Every time I visit the doctor, I feel like I live in the dark ages

Health care is a misnomer for our medical system–It should be called sick care. Doctors mostly make their money when we are sick. What if doctors really could prevent disease? —well they can, but you need to be prepared to do the work because disease prevention is about:

  1. Lifestyle (what you eat, your weight and how much you exercise—covered here)
  2. Exposure to disease (wash your hands)
  3. Keeping great medical records (don’t get me started on a. doctors keeping paper files, b. doctors making it difficult to get your medical records (push them) and c. electronic medical record systems having different formats for the data (more))
  4. Documenting and understanding your genome (DNA)

This set of notes will dig into “4” – Your genome!  My hope is to explain this subject in a way where you can understand how to get your genome data, view it at a high level, view the details and begin to understand the interworking’s of your genetic makeup so you understand the value of leaving your ‘sick care’ doctor behind and finding a true personalized ‘health care’ MD).

Step 1: Have your genome mapped

There are many low-cost direct-to-consumer DNA mapping sites and this linked article will explain a few options for you to consider (here is another).  I personally like 23andMe ($199 USD) because it does a great job of explaining DNA to a novice and a professional, they seek FDA approval, and the site allows you to download your data.

Let’s first cover a few standard definitions to make sure we are all on the same page:

  • DNA (deoxyribonucleic acid) – A molecule composed of two chains that coil around each other to form a double helix carrying the genetic instructions used in the growth, development, functioning, and reproduction of all known living organisms and many viruses.
  • Chromosome – a DNA molecule with part or all the genetic material (genome) of an organism. Human cells have 23 pairs of chromosomes (22 pairs of autosomes and one pair of sex chromosomes), giving a total of 46.
  • Genes – From 23andMe, “Genes are segments of DNA that tell your body how to function and what traits to express. People have about 22,000 genes in their genome. Most of these come in duplicate – one copy from your mother and one from your father. Everyone has the same set of genes, but each one can vary by a few letters (bases) between people. These “variants” can lead to differences in the way you look, how you respond to stimuli, and whether or not you are predisposed to certain diseases.”

Once you get your data back from one of these direct-to-consumer genome mapping sites you will have access to their portal.  I’m going to use 23andMe as the example, but many are similar. When you get your report, you can easily go to the ‘Health’ section and see what it is reporting. It will look something like the following:

Step 2: Download your raw genome data to a safe password protected and encrypted location.  

If you are using 23andMe you can download your raw data using these instructions.  If you know what you are looking for you can also dig into your raw data here (more on this later).

But what can you do with your raw genome data?

WARNING: This is where things get a bit tricky. There are five very important things to know:

  1. If you upload your raw data to a website (here is a list of websites and another) you need to be very careful about things like, who is behind the site, what is their country of origin, what is their security policy and most important what is their privacy policy.
  2. Some sites (like Promethease) list all the SNP markers (From 23andMe, “A marker is a specific location in the genome where a genetic sequence has been shown to vary between people. Markers are denoted by a unique identifier, most often an “rs number”) associated with different traits and diseases, as curated from SNPedia. Drawing any conclusion from this reporting is often frowned upon by geneticists. There is such a thing as an SNP that is strongly associated with a disease (These are typically the ones 23andme has FDA approval to report—example BRCA1/2  The individual gene mutations BRCA1 increases the risk of breast cancer. Angelina Jolie is just one of the thousands of women who chose bilateral prophylactic mastectomy to mitigate the increased risk of the BRCA1 mutation.) but most common diseases are not really affected by any given SNP.
  3. The best analysis uses the compound effect of many SNPs with an understanding that each only contributes a small effect. This concept is called polygenic risk scoring (PRS).  This allows scientists to take anyone’s genome and calculate your aggregate risk for certain diseases even if you don’t have one of the known major mutations. Polygenic Risk Scoring is the total score of all the minor gene variations that increase disease risk. This is a powerful upgrade to your doctor’s ability to predict disease in any given patient. This means doctors are no longer in the dark with only the family history to guide them.  (here, here, here and here are 4 great articles on PRS)
  4. From the Norton & Elaine Sarnoff Center for Jewish Genetics: “Your “risk score” is not an absolute determinant of your health, personal lifestyle choices have an effect – You’ve heard of nature versus nurture. If an individual with a high “risk score” acts on preventative care advice, they may decrease their risk of having a genetic disease. The opposite can be true of someone with a low “risk score”. (Read more: How do your genes and the environment interact?)”
  5. Be careful of companies target marketing supplements or programs at gene variants –always check with a licensed medical doctor (MD) before taking any actions.

Step 3: Mapping your raw data to the SNPedia database (but heed warning #2 above)

I am going to use the Promethease site.  A report is $12, and it can directly connect your 23andMe DNA data with the SNPedia human genetics wiki. It also provides information on the effects of genetic variants on Phenotypes (the composite of the organism’s observable characteristics or traits, including its physical form and structure; its developmental processes; its biochemical and physiological properties; its behavior, and the products of behavior, for example, a bird’s nest. An organism’s phenotype results from two basic factors: the expression of an organism’s genetic code, and the influence of environmental factors.) and the information is sourced from peer-reviewed scientific publications. Keep in mind that the match against the SNPedia database may be wrong, as the raw data is not held to the same quality level as that which is part of an FDA approved report from 23andMe.

The report only takes 5 to 10 minutes to generate and you will get it via email as a zip file and via their website.  It will look like the figure below where you have a search panel on the right and the data on the left.  In the example below, you can see the SNP (Single Nucleotide Polymorphism) marker is rs1333049 (From 23andMe, “A marker (SNP) is a specific location in the genome where a genetic sequence has been shown to vary between people. Markers are denoted by a unique identifier, most often an “rs number”, or “rsid”.”).  You will also see the Position (From 23andMe, “If you stretched out all of the DNA in a chromosome from end to end, you could count the position of each letter (A,C,T,G) relative to the first one in the sequence. This count is referred to as a genome coordinate or position. 23andMe uses the same coordinates as the National Center for Biotechnology Information (NCBI), build 37.”).  You will also see the Magnitude (From SNPedia.com, “Magnitude is a subjective measure of interest varying from 0 to 10. Over time it should be adjusted up or down by the community.” The range is from 0 (you have the common genotype) to 10 (significant information).)  You probably only want to review magnitude 3 and above.

