.

In the end, in order to produce 500k words of actually useful and entertaining prose, the user may end up spending many millions of tokens, with most of them wasted due to hallucinations. More importantly, a lot of human time will be consumed reviewing and effectively redoing the LLM’s work.

Whether this is worth it depends a lot on the project at hand and the user’s circumstances. As an example, for someone who is not trained in computer science, being able to just produce any code would be a huge win. But for a trained and seasoned software engineer, the benefits can be much more dubious, especially when you are considering mission critical code where subtle bugs and security implications are not obvious and the inexperienced will simply not be able to even realize these issues need more thought/work.

My take

My personal take is that as things stand, LLMs are not going to lead to AI, absent dramatic changes to the fundamental basis of LLMs, such that whatever comes out will not look very much like the LLMs of today.

At their core, LLMs and all other related statistical prediction models are generally very good at predicting the “next thing given a series of things”, but are pretty terrible at innovation and making decisions based on novel situations — both critical components of intelligence as most would understand the word. Recall from the examples above, that a human supervisor is still needed to ensure correct output!

In my opinion, LLMs may very well form parts of AI, if and when it emerges, but won’t be the whole. Instead, I have been toying with the idea of a “meta model” — essentially a “thinking” and “decision making” layer on top of a bunch of other “doing” models.

For example, the “meta model” may decide that “for the problem at hand, we need to generate an essay about AI”, and hand the task off to a “doing” model that is based on an LLM. Or it may decide that in order to generate that essay, the LLM needs to be supervised by a more generalized RNN model that researches the output of the LLM to validate correctness in an iterative process — in this case, the RNN model, possibly with aid from the “meta model” will do the work of what the human supervision would be doing today.

This paradigm has benefits — the “doing” models can be specialized to various tasks for which they are best suited. Many tasks required of humans can be easily graded as “right” or “wrong”, and it is in these well defined problem spaces that LLMs thrive. Building bespoke models tailored to specific tasks has, historically, been an extremely successful approach in ML.

What, then, would be used to build this “meta model”? Honestly, I have no idea. If I were to guess, it’d be some hybrid of HMMs and ANNs. HMMs are good at predicting things based on internal, unobservable states and ANNs are good at predicting things based on historical correlations. But that’s just me.

Finance

What does any of the above have to do with finance? This is, after all, a finance blog! Well, a lot.

There are many avenues to invest in LLMs, from NVidia stock (still the gold standard of GPU chips, a critical component of building and running LLMs), to private investments in various LLM startups, to datacenter providers (GPUs need to be put somewhere), to hyperscalers that provide a more hands-off approach to dealing with the hardware.

The key to remember is that as of today, no LLM startup is profitable — all of them are burning money like there’s no tomorrow. Even more concerning, many businesses renting out the hardware for building and running LLMs are arguably in the red, with dubious progress toward profitability. Pretty much the only companies reaping outsized profits in this space are NVidia, and a handful of smaller energy and component suppliers. Actually running the hardware or LLMs has been extremely disappointing from a PnL perspective, despite the huge amounts of investments made.

No hope?

That’s not to say that there’s no hope. With enough research, it might be possible to pivot an LLM startup to actual profitable use, for example by focusing in a vertical where LLMs are particularly suited.

Also, somewhat more cynically, speculating in LLM companies can be profitable for investors if the companies get acquihired by larger players not so much for their products, but for their human talents, in a giant game of greater fools.

It is somewhat ironic that in the business of AI, the most valuable products thus far appear to be the humans.

Weekend video binge

To end, a trio of videos from notable people in the field discussing AI and LLMs. Enjoy!

Tariffs

Foreword

The SPX just had its worst week since 2020. You know, the year where everything shut down. Because of tariffs that everyone was warned about, for almost a year now. What happened?

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Boom! Tariff the World

After the market closed slightly up on Wednesday (4/2/2025), the president announced the actual tariffs that he and his team have been talking about for months (since before they were elected).

Despite having been forewarned about the tariffs for almost a year, the next day (4/3) markets dropped the most in percentage terms since the early days of 2020 around the start of the pandemic, and dropped even more the day after (4/4). Combined, this is the largest weekly percentage drop of the SPX since the chaos of early 2020, and the largest absolute 2 days points drop ever.

Tariffs He Wrote

Despite the tariffs being announced well ahead of time, it was still shocking because the administration had been touting a “reciprocal tariff”, but when the details were revealed, what actually happened was anything but.

Reciprocal tariffs on most nations would amount to at most 10-20% for most items with a large number of items excluded. Instead, the administration went as far as to tariff effectively every nation by at least 10% for all imports, with some going as high as 50%. To justify the tariffs, the administration came up with what looks effectively like bogus tariffs the nations supposedly charge US exporters, even claiming that an uninhabited island populated mainly by penguins is charging tariffs on US exporters. I guess they don’t really like US fish?

Penguins tariff US exporters by 10%

After many commentors cried foul, the administration finally came clean and noted that the supposed tariffs imposed by other nations on US exporters is really just the ratio of US trade deficits to US imports from the country, with a 10% minimum cap.

To be absolutely clear, as many journalists, economists, financial advisors, finance professors and commentors have noted, this equation is utter bovine feces — despite dressing up the explanation with fancy maths symbols (that mean nothing!), the equation is meaningless in both economics and finance, an entire fabrication out of thin air.

Trade Deficits

In this one, incredibly unsophisticated, move, the administration has shown that it is deeply concerned about US trade deficits. So let’s talk about that for a while.

To simplify somewhat, a trade deficit is when a country (USA in this case) exports less to another nation than it imports from that nation. The deficit is simply the dollar amount of the difference between exports and imports to/from that nation.

As a general rule, deficits between 2 nations is a non-issue. Since trade is global and bilateral between different nation pairs, it is inevitable that there is an imbalance in trade between any 2 nations pair.

For example, Madagascar exports mainly vanilla beans to the USA, something that does not grow very well on American soil and climate, and so the USA has no real vanilla bean industry. However, because Madagascar is so poor, with the average person making just over $500 USD a year, there simply isn’t a lot that the average Madagascan can afford, and thus they simply don’t import a whole lot from developed nations which generally produce higher value added, and higher priced, goods — when you make $500 a year, an iPhone really isn’t something you think much about.

