Author Archives: theusernamewhichismine

10x Genomics: what happened to all the DNA stocks?

2020 was the year of COVID, but it was also the year of DNA. Thousands of DNA companies and researchers got in on the pandemic since there was a sudden surge in demand for COVID testing, contact tracing, and virus studying. Now, COVID is an RNA virus, but RNA and DNA work so similarly that most organizations that do one can do both. Even the Universities got into it, I know the Genomics Research Core Facility at the university I used to work for got money from city, state, and federal governments to process COVID tests, which was way more profitable for them than sequencing my plasmids once a month.

So 10x Genomics was a DNA sequencing company that, like so many others, skyrocketed in valuation during 2020. It hit its absolute peak in early 2021 and then fell precipitously through 2022. That describes a lot of companies but it especially seems to describe DNA companies. Still, I wanted to know if 10x Genomics was a buy, and considering my LinkedIn account got spammed all last year with recruiters and ads for the company, I figured they were at least worth a look. The result? A resounding “eh.”

One of 10x Genomics’ big claims to fame is their ability to perform reads of long segments of DNA as opposed to the shorter segments read by rival Illumina. Sequencing DNA gets less accurate the longer the DNA is, so Illumina and others use a technique of chopping the DNA into pieces, sequencing each piece, and putting them all back together. This usually works fine because there are enough overlapping pieces to make the puzzle fit, if you know read 3 different pieces with letters “AATT”, “TTGG” and “GGCC” then you can hazard a guess that the full sequence reads “AATTGGCC” and that the 3 pieces simply overlapped each other. This doesn’t work with long sequences of a single letter or repeating patters. If you simply have “AAAA” “AAAA” “AAAA” then you actually don’t know how long that string of As is. Those 3 reads could overlap on 2 letter and the result could be “AAAAAAAA” or they could overlap completely and the result is simply “AAAA.” About 8% of the human genome is these sorts of repeating patterns that Illumina and others are ill-equipped to read, which gives 10x an exploitable niche.

Now this is a genuinely interesting piece of equipment and their barcoding of DNA segments to read them in the correct order is a nice bit of chemistry, but was this a company that was ever worth 21 billion dollars? In my opinion *no*. The COVID era was a bubble in a number of ways, the easy-money policies of the post Financial Crisis era led to the super-duper-easy-money policies of the COVID era. Operation Warp Speed and other pandemic-focused funding sources meant that money was flowing into the biotech sector, and with most of the world still coming out of lockdown investors were desperate to park their money in companies that were still able to operate. It seemed like the moment for Biotech had come, and companies like 10x Genomics rode the wave to the very top. But from where I’m standing this was always an obvious bubble, and people were making claims about DNA companies that were woefully unfounded.

I’ve just written a lot about 10x Genomics, but all this could apply to most any DNA/RNA startup around. They all had neat ideas, got woefully overvalued during the pandemic, and have since crashed to earth taking shareholder value along with them. My question today then is why, why does it seem like Wall Street Investors saw something in DNA/RNA companies that I, a biology researcher, never did? Now part of that is that I’m just curmudgeony by nature, but part of that is that I think a lot of investors have this Sci-Fi idea of genetics in their head that isn’t really reflected in the field. I could just point to Cathie Wood and say “she doesn’t know Jack” but I want to dig a little deeper into some of the strange narratives that surround nucleic acids.

