Inflation Linked Bonds Demand (Bitcoin)

Measures the asset's sensitivity to inflation-linked US government bonds, captures the lead-lag relationship between the two assets.

Predictive Strength

Negligible

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Bitcoin historically had ▲ 23.64% 30 days returns when Inflation Linked Bonds Demand was ▆ Very High (0.8 - 1). It indicates higher than average expected returns.

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BTC Price with Inflation Linked Bonds Demand

Inflation Linked Bonds Demand Predictive Strength Analysis

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▆ Very Low▆ Low▆ Moderate▆ High▆ Very High

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Our Methodology

Predictive Strength

Negligible

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Measures the asset's sensitivity to inflation-linked US government bonds, captures the lead-lag relationship between the two assets.

Potential Edge

Inflation Regime Signaling Mechanism

Rising demand for TIPS and similar instruments acts as a real-time referendum on institutional inflation expectations. Crypto markets may react to these signals with a lag as:

Bond buyers represent institutional capital flows anticipating macro shifts
Crypto's "digital gold" narrative gets repriced after traditional inflation hedges move

Policy Expectation Arbitrage

Front-end bond demand reflects expectations for:

Fed put strikes (rate cut thresholds)
Fiscal dominance dynamics impacting money supply
Currency debasement trade entry/exit points

Crypto markets price these factors through optionality structures (e.g., Bitcoin's fixed supply narrative) with inherent time lag.

Data Collection Methodology

The data for "Inflation Linked Bonds Demand" is sourced from real-time/historical market feeds tracking US inflation-linked bonds (e.g., TIPS), with normalization applied to compare current demand levels against historical averages. Normalization ensures values reflect relative positioning rather than absolute metrics.

Backtest (Strategy Performance) - Strategy

Strategy Yearly Returns (CAGR)

100.00%

Sharpe Ratio

1.00

Max Drawdown

100.00%

Beta

1.00

Volatility

42.88%

To understand a predictive factors predictive power, we create a simple long/short strategy and simulate its past performance (with daily rebalancing):

Long when the predictive factor is above 0, with a position size equivalent to the predictive factor value.
Short when the predictive factor is below 0, with a position size equivalent to the predictive factor value.

The strategy is rebalanced daily, on a continuous basis. There are 0.5% transaction costs applied on each position adjustment.

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