In theory, this trade deficit “goes away” when we consider the entire world. Let’s say the US imports a lot of Chinese stools, but exports a relatively smaller amount of tables to China — the US has a trade deficit with China. In the idealized Econs 101 case, this is fine because, in theory, the US will have a trade surplus (exports more to this country than the US imports from this country) with a 3rd country, say, Germany. Germany in turn has a trade surplus with China. So while every nation in our 3 nations scenario has a trade deficit with one nation, they also have a trade surplus with another, and the balance of trade (the sum of all trade deficits and surpluses for a single nation) will be 0, or at least very close to 0 over time, for all 3 nations.

In practice, this doesn’t really work. Empirically, we know that most developed nations have been consistently running balance of trade deficits for years, if not decades. There are many reasons for this phenomenon, but a large part of which is what the president said he is trying to address — unfair competition from some countries, such as China, where a combination of state level subsidies to domestic producers and tariffs or other barriers to foreign producers result in extremely one sided trade dynamics.

Face Off

But are trade deficits really bad? Think about it — some country is putting their citizens to work, and putting in their natural resources, to make a product that they then send to us. That country has spent non-trivial amounts of resources to produce that product, and in return, all they want from us is a few pieces of green paper. Green paper that we, as a country, can create almost for free.

In fact, Milton Friedman, a celebrated economist, made this point exactly.

Now, if you look at it from that perspective, it would seem that America should strive for larger trade deficits, not smaller!

Of course, reality is not quite so simple. There are very good reasons why a country would want to have a smaller balance of trade deficit:

  • It is painful for those workers who are displaced by foreign goods. Yes, perhaps if you reduce the balance of trade deficit, you’ll incur a larger loss of jobs via not creating jobs in new industries that are never borne as the necessary inputs are never imported (as part of reducing your deficit). But as Milton Friedman notes (in the video above), those displaced are real people, with real voices, while those jobs that you never gain? They don’t exist yet, and thus have no say in the matter.
  • If a country allows its industries to atrophy due to cheaper foreign imports, then at some point, expertise for producing those goods will be lost to that country. This means that any future goods based on that product may not be invented in that country simply because it doesn’t have that industry anymore. For example, a country is unlikely to invent the next generation of chips if they don’t even a chips industry.
  • There are some products that a country needs in order to be independently strong. For example, steel is needed to build weaponry, and if a country imports all of its steel, then it is at the mercy of whoever sells it that steel — if they cut off supply, and then invades, the country will be in a pretty serious pickle.
  • A large and prolonged balance of trade deficit is not sustainable. It may not be an issue in the near term, and problems may not emerge for many decades, but eventually, a country’s trade partners may find that they don’t really care for anything it produces, thus they have no need of its green pieces of paper, so they just cut it off from their goods. What then? Without industries, and without the expertise to restart those industries, the country would be at a dead end.

In summary, while deficits in the short term are good — they improve the average standard of living of the country’s inhabitants, in the long term, they can cause very serious issues for the country as a whole.

Sliding Doors

To be clear — I agree in general that a country needs to protect certain critical industries in order to remain independent and prosperous, and that tariffs are one of the tools to achieve those ends.

However, this needs to be better thought out and implemented. From inauguration day till just before the tariff details announcement on 4/2, the president made around 20 tariff announcements (in around 2 months!), most of which were changed or rescinded completely within days, if not hours. And then, out of nowhere, he announces tariffs that are wildly out of proportion to their stated intent, with what many speculators are saying seems like the output of a particularly bad LLM hallucination.

At the same time, the flipflopping of tariff policies resulted in serious business paralysis. Businesses typically order their inputs months in advance. If they cannot be sure what price they’ll ultimately pay for the inputs (since payment and tariffs both apply after the goods arrive), they simply cannot make any major decisions with regards to their supply chains and operations.

Finally, it is important to recognize that it takes years to build factories and to plan out supply chains. You simply cannot impose a tariff and demand companies shift their productions onshore in order to avoid the tariffs the next day. In the short run, there is nothing a company can do about their current supply chain, so they are forced to pay the tariff, even if they want to onshore their productions eventually.

If the short term goal of the tariffs are indeed to rebuild America’s industries, I’m all for it. But we have to recognize that rebuilding America’s industries is to serve a longer term goal, which is to strengthen the nation and enrich its people. Trying to rebuild industries by creating chaos in the business and international trading landscapes, while simultaneously alienating and insulting our allies is going to isolate America while making it that much harder to do business either domestically or internationally — the exact opposite of the end goal of a strong and prosperous nation.

Inflation

As discussed in Politinomics, tariffs are inflationary. There are some who argue against this, but I believe those arguments are wrong.

Some argue that tariffs are not inflationary because if the imported good becomes more expensive because of the tariff, consumers can simply substitute with domestic goods. This is a flawed argument, because it conflates inflation with inflation measures.

A similar argument is that as foreign goods become more expensive, it’ll trigger a recession, because consumers simply cannot afford to consume as much goods. As recessions are deflationary, the argument then concludes that tariffs are deflationary. Again, I believe this is a flawed argument, for the same reason:

As mentioned in Inflations, inflation measures are very flawed, though they are pretty much the best that we have right now. One pet peeve of mine about most inflation measures is that they usually take a basket of goods at some point in time, then measure the change in prices of those goods over some period of time to compute inflation rates. Most measures use baskets based on what consumers actually buy, which seems reasonable, except that it has a “too expensive” problem.

Imagine that you are currently able to afford to eat out every meal. However, for whatever reasons, restaurants all around the world suddenly raise their prices by 1,000%, though all other goods and services remain at the same prices. After the price hikes, you no longer are able to afford to eat out at all, so instead, you cook at home, which turns out to be cheaper than eating out before the price hikes, though it is not your preference.

In our scenario above, would you say that inflation is up, down or flat? Most people would say that inflation was up, despite the fact that you are now spending less money cooking at home. However, most inflation measures that use the “basket of goods consumers buy” approach will initially register a spike in inflation (due to the 10x increase in eating out costs), until the basket of goods is updated to reflect that you no longer eat out, at which point it’ll register deflation, because now you are spending less money on your basket of goods.

Obviously, this is wrong — inflation clearly went up, the fact that you are no longer able to afford your previous lifestyle is testimony to that.

Finally, the last argument I’ve heard is that tariffs are paid for by the exporters, and that somehow, tariffs are a tax on the exporters and so consumers will not see price hikes. Empirically, this is wrong — multiple goods are forecasted to go up in prices, and multiple companies have stated that they plan to hike prices in response to the tariffs.