If you click on the SNP marker hyperlink rs1333049 you will be taken to the details page in the WIKI.

From the page above on the far right, you have links to many great sites including Ensembl and 23andMe’s detail pages.

You can see more about the Ensembl tool in the article published at https://scottsuhy.com/2018/12/11/dmd-going-one-level-deeper-a-personal-problem/

Once on the 23andMe page you can also see the Variant (From 23andMe, “At any position in the genome that varies, there is more than one possible version (or variant) of the DNA sequence. For example, some people might have an A at a certain position, whereas other people might have a T.” Genetic variations, or variants, are the differences that make each person’s genome unique. DNA sequencing identifies an individual’s variants by comparing the DNA sequence of an individual to the DNA sequence of a reference genome maintained by the Genome Reference Consortium (GRC).) and Your genotype at a marker (From 23andMe, “Your genotype at a marker is the combination of variants that you have at that position on both chromosomes’ copies. For example, if you have the A on one chromosome copy and a T on the other one, your genotype is AT. Some chromosomes don’t come in pairs (i.e. the mitochondrial chromosome and, for the most part, the X and Y chromosomes in men), so your genotype can sometimes be a single letter.”)

There are several other tools out there to get information on each one of the SNP markers.  One of the best is found here at NIH.gov.  With this, you can search for many research articles per SNP marker.

Now that you have all that data, please reread Warning #2 above!

Step 4: Map your data to known polygenic algorithms

These sites are reported to be working with polygenic risk scores:

Keep in mind that this is a relatively new science that has been enabled by the mapping of the human genome. The research is coming out fast. As an example, Sekar Kathiresan and his colleagues at Harvard University and the Broad Institute have been focused on variations linked to coronary artery disease, atrial fibrillation (an irregular heart rate), type 2 diabetes, inflammatory bowel disease, and breast cancer.  They developed an algorithm that could use all this information on a disease’s genetic variants to produce a polygenic risk score, a single number that would indicate a person’s risk of developing each disease based on their genomic data. Their algorithm identified 20 times more people at high risk of a heart attack than did the traditional method of just looking for the variant that indicates inherited high cholesterol. If more people know they’re at risk, they can go on medication or start making lifestyle changes to prevent the onset of the disease.  You can get a copy of the report here or here.

As an example, here is data from Impute.me a non-profit (please donate) genetics analysis site run by independent academics since August 2015. Their design goal is to provide analysis at the cutting edge of what is currently known and possible in genetics research. A central part of their site is the creation of a guidebook for personal genome analysis. This book provides more in-depth explanations for many of the concepts involved and it’s highly recommended as a guide to accompany your analysis. (New: Updates to the site will be announced at twitter). 

Let’s go into a couple interesting things you can do with their site.  Note that I am using the text below directly from the Input.me website.

Complex Disease

A polygenic risk score is a value that gives a summary of a large number of different SNPs – each of which contributes a little to disease risk. The higher the value, the higher the risk of developing the disease. Of course, the interpretation of this risk depends a lot on other factors as well: How heritable the disease is. How much of this heritability we can explain with known SNPs. And not least, what would the risk of disease be for you otherwise, i.e. without taking the genetic component into account. Because the polygenic risk score is only a risk-modifier, knowledge of these three other values are all required if you want to know your overall risk is, i.e. what’s the chance in percent. This calculator cannot provide that. But it can provide a view of the known genetic component of your disease risk, based on all the SNPs that we know are associated with the disease. This, we believe, makes it a better choice for complex diseases than the typical one-SNP-at-the time analysis typically seen in consumer genetics.

If you upload your 23andMe data after a couple of days you will have access to this site and a unique ID that will be good for 2 weeks.

Precision Medicine

This is a module that can visualize the entire compendium of human disease – at each point showing relevant genetic findings. The goal is to illustrate how to present genetic data depending on a medical status.

Diseases, where one mutation has a strong medical effect on you are luckily rare. For the majority of people, learning from our genes is instead matter risk modifications and weak predictions. For a healthy adult, these are typically of little practical use. However, the assumption changes drastically if you are not healthy; If you are anyway being evaluated for a given disease, it may very well be useful to know if a different but medically related diagnosis has a particularly high or low risk. 

For example, if a person is suffering from mental problems, but have not yet been properly evaluated for any specific diagnosis, then genetic risk information for all diseases related to mental problems may become useful knowledge. Because the information can then serve as a guiding point in that difficult challenge of first diagnosis. Similar examples can be made for virtually all areas of early medical evaluation.

It is the purpose of the module to help with this: By forcing browsing into pre-defined sets of disease-areas, the algorithm provides you only with genetic information that is relevant to.your current medical status. Nothing more, nothing less. Risk scores relevant to the medical area you are interested in will be shown. Fluke signals from irrelevant disorders will not. The details behind all information given here can be explored in the remaining modules of the site, as indicated when you click on each of colored bubbles above. As such this module can serve as an entry-way into the entire site, depending on your context and interest.

In the root of the tree, we find ‘feeling fine’, which is always a neutral color: People who feel fine don’t need to worry about their genetic risk scores. However, when selecting ‘heading to hospital’, climbing up the tree, the genetic risk scores are revealed as they become relevant. More of the thinking behind this module is explained in this short animation-video from 2017.

Rare Disease

The overview of rare disease variants found in this module is not the most extensive single-SNP effects available online. They are shown here because they are all well-supported strong genetic effects, for a selection of rare inherited diseases where microarray analysis made sense. This was the reason these SNPs were included in the 2016-version of the 23andme health.

Especially the last part – that microarray analysis made sense – is very important when analyzing the genetics of rare disease; the microarray technology used in consumer genetics is not optimal because the really strong mutations typically are not measured on a microarray. DNA-sequencing is required to detect them. Therefore microarray analysis of rare disease effects has many problems with false negative results. There’s a lot of further details to this discussion, chapter 3.5 in this book is a good place to seek more information.

