In Data we trust: not just a clever tag line

The term “In God We Trust” was first printed on paper currency in 1956 and first appeared on US coins in 1864. Although the phrase is widely accepted to be the official motto of the United States, a variation of the phrase (In Data we trust) can quite aptly describe the implications of the bitcoin network.

Before I delve deeper, let’s have a quick 101 on money supply. The total money supply in the economy has direct implications on inflationary and deflationary pressures in the economy. This is why the US Treasury can’t simply “print more money” to pay off its debts – a drastic increase in money supply would cause hyperinflation and has ruined a number of economies in history.

Interestingly, it’s not just irresponsible policy that can lead to hyperinflation. By the end of 1780, Continental Currency (the precursor to the US Dollar) lost a majority of its face value due to rampant counterfeiting by the British who used it as a tactic to weaken the revolutionaries of the “Thirteen Colonies”. This lead to the Coinage Act of 1792 which mandated a certain amount of gold and sliver in coins to prevent counterfeiting.

The total money supply in an economy is often referred to as M1. M1 refers to both money created by the central bank (the monetary base) and money created by commercial banks. The money created by commercial banks (fractional reserve banking) is the money created through lending and is a function of the monetary base and liquidity reserve requirements.

For example, the government might print $10,000 and circulates it to banks. Total M1 is now $10,000. At the same time, the government has a 1% mandatory liquidity reserve ratio for all banks. Which basically means for every $100 that a bank lends out, it only has to have $1 in reserves. So for each dollar created by the government, the banks can lend out $100. This is referred to as the Money Multiplier. So in our example, each $1 in the $10,000 can be lent out 100 times making the total M1 ($10,000 * $100) = $1,000,000.

Now, back to data. By design, the total amount of bitcoin created is strictly regulated and predictable through it’s algorithm. Below shows a chart of growth in bitcoin’s monetary base.



The monetary base of bitcoin is the money created through “mining” (mining is the process through which money is created in the bitcoin system – a process worthy of a seperate blog post).

In our original M1 equation, we had two relative unknowns i.e. we didn’t know how much money the central bank will create and we didn’t know how much money banks will lend out.

Bitcoin at least solves the first part of the equation – we know exactly how much bitcoin is going to be created in the next 100 years.

Why is this important? Risk & uncertainty are kryptonite for commerce. In growing and developing economies the risk of the central bank exercising irresponsible monetary policy and printing money is high which significantly increases a merchant’s risk of conducting business in the local market.

If a global merchant conducts business in a developing economy through bitcoin, the exchange rate and currency risk are completely mitigated. Additionally, most traditional banks charge higher fees for foreign transactions to act as an “insurance policy” against the risks outlined above. Bitcoin doesn’t need to charge these exorbitant transaction fees.

There are also implications for developed economies. The Fed holds 8 regularly scheduled meetings each year where each word is analyzed by the Bloombergs and CNBCs of the world looking for hints for changes in monetary policy. The decisions which the Fed makes has far reaching implications on borrowing rates, financial models and inflation. If some of the decisions the Fed makes were known in advance, some uncertainty would be moved out of the system. As an example, the monetary base is one of the factors which are affected by the Fed.

So, what does this mean? Is the Fed going to go away? No. Even if the whole world transitioned to bitcoin we would still need a regulatory authority to manage issues such as fractional reserve banking (second part of the M1 equation mentioned above). Bitcoin does not have a way to regulate irresponsible lending. But perhaps, that might be the next breakthrough in the bitcoin network?

So, in Data we trust to provide a steady predictable monetary base to conduct commerce creating marketplaces and use cases previously thought impossible with centralized constructs of monetary policy. Data has replaced trust in certain instances. Previously we “trusted” the US Government to exercise responsible monetary policy. Now, it’s Data that ensures responsible monetary policy.

P.S. If you’re curious, below is a chart showing the growth in M1 in the US from the Board of Governors of the Federal Reserve System.

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Marketplaces: Are they just a big bang?

Physics and Economics were my favorite subjects in high school. What fascinated me was that both disciplines study complex systems put in place by nature and/or man.

Both have a strong empirical component (Macro economics/Quantum Physics) and a strong deterministic component (Micro economics/Classical Physics).

No wonder most Physics PhDs end up as traders on Wall Street. Or more recently, Data Scientists at Facebook.

Being a poster child capitalist, I wanted to explore using concepts defined in physics to better understand marketplace phenomena.

During the inception of marketplaces, there are a lot of unknowns. How many buyers are going to show up? How many sellers are going to show up? What goods will be sold? What’s going to be the starting bid?

The answers to these questions during the early stages will ultimately decide the characteristics and long term fate of the marketplace.

That’s exactly what happened during the big bang. The basic chemical DNA of the cosmos that was created during the first few moments decided the elements necessary for life to exist and governed the behaviors of species for the consequent eons (and still does).

Ok, so what? Being an early participant during the inception of a marketplace can you give significant power towards influencing the ultimate natural state of the marketplace.

For example, the bitcoin marketplace was officially “created” when the first transaction was completed in February 2010. Although the behavior of the bitcoin marketplace is largely determined by an algorithm, at the initial asking price of $0.01 per BTC you could buy a huge chunk of bitcoin and ultimately own a large piece of the marketplace.

Yes, hind sight is always 20/20 – but if you understood at the time a new marketplace was forming, you could’ve capitalized on the opportunity.

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Do you even Data, bro

After thinking about it for a while now, I’ve finally decided to start a blog. I’ll post my thesis on marketplaces, hypotheses on human behavior and general thoughts on the future.

In an era of “Data Science”, it’s easy to lose sight of simple answers to powerful questions.

To start, let’s look at a simple chart from Google’s Ngram viewer. The below chart shows the percentage occurrence of the word data in Google’s corpus of books since 1800 with a smoothing of 3 years. Trends are more apparent if you deploy a moving average – this allows to “smooth” anomalies such as seasonal variations. So in this case each data point is actually an average of the last three years.

The Y-axis shows of all the unigrams in Google Books sample, the unigram (data in this case) was used Y % of the time.

Now, why is this chart important? The use of data in the common lexicon skyrocketed in the 1900s. We also started seeing unprecedented productivity gains starting in the 1900s. The use of data allows us to make intelligent calculated decisions to set us up for success.

Of course, we must not forget : correlation doesn’t imply causation.

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