First, “DNA as a coding language.” I wonder if computer scientists just latch onto the word “code” or something, because the genetic code is no where near to being something that we can manipulate like computer code, and probably won’t be for decades. We’ve been inserting novel DNA into organisms since the 70s, but recently there’s been a spate of investors and analysts who believe that we’re on the cusp of truly programming cells, being able to manipulate them into doing everything we want as cleanly and as easily as a computer. This would definitely unlock a whole host of industries, it’s also not going to happen for a long while yet. DNA codes for proteins, and proteins are the functional units of most biological processes. Nothing you change in the DNA matters until it shows up in the proteins, and we are far, FAR from being able to understand how to manipulate proteins as easily as we do computers. You cannot simply say “let’s add a gene to make this wheat crop use less water,” you have to find a protein from another plant that causes it to use less water, insert that gene into wheat, do tests to make sure the wheat crop tolerates the new protein, alter the protein to account for unexpected cross reactions, and then finally test your finished wheat product out to make sure it works as designed. Any one of these steps could require an entire company to do, and each step could prove impossible and bankrupt the company working on it. We can’t just make de novo proteins to do our bidding because we don’t even know yet how to predict what a protein will look like when we code for it. Folding at home and other machine learning projects have helped us get partway there, but it will still take many Nobel Prizes before we can make de novo proteins as easily as we make de novo programs. So while there is a genomics revolution going on, it’s still an expensive and time consuming one, it’s not going to solve all our problems in a single go.

Second, “DNA as a storage medium.” I’ve said before that while DNA does store and transmit information, that information cannot be well integrated with our modern technology. The readout of DNA information is in RNA and proteins, while the readout of the circuits in your computer is photons on a screen or electrons in a modem. RNA and proteins do not easily produce or absorb electrons and photons, so having DNA communicate with our current technology is not currently doable. In addition, the time lag between reading DNA and making RNA/proteins is astronomical compared to the speed of information retrieval in semiconductors. I sometimes get an annoyed by the seconds-long delay it takes to load a webpage, but I’d be tearing my hair out if I had to wait on the minutes-long delay for DNA to be transcribed into RNA! At this time I really don’t see any reason to use DNA as a storage medium and I certainly don’t see a path to profit for any company trying to use it as such.

Third, curing genetic diseases. There is definitely a market for curing genetic diseases, let me just say that first, but many of the hyped-up corporate solutions are not feasible and rely more on sci-fi than actual science. I’ve discussed how even though CRISPR can change a cell’s DNA, bringing the CRISPR and cell together is much more challenging. The human body has a lot of defenses to protect itself from exogenous DNA and proteins, and getting around those defenses is a challenge. But in addition I don’t think investors realize that DNA is not the end-all be-all of genetic diseases, and so they tack things on to the Total Addressable Market (TAM) of DNA companies that shouldn’t really be there. Then they get flummoxed when the company has no path to addressing its TAM. Valuing companies based on what they can’t do is a bad investment strategy that I see over and over again with DNA companies. As to genetic disease themselves: there’s a truism in biology that “you are what your proteins are”. Although DNA codes for those proteins, once they’re coded they act all on their own, and some of their actions cannot readily be undone. When a body is growing and developing, its proteins can act up in ways that cause permanent alterations, and after they’ve done so changing the DNA won’t change things back. There are a number of genetic-linked diseases which are not amenable to CRISPR treatment because by the time the disease is discovered the damage has been done and changing the DNA won’t undo the damage.

Finally, “move fast and break things” doesn’t work with DNA the way it does with computers. I’ve worked on both coding projects and wet-lab projects. When something goes wrong in my computer code, fixing it is a long and arduous process but I have tools available that let me know what exactly the code is doing every step of the way. I can step through the code line by line and find out exactly what went wrong, and use that knowledge to fix things. Nothing is so straightforward when working with DNA, your ability to bugfix is only as good as your ability to read the code and reading DNA is a difficult and time-consuming process. Not only that, remember how I said above that we don’t know the exact relation between the DNA we put in and the DNA product we get out? If I’m trying to make a novel protein using novel DNA and it doesn’t get made, what went wrong? I can’t step through the code on this one because there’s no way to read out the activity of every RNA polymerase, every ribosome, or every post-transcriptional enzyme in the cell. I can make hypotheses and do experiments to try to guess at what is going on, but I can’t bugfix by stepping through the code, even using Green Fluorescent Protein as a print(“here”) crutch is difficult and time consuming. Even if I try to bugfix, the time lag between making a change and seeing the results can be weeks, months, or years depending on what system I’m working in, a far cry from how long it takes to compile code! A DNA-based R&D pipeline just doesn’t have the speed necessary to scale the way a coding house does, once you’ve got a program working the cost of sharing it is basically zero and the cost of starting a new project isn’t that great. That speed isn’t’ available to DNA companies yet.