Nonetheless, the 2016-selection of microarray-measurable SNPs made by 23andme still is reasonably relevant to report, particularly for the carrier-information. For non-23andme users, this module has the additional benefit of translating the data for proprietary 23andme SNPs, with the caveat that because the SNPs are very rare they are often hard to impute.

Drug Response

This is a test of a systematic approach to drug-response SNPs. Most of the known drug-response-associated genetics concern liver enzymes (e.g. CYP2C19) and their break-down of drug metabolites. These are well characterized elsewhere already. The focus of this module is to integrate systematic multi-SNP profiles beyond liver enzymes and provide estimates of drug-response.

To illustrate how this works, the module shows the calculations that take place for a number of drug response predictions, both on a per-drug level and on a per-SNP level, corresponding to the first and the second table. The first table summarizes per-drug calculation whenever possible. If possible, a Z-score is calculated in the same way as also described in the complex disease module. If not, it is indicated as ‘not calculated’. In that case, it is necessary to look at the second table for comments on the individual SNPs from the input studies. The Z-score approach takes information from many SNPs, and can, therefore, be considered as more thorough, of course depending on the underlying scientific study.

Gene Mutations

Most SNPs in the genome are not actually found within a gene: They are ‘intergenic’. When talking about a gene-mutation however, as is done in popular media, most often the meaning is a SNP that alters the sequence of a gene. Because of selection pressure throughout our evolution, these are rare. Also, they are often the focus of scientific studies using DNA-sequencing technology to discover the causes of rare diseases. However, interestingly many of us actually have these ‘gene-breaking’ SNPs while nonetheless being perfectly healthy. The imputation technology used with this site gives the opportunity to identify a number of these based on just on genotyping microarray results. If you give your ID-code to this module a table of all measured missense and nonsense mutations will be presented. 

Interpretation of the table can be done in many ways and unlike other modules, this does not give ‘one true answer’. One method is to search for SNPs where you have one or two copies of the non-common allele and then investigate the consequence using other resources such as dbSnp or ExAC. Note however that the definition of ‘common’ is very dependent on ethnicity: in this browser common just means the allele most often found in impute.me-users. However, it is recommended to check the ethical distribution in e.g. the 1000 genomes browser. Another help provided is the polyphen and SIFT-scores, which can give an indication of the consequence. Ultimately the goal of this is to satisfy one’s curiosity about the state of your functional genes. If you happen to find out that you carry two copies of completely deleterious mutations (nonsense mutation) but otherwise feel healthy, feel free to contact us. By being healthy, in spite of a specific broken gene, you’d be contributing to complete our view of genes and how they work.

BRCA

Thousands of mutations in the BRCA1 and BRCA2 genes have been documented. 23andMe reports data for three mutations that account much of inherited breast cancer, but other possible mutations in these two genes are not included in the 23andme report. Many can only be detected by sequencing, such as from myriad genetics. However, dozens of extra possible mutations of interest can be reached with imputation analysis. The following lists your genotype for the directly measured three 23andme-SNPs as well as all other SNPs in the two genes that are either missense or nonsense. For interpretation, we recommend reading more about polyphensift-scores, and clinvar.

If clinvar is indicated as pathogenic and the SNP is measured in your genome and your genotype is not of the genotype indicates as normal, then this indicates a potential problem. The list is sorted according to the clinvar variable by default.

UK Bio-bank Calculator

A study of ~½ million UK residents, known as the UK biobank, has recently been published. This module allows the calculation of a genetic risk score for any of the published traits.

Now that you have all that data please reread Warning #4 above.

Step 5. Make a plan.

If you are high risk for coronary artery disease see a cardiologist. If you are at high risk for breast cancer, mental illness, eye problems etc. see a medical (MD) specialist.

…but be wary of Warning #5 above–don’t go see a “quack” and don’t self medicate!

..but also do your homework and understand if the specialist is up to date on the latest and greatest –for example, if you see a psychiatrist for ADHD make sure they are trained in epigenetics. 

Other Information:

Other Tools:

Spinning out

Over the past couple of years, I’ve been called in by executives, bankers, and investors to determine if an entity (company, university or government) should spin out some technology into a new business. Some have already made up their minds and others are in the fact-finding stage.  This is the process I use to suss it all out…

The first thing you must do is figure out if the entity has given this spinout a lot of thought or is this just an idea? To find out you must get their answers to 11 questions. You are trying to figure out the level of depth in their thought process—is it cursory or at a grand level of depth?

  1. The Problem: What is the business problem that a NewCo would use this IP to solve?
  2. The Solution: How does the IP solve the problem?
  3. The Value: How much impact would the solution have on a company’s cost savings or increased productivity or increased security etc.
  4. The Market Size: How big is the market for the solution?
  5. The Timing: Why is now a good time for this type of solution?
  6. The Proof: What proof/milestones have been achieved that prove there is a market for the solution?  
  7. The Plan: What does the entity see as NewCo’s strategy for taking the solution to market?
  8. The Competition: Who else is out there selling a similar solution? How well are they doing? What does this IP have that others are missing?
  9. The Obstacles: What obstacles would be in the way of NewCo’s success?
  10. The Team: What team members would go with the IP (if any at all)?
  11. The Financial Model: How much cost would it take to build a NewCo and how much value could it return over what time frame?

If the entity is experienced and has sold or licensed IP in the past, or has funded companies as subsidiaries or new entities previously, they likely have thought through these 11 items in quite a bit of detail and understand the value of their asset and who in the market is the likely ‘acquirers of’ / ’investors in’ such an asset. If not, then there is market-analysis work to do first to determine if this exercise is an event worth the energy. 

The second thing you must do is understand ‘why’–the Motivation.  Why would the entity spinout IP versus capitalizing on its value?  It’s easy to understand why a university or government would spin tech out (they can’t capitalize on it easily) but for a corporation to do it, there must be a good reason. 

