Direct Answer
A structural credit measure from the Merton model: how many standard deviations a firm's asset value sits above its debt obligation at the horizon. Larger values indicate lower modeled default risk. A higher distance to default means the asset value would need a larger fall to hit the default point; values near zero or below indicate elevated modeled default risk.
Distance to Default: Formula, Meaning, Signals, Examples and How to Use It
How Is Distance to Default Calculated?
A structural credit measure from the Merton model: how many standard deviations a firm's asset value sits above its debt obligation at the horizon. Larger values indicate lower modeled default risk.
Formula: DD = (ln(V / D) + (mu - 0.5 x sigma^2) x T) / (sigma x sqrt(T))
Inputs:
- Market value of assets V
- Default point D (debt due)
- Asset drift mu
- Asset volatility sigma
- Horizon T in years
Worked example. Assets of 150, debt of 100, 5% drift, 25% asset volatility and a one-year horizon give a distance to default of 1.70. The inputs are illustrative numbers, not market data.
Reading it. A higher distance to default means the asset value would need a larger fall to hit the default point; values near zero or below indicate elevated modeled default risk.
Limits. Asset value and asset volatility are not observed and must be inferred from equity prices and equity volatility, so results depend on the estimation method and on how the default point is defined.
What is Distance to Default?
A structural credit measure from the Merton model: how many standard deviations a firm's asset value sits above its debt obligation at the horizon. Larger values indicate lower modeled default risk.
How to use Distance to Default
A higher distance to default means the asset value would need a larger fall to hit the default point; values near zero or below indicate elevated modeled default risk. A reading alone is never a buy or sell signal; it needs context from price structure, volume, volatility and the broader market regime.
Strengths
- It expresses leverage and volatility in one standardized count of standard deviations, so firms of different size can be placed on one scale.
- The formula feeds on market equity data that updates daily, so it can absorb new information sooner than ratings or annual accounts.
- Reproducible when the formula and data convention are fixed.
Weaknesses and limitations
- A normal distribution of asset returns is assumed, so the link from distance to default probability inherits the thin tails of that assumption.
- The model sees default only at the horizon date, so firms that fail earlier through a covenant breach or liquidity squeeze are not described.
- Correlated indicators can create false confidence by repeating the same underlying information.
Editorial and risk note
This page is educational content, not individualized investment advice. It should not imply guaranteed prediction, accuracy or outperformance.
Frequently Asked Questions
Is Distance to Default a buy or sell signal?
No. A higher distance to default means the asset value would need a larger fall to hit the default point; values near zero or below indicate elevated modeled default risk. Asset value and asset volatility are not observed and must be inferred from equity prices and equity volatility, so results depend on the estimation method and on how the default point is defined. A trade built on it still needs a trigger, an invalidation rule, a position size and realistic execution assumptions.
What is the best setting for Distance to Default?
Distance to Default is computed from market value of assets V; default point D (debt due); asset drift mu, so the choices that matter are the data convention and the window it is read over. Test those across instruments, regimes and out-of-sample periods instead of fitting one historical winner.
Can Distance to Default be used by itself?
Asset value and asset volatility are not observed and must be inferred from equity prices and equity volatility, so results depend on the estimation method and on how the default point is defined. For that reason it is read next to measures of direction, participation, valuation, liquidity and risk, not alone.
Does Distance to Default work on every timeframe?
The calculation (DD = (ln(V / D) + (mu - 0.5 x sigma^2) x T) / (sigma x sqrt(T))) can be run on any bar size, but behavior is not portable: a reading on a five-minute chart describes a very different market window from the same reading on a daily chart. Validate the exact timeframe before relying on it.
Why does Distance to Default give false signals?
A normal distribution of asset returns is assumed, so the link from distance to default probability inherits the thin tails of that assumption. The model sees default only at the horizon date, so firms that fail earlier through a covenant breach or liquidity squeeze are not described. Lag, noise and regime changes add to this, because market participants react to new information after the reading is calculated.
How should Distance to Default be backtested?
Rebuild Distance to Default from market value of assets V using point-in-time data, write the rules before testing, include delisted securities where relevant, model realistic fills and costs, reserve a validation sample and compare with a simpler baseline.