This was a lot of words not just on 10x Genomics but on DNA-based companies in general. The pandemic-era highs may never be seen again for many of these companies, much like how some companies never again saw the highs of the Dotcom bubble. I think it’s important for investors to take a level-headed approach to DNA-based companies and not get caught up in the sci-fi hype. Anyone can sell you an idea, it takes a lot more work to make a product.

A series of proposals for testing the validity of technical analysis (TA)

I’ve said before that I think TA is astrology, and I still haven’t seen any evidence to rid me of that belief. I’ve thought about genuine scientific experiments that could be done to see if it’s true and I’m wondering if people have already done them.

See if TA-knowers all move the same way by giving a bunch of them a chart and have them predict the forward movement of the stock based on that chart. Two key ways you know astrology/fortune telling is fake are 1. that it uses weasel-words and vagueness to make predictions, and 2. because the same data can cause its practitioners to make wildly different predictions. In actual science however, any two scientists should be able to take the same data and make the same prediction: if two bowling balls of different weights are dropped from the Eiffel Tower, which hits the ground first? Any physicist can tell you the answer. Now to be clear, second opinions in medicine do exist, but these occur because we often work with incomplete information and have to use priors and estimations for the rest. But TA claims that the chart is the information, so if the information is complete than the prediction should always be the same. So if 100 TA-knowers all make the same prediction using the same chart, then perhaps we can start treating this as a complete and testable theory. If they all draw different lines on it then it becomes more clear we’re dealing with astrology.

Find out if the TA of ETFs follow the TA of their underlying assets. The mechanisms of ETFs ensures that their price never deviates far from the price of their underlying assets, and if both ETFs and the securities they contain obey TA then the movement of the two should correlate. Essentially you should be able to make predictions of the movement of an ETF by performing TA on the stocks that compose it, and I’d like to know if this is true.

Correlation analysis. Most theories of the stock market claim that the movement of a stock price is uncorrelated with any of it’s previous prices. Just because a stock is down 50% doesn’t mean it’s dead or a bargain. If I’m going to believe TA I’d like a TA-believer to prove to me that price movement is correlated with previous prices.

A working, mathematical definition of “resistance” and “support.” I understand that these are TA terms, but I’ve asked 5 different TA people for a true definition of them and have gotten 5 different answers. If TA really is based on math then these terms need to be mathematically defined, not emotionally defined based on how someone wants to analyze a chart at that time.

These are just a few of the things I’d like to be demonstrated before I start believing in TA.

What was the best 10-year period to invest in the S&P 500?

I’m doing a small project right now looking at whether stop losses are actually useful in investing. When FTX blew up, it was noted that the traders there didn’t believe in stop losses, for which they were ridiculed on social media. Of course, do stop losses actually help? Or are they more likely to kick you out of a volatile-but-profitable investment than save you from an unprofitable one? Well I can’t answer that yet, but I can answer a different question.

To start my project, I downloaded 30ish years of S&P 500 data starting September 1990 and asked a quick question: what 10-year period gave the best return if you had invested in the S&P? Once I get the baseline return down, I can add in things like stop-losses and momentum strategies to see if a savvy investor could have improved their return with simple rules. Anyway, here’s the data:

I make a small program to estimate the return if you have bought $10,000 of S&P 500 stocks and simply held them for 10 years, selling them at the end of the 10th year. From this we can see that 1990 would have by far been the best years to start as you would have been able to sell at the peak of the Dotcom Bubble. Just a couple of years later however and you would have sold into the Dotcom Crash instead, drastically lowering your returns. The worst years for a 10-year buy-and-hold were 1998-2000 as you would have sold into the teeth of the Financial Crisis. These are only years where your 10-year return would have been negative. Then we can see 2008-2009 themselves as some of the best years to start investing, since you would have bought right at the bottom and ridden strong returns into 2018-2019.