  • Is it easier and cheaper for R&D to be done outside the company?
  • Is it a deviation from corporate priorities (example: we do R&D for the government)?
  • It’s used internally with great value, but the tech would have even more value to the entity if thousands of other companies were using it as well.

It’s important to understand the underlying motivations so you can begin to understand the dynamics of the situation.

The third item to figure out is if the entity has an expectation of value?  Some entities have divested of a lot of IP in the past and for others, this may be the first time.  You must figure out if the entity’s expectations are reasonable.

Last, does the entity have a business model in mind? Do they just want to sell the IP to a buyer, or do they want to fund a startup? …or is the answer somewhere in between (license the technology to NewCo for a % of sales as one example). You must figure out if they want a short or long-term return, and do they understand the ramifications (additional investment may be required; legal fees etc.).

Market Analysis

Let’s go a little deeper into item 1 above as it will begin to shape the entire conversation with the entity.

What category does this IP fit in, regarding the tech ecosystem? A great place to start is Crunchbase.

As an example, let’s say that the IP in question helps the entity’s corporate employees communicate better on tasks, in and between, corporate silos.  You dig into CrunchBase and find 475 companies competing in the ‘Task Management’ category and another 2,400 competing in the ‘Collaboration’ category and 108 companies with both. Obviously, there are many solutions in each of these sub-categories solving different aspects of collaboration for different audiences and there is a lot of overlap, so the sub-categories are difficult to navigate but you can ascertain there is a great deal of competition in each of the collaboration submarkets.

Are there market leaders leveraging similar IP? One easy way to tell is if Gartner, Forrester, IDC or another large trusted enterprise research organizations has created a market guide.

If we take our task management example a bit further, we might see a few big horizontal areas where the tech is applicable (possibly Project Management, CRM and IT Service Management) and who some of the dominant players in the market are today. Gartner does a nice job of showing this in something they call a magic quadrant. 

You can see that the market (at least in the past) really splits between two areas:

  • Externally facing: Customer Relationship Management (CRM) – Salesforce.com is the leader
  • Internally facing: IT Services Management (ITSM), PM, HR, Product Development – ServiceNow, Planview, and Atlassian are market leaders

You can also build some market reference points on these leaders.  For example, ServiceNow finished 2018 with about $2.8 billion in annual revenue (and Q2 revenue was up 45%) and Salesforce increased its market share in 2017 by more percentage points than the rest of the top twenty CRM vendors combined.

If enterprise solutions are being sold with similar IP you can generally get access to market size data that the Enterprise Research Analysts have published—it might cost you a Gartner subscription but there is great value in the research.

Who are the new market challengers that are doing something with similar IP? Every space is being disintermediated in some way, shape or form so you need to understand how the market where your IP fits is changing and how much is being invested in the changing landscape.

With our example, you will see that companies like Asana and Trello are having a major impact on the future of the space.  You can also see that a great deal of funding is going into these new platforms from well-known venture capital companies. You can find all this data at no-cost in Crunchbase.

Looking at both market leaders and challengers will help you start to understand the ‘problems’ being solved, the ‘solutions’ being used/sold, the ‘value’ being created, and the ‘pricing’ being used by similar IP in the market.

Are there changes on the horizon for the future of the markets where this IP fits? Once you dig into the enterprise plays and compare the market-challengers you will soon see if any patterns emerge.   This could start to provide you a view into ‘timing’ and market adoption and will allow you to determine if your IP is too old or is it perfectly timed for where the market is going to be in a few years.  This will also help you to start formulating some of the obstacles with the IP.

If we continue with our same task management example, you will see that the market is moving toward platforms that enable many solutions that are tightly integrated.  The market has coined the term Platform-as-a-Serve (PaaS) for the shift.  Gartner even has a magic quadrant referencing the platform enablers for the shift.

And if you dig into the market challengers to this platform shift you will additionally find all the Function-as-a-Service (FaaS) or Serverless discussions.

Timing. As a new company, if you are late to the market, you will likely lose. Only fast followers that differentiate primarily based on a superior cost structure due to scale can win as a follower.  If you follow Pete Flint’s NfX model for startup timing “it’s all about who enters the market closest to the critical mass point. It’s at this point when technology, economic and cultural forces can combine to enable explosive growth”. 

With our task management example, given the onset of FaaS and current enterprise companies already fully entrenched in PaaS the IP would have to already be written with FaaS in mind to have a chance at competing with the momentum of the challengers or the entrenchment of the enterprise PaaS solution….or the idea would have to be so unique that a rewrite of the code would be worth the effort/cost.

Proof.  You must be able to prove there is value for this IP in the market and to the best extent possible minimize risks. Simple questions that need to be answered are as follows:

  • Who is using the IP today? Is there or can there be a detailed case study written? Can the value be quantified with the current use case? Have others seen, requested or been given access to the IP and what is their feedback?
  • How much has been invested to build the current IP (in dollars and time)? How big was the team? What are the skills of each of the people on the team? When was the IP last updated? How well is the IP documented? Are there patents from the company or others that infringe on the IP (you must do a patent review prior to next steps—do a preliminary review here).
  • Is the current IP part of a Continuous Delivery process and is it well documented?
  • What languages were used to build the IP? What open-source libraries? What are the licenses of each of those libraries? Has an inventory of the code been documented by a group such as Black Duck?  Are there any proprietary libraries being leveraged that lock the IP into a certain platform (such as AWS)?

With our task management example, the code is being used by the entity so there is a great deal of information that can be gathered and used. The code also would come with its first customer (the entity).  If the entity isn’t willing to continue to be the first customer then this may be a warning sign and should be discussed.

Plan. What strategies are potentially applicable to build a company around the IP?  An easy way to start digging into opportunities for different strategies is to leverage the “Blue Ocean Strategy” and to dig into different uncontested markets for the IP.  Are there areas in the market that are uncontested, and the IP is a perfect fit?

You also have to know how the IP lines up with a Lean Startup  Minimum Viable Product (MVP) for the uncontested market and how long it will be until the IP is read to put in front of customers to test assumptions.  This is critical for early decision making.

