Tuesday, February 22, 2022

Range-Based ("Candlestick") Volatility Estimation Slides



 

Reading the Candlesticks:

An OK Estimator for Volatility

Paper by J. Li, D. Wang and Q. Zhang (LWZ)

Discussion by F.X. Diebold

Society for Financial Econometrics

February 21, 2002

 


Reading the Candlesticks:

An OK Estimator for Volatility

Paper by J. Li, D. Wang and Q. Zhang (LWZ)

Discussion by F.X. Diebold

Society for Financial Econometrics

February 21, 2002

 

(***) Consider a different title…

Classic Traditions: University of Chicago, Journal of Business, Al Madansky, …

n  CLI, CCI analyses related to modern macro/BC nowcasting (Zarnowitz, Neftci, ...)

n  Range-based volatility estimation related to modern financial volatility nowcasting

The Extreme Value Method for Estimating the Variance of the Rate of Return

Author(s): Michael Parkinson

Source: The Journal of Business , Jan., 1980, Vol. 53, No. 1 (Jan., 1980), pp. 61-65

 

On the Estimation of Security Price Volatilities from Historical Data

Author(s): Mark B. Garman and Michael J. Klass

Source: The Journal of Business , Jan., 1980, Vol. 53, No. 1 (Jan., 1980), pp. 67-78

Others have extended:

n  HLC-based estimation (e.g., Beckers, 1983; Rogers and Satchell, 1991)

n  HLOC-based estimation (e.g., Yang and Zhang, 2000)

(***) Should be discussed

In Yang and Zhang (2000):

VOL = O - .383 C + 1.364 HL + 0.019 HLC

(***) LWZ results have strong resemblance


In LWZ:

VOL  = λ1 (H-L) + λ2 |C-O| (by assumption)

(***) Restrictive ?

VOL* = 0.811 (H-L) – 0.369 |C-O|

How does the range fit in?

Efficiency hierarchy (worst to best):

r^2

|r|

HL range

HLC

HLOC

“large-k” RV

r^2 or |r|:  r=0 implies vol=0


r^2 or |r|: Even when r non-zero, very different paths can be scored the same

Range:  The key vol info is embedded


different days can be scored the same


Range: Even the range can be tricked
(Only large-k RV can’t be tricked…)

Why care about the range?

(if only large-k RV can’t be tricked…)

n  Effortless yet highly efficient 

n  Robust to microstructure noise
(bias is just average B/A spread)

n  Available over long historical periods
(and risk premia are all about recessions)

 

Also, using range improves large-k RV

 

Christensen and Podolskij (2007)
(* Needs more discussion)

 

Not so compelling in large-k contexts?

 


 

What to do when you can’t do
(or don’t want to do) large-k RV?

n  Fixed(small)-k r^2-based RV (Bollerslev, Li and Liao, 2021 (BLL))

n  Fixed(small)-k range-based RV (LWZ)
(More compelling than large-k range-based RV:  Efficiency, robustness, …)

RV Volatility Proxies and Treatment of k

                                  k:

Large k

Fixed(Small) k

Vol Proxy:

 

 

r^2

ABDL 2001

BNS 2002

ABDL 2003

BLL 2021

Range

CP 2007

LWZ 2022


ABDL 2001   Andersen, Bollerslev, Diebold and Labys, JASA

BNS 2002     Barndorff-Nielsen and Shephard, JRSS

ABDL 2003   Andersen, Bollerslev, Diebold and Labys, Ectca

CP 2007        Christensen and Podolskij, JoE

BLL 2021      Bollerslev, Li, and Liao, JoE

LWZ 2022    Li, Wang and Zhang, unpublished – NICE!

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