The key to remember is this — businesses are commercial ventures, they need to make a profit to survive. There is no business in the world that can survive losing money perpetually (companies that do that are called charities, not businesses, and they are funded by donations).

Now, some may claim that businesses are making so much money, they can afford to make a little less. That argument may sound correct, right up till you look at the details. Most businesses (outside of tech and finance) make profit margins of around 5-15%. Retail businesses, in particular, are famous for having razor thin margins, some as low as 1-3%. What do you think happens if you are making 10% margins, and then a minimum 10% tariff is imposed on the inputs into your businesses? 10 – 10 = 0.

Immediately after the tariffs are imposed, some businesses may be able to raise prices, while others may not raise prices for a while. For example, companies which sell mostly online tend to be able to adjust prices faster, while brick and mortar stores tend to lag because their prices are on physical price tags and it takes a while to manually adjust all the price tags. Similarly, businesses locked into long term purchase orders may not be able to raise prices due to contractual obligations.

However, in the long run, where short run considerations like price tags and time limited contracts are no longer factors, the business can, and literally must (in order to stay alive), raise their prices. These raises may be gradual or fast, depending on the industry, and they may be explicit (prices actually going up) or implicit (reduction in costs due to better productivity not being passed on to customers as price decreases). But one way or another, the business must raise its prices due to the tariffs, or they simply go bankrupt.

Possibilities

So what are the possible outcomes of these tariffs? First, I must say that I am extremely unqualified to discuss this — I have no inside knowledge of how the administration thinks, and obviously I cannot see the future. Also, all of these are extremes — I don’t think any of them will become reality in their entirety, but instead, the final outcome may incorporate aspects of each of these.

Tariff gotcha

Possibly the best possible outcome for America. The president uses the tariffs for bargaining leverage to negotiate better trading terms with the rest of the world, and the tariffs are never actually implemented, or they are only live for a very short (days) period of time.

Soon after the announcements of the tariffs, Vietnam is already in talks with the president to reduce their duties on US goods.

Oh, never mind

The president, willingly or forced, retracts the tariffs without getting a deal with the rest of the world, before tariffs actually go live, or go live for only a very short (days) period of time.

Tariffs are, legally, a tax, and the Constitution endows only Congress with the power to impose new taxes or update existing ones. However, Congress has passed laws in the past which allowed the president to unilaterally impose or adjust tariffs in certain circumstances. It is possible that Congress changes its mind and removes the president’s authority to impose/update tariffs.

Fight club

The tariffed countries retaliate by imposing their own tariffs or other trade barriers, effectively engaging the trade war head on. The fight may spiral with each side escalating back and forth until one side surrenders, or some compromise is reached.

This would be seriously detrimental to the economies of both the US and the countries involved (assuming both sides are a large percentage of trade of the other). There is no winner in this situation, only a loser and a slightly less battled loser.

In particular, the tariffs currently slated to be implemented are already so high for some countries that they are effectively already cut off from the US market. This means that for them, higher US tariffs would make very little meaningful difference, so they may be more inclined to fight.

Given that many goods imported into the US have no other source of readily available producers, this would mean that US consumers will simply be deprived of those goods until new production can be started up somewhere else (or in the US itself), which can take years/decades, depending on the goods.

China has already announced actually reciprocal tariffs on the USA.

New BFFs

The worst possible outcome for the USA, would be if some of America’s largest trading partners decide to cooperate and defend against the new tariffs as a bloc. The new bloc could be used to gain leverage over the US to extract better trading terms, possibly even worse (for the US) terms than existing ones, or, much worse yet, the bloc could effectively trade amongst themselves, cutting out the US entirely.

Canada sent trade envoys to the EU soon after their recent elections (before tariff details were revealed), and rumors are that they are thinking of forming a bloc to better negotiate with the US, or perhaps even to cut out the US entirely.

Fin

Nobody really knows how this will all end. While some countries have stated that they will not contest the tariffs but will instead work towards a compromise, they may change their minds if other countries start getting preferential treatment. At the same time, countries that opted to fight may find the president to be unyielding, and quickly lose their appetite to continue the war.

In the end, this entire mess creates chaos in international trading, a lifeblood of effectively all large businesses and many/most small/medium ones as well. It is no wonder that the markets are treating this as a very serious event, on par with the pandemic.

For now, all we can do is watch helplessly as the leaders of the world try and secure what’s best for their nations, praying that whatever happens won’t be too detrimental for us, personally.

Are you not liberated?

March 16th, 2025: Weekend video binge – Sequence of Returns Risk

Foreword

This is a quick note, which tends to be just off the cuff thoughts/ideas that look at current market situations, and to try to encourage some discussions.

Ben Felix, an actual financial advisor, is out with a video about sequence of returns risk, a topic that we covered somewhat in Monte Carlo.

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Sequence of Returns Risk

To put it simply, sequence of returns risk (or sequencing risk) is the risk that a series of bad market returns during the early years of your retirement can dramatically reduce your future purchasing power by diluting the value of your portfolio before it has a chance to grow, resulting in you having to withdraw “more expensive” money in the short term to meet day to day needs.

While Ben is right that historically, a portfolio of 100% stocks statistically works better, and that the other proposed methods of retirement planning (diversification, bucketing, safe withdrawal rate, etc.) tend to results in worse results (i.e. less money to spend) at least based on historical data, there are some points which I think he did not address:

  • If you are planning on leaving an inheritance to your heirs, then having more assets left over at death need not be a bad thing — your heirs just get more in their inheritance.
  • There is, arguably, a regime change in the financial markets recently compared to the past ~50 years — interest rates have been steadily coming down since the late 1970s to the early 2020s, but has since then broken the trend and started going up. Perhaps this is a blip and interest rates will resume going down, or they may continue going up — nobody really knows. But a diametrical change in interest rates trends can potentially have dramatic effects on how assets perform going forward.
  • For retirement planning purposes, you have to make some assumptions about the future in terms of rates of return, spending needs, etc. Given that for some, retirement can be a semi-permanent thing (especially for tech workers, where the probability that you’ll be hired at a salary anywhere close to what you were making pre-retirement is very low), it makes sense to use more conservative estimates to build headroom for your calculations. After you actually retire, you can choose to adjust up your spending budget if your assumptions prove too conservative.