I hope to update the program soon to see if momentum strategies beat buy-and-hold, but for now this gives a good picture of the historical returns for the S&P 500. The average 10-year-return was 100%, but with an 80% standard deviation. The absolute worst return would have been to start investing March 30th 1999, you would have bought into the Dotcom Bubble and sold into the Financial Crisis with a net return of -48%. The best 10-year-return was to start October 11, 1990, which would have had you buy very low and sell near the tippy top of the Dotcom Bubble for a 510% return. There are some wild swings with the buy-and-hold strategy, but the average is still very positive, we’ll see later if stop-losses can beat that.

Send troops to the Fed?

Pardon me for wading into Twitter Drama, but Rohan Grey is a remarkably unserious “intellectual” and I couldn’t help myself.

Before I start, let me share a tiny story from “Zen and the Art of Motorcycle Maintenance.” This book was a thoroughly unenjoyable read for teenaged me, but it has one anecdote that still sticks with me. If memory serves, there is a university that is being threatened with losing its accreditation due to repeated failures and the students are naturally protesting as this would make their degrees worthless. One student talks to the narrator and claims that the University in fact can’t lose its accreditation, because if someone tried to take it “the Governor would send the national guard to protect us!”

I shouldn’t have to spell out the ridiculousness, but I want to hit word count so I will. Accreditation isn’t held in a vault, it isn’t something you can protect with guns and soldiers. Accreditation is the trust that other institutions have in you, and while some of it is legally codified most of its power is in the uncodified trust that a society is built on. You can’t protect accreditation with and soldiers any more than you can protect trust or friendship.

And so it was with bewilderment that I read an Assistant Law Professor on Twitter making the same mistakes as the nameless student from a book. Rohan Grey wants to do an end-run around the debt ceiling by having the Treasury mint a one trillion dollar platinum coin and deposit it in the Federal Reserve. This coin would then pay for the USA’s financial obligations without the need to borrow money. A big (and usually ignored) problem is that the Fed would have to accept the coin, and as Josh Barro writes, the Fed has expressed the opinion that this chicanery is illegal and undermines Fed independence. (Read Barro’s article, it goes into great detail as to why this idea probably wouldn’t work). Undeterred, Grey thinks the Fed’s opinion doesn’t matter, and that if they refuse to accept the coin then Biden should send troops to the Federal Reserve and force them to accept it.

Grey’s mistake is thinking that guns can be used to enforce trust. The Federal Reserve has the trust of the markets, and its power to move markets is based on that trust as much as anything else. The Federal Reserve trades bonds and sets rates, but those bonds and rates have value because people trust the Fed to keep its word, Jerome Powell’s speeches about the Fed’s plans have as much or more power as any action taken by the Fed. Now imagine a scenario where troops are instructed to besiege and occupy the Federal Reserve, where Powell is held at gunpoint and forced to accept a one trillion dollar deposit from the Treasury which he and the Fed have gone on record as saying is illegal. Trust in the Fed would be shattered, nothing Powell says or does matters anymore because the troops (and by extension the President) are running the show. Investors would flee from US government bonds, causing yields (and thus America’s cost of borrowing) to skyrocket, because America’s currency will have been debased against the will of its central banks, and will now be at the whims of the President.

And you may say “that’s fine, I like Biden as President” but do you like DeSantis? Do you trust that DeSantis wouldn’t be willing to send his own troops to force his will on the Fed? Would you buy a 10-year government bond if there’s a chance that DeSantis or Trump will be controlling it 2 years? And furthermore, Powell’s remarks on inflation will become worthless. Maybe Biden doesn’t like the rate rising that Powell needs to do, or maybe when the election comes he wants to juice the economy. So what’s to stop him from leaning over and reminding Powell who’s boss? What’s to stop Trump or DeSantis from doing the same? People like Grey once griped that Trump’s complaining caused the Fed to pause rate rises in 2019 (ignoring of course that inflation went under the Fed’s 2% target, which should cause them to pause rate hikes all on its own). Now Grey wants to make the Fed wholly subsumed by the President, so Trump would be able to do whatever he wanted.