With our previous example, it’s difficult to find uncontested space given how big the entrenched players are and how much energy (VC $) is going into the hundreds of challengers. There may be a play for AI, IoT or Consumers—and then again, there may be an uncontested space that’s not well understood still available.

Team. How big was the team that built the IP? What are the skills of each of the people on the team? Where are they located? How are they compensated? What are they doing now? Are any of the people that built the IP willing to move with the IP?

Financial Model.  Given most IP today is delivered via the Cloud it would be good to have some idea of the cost of building such a company.  The spreadsheet outlined in this post by Gary Gaspar (and in the comments) is good enough to start getting a handle on what it would likely cost to get such a company testing the uncontested spaces you found previously.

At the end of the day, the more you know about the market for the IP and the opportunities the better decision you will make about what to do with it in the market.

However, never forget the golden rule: Building a company is NEVER about the idea… and it’s not about the plan… It’s ALL about the team and how the plan is Executed!

More to read:

We all use the same data…

I had a money manager say something to me the other day that struck me as odd—so I thought I’d dig in a bit to see if I can rationalize his comment.   He said, “We are all using the same data” when I asked him about an opinion that I heard from someone else about the stock market over the next few months. His basic point was that the market is about valuations & fundamentals” (more) and significant deviations from intrinsic value are rare, and markets usually revert rapidly to share prices commensurate with economic fundamentals.  Therefore, if you use tried-and-true analysis of a company’s discounted cash flow to make your valuation decisions you will be fine over the long run.

I think the most important thing he said was “over the long run”.  Because some investors do have access to fundamental data (private feeds) that others don’t and if a proprietary feed is faster and gives the investor a ‘speed advantage’ in trading then that is an unfair advantage. For example, if the price of a stock goes from $100 a share to $95, and you know that and someone else doesn’t, it makes sense to sell at $100 to a buyer when the investor knows the price is now $95. If you are a high-frequency trader and you know prices are changing millions of times a day across many securities, you can make a great deal of money.

“…our system for telling investors what stocks are worth should be straightforward. Instead, we have created a two-tier system of stock-price information—a lower-quality public feed and generally higher-quality private ones.”  Commissioner Robert J. Jackson Jr. (more on Public versus Private feeds)

Some investors also have access to “alternative data” like satellite imagery to analyze information such as parking lots, web scraping to track items such as consumer preferences and geolocation data to analyze information such as consumer traffic to certain stores.  With tools like Artificial Intelligence/Machine Learning the new Quant 2.0 Wall-Street geniuses can take proprietary fundamental feeds and these new alternative datasets and do Algorithmic trading to uncover value faster than any old school hedge fund manager (example).

But at the end of the day, you don’t have access to any of these tools… So, if you can suffer through all the volatility and you trust that your money manager is on top of your portfolio’s underlying fundamentals then yes, the market can still work for you over the long run.  However, just know that many strategic investors will have made a lot more money than you, on those same investments, by leveraging better tools and quant 2.0 type talent.

…you can throw all this long term investing out the window if you have a mere $7.5 billion to invest and then Bridgewater Associates can do it for you and you will likely do very well.

While the Quant’s and AI-powered algorithms can crunch numbers and make an investment decision, they can’t offer the human touch and it has become evident to me that the human touch is an essential component to long-term investing—net: you need a coach to get you through the stress of the volatility–get a good money manager.

Footnote: and never forget that you need to respect market sentiment.

How do new blockchain/crypto business model incentives differ from old school companies like Facebook?

I recently read Chris Dixon’s article at WIRED titled “BLOCKCHAIN CAN WREST THE INTERNET FROM CORPORATIONS’ GRASP” found here https://www.wired.com/story/how-blockchain-can-wrest-the-internet-from-corporations/.

The article was a fun read but it was very high level and left me with questions about how the incentives for founders, investors, customers, and the employees change in this new world (i.e. when governance is provided by the community versus the company). For example, if you compare the company Facebook to a NewCo like a steemit.

I listed my assumptions in the table below after reading the article. It would be great for this community to help contrast the changes between models (I also posted this article on steemit and I’m spending some time learning the platform as well as the new crypto/blockchain models that have momentum).

Please comment on what is right/wrong or needs to be better articulated in the table below…

Facebook (Governance provided by the Company) NewCo’s (Governance provided by the Community)
Founders invest time and $ upfront and are rewarded by pay in $ and exit (sale or IPO) in $ of shares they own Founders invest time and $ upfront and are rewarded by pay in $ from ICO/STO and from an increase in the token price of held back tokens which are eventually sold for $

Note: Founders hold back tokens that they personally own that are valued and can be sold on an exchange for $ once vested

Change= Founders can sell tokens for $ once tokens vest versus at exit or IPO

Risk: From day 1 the company is public which comes with a great deal of overhead; Founders can also cash out once vested.

Investors buy shares or debt in company in series A, B, C etc for $ and get rewarded by increased share price (over time) which in turn is sold for $ upon exit Investors buy tokens (example: STEEM, SP or SBD) in company at any time for $ and get rewarded by increased token price or interest on debt (ex:SBD)which in turn is sold for $

Change = Investors buy tokens at any time versus shares in the company

Company provides proprietary service at no-cost and sells advertising and get rewarded with $Change = Company gives proprietary service away for free versus an old school MSFT model where proprietary software is sold for $ Company provides open-source service at no-cost and sell nothing and get no reward (other than token appreciation in the market)

Note: Company holds back tokens from market to be sold for $ and used to run company

Change = Company sells nothing

Change = Company reward is 0

Employees help company make proprietary service; sell advertising and get rewarded with $ Employees help make & sell open-source service and get rewarded with pay ($ from held back tokens); Community helps company make open-source service and gets rewarded with tokens which can be sold for $

Change=Community helps develop open-source code

Customers get proprietary service and pay with their data and get rewarded with value Customers get open-source service and pay with activity and get rewarded with value and tokens which they can sell for $

What others report:

> From TechCrunch: Tokens (versus options) can better incentivize startup employees than equity “One of the largest differences between tokens and equity is that tokens are immediately liquid, assuming that they have already been listed on an exchange.”–however, as commenters to the article point out easy liquidity for employees can be bad for a startup. It can also cause tax issues for the employees.