Note that none of the points above invalidates Ben’s arguments — his arguments are still very sound. But his arguments are based on historical data, and while there’s a good chance the arguments will prove true, there is also a non-negligible chance that, well, some things may change.

Whether you want to hedge that (possibly very small) risk, or are willing to chance it, depends on your tolerance for the risk.

SPY vs VOO

Foreword

SPY is the first S&P500 ETF ever listed, and because of that first mover advantage, it has amassed a large number of shareholders. However, VOO, a competitor from Vanguard now beats SPY by net asset value, even though it launched much later. Should you switch?

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Background

SPY is an ETF that tracks the S&P500 index, and so is VOO. In practice, the ETF providers have some leeway on how they actually implement the fund, but for the most part, they have a very high correlation and most people can treat them as effectively the same thing.

However, SPY has a 9bps (0.09%) expense ratio, while VOO has a 3bps (0.03%) expense ratio, making VOO slightly cheaper in terms of fees that users pay to own the shares 1.

Because VOO has a lower expense ratio, and I believe it is one of the cheapest, if not the cheapest, S&P500 funds, it has drawn significant interest from many investors.

Expense ratio

You can think of the expense ratio as roughly “how much I pay per year to own this fund”. So for SPY, if you’ve bought $10,000 worth of SPY shares, then every year you will pay about $9 — this is done by the fund provider selling $9 worth of assets in the fund to cover your share of the fees. One way to think about it is, absent all other factors, the value of your holdings in the fund goes down by $9 per year.

Similarly, for VOO, you will pay about $3 per year if you had bought $10,000 worth of VOO shares.

So, if you bought VOO instead of SPY, you would save about $6 a year.

$6 isn’t a whole lot, but it’s not nothing. And given that there’s nothing you need to do, it seems like a no-brainer, right?

Liquidity

If it is a no-brainer, then why does SPY even have shareholders? Why don’t all investors just sell out of SPY and buy VOO instead? And why hasn’t the provider of SPY just lowered their fees to compete?

Well, the answer is that it is not that simple. It never is.

This is a screenshot from Interactive Brokers sometime this afternoon (Feb 21st, 2025) showing the prices of SPY vs VOO (edited to show the relevant bits):

As you can see, VOO has bid/ask prices of 557.68 vs 557.71, while SPY has bid/ask prices of 606.47 vs 606.48. As a simple model, let’s say the “correct” prices of a security is the midpoint price, i.e. the average of the bid and ask price. So for VOO, the “correct” price is 557.695, while for SPY it would be 606.475.

From the quotes, VOO trades with a spread (ask price – bid price) of 3 cents, while SPY trades with a spread of 1 cent. As a rough approximation, you can think of the spread as how much you pay (excluding broker and exchange fees) every time you buy and sell (i.e. one roundtrip) a share. So if you buy and immediately sold VOO, you’d pay 557.71 to buy, but only get back 557.68 when you sold, giving you a loss of 3 cents.

So, as a percentage of the “correct” price, the spread for VOO is about 0.5bps (0.00005%), while the spread for SPY is about 0.2bps. In other words, if you trade in and out of both SPY and VOO, you’d pay about 3x more for the trades due to the spread for VOO, than for SPY.

In concrete terms, if you buy $10,000 of SPY, you’ll pay in spread about 8 cents (0.01 * (10000 / 606.475) / 2), while for VOO, you’ll pay about 27 cents (0.03 * (10000 / 557.695) / 2). Note that divide by 2, because we are only buying and not selling, so we “pay” half the spread2. Or, if you trade in and out of either position, you’ll pay 16 cents for SPY and 54 cents for VOO.

Given these numbers, if you trade in and out of your position 16 or more times a year, then it would make more sense to trade SPY than VOO — even if you hold the position everyday at the end of day, and thus pay the full $6 additional fee for holding SPY, you’ll more than make up for that by paying less in spreads when you trade — (54c – 16c) * 16 = $6.08.

If you don’t even hold the position at the end of every day, then trading SPY will come out further ahead, since you will pay a smaller fee to the provider (as a ratio of how many days you actually own the position out of the year).

16!

“But I’m a buy and hold investor”, you say, “I’m not going to trade in and out 16 times a year!”

And that is very true. Most people do not turn over their entire portfolio 16 times a year.

But that’s just one part of the liquidity story.

Here are some screenshots (again, edited for focus) of options expiring on March 21st, 2025 for SPY:

and VOO:

As you can see, an at the money call option for SPY trades at 9.17/9.20 bid/ask, while a similar at the money call option for VOO trades at 7.40/7.80 bid/ask.

As a percentage of the “correct” price per share, the SPY option has a spread cost of about 0.5bps, while the VOO option has a spread cost of about 7bps, an order of magnitude higher.

Which is to say, if you, like me, like to occasionally sell calls against, or buy puts to protect your S&P500 position, just buying 2 rounds of puts (or selling 2 rounds of calls) per year will result in SPY being a better vehicle for your portfolio — You’d pay roughly 6.5bps higher in spread costs to buy 2 rounds of puts (or sell 2 rounds of calls), if you let the options expire (i.e. you only pay the half the spread cost per trade), if you had used VOO instead of SPY (edit: for clarity).

While I don’t really trade that much, I almost definitely sell more than 2 rounds of calls per year on my holdings to juice my returns when I feel that the markets are especially richly valued, so for me, personally, trading SPY is usually a better idea.

Summary

While it is true that holding VOO is cheaper in terms of fees paid to the fund provider, be careful of all the other costs of investing. The 6bps you save per year by holding VOO instead of SPY is easily eroded if you trade options or the underlying even semi-frequently.

Of course, if you are a pure buy and hold investor who holds for the long term, then as of right now, VOO does indeed seem to be a no-brainer.

Footnotes

  1. Users don’t actually get a bill or send money — the ETF provider just sells some of the assets of the fund to pay itself. ↩︎
  2. Experienced traders will know that you can actually buy and sell closer to the midpoint than the spread, but that’s a story for another time. ↩︎

January 19th, 2025: Weekend Video Binge – Monetary policy, fiscal policy and central banks

Foreword

This is a quick note, which tends to be just off the cuff thoughts/ideas that look at current market situations, and to try to encourage some discussions.

Richard Koo, celebrated economist who has worked in the Federal Reserve and is now chief economist at Nomura Research Institute, joins Adam Taggart in this fascinating and detailed look into monetary policy, fiscal policy and central banks.

