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Estimates on the price impact and capital inflows of a Bitcoin ETF

This infographic of Bitcoin’s price is something I’ve been pondering today. It tells Bitcoin’s often dramatic price story in fundamental trend lines on top of which lives some serious doses of speculative activity. There’s a lot in this chart so lets break it down.

  • In late 2015 through to May 2016 we saw a three cats and a moon consolidation pattern play out over 6 months after an MMM pyramid scheme took Bitcoin price action through some exciting times.
  • By early June 2016 we saw a speculative bubble (marked in green above) as the market speculated on the upcoming block reward halving event. This was to be the second halving event, slashing payout and therefore the supply of new bitcoins from 25BTC every 10 minutes to… well, exactly half to 12.5BTC.
  • Leading up to this many people we afraid the miners would exit their protective hashing power, the block processing caught between network adjustments could slow to a crawl and the price could crash. This did not happen. What happened was simply the markets saw less selling pressure from miners who had less newly minted coins to sell. The blue trend shows the steeper rate of price appreciation this had on the markets.
  • Finally what we may be seeing is the Q4 of 2016 to present is the market undergoing a much larger and longer speculative phase for the upcoming Bitcoin ETF decision. If approved hundreds of millions at a minimum are expected to be poured into Bitcoin. Understandably the blue shaded area in our infographic would map to the drawn out and much delayed ETF decision which will finalise on March 11th, 2017.

If this story is fundamentally correct, the picture it paints is quite useful. In fact, we can deduce the impact of what a controlled reduction of coin supply from the markets will have to the price, furthermore we can gauge the amount of capital that the markets expect to be injected.

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Three cats and a moon – a data driven analysis of Bitcoin trader psychology for predictive price signalling

Here at Woobull Labs we take data driven analysis very seriously. Today, I’m pleased to present the culmination of 4 years of data gathering and analysis on Bitcoin trader psychology.

The sketch above depicts the basic rig we used for our epic research. The dataset includes readings over 4 years at 10 minute intervals (210,240 readings per subject). In total we collected the psychological brainwave pattern of 100,000 of Bitcoin traders – a staggering 210,240,000,000 data points in total as they tapped away on their keyboards.

Yes very epic.

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Estimating the true Bitcoin trading volumes in China, a data-driven approach

Today Chinese exchanges report 98% of global volume. This shows huge dominance by Chinese markets. Unfortunately we know that most of this volume is fake.

Why is it fake?

Unlike the rest of the world, Chinese exchanges are unique in that they do not charge fees on trades. Instead they make their money via withdrawal charges out of the exchange. These fees reduce as your trading volume increase, so this incentivises traders to rack up their trade volume via buying and selling from themselves at zero cost.

There’s a ocean of data coming from the markets, and they hold hidden secrets. In this study, I’ll peer into the data and attempt, as far as I know, the first estimate of true Chinese volumes using data driven methods. I’ll define “true volume” as what the volumes would have been, had their markets actually charged at trading fee.

Prior estimates, really just educated guesses, have put Chinese volumes at 50% of the global market, let’s see how well this compares with the data.

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The network effects of volatility and liquidity, Bitcoin vs other payment coins


The Volatility of 600 cryptocurrencies
Alt-coin volatility proportional to bubble size

2016 has been a bull year for privacy coins. Earlier this year we saw mooning of Monero which saw subsequent pumps in other dark-coins including ShadowCash and Navcoin. Then we witnessed a mega-hyped launch of ZCash which peaked at an astounding $5.3k per coin.

All of these coins are Payment Coins competing in the battle win the war to be General Money. Let me explain. While most alt-coins tend to be forging into market specific app-coin territory, what makes payment coins unique is the shear size of the potential win, while app-coins can capture a market segment which effectively puts a cap on their valuation, payment coins being a kind of generalised money can capture “M2 money supply” as a ceiling, i.e. trillions.

When I look at payment coins I see very strong economic network effects are in play. I covered earlier with my Commerce Index that liquidity and low volatility are very important for a coin to be useful for general trade. Both of these qualities are crucial to make it compelling for end consumers to charge their wallet with a payment token to spend. With high volatility there’s too much risk holding funds and with insufficient liquidity wallet recharge and merchant fees will be high.

When looking at the combined qualities of liquidity and price stability together as a Commerce Index, we could see other coins catching up with Bitcoin. In this study I will be doing a deeper dive into these two qualities individually.

For the sake of this study, I will be looking at the leading coins by market cap, namely Bitcoin, Monero, Dash, ZCash and ShadowCash. All of these coins are well above $5m market cap, NavCoin and others at less than $3m have been excluded.

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Bitcoin’s dilution-adjusted price

Bitcoin dilution adjusted price

This chart is the Bitcoin historically adjusted price taking into account lost coins and inflation effects of new coins mined into existence, if you were to treat bitcoin like a company. (Yes we are very close to an all time high.)

I thought it would be fun to plot this after reading Vinny Lingham’s post on deconstructing Bitcoin’s marketcap. Lingham reasons that since more coins are mined into existence daily, this has the effect of a continual stock split. All stock charts we see on Wall Street correct for this dilution effect so we can compare today’s price with past prices never mind the actual number of shares in existence. In this plot, we are assuming approximately 2.5m coins have been lost.

[Live chart]

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Estimating return potential for alt-coins and Bitcoin

Valuing cryptocurrency using the quantity theory of money

I personally think very few people grasp how to gauge the long term return potential of Bitcoin vs alt-coins. I often hear people say that Bitcoin is no longer cheap and that alt-coins have more return potential being in their earlier stages, while they chase returns similar to Bitcoin’s ungodly growth during its drug-induced SilkRoad euphoric climb to notoriety.

In this article I’m going to apply some actual theory in order to get solid numerically based estimates on what the limits on returns are for Bitcoin and alt-coins. To do this, I’ll be using The Quantity Theory of Money. In essence this is a pretty obvious equation that economists like to use to describe economies.

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Does ViaBTC have veto power over Segwit activation?

ViaBTC mining power distribution

Segregated Witness or Bitcoin Core release 13.1 has been released! This update promises to end a 2 year civil war within Bitcoin’s community over scaling, which unresolved,  poses a systemic risk to the network.

To the investor, the war has almost certainly had a bearish influence on bitcoin price. But before we can celebrate, Segwit only turns on when a minimum 95% of the last 2016 blocks have been mined with the Segwit code.

Now most people are jumping to the conclusion that any mining pool with more than 5% of the network’s mining power will have veto power to block Segwit from activating. It just so happens that the mining pool ViaBTC, who are fans of Bitcoin Unlimited, are opposing to Segwit. They control 6.7% of hashing power at the time of writing (Source:

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Startup investment analogies applied to alt-coins

Alt-coins startup funding analogy

I can’t help but apply startup investment learnings onto the landscape of crypto-currency investments.

Any startup investor will tell you very few startups make it to success. The path to success looks something like this:

  1. Build a team, experiment with an idea, build a prototype, try and show there’s a market need.
  2. Seed round to try and get some semblance of traction.
  3. Get series A funding ($2-15m) to improve your product as you have shown there’s real potential
  4. Get Series B funding ($7m+) to mature your product beyond developmental
  5. Get Series C, D, E…. you’re in fast growth now, it’s time to scale, scale, scale
  6. IPO onto the public markets, be a house-hold name.

Now here’s the approximate survival rates:

  • pre seed 1-2%
  • seed funded 2-5%
  • series A funded 10-20%

This should be sobering to alt-coin investors. But the story gets worse…

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