> From CoinDesk: The Biggest Problem for ICOs? In 2018, It Was Their Own Investors” Instead of treating individuals who make early contributions as merely financial investors, projects that are truly pursuing decentralization should recognize them as more akin to employees who receive stock options (and can actively contribute to the network from outside the organization) and adopt a philosophy of ‘compensation through the protocol’ to leverage them.” — ‘Proof of Contribution’

Georgetown Retail

This is an update to my notes from last July (found here). Update since: By the time the summer ended the city had cleaned up the graffiti and fixed several of the sidewalks—great job! However, there are still issues to discuss such as the retail vacancies.

I attended the “The Future of Georgetown” meeting on 1/15/19 hosted by the amazing Citizens of Georgetown (CAG) group and spectacular Advisory Neighborhood Commission (ANC 2E) but came away a bit disappointed with what the Georgetown Business Improvement District (BID) presented as the areas future of retail.

The BID spent 30 minutes of the presentation on why it’s so hard to have a good retail ecosystem in Georgetown (i.e. Amazon, unrealistic landlords/rents, awkward spaces in old buildings) and how many retailers are going out of business.  They also painted a picture on why it’s not as bad as it looks –even though I counted 19 vacancies when I walked down Wisconsin Ave to get to the meeting. …but what really got to me was at the end of their presentation they said that this is all part of a cycle and Georgetown’s business district will still be here when other locations fail—and that’s just not a good way to manage the area’s future (i.e. telling people to wait and have hope).  I personally don’t think this is a cycle—retail as we have known it is dying and if we don’t have a well thought out strategy for how to grow with these changes then the business district will die a slow death and Georgetown will no longer be the tourist destination or the exciting place to live that it is currently.

Don’t get me wrong, this is a wonderful community (in a remarkable city) with a beautiful waterfront and a great plan for the canal (being done by the same team that did NYC High Line)—but we need a better plan for our diminishing retail market than wait for the cycle to rebound.  This 2028 strategic plan is good and the update speaks volumes but we need to have a more thoughtful discussion about the Georgetown retail problem (everything needs to be on the table—policy, zoning, investment etc.).

I don’t disagree with anything the BID laid out in regards to our challenges (most big city retail communities are facing the same issues) but what the presentation made me think is that the ‘Free Market’ is not working for Georgetown’s retail district if online commerce is hurting it, absent/uncaring landlords are leaving spaces vacant for years and the city infrastructure is not desirable because it’s old/lacks parking & a metro—and when the free market doesn’t work policymakers need to get involved. I didn’t see any policy ‘makers’ (Jack-Ward 2, Kenyan-Chair Committee on Bus & Economic Dev) at the meeting but I may have missed them—however I would not have expected them at the meeting as the ANC had it covered very well and that is our voice to the policy makers–and they did ask for our feedback (hence this update)!

What I hear from the community is that Georgetown visitors and locals want great restaurants, art & entertainment, shopping, and experiences—but most importantly they want Georgetown to stay relevant to the world as a brand destination and a great place to live. The ANC asked for feedback and ideas:

Maybe to ensure Georgetown stays relevant we could:

  • Make it harder for landlords to leave storefronts vacant via new legislative policies (examples & risks). 
  • Create income tax abatements for commercial building rehab or new development (example from Falls Church VA).
  • Ring-fence grant funding for the types of businesses we want to attract (maybe extend this program to include M Street and understand if it worked for Wisconsin and push to increase funding).
  • Revisit zoning laws for Wisconsin Avenue (old article)
  • Invest in a metro rather than a gondola 😊 (old article)
  • Learn from others success… Just look across the river at https://nationallanding.com/

We also have an incredible resource of entrepreneurs & professors at the Georgetown MBA (ranked #19 in US) and Legal schools within the University–Maybe we could lean on them for some help…   

Just some ideas—I’ll add more as I read about other’s successes…

Wake up! You are being manipulated.

This holiday season I talked to several people with different opinions from my own. I met a young 20-year-old woman that said she would never bring kids into this world because global warming meant we have no future… I chatted at a party with a Trump supporter that was convinced tariffs were good policy.  I listened to a young person (under 18) tell me that Socialism was indeed better than Capitalism. I’m not saying any of these opinions were wrong but I did notice that NONE of them were based on a broad set of knowledge—they were all drawn from a few headlines, things they heard or opinions they created themselves based on their belief system. You might say that this has been going on since the beginning of humanity (people formulating strong opinions without a lot of facts)—but it seems much more pronounced now.  (As you will read below this might be due to me having a slight Negativity Bias.)

I get it, we are human, and we have innate flaws that allow us to be influenced –but how and why? I thought it was time to do some digging, take some notes, and begin a list of all the ways I could be manipulated so I can defend against it in the future.

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Political ads, search and social media advertising, partisan cable TV and fake news content is constantly being pushed at all of us–While product designers create products that cause addictive behavior to distribute such content.  Design engineers read books like Hooked: How to Build Habit-Forming Products to understand how to build products & services that we have to constantly check for a little boost of dopamine. In the past, this wasn’t as big of an issue because the portals for distributing content were not as widely used (as our smartphones are today) for such a large part of the day and their influence was not as personalized (more on how much just a couple tech firms knows about you found here).

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To understand how we are being manipulated we need to understand one of our many glitches–Bias.

Everyone is susceptible to some form of Bias

Response to the survey question “Do you think human activity is a significant contributing factor in changing mean global temperatures?”

The first thing I’d ask is why less than 60% of the general public believe human activities are a significant contributing factor in climate change when >95% of the scientists that study climate change for a living (PHDs) are adamant about the fact.  Think about this for a second–These specialists have studied climate for their entire professional careers, yet a large majority of people that NEVER studied the climate don’t believe them—that’s just crazy!  Are these non-believers’ lives impacted negatively by climate change policy? Are these non-believers’ drawing conclusions based on how much snow they saw in their backyard this past winter? Take this a step further—these non-believers are voters and 40% is a lot of people (more on a related subject). Reference this video about bias and climate change:

Most (if not all) people have a “bias blind spot”. Humans are less likely to detect bias in themselves than in others per published research in Management Science. The reality is that people are susceptible to all kinds of bias (defined as a mental leaning or inclination; partiality; prejudice; bent).