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Fiscal policy vs monetary policy

Something which seems to confuse many people — monetary policy and fiscal policy are not the same thing.

Monetary policy is a set of actions taken to control the money supply, typically via interest rates policies and/or reserves requirements of banks. These are typically done by a country’s central bank.

Fiscal policy is the set of actions taken to control the cash flow of a country’s government, e.g. via public spending and taxation policies. These are typically done by the government of a country.

To put it somewhat crudely, monetary policy determines how easy it is to borrow money. It doesn’t mean that anyone actually has to borrow the money. Fiscal policy, on the other hand, determines how much money is coming in or going out of the government’s coffers, and if there is a deficit (i.e. more money going out than coming in), then the balance needs to be borrowed.

To simplify even more, monetary policy makes it easier for the government to borrow money, but fiscal policy determines if the government actually borrows money.

Choice quotes

Enjoy!

The RSU Sleight of Hand

Foreword

Nowadays, many tech companies compensate their employees with restricted stock units (RSUs), effectively stock grants that vest over time. In most discussions with recruiters I’ve had, wonky maths was used to describe the actual compensation that is actually being offered, making comparisons between RSU-based and non-RSU based compensation packages difficult.

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Restricted Stock Units

The typical RSU award works like this:

Let’s say your employer wants to pay you $100k over 4 years in RSUs. They will figure out a reference price of the stock at the time of the grant (i.e. when they decided to give you the award). Usually this is the price of the stock at market close on some particular day, or the average of the market closing price of some number of days.

Let’s say for our example the reference price is $100. In this case, you would be awarded with 1000 RSUs. The grant itself typically does not actually result in you getting shares. Instead, the grant is the promise of future shares. You only get the shares at set dates in the future, called vesting dates. For example, let’s say the shares vest once per quarter for the next 4 years. So each quarter, for the next 16 quarters, you’ll get 1000/16 = 62.5 shares each.

Vesting dates typically come with the stipulation that you remain employed with the employer — that is, if you quit (or are fired) before the full 16 quarters are up, you’ll forfeit any unvested shares of the grant.

To further complicate things, it’s common that a (large) part of your total compensation will come in the form of refresh grants, which are annual grants of new RSU awards, each of which are tied to a different reference price as well as award value (i.e. how much money your employer wants to actually give you). The employer may or may not disclose the reference price and/or award value, and may instead just choose to give you the total number of shares for each grant.

So, what you end up with, is a vesting schedule that looks something like this (assuming 1000 shares per grant, and consolidating all grants in the same year to shorten the table):

YearGrant 1Grant 2Grant 3Grant 4Total
1250250
2250250500
3250250250750
42502502502501000

After the 16th quarter, the first grant will be fully vested and you’ll stop getting shares from it. But the 5th grant will kick in, so you’ll continue getting 250 shares per quarter.

Note that typically the first grant is much larger than the refresher grants — this is because it is actually 2 grants in 1 — the first is the typical annual grant like a refresher grant, and the second is actually you sign on bonus. For simplicity, I’m ignoring the sign on bonus component for now, so all grants are more similar in size.

Presentation

When the RSUs award schedule is presented, recruiter will usually present the actual dollar amount of the shares you’ll get. Assuming that the shares start at $100 and increase by 10% per year, then the dollar amount of the vesting schedule looks like:

YearTotal shares vestedDollar amount
1250$25,000
2500$55,000
3750$90,750
41000$133,100

And from then on, the total value will increase by 10% a year (same number of shares, but share price increases 10% per year).

Now, if you want to estimate the value of your total RSU compensation in year 3, it is natural to think that it is $90,750. Did you notice the sleight of hand?

Sleight of Hand

There are 2 main issues with computing your actual RSU compensation:

  • The increase in the share price confuses the matter
  • You forfeit whatever shares are not vested in all grants if you leave the company

Now, given that, what do you think is the RSU based compensation for the 3rd year? Is it

  • $90,750 — the actual value of RSUs received in year 3

OR

  • $121,000 — the actual value of RSUs granted in year 3

?

The answer is… neither. It is actually $82,750, which is $25,000 (the value from the first grant) + $27,500 (the value from the second grant) + $30,250 (the value from the third grant).

Think of it this way — because you forfeit any shares not vested if you leave the company, at the time of the grant, you haven’t actually earned the award yet, so $121,000 is wrong.

At the same time, the first grant is worth only $25,000, despite you getting $30,250 from the 250 shares because that’s what the company intended to pay you when it made the grant — 250 shares at $100 each. The fact that the shares have gone up in value over the next 2 years is irrelevant — the additional 30,250 – 25,000 = $5,250 is the compensation you get for taking the risk of the stock exposure! Remember that instead of going up 10% a year, the stock price could just as easily have gone down instead.

Another way of thinking of it is this — if instead of giving you a 4 year deferred grant 1, the company had just given you the $100,000 flat out. In this case, you would have the choice of whether to buy the company’s stock or not. If you did, then you’d have bought 1000 shares (at a price of $100 per share). After the 4th year, your shares would then be worth $133,100. Would you now say that the first grant was $133,100 instead of $100,000? Obviously not!

If you had valued grant 1’s shares at the vesting price instead of the reference price, then you would value grant 1’s RSUs at a total of $25,000 + $27,500 + $30,250 + $33,275 = $116,025 over the 4 years, and that just doesn’t make sense — receiving the $100,000 upfront in year 1 is clearly better, since you get the money earlier, and you have the optionality of what to do with the money, so how can it be worth less than being forced to effectively buy your employer’s stock and to hold the stock for 4 years, while risk forfeiting part of the grant if you leave the employer early?

Taxes

One argument that some make for the RSUs instead of cash upfront, is that by deferring the payment, you are also deferring taxes, and since you are getting stock, you are benefiting from the deferred payment being invested, effectively compounding the part of the upfront payment that would have been paid in taxes.

Let’s model this out. Let’s say you pay long term capital gains taxes of 20% (highest) and marginal income taxes of 25% (somewhere in the middle).

