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Quantitative Easing, Stablecoins, and Bitcoin’s Fixed Supply: Why Neither Crypto ‘Solution’ Fixes the Money Problem
Money supports a modern economy by enabling exchange, providing a unit of account and acting as a store of value. Fiat money works because it is backed by law, taxation and a central bank that stabilises the financial system. Most money is created by private banks when they make loans, and banks settle their net flows using reserves in the overnight market. Central banks guide the cost of this funding through open market operations, influencing borrowing conditions across the economy. When interest rates are near zero, they turn to quantitative easing, which creates reserves to buy longer-dated government and high-quality private assets in order to support liquidity and lower long-term rates. QE appeared profitable when rates were low but has since become costly as reserve remuneration has risen, yet its role in preventing financial collapse shows why a centralised banking system remains indispensable.
Crypto experiments test whether parts of this system can be replaced. Stablecoins depend on private issuers managing reserve portfolios without a public backstop, which makes their one-to-one promises vulnerable to runs when assets fall or liquidity dries up. Bitcoin avoids runs because it has no issuer and no redemption promise, but a fixed supply, high volatility and the lack of a lender of last resort mean it cannot meet the needs of a large, dynamic economy. Its long-term security also depends on transaction fees once block subsidy ends. Overall, these technologies cannot replicate the trust, elasticity and institutional support that make fiat money and centralised banking both stable and efficient.
Private Assets: Evidence, Access and Implications for Investors
Private markets span buyouts, venture capital, private credit and private real estate and have grown from niche allocations into large ecosystems with specialist managers and active secondary trading. Advocates often claim higher returns with lower volatility and low correlations vis-à-vis the public markets, yet results depend on how returns are measured, which benchmarks are chosen and how fees and carry flow through to what investors actually keep.
IRR can flatter early realisations, TVPI shows the multiple without timing, and public market equivalent asks whether the same cash flows would have matched a suitable public index. Once style is matched properly, much headline outperformance in buyouts compresses; venture capital offers a clearer diversification case; private credit behaves more like high yield than like defensive bonds. With dispersion high, persistence uncertain and capacity constrained, an edge in private markets is hard to get.
How Long Would an Active Fund Manager Need to Demonstrate Outperformance to Be Confident in Their Results?
Most discretionary active fund managers underperform a style-matched benchmark over meaningful periods of ten years or more. A small minority appear to outperform, but how can investors tell whether this reflects skill or luck? The Information ratio (IR) helps quantify this. Even a strong IR of 0.5 implies that investors would need around sixteen years of data before being 95 per cent confident that the fund manager’s results were due to skill. Most managers have far lower IRs, meaning the odds of proving genuine ability are vanishingly small. The mathematics simply does not support the claim of persistent skill.
Profitability and Investment Premia: What Fama–French’s ‘Quality’ Factors Mean for Investors
The Capital Asset Pricing Model (CAPM) assumes that a stock’s expected return is explained entirely by its sensitivity to the market portfolio: one factor, one beta. Yet in practice, the CAPM leaves much unexplained. Fama and French (1993) formalised these findings in their three-factor model, adding size (SMB) and value (HML) to the market factor.
Even then, further anomalies persisted. Portfolios sorted by profitability and investment intensity were not explained by the three-factor model. Fama and French (2015) expanded the framework to five factors, adding profitability (RMW—robust minus weak) and investment (CMA—conservative minus aggressive). This version explains the cross-section of returns more effectively, showing that much of what was previously attributed to value is better captured by profitability and investment.
For investors, RMW rewards exposure to firms with sustainable earnings, whilst CMA rewards avoiding those that pursue growth too aggressively. Profitability has been a consistent and defensive premium; investment more cyclical but valuable in filtering out overpriced growth.
Good financial decisions aren’t about predicting the future, they’re about following a sound process today.
In investing, outcomes are noisy. Short-term performance often reflects randomness, not skill. Yet fund managers continue to pitch five-year track records as if they prove anything. They don’t.
As Ken French puts it, a five-year chart ‘tells you nothing’. The real skill lies in filtering out the noise, evaluating strategy, incentives, costs, and behavioural fit.
Don’t chase what worked recently. Stick with what works reliably.