  • We love to agree with people that agree with us—This is called confirmation bias. To compensate we should surround ourselves with a diverse set of people that have different backgrounds and experience than your own.
  • We jump to conclusions without having a lot of information – This is called Anchoring Bias. To compensate we can draw upon tools such as the Ladder of Inference to help us make decisions.
  • We may believe that after flipping a coin 5 times and getting heads all 5 times that there is an increased likelihood that the next coin toss will be tails and the odd would be in our favor.   They are not.  This is called Positive Expectation Bias and forms the basis of gambling addictions. To compensate, we need to look at trends from a number of angles versus just chronologically.
  • We blame others when something goes wrong. Perhaps blaming the other driver for being a ‘bad driver’ in a traffic accident versus blaming the weather. This is an Attribution Bias. To compensate we need to look at others as people and use empathy versus treating them as objects (use tools like Arbinger Institutes Leadership and Self Deception framework).
  • We overlook faults or defects with a large purchase of an expensive product or service in order to justify the purchase – this is a form of cognitive bias called Buyer’s Stockholm Syndrome
  • We might despise the opposing political party.  Negative feelings towards another group form from favoritism towards one’s own group – This is called Ingroup bias and forms the basis of discrimination.
  • We fear flying more than driving even though statistically, we have a 1 in 84 chance of dying in a vehicular accident, as compared to a 1 in 5,000 chance of dying in a plane crash [other sources indicate odds as high as 1 in 20,000]) – this is called Neglecting Probability Bias.
  • We start to see our new car everywhere after we purchase it—this is called Observational Selectional Bias and it causes us to actually believe this is happening with increased frequency.
  • We often say “If it ain’t broke, don’t fix it” – This is called status-quo bias
  • We think that things are getting worse in the world not better. – This is Negativity Bias and is the basis of Steven Pinker’s book The Better Angels of Our Nature: Why Violence Has Declined.  In general, people tend to pay more attention to bad news than good.

The human brain is easily deceived, and we have to be diligent in not letting others manipulate us because of its natural bias. After all, marketing professionals have been exploiting these fundamental human flaws for years.  Here is a great article outlining how titled “How marketers use 20 cognitive biases that screw up your decisions” by Paul Marsden.

Here is a link to all bias’s (specifically cognitive bias) in which we are all susceptible.

We must constantly ask ourselves if our personal bias is making us draw conclusions without all the data… have we listened to the other side?  Do we have empathy for the people on the other side of the dialog or are they ‘objects’ to us? Are we only listening to news that confirms our personal bias?  Are we being manipulated or are we thinking about all sides of an argument? –don’t be the nitwit that doesn’t believe in global warming when >95% of all climate scientists (who spent their entire careers studying the issue) believe humans are at fault.

We are vulnerable to The Sleeper Effect

This was first identified in U.S. soldiers during World War II. Scientists measured a soldier’s opinions 5 days and 9 weeks after they were shown a movie of propaganda. They found that the difference in opinions of those who had observed the movie and those who did not watch the movie were greater 9 weeks after viewing it than 5 days. This leads us to believe that our impressions have more influence on us than rational thinking over time. Maybe this is why drug companies place disclaimers at the end of a commercial because we won’t remember them over time. Could this be why the older generation wants to Make America Great Again…

Some are vulnerable to Group Think

The brain is always looking for approval from other people and this can be perverted in all kinds of unsettling ways. Our brains prioritize ‘being liked’ over ‘being right.’ so people will go along with a crowd and engage in activities they would never pursue by themselves for the sake of fitting in.  Terrorism is a great example—it occurs when ‘group think’ morphs into ‘group polarization’. For more on this subject there is a great study in the Journal of Social and Political Psychology titled “Social Psychological Perspectives on Trump Supporters”.

Some are vulnerable to Cognitive Dissonance

Not knowing things makes humans anxious. When we are not given adequate closure, we fill in the gaps to create a cohesive whole that makes sense to us. It’s why some of us believe in heaven, astrology, or ghosts. Humans fear the unknown, and intrinsically combat this angst by supplementing our limited information with things that fit a particular paradigm. It’s why we create religions and subscribe to them to our death to give us answers to life’s complex questions.

“When a thousand people believe some made-up story for a month — that’s fake news. When a billion people believe it for a thousand years — that’s a religion,”- Yuval Noah Harari.

Most may be susceptible to some level of hypnotism

I know… this sounds farfetched but it’s not. We know the result of hypnosis is real—but we don’t understand how it works.

“Follow the Lord!” says the priest. “Defeat the Enemy!” says the politician. “Place your Order within the next Ten Minutes for Double the Benefit!” says the sales person. These are all examples of mass hypnosis—used just the same way that Stalin and Hitler practiced it. Manipulating emotions is a way to seize control over someone’s body and mind.  The more we understand our subconscious mind, the greater our ability to make rational decisions.

Hypnosis is generally regarded as an altered state of consciousness—but since consciousness isn’t understood, alterations to it such as hypnosis, meditation and psychosis aren’t very well understood either. David Spiegel M.D. does a great job explaining what is known about hypnosis in this 9 chapter lecture titled “Tranceformation: Hypnosis in Brain and Body” found on NIH.gov.

Someone can learn how susceptible they are to hypnosis here.

It may be based somewhat on intelligence

Gordon Pennycook and colleagues published a paper titled “On the reception and detection of pseudo-profound bullshit” and found that people who are more susceptible to BS score lower for verbal and fluid intelligence, are more prone to “conspiratorial ideation,” and more likely to “endorse complementary and alternative medicine.”

A person’s intelligence is not set in genetic stone—Here are some ideas on how to increase intelligence.