In the RSU case, you would then receive:

YearVesting sharesReceived sharesTotal sharesShares value (pretax)Shares value (post tax)
1250187.5187.5$18,750$18,750
2500375562.5$61,875$61,500
3750562.51125$136,125$134,512.50
410007501875$249,562.5$245,227.50

If instead you had been paid cash upfront, paid your taxes, and then bought the shares:

YearPost tax grantTotal sharesShares value (pretax)Shares value (post tax)
1$75,000750$75,000$75,000
2$82,5001500$165,000$150,000
3$90,7502250$272,250$267,450
4$99,8253000$399,300$389,055

I think it should be clear in terms of cash flow, getting the cash upfront is better. However, if we just look at the first grant mathematically, in year 4, it will be worth:

  • If received in RSUs, with 187.5 vested at 100, 187.5 vested at 110, 187.5 vested at 121, 187.5 vested at 133.10, for a total of 750 shares worth $99,825 pretax, or $97,263.75 post tax.
  • If received in upfront cash, you’ll still end up with 750 shares, but worth $94,860 post tax, due to the lower cost basis of 100 for all shares.

So the main benefit of the deferral is that you have a higher cost basis for the shares received later, which does translate to a higher after tax dollar value if sold.

Whether this benefit is enough compensation for losing control/optionality of the grant for 4 years, and having to forfeit the unvested shares if you leave the employer early, is up to you.

Comparison shopping

When comparing compensation packages between an employer that pays with RSUs, vs another one that pays with cash, it is important to remember the RSU sleight of hand, and properly value what your compensation package will actually be.

The 3 key points to watch out for are:

  • If you leave the employer, will the deferred part of the compensation still be paid?1
  • Properly value the dollar value of each grant by adjusting for the risk you are taking by being forced to effectively buy your employer’s stock.2
  • The tax benefits of a higher cost basis for those shares that vest at a higher stock price than the reference price.

Footnotes

  1. Some employers may have wording in the contract to the effect of “if you do something we do not like, and you get terminated for it, then the deferred part is forfeit”. In these cases, you’ll have to estimate for yourself how likely it is that you fall afoul of those rules. In many cases, the rules are actually pretty generous and you only forfeit the deferred payments if you break a law or otherwise get involved in some serious shenanigans.

    If you are confident the deferred payments will actually be made, then you should consider the payments to be made at time of grant (because that’s also when they vest). ↩︎
  2. If the deferred portion is paid in cash, then you may need to discount the value of that cash to the time of vesting. ↩︎

December 27th, 2024: Weekend Video Binge

Foreword

This is a quick note, which tends to be just off the cuff thoughts/ideas that look at current market situations, and to try to encourage some discussions.

Adam Taggart is out with a fantastic interview with Graham Weaver — professional PE fund manager, Stanford professor and blogger/youtuber.

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Graham Weaver

Graham Weaver is a more traditional private equity fund manager, along the styles of Warren
Buffett — someone who invests in boring, predictable, but highly cash flow generative businesses, and holds them for the long term.

In this interview, he discusses the philosophy behind his investing style, and what contributes to his success. Well worth a watch.

Alpha

Foreword

Everyone in finance seems to be chasing alpha, but very few people seem to really understand what it is. What is alpha, and why does it matter?

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Simply alpha

Alpha, in finance, specifically quantitative finance, is defined as the excess returns of a strategy above and beyond market returns. In other words, alpha measures the outperformance of a strategy — the higher the alpha, the better the strategy1.

And because everything in finance is about *ahem* number measuring exercises, everyone in finance seems to be striving for higher alpha.

Unfortunately, many people, including those working in finance, don’t really understand what alpha is, and often conflate increased risk (which you do not want) with increased alpha (which you do want).

Maths

According to https://corporatefinanceinstitute.com/resources/career-map/sell-side/capital-markets/alpha/, the mathematical formula for alpha is:

Alpha definition, https://corporatefinanceinstitute.com/resources/career-map/sell-side/capital-markets/alpha/

If you look at the equation more carefully, you’ll realize that:

  • Alpha is net of the risk free rate.
  • Alpha is independent of market return.

Which is to say, if all the return of a strategy can be expressed as a function of market return, then that strategy, by definition, has zero alpha.

To “simplify” things a bit, to compute the alpha of a strategy, run a correlation test of that strategy’s returns against SPX minus the risk-free rate (assuming you are using SPX as a benchmark), and the correlation, with magnitude, is your beta. (edit: clarified that beta is correlation + magnitude)

The part of the strategy’s return beyond that which can be explained by market returns (i.e. beta(Rm – Rf)) would be alpha + Rf, so you can compute alpha by just taking away from that remainder the risk-free rate.

Some examples

Now, let’s consider some examples:

  • A fund that simply buys SPY, returning 33% in 2021, -14% in 2022 and 19% in 2023, with a cumulative total return over the 3 years of 34%.
  • A fund that simply buys UPRO (3x SPY), returning 106% in 2021, -49% in 2022 and 43% in 2023, with a cumulative total return over the 3 years of 50%.
  • A fund that returned 6% in 2021, 8% in 2022 and 9% in 2023, with a cumulative total return over the 3 years of 25%.

Clearly, the second fund has the highest cumulative total return, but which strategy has higher alpha?

Well, SPY is basically just the ETF expression of SPX, and UPRO is just 3x SPY, so the correlation of both funds would be very close to 1 (with SPY having a beta of around 1, and UPRO having a beta of around 3, edit: clarified that beta is correlation + magnitude), which implies both funds have zero alpha. However, the 3rd fund clearly does not move with the market — it goes up every year even when the SPX went down in 2022, and if you do the maths, it is returning about 5% above the risk-free rate every year. So the alpha of the 3rd fund is actually 5%.

Cue surprise

The above result often surprises many who don’t really understand what alpha means — how can a fund that returns less than SPY be considered to have alpha, while a fund that returned almost double of SPY has 0 alpha?

Recall that alpha is the part of the return that is above and beyond what can be explained by market returns. Both SPY and UPRO explicitly try to mimic market returns, with the exception that UPRO does it with 3x leverage. So neither have an excess return above that which can be explained by market returns, and the additional return UPRO provides over SPY is really just the result of UPRO taking more risk, in the form of using leverage.

Recall when we said people often confuse more risk (bad!) with more alpha (good!)? There you go.

The 3rd fund, on the other hand, has 0 beta2, so all its returns are just alpha + Rf, and if you subtract the risk-free rate (generally assumed to be 10Y US Treasury yield), you get about 5% alpha per year.

But the returns suck!

