How volatility evolves over time

How illiquidity evolves over time

{name} Model Equation

How returns affect tomorrow's volatility

How returns affect tomorrow's illiquidity

Spline Coefficients

Value at Risk (VaR) estimates the maximum loss at a given confidence level. Expected Shortfall (ES) estimates the average loss beyond VaR.

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Param	Value	t-stat
mwindow	21
αARCH	0.4616	5.28***
βGARCH	0.2954	5.29***
γleverage	-0.1593	-2.21**
λ₁tau intercept	2.4996	1.42
λ₂forecast adj.	1.0000	21.32***
λ₃tau persistence	0.0000	0.03

Parameter	Value	t-statistic
m window Rolling window length	21
α ARCH Response to squared shocks	0.4616	5.28***
β GARCH Volatility persistence	0.2954	5.29***
γ leverage Additional response to negative shocks	-0.1593	-2.21**
λ₁ tau intercept Baseline long-term coefficient	2.4996	1.42
λ₂ forecast adj. Forecast performance sensitivity	1.0000	21.32***
λ₃ tau persistence Long-term factor persistence	0.0000	0.03

V-Lab

Peker Gayrimenkul ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Peker Gayrimenkul Analyses