It may be in our genes

Bradley B. Doll, Kent E. Hutchison and Michael J. Frank published a paper in The Journal of Neuroscience titled “Dopaminergic Genes Predict Individual Differences in Susceptibility to Confirmation Bias” that suggested that variants in the genes involved in the prefrontal dopaminergic reward system predicted the degree to which study volunteers persisted in responding to a test, following previous instructions, even as evidence against the veracity of the instructions accumulated. In contrast, variants in genes associated with dopamine function in the striatum correlated with the ability to learn from actual experience.

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Conclusion: We are not flawed, we are human.  The key is to understand how our brains work and to defending against others that try to exploit our human design.

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More information:

Will the US debt eventually make the economy implode?

I just started reading Ray Dalio’s new book “Principles For Navigating BIG DEBT CRISES” and I decided to ask my money manager about his thoughts on some of the concepts in the book. My first question was what he thought about the USA’s National Debt situation and if it was going to have an impact on the future economy/stock market.  His answer, “it’s been an issue for years and if you worried about it you would have never made any returns.” He pontificated about a few other charming variables but for a guy that likes more detail, it was NOT a great answer—so let’s start digging and taking some notes. Ray’s book makes some assumptions that the reader understands these concepts so it’s good to do a review as I forgot most of what I learned in high school finance (wait, they didn’t teach finance in my high school–well, they should…).

We must start with the basics: What is credit, trust, spending power, and debt? 

Debt is money a borrower owes in the future to a lender.   Credit is the trust which allows a lender to provide money to a borrower where that borrower repays the money (and usually interest) at a later date. Credit creates both spending power and debt. The key is to use the borrowed money productively to generate enough income to pay back the debt.

What is the national debt?

The national debt of the United States is the funds that the country borrowed (via selling securities issued by federal government agencies such as the Treasury). If the federal government runs a “deficit” (spends more than it takes in) the country has to borrow to cover the delta and this increases the debt.

Who is lending the US money to cover the debt?

The current US National Debt can be found here.

You can find details here but ~28% of the debt is held by intra-governmental agencies and the rest (public debt) is held by foreign governments other governmental entities (Federal Reserve and state and local governments), mutual funds, private pension funds, holders of savings bonds and Treasury notes, banks, insurance companies, trusts, companies, and investors.

In regards to foreign ownership, in October 2018, China owned $1.14 trillion of U.S. debt,  Japan at $1.023 trillion. Why? Because, both Japan and China want to keep the value of the dollar higher than the value of their currencies to keep their exports affordable for the United States, which helps their economies grow.

What are unfunded obligations?

Note that the US published National Debt number does NOT include Medicare, Medicaid and Social Security—these are considered “unfunded obligations”.  It’s estimated that the US has between $47 Trillion and $210 Trillion of unfunded obligations (here or here).

What is GDP (Gross Domestic Product)?

GDP is a measure of the total size and output of the economy of a country in a year.

Why is the Debt-to-GDP ratio important?

A debt-to-GDP ratio under 100% simply indicates that the economy produces and sells goods and services enough to pay back debts without incurring further debt. Here is a chart that shows this % since 1900 –note that we were over 100% around the time of World War II. The current ratio is~106% and climbing.

How does the USA’s debt-to-GDP ratio compare to other countries?

You can find a chart comparing all countries here.  If you take all the countries around the world and sort them by the % highest to lowest you will see the following:

How do we stack up if you include unfunded obligations in our numerator?

So, what’s the problem?

Borrowing is OK if it allows for development. However, if the return on the loan is such that it doesn’t produce enough to repay the loan then we are essentially bankrupt.  We see above that for several recent years the US has been borrowing from its future.  How much is too much?

What happens if we default? Great article here.

What is Reserve Currency status and why does it matter?

By the end of the 20th century, the United States dollar (USD) was considered the world’s most dominant reserve currency. Most countries hold most of their reserves in USD. Why? It’s because the United States has:

  • large, liquid financial markets capable of taking huge investments
  • a reputation for safety and rule of law, so that other countries are willing to invest billions and billions of dollars in that country’s government securities
  • a willingness to run current account deficits indefinitely since that’s the counterpart of a capital account surplus.

Being a dominant reserve currency causes the country’s currency to appreciate due to foreign demand.  This then dampens growth, and it causes unemployment (US exports would be more competitive, and more people in the US would have jobs making goods for exports).

The fact that the USD is the world’s major reserve currency is one of the main reasons why it has run a current account deficit for most of the last 30 years. (known as the Triffin dilemma).

So, what are the benefits of being the country with the dominant reserve currency? From Michael Pettis in 2016it isn’t easy to list these benefits because for all the conviction that they are substantial, few analysts can identify them except very vaguely. The main benefits seem to include:

  • It lowers US government borrowing costs.
  • It allows Americans to consume beyond their means.
  • Outstanding currency notes provide seignorage benefits. 
  • The US sells economic insurance.”

Others are pointing out that the debt will cause the US to lose it’s reserve currency status and it has already started (see here).  Others refute that it will happen (more) – “the US dollar will continue to be the dominant reserve currency for the next several decades unless the US government itself decides to prevent or limit the ability of foreign central to accumulate reserves in US dollars”.

More on the subject of ‘what happens if…’ (consider source with caution given HQ in Moscow)

Other reading:

Take the following propaganda with MAJOR CAUTION GIVEN THE SOURCE but if you want to see a very negative view of the US debt situation from the RUSSIAN accounting firm Awara read “An Awara Accounting Study on US Economy 2018: Signs that the US Debt-Fueled Economy Might Actually Collapse” found here. “it is clear that the present US economic system will not survive over the coming 5 to 10 years. Massive changes in the economic model would have to be undertaken either in an organized fashion (hardly imaginable) or through a mega financial crisis.”

One of the best debates that leans toward the US debt NOT having a big impact on the future economy can be found here at a podcast that I enjoy called: Money for the rest of us

Net/Net: It’s really hard to tell when/if the US National Debt will eventually sink our economic ship and I think my money manager gave me the best advice he could as I’m sure he has no clue either…

Great info to share with your kids:

OK, back to Ray Dalio’s new book…