Yes. Compared to both the first 2 funds, the return of the 3rd fund is indeed subpar. This is a common theme of true alpha funds — their returns tend to be around the 5-10% mark annually (edit: This is net of risk-free rate, i.e. alpha). Yes, there are some funds that have much higher alpha (e.g. the Medallion fund from Renaissance), but those tend to be closed off to outside investors.

The reason alpha funds tend to have lower returns, is because they are hard, and more often than not, they are rare. Alpha is hard because it is genuinely hard to find a strategy which will do well regardless of what the market does — most strategies have some non-trivial amount of beta associated with it just because they need to operate in the market. They are also rare, because most alpha strategies tend to have low capacity, meaning you can only put so much money into the strategy, before your positions affect the markets, and you distort the market enough that the returns dissipate.

Constructing an alpha only fund

To get some insights into a true alpha fund, consider a fund which returns 5% of alpha, and 80% of beta, i.e. the fund returns 80% of whatever SPX returns in any single year, and on top of that, returns 5% additionally (+ risk-free rate).

Well, we can convert such a fund into a true alpha fund by simply bundling this fund with a short up to 80% of your portfolio value of SPY. The total return of this bundle will now be: 5% + 80%SPY – 80%SPY = 5%, the alpha.

Not so fast though — shorting is not free. You typically pay a fee (short borrow fee, maybe margin costs, etc.) to short. To keep the maths simple, let’s say that the total fee for this shorting is 1% of total returns.

Which means, your true alpha fund, the bundle, will only return 4% alpha.

In general, a true alpha fund tends to involve a lot of trades to hedge out market exposure, which in turn will reduce the actual return (and thus alpha) of the fund.

Why bother?

So to recap, a true alpha fund first needs to find a good strategy, then pay fees to trade that strategy, and pay more fees to hedge out market exposure, just to get a net return of around 5-10% of alpha. While market return, at least in the past few years, has dramatically outperformed that with much less hassle.

So… why bother? Are Wall Streeters just stupid? Or maybe they just like Rube Goldberg-esque exercises in futility?

Let’s consider our 3rd fund again, which returned 5% alpha, i.e. 5% return net of risk-free rate.

Large institutional traders (and even savvy individual traders), can often get financing (i.e. loans) at, or close to, the risk-free rate.

If you are in such a position, then you can borrow, say $1m, at risk-free rate (Rf), then put that $1m into the fund to deliver a total return of alpha + Rf, which means effectively you get a return of alpha “for free”. Since this is a positive value arbitrage, you can simply re-lever your positions to get another loan at risk-free rate, put that new money into the fund to increase your returns. This process can be repeated forever — an infinite money glitch.

The ability to re-lever into positive alpha strategies, is also why these strategies tend to be rare — any existing alpha found will likely be pushed to its limits, until little, if any, alpha is left.

You can also lever into beta funds (i.e. buy UPRO), but that has limits — because market return can be negative, you cannot re-lever into the fund infinitely; There is a chance that a large enough negative year will wipe you out, so your lenders will likely place very strict and very conservative limits to how much leverage you can apply. After all, even if your strategy blows up, they still want to be paid!

Quickly identifying alpha

To conclude, if you are looking at a strategy, and you’re trying to figure out if the strategy has alpha, a simple way to quickly estimate this is just to look at the strategy’s total return over a period which includes a number of high return years and negative return years.

If any of these are true, then there’s a good chance that the strategy has positive alpha:

  • The strategy manages to return more than the market in all of those years.
  • The strategy has a fairly stable, positive return in all of those years.

But if the strategy simply returns more in good years, but also loses more in bad years, then even if the strategy’s total return over all the years is greater than the market, the fund may not have alpha, or may even have negative alpha.

Footnotes

  1. A better and more complete definition can be found at https://corporatefinanceinstitute.com/resources/career-map/sell-side/capital-markets/alpha/. ↩︎
  2. You can’t compute this based on the data provided, but let’s go with it. ↩︎

November 22nd, 2024: Weekend Video Binge

Foreword

This is a quick note, which tends to be just off the cuff thoughts/ideas that look at current market situations, and to try to encourage some discussions.

Adam Taggart is out with a fantastic interview with Grant Williams.

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Grant Williams

Grant Williams is the author of “Things That Make You Go Hmmm…”, which discusses interesting phenomena in finance over time.

In this interview, Grant talks about what he expects in the near-term future, the phenomenon such as the meme stock craze, crypto, etc.

In particular, at the 58m 52s mark, he talks about something dear and close to my heart — the differences between investing and speculating. Something which, it seems, many younger “investors” should really understand.

Politinomics

Foreword

The country has decided — Trump is the next president of the United States of America. What does that mean economically and financially?

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Politics

To be absolutely clear — I am a registered Democrat and I voted for Harris. She lost, Trump won. I’m not happy about it, but the country voted, and a democracy, a strong democracy, is one where the will of the people is respected. If you do not like the result, you certainly have the right to be upset and protest. But that right only extends to doing so peacefully and respectfully.

Other than the little paragraph on top, this post is about finance and economics, specifically what I think the results of Trump’s stated preferences, as well as his actions in office the first time around, have on the country.

Explicitly, this post is not about the differences in policies between Trump and Harris, nor why I (or anyone) prefer one candidate over the other, nor why one candidate’s policies are better or worse than the other.

Tariffs

Trump has made no secret of his love for tariffs, and how he intends to raise the tariffs of all imported goods by astronomical amounts once in office. As far as I can tell (and I am NOT a lawyer nor am I in any way qualified to say so authoritatively), I believe this is something that the president can do, almost unilaterally.

First off, and let’s get it out of the way — despite what the Republicans say, tariffs are inflationary. Yes, I understand that Trump may just be using the tariffs as a negotiating tool to get companies to reshore their factories. That’s irrelevant — tariffs are inflationary. To put it simply, consider this — why do you think companies offshore much of their manufacturing processes? If you say because it is cheaper, then give yourself a pat on the back. For better or worse, many workers in less developed countries are willing to work in manufacturing jobs for a lot less than what the typical American worker is willing to accept.

So, if the tariffs don’t work to push companies to reshore, then the cost of the tariffs will mostly be passed on to consumers via higher prices. But even if they do work, and companies reshore their factories, that just means that companies pay higher prices for the labor in their factories. Again, the cost of this will be passed on to the consumer in the form of higher prices. Either way, prices of goods and services that are hit by tariffs will likely go up. The only question is, by how much and when.

