Bitcoin mining uses a lot of power, and because this power isn’t 100% renewable, Bitcoin has a carbon footprint. That’s a fact.

A lot of the criticism that’s directed at Bitcoin is based on the assumption that it’s useless. A digital mirage which neither has substance nor intrinsic value. A scam of sorts that requires a power socket to run.

On the other side of that argument sits a market with more than a trillion in capitalization. It seems the market disagrees with the “it’s useless” argument.

If Bitcoin is useless because it uses power, what about Christmas lights? What…


Investors do not necessarily lower their risk by reducing the volatility expectation of their returns. That’s because volatility and risk are two very separate matters.

When investors are too keen on obtaining a smooth “all weather” return stream, odds are that at some point they will end up with the opposite. That opposite is negative skew and negative return convexity.

Trend following traders tend to be on the other side of that return distribution, realizing positive skew and positive return convexity.

Kahneman and Tversky’s Prospect Theory shows that most investors feel losses stronger than gains of equal magnitude, which is…


How (un-)sustainable are they?

According to Digiconomist, Bitcoin’s (BTC) annual carbon footprint equals that of Switzerland (40 Mt CO2) because running its network is power-intensive, consuming approximately as much power as Finland requires in a single year (85 TWh).

The numbers for Ethereum (ETH) are smaller (14 Mt CO2, which is about the same as the annual CO2 emissions of the video platform YouTube, and 29 TWh, which comes close to the annual power consumption of Ireland).

Looks massive and sounds bad. But let’s put these numbers into perspective.

Below is a chart from Our World in Data which shows all global greenhouse gas…


Good investment performance tends to attract assets. Investors are inclined to chase returns as they attribute a fund manager’s outperformance, even over short time horizons, to skill. However, by neglecting the role of randomness in track records, many investors assume that past performance is a good predictor of future performance. That’s a problem and this article explains why.

Separating skill from luck: The importance of sample size and time

Trading results include both skill and luck. When analyzing small sample sizes, skill is hard to detect. An outperforming trader could be an unskilled trader on a lucky streak. Likewise, an underperforming trader may be suffering through a period of bad luck…

Moritz Seibert

Quant-driven trader, one of the Two Quants at www.twoquants.com and CEO/CIO at Munich Re Investment Partners.

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