- 01/2013 to today
- 87,786 individual datasets
- 8,000+ symbols (US stocks, ETFs & indices)
- Available via Quandl
Volatility and Risk Factors Database
Updated daily, this database offers data on volatility and other risk factors for 8,000+ financial instruments, including stocks, stock indices and ETFs. Subscription is availble via Quandl.
Metrics Coverage
Code | Description |
---|---|
RET | Average return (expected return) |
VAR | Variance (volatility, squared standard deviation) of price returns |
SKEW | Skewness of price returns |
KURT | Kurtosis of price returns |
MOM3 | 3rd moment of price returns |
MOM4 | 4th moment of price returns |
ALPHA | Alpha (Jensen's alpha, excess return, ex-post alpha) of price returns |
BETA | Beta (market sensitivity) of price returns |
HURST | Hurst exponent (long memory measure) of price returns |
FDIM | Fractal dimension of price returns |
Window Length
Each metric is available in multiple flavors, depending on the rolling window length used for its calculation. Metrics at longer windows (e.g. 1 week) are less sensitive to recent price changes, while capturing important aspects of long-term price behavior. Same metrics at shorter time windows (e.g. 1 day) use fewer price points, but are much more responsive to the latest market dynamics (e.g. new volatility regime after a news release).
Length | Description | Available via Quandl |
---|---|---|
1_WEEK | 1 week (5 trading days) window | Yes |
1_DAY | 1 day window | Yes |
1_HOUR | 1 hour window | No |
1_MIN | 1 minute window | No |
1_SEC | 1 second window | No |
Methodology
Metrics are computed using a time series of high frequency price returns of an instrument in a rolling window of given length and then rescaled to a 1 day horizon. PortfolioEffect features a next-generation “smart” model pipeline for high frequency data. Returns are processed with a series of auto-calibrating models for high frequency market microstructure noise, price jumps/outliers, fat distribution tails (extreme events), long memory (price fractality) and intaday risk factors (single index model).
- 01/2013 to today
- 148,057 individual datasets
- 8,000+ symbols (US stocks, ETFs & indices)
- Available via Quandl
Risk and Performance Metrics Database
Updated daily, this database offers data on risk and performance metrics for 8,000+ financial instruments, including stocks, stock indices and ETFs. Subscription is availble via Quandl.
Metrics Coverage
Code | Description |
---|---|
SHARPE_RATIO | Sharpe ratio |
VALUE_AT_RISK | Value-at-Risk (at 95% and 99% confidence intervals) |
EXPECTED_SHORTFALL | Expected shortfall, expected tail loss (at 95% and 99% confidence intervals) |
MOD_SHARPE_RATIO | Modified Sharpe ratio (at 95% & 99% confidence intervals) |
TREYNOR_RATIO | Treynor ratio |
SORTINO_RATIO | Sortino ratio at 0% return threshold |
INFORMATION_RATIO | Information ratio |
STARR_RATIO | STARR ratio (at 95% and 99% confidence intervals) |
RACHEV_RATIO | Rachev ratio (at 95% and 99% confidence intervals) |
GAIN_VARIANCE | Gain variance |
LOSS_VARIANCE | Loss variance |
GAIN_LOSS_VARIANCE_RATIO | Gain to loss variance ratio |
Window Length
Each metric is available in multiple flavors, depending on the rolling window length used for its calculation. Metrics at longer windows (e.g. 1 week) are less sensitive to recent price changes, while capturing important aspects of long-term price behavior. Same metrics at shorter time windows (e.g. 1 day) use fewer price points, but are much more responsive to the latest market dynamics (e.g. new volatility regime after a news release).
Length | Description | Available via Quandl |
---|---|---|
1_WEEK | 1 week (5 trading days) window | Yes |
1_DAY | 1 day window | Yes |
1_HOUR | 1 hour window | No |
1_MIN | 1 minute window | No |
1_SEC | 1 second window | No |
Methodology
Metrics are computed using a time series of high frequency price returns of an instrument in a rolling window of given length and then rescaled to a 1 day horizon. PortfolioEffect features a next-generation “smart” model pipeline for high frequency data. Returns are processed with a series of auto-calibrating models for high frequency market microstructure noise, price jumps/outliers, fat distribution tails (extreme events), long memory (price fractality) and intaday risk factors (single index model).