That said, tariffs aren’t all bad. If the gambit to reshore jobs work, there is a good chance that it’ll reinvigorate the flailing manufacturing sectors in many parts of America, and that can be a very good thing — providing dignified, good paying jobs to many despondent Americans, while increasing the income tax base significantly.

However, the inflation hit will be immediate and certain — companies can pass on higher costs (tariffs in the short run, higher wage costs in the long run) very easily, while factories and supply lines take years to build so any potential benefits may not even be materialized until Trump is out of office. On the bright side, if the introduction and management of the tariffs are managed well, the inflationary hit may be dispersed over time, so that it is less onerous.

In summary, this is a gamble, and a pretty high stakes one. But one where the reward could be potentially game changing for many, many American families. In that regard, and while I don’t particularly like the man, I certainly hope he succeeds in this goal.

Foreign workers

This is a thorny subject, and to be clear, I am biased — I’ve worked my entire life in tech, and foreign workers are a fact of life in tech — there simply aren’t enough Americans with the right qualifications to satisfy the needs of all our tech companies, and so a large part of the tech workforce are foreigners.

There are, in my opinion, 3 types of foreign workers:

  • High skilled, consisting mostly of college graduates in STEM fields.
  • Low skilled, consisting mostly of agricultural workers, temporary workers and family members of other foreign workers who don’t have the necessary qualifications for higher paying jobs.
  • Illegal/undocumented/unauthorized workers. Regardless of their qualifications, these are generally low skilled workers, since they don’t have the legal right to work.

Trump is on the record for saying that he’s pro high skilled immigrants, going as far as to say that anyone who graduates from an American college with the right qualifications should be given a green card (permanent residency). I don’t know if the president has the ability to do so unilaterally, though I don’t believe so.

As for low skilled foreign workers, Trump hasn’t really made his stance clear as far as I know.

Lastly, for illegal workers, his stance is, frankly, abhorrent — often labeling and maligning them as criminals, especially violent ones.

To be clear, data has shown, consistently, that while undocumented workers do sometimes resort to crimes, the rates at which these workers commit crimes is much lower than American citizens. This makes sense — if you are in the country illegally, the last thing you’ll want to do is to draw attention to yourself. Keeping your head down, doing your job and getting paid while remaining outside of the radar of law enforcement seems paramount. Which is to say, the vast majority of undocumented workers really only want to do their jobs, to provide a better life for their families and to live their lives in peace.

Finally, the data has, consistently, shown that illegal workers are doing jobs that most American citizens don’t actually want to do — those low paid jobs that are less glamourous like agricultural work, janitorial work, construction, hospitality, etc.

For a more nuanced look at illegal immigration, I recommend reviewing these videos which at least try to be informative and neutral, rather than pure scaremongering:

This is not to say that undocumented workers are a boon for the US — they do have a negative downside for Americans, particularly those who are less educated via the crowding out effect, and as such, contribute to (though not the only nor even the main reason for) the economic malaise of those same Americans.

If the flow of unauthorized workers was to suddenly stop, then certain industries will be affected negatively — they would be forced to offer higher wages to American workers, and at the same time, be forced to deal with a labor force that is less motivated to work. These naturally translate into higher costs, which will then be mostly passed on to the consumer, resulting in inflationary pressures.

On the other hand, assuming an equilibrium can be reached such that these less glamourous jobs can be filled, at a labor cost that is not prohibitive, then an argument can be made that this will revitalize many segments of American society, which can have a positive multiplicative effect on the economy. As with the tariffs issue, though, the benefits are likely to take much longer to materialize than the downsides.

In the end, the issue of foreign workers in general and illegal workers in particular is nuanced and complex. There are pros and cons to whatever policies are implemented, whether welcoming them or not, and certainly broad brushes to try and get a quick fix are unlikely to work.

Global order

Anyone who has been paying attention for the past 50-60 years, will know that to a first approximation, the USA has been the underwriter of global security to a very large extent. By this, I mean that the USA has been active in many regions of the world, forming alliances, providing security guarantees, and maintaining military bases pretty much throughout the world.

There are complex geopolitical issues involved in this, and certainly not everyone is happy about the arrangement. To avoid the more thorny issues, I’m focusing mainly on the security of trade routes against illegal non-state actors (i.e. pirates, bandits, etc.), and ignoring the political issues.

While not always successful (see the attacks on ships around the Red Sea), the presence of a well armed and coordinated military has been made a real difference against less organized attackers such as around the Cape of Good Hope, South East Asia, etc.

This has resulted in reduced insurance (and thus carrier) costs for shippers and more shipping routes opening up, which then translates into deflationary forces for imported goods, which is a huge boon for both American consumers and many export-oriented economies, as the USA is the single largest importer in the world.

If the USA was to shift its focus dramatically inwards, as Trump’s (nuanced) isolationist tendencies have hinted at, this could spell trouble for the current system of global trade routes. Whether Trump will do that, though, is not certain — as noted, while he displays isolationist tendencies, it is more nuanced than that, and an outright withdrawal from the world seems unlikely.

Another thing to remember, is that the USA is uniquely positioned in the world — she has abundant natural resources, and is self-sufficient in most critical sectors (or can be with enough effort). So a truly isolated USA may not be economically bad… for the USA.

For the rest of the world, though, it is likely to be an extremely painful adjustment. The bulk of the world’s trades are conducted in dollars, and a large fraction of international debt is denominated in dollars. To simplify things massively, the world (minus the USA) is dramatically short the US dollar. If the US was to draw inwards, the flow of US dollars out of the USA to pay for her imports will slow dramatically, which will likely result in a massive shortage of US dollars around the world. This is likely to result in financial ruptures in hard to predict regions of the world, and can be extremely disruptive.

Summary

Trump’s policies, as he has opined on them publicly, are a fairly dramatic departure from the policies of both Republican and Democrat presidents in the recent past. Many of them have the potential to result in dramatic upsides for the USA in the long run, though come at a fairly high short term cost. Also, remember that we are now discussing the policies in a vacuum — the world is unlikely to sit still and do nothing, and the world’s reactions to Trump’s policies are likely to affect the outcomes as well.

In short, the only thing that seems certain right now, is that the economic and financial landscapes are likely to be volatile for the next 4’ish years. The question is, will this be the kind of volatility that ultimately results in good outcomes? Or not?