Once you’ve sent troops to the Fed, you can’t unring that bell. Investors invest in American Dollars and American bonds in large part because they trust the Federal Reserve to do its duty with regards to the currency. Shattering that trust with soldiers would shatter investor confidence in the American economy as a whole. You’d have a trillion shiny dollars, but they wouldn’t be worth a pence.

Quick post: naysayers aren’t always wrong

There was recently a nuclear fusion “breakthrough” which brought the naysayers out of the woodwork. The breakthrough claimed that scientists had used fusion to generate more energy than was put in. This claim, however, discounted the energy cost of the lasers used to achieve the fusion, which is like saying your company is profitable is you ignore all the salaries. Not only that, this breakthrough isn’t even on the way to creating a self-sustaining fusion reaction, it can not create a self-sustaining reaction due to the need to add and target new material in between each laser pulse. This “breakthrough” is seeming more and more like a nothingburger, and the naysayers have come out to say nay on it.

This has led to the usual backlash from the yaysayers: “they said at airplanes and steamships would never work! You’re ignorant if you don’t believe fusion won’t work!” It’s true that naysayers often laugh and disparage the geniuses of the age, they laughed at the Wright Brothers, they laughed at Edison, but remember they also laughed at Bozo the clown. Yaysayers don’t ever seem to acquiesce to the numerous promised technologies that never really worked, only focusing on those that did work and claiming a direct connection to the current one. So I thought I’d illuminate some prior failures.

Flying cars: everyone knows that the promise of flying cars never panned out despite much public mindshare and media hype. You may counter that “flying cars aren’t impossible, trying to make them is just expensive, difficult, and unnecessary” to which I say “perhaps so is fusion.” The possibility of making a toy-flying car which would never be road-legal is akin to using 300 megajoules to get 3 megajoules out of a fusion pellet, and claiming you have a breakthrough. Doable yes, but it doesn’t prove the endeavor to be doable at scale.

Antigravity elevators. Albert Einstein made several attempts at unifying the (then known) forces of the Universe together. When he started, physicists only knew about electromagnetism and gravity, but it was very enticing that these forces act so similarly in that they have infinite range and their power falls off with the square of the distance. Einstein and others theorized that there was some way to change electricity into gravity and vice versa, and charlatans/”inventors” jumped on the idea. One theory was an antigravity elevator which, by transporting passengers up and down through gravity waves instead of a moving cab, would be much more efficient and perhaps easier to maintain. Of course this idea never came to pass, not least because theories on the unification of gravity with electromagnetism were still missing half the puzzle: the strong and weak nuclear forces.

And here’s a great one: Supersonic flight transport aircraft. Now this might seem a weird one, Concorde showed it isn’t impossible, but as I’ve discussed before history has shown it to be clearly uneconomical when compared to its competitors. An idea doesn’t have to be impossible to get tossed aside, merely uneconomical.

I feel like people don’t realize how many seemingly great ideas have come and failed because they just aren’t economical even if they aren’t impossible. Fusion could well be one of those ideas, sure it works in physics but in economics who’s to say fission and renewables aren’t just objectively better? We’re still decades off even a working test reactor, and the one being planned is already about 4x over budget. Private companies have claimed they’ll come in and disrupt the industry but we had the same claims about a lot of failed projects over the years, who’s to say fusion will be any different? I know that fusion power as a scientific concept is perfectly sound, but as an engineering challenge or a profitable industry I remain skeptical.

Invest in what you know? How much do I need to know?

