Week 42: Bitcoin Futures ETF, Buy-Now-Pay-Later, Robotics Incentives

Briefing:

  • This week’s new Bitcoin ETF invests in futures rather than actual Bitcoin. It’s an important distinction that we don’t think most people are aware of the difference.
  • Software-based lending solutions are a natural and welcome evolution. The new leaders are early and will be dramatically better than their traditional counterparts.
  • Increasing employment costs will lead to increasing automation.

The Bitcoin Futures ETF Is A Bit Strange

On Tuesday, the SEC approved the first Bitcoin futures ETF, and it raised $1.1 billion in its first two days, the fastest ETF launch ever. We suspect most retail investors think owning this ETF means owning Bitcoin when it owns futures contracts.

A fundamental feature of Bitcoin is the 21,000,000 coin limit. What’s strange here is there is no limit to the number of Bitcoin futures. The $1.1B that went into the Bitcoin futures ETF so far is simply betting on the futures prices and not buying any Bitcoin tokens. By comparison, it’s well documented in the gold market that there is more “paper gold” in the financial world than actual real-world gold. This difference doesn’t matter because futures aren’t required to deliver physical gold, and they can choose to settle in cash.

Arbitrage will close gaps between the futures market prices and the Bitcoin prices, but dislocations could create big holes in performance. If futures prices rise too much, traders sell the futures and buy actual bitcoin until the gap is closed. At the very least, this does create buying pressure on those scarce 21 million coins.

This move is another step towards pairing the tens of trillions of dollars in traditional brokerage accounts with cryptocurrency assets. At some point, Fidelity, Schwab, Goldman, UBS, etc., will open the doors to their client’s capital and do what Coinbase has been doing for years, but they are taking their time. The futures ETF is a small actual step but a big branding headline moment.

New Lending Engines

Most people intuitively avoid debt out of discomfort, but debt allows the modern world to function and grow. Bridges, schools, subways, stadiums and hospitals have useful lifespans that may be 50+ years, which is why we finance them and pay for them over time rather than all at once. This type of debt is “good” debt. Thanks to the internet, cloud computing and scalable software, it’s now possible to safely offer these same terms and opportunities at the consumer level.

Buy Now Pay Later (BNPL) via platforms like Affirm offers Peloton bike purchasers 39 months to pay back $1500. 3.25 years is probably appropriate financing terms as it lowers the payment to $39/mo with no upfront payment and Affirm fronts the money to Peloton so they can continue to reinvest in their business. The number of people who can afford $39/mo is dramatically higher than those who can afford $1500 upfront, which should increase overall consumption rates and economic activity across the board. BNPL is genuinely helpful for people who have regular paychecks but can’t afford to pay upfront for items they plan to use over time.

Software engineers have an incredible opportunity to redesign lending markets. Companies like Upstart are using up to 1,600 different data metrics to judge creditworthiness. There are network effects at play here. The more data and users these companies have access to, the better their models will be, and the more they can profitably capture market share by undercutting traditional lenders. As Jeff Bezos says, “your margin is my opportunity.”

Employment and Robotics/Automation

The drive for financial efficiency is always a priority. Europe is perpetually ahead of the US in renewable energy because oil is relatively expensive there. It’s financially efficient for European countries to prioritize renewable energy alternatives. In the US, increasing oil prices are great for renewable energy as the cost difference starts to slant in favor of more climate-friendly options.

This same drive for financial efficiency is at play today within employment markets. As employment costs rise, as they are now, companies begin to look to automation and robotics solutions. As this trend continues, we will see more capital flowing into automation solutions and less towards traditional salaries. Unfortunately, higher minimum wages will accelerate this trend. Job losses due to automation also create more pressure for an eventual UBI – a universal basic income standard.

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