I’m a biochemical scientist. I’ve published papers. I’ve got degrees. As an investor, I’ve often been given the advice (whether from friends or randos on the internet) that to “invest in what you know” is the safest kind of investment. For me personally though, I’ve avoided investing in any particular biotech or med-tech companies outside of passive ETFs, because I feel like while I know a lot about biochemistry in general I don’t know enough in specific to have any kind of advantage in those areas. I know about Alzheimer’s disease, but I don’t know much about pharmacology so how would I discriminate between two Alzheimer’s drug companies I wanted to invest in? I know about CRISPR/Cas, but I don’t know enough about its delivery system in humans to feel confident that I could pick the winners in today’s more crowded CRISPR field. There are a lot of areas of biology that I feel I have a little knowledge, but not enough to give me an edge.

Maybe there’s a Dunning-Kruger effect here though, because while I can’t explain what cloud computing is besides “it’s like renting another person’s computer,” I have thrown a bunch of money into Microsoft and been happily watching it grow. I like my Microsoft products and my office suite, so I feel good enough about them that I feel they’re doing alright. Yet I clearly know a hell of a lot less about Microsoft than I do any of the biotech companies of the world, so why do I feel so confident investing here?

I don’t know, it’s hard to psycho-analyze myself, but am I making all the wrong moves? Should I focus on investing in biotech companies, confident that my background would give me an edge in picking the winners and avoiding the losers? For now, ETFs for me I guess, but I’ll keep blogging about them since they’re fun.

The nuclear fusion breakthrough that wasn’t

There was recently a nuclear fusion “breakthrough” which I just had to check out. I was disappointed to learn that this wasn’t a breakthrough at all, but a clever bit of marketing dressing up a modest scientific experiment. To explain what happened, a laboratory used around 300 megajoules of energy to create a 2 megajoule laser pulse. That pulse then hit a pellet of material, releasing 3 megajoules of energy as the pellet underwent nuclear fusion. The holy grail of fusion is a self-sustaining reaction, one necessity of such a reaction is that more energy must be released than is put in, and this experiment was hails as doing just that since the 3 megajoules of released energy is more than the 2 megajoule laser pulse. Yet that isn’t actually true because 300 megajoules went into creating that laser pulse, this is like saying a company is profitable if you ignore all salary costs. At the end of the day we want to develop a fusion reaction such that energy out > energy in, and this reaction simply did not do that.

I know why they tried to spin it this way, it’s a longstanding trick of pulsed-laser experiments to report only the amount of energy delivered by the laser, ignoring the amount of energy it takes to create that laser pulse. It makes your reactions seem a lot more efficient and feasible than they really are. But this kind of lying does the entire industry a disservice because it’s just more evidence on the pile of fusion-boosters overpromising and underdelivering. Reading this news you’d mistakenly believe we are now on the precipice of economical and available fusion power when in actuality we’re about as far as we’ve always been.

Rest in Peace, Shamus Young

Yesterday, I wrote a post where I offhandedly mentioned the death of Shamus Young.  I had done so because during the post I remembered a decade old post of his (that I still can’t find!) that had so succinctly explained everything I was talking about.  I finished the blog post, and while looking for Shamus’ post so I could link to it, I learned that he had died last year. 

I’m pretty late to the party on this one, I haven’t been following him for a few years.  But I first heard about him when he published DM of the Rings around a decade and a half ago, and for a while he was my main source of gaming news and reviews.  I first played Oblivion because of a post he wrote about it, same with Morrowind and even the original X-Com.  I got a lot of my early gaming exposure from him and his blog, and I still think a lot about some of the things I read from him.  My previous post on Skyrim is based heavily on a post I remember him writing about Oblivion and RPGs in general, and a lot of the concepts he wrote about still come back to me.  Learning that he had passed, at what seems like an early age, kind of hits me.  I was never more than a lurker to his blog, and I don’t really know what I wanted to say with this post.  I’m so late to the party and was no more than a reader, so I can’t really share in the grief with others.  But I just wanted to say that he was incredibly fun and funny, and I’m glad I got to read him.

If you’ve never read it, DM of the Rings is well worth your time.  Farewell to a really cool guy.