What's are some go-to packages in R/Finance for detecting shocks in financial time series?

wrote:

Hi Ilya,

If your focus is on intraday price shocks - you could check out our
PortfolioEffectHFT package.

Right now it's available at:
https://www.portfolioeffect.com/docs/platform/quant/downloads
It would also be available on CRAN shortly under BSD license - we are
doing second round of submission corrections.

The setting you might be interested is

https://www.portfolioeffect.com/docs/platform/quant/manuals/portfolio-settings/model-pipeline#jumps_model

It is using a combination of several jump detection methods (quantile,
wavelet-based, etc.).
For intraday volatility estimators see portfolio_variance
<https://www.portfolioeffect.com/docs/platform/quant/functions/absolute-risk-measures/portfolio-variance>
& position_
<https://www.portfolioeffect.com/docs/platform/quant/functions/absolute-risk-measures/position-variance>
variance
<https://www.portfolioeffect.com/docs/platform/quant/functions/absolute-risk-measures/position-variance>
methods.

PortfolioEffect service is free to use with your own pricing data.
There is optional access to HF market data history for 8000+ US equities
since 2013 if you need that.

Best,

Alex


2015-09-28 17:55 GMT-04:00 Ilya Kipnis <ilya.kipnis at gmail.com>:

So, I'm back to researching trading strategies on volatility. However, as
the mailing list knows, volatility ETFs are characterized by price shocks
more often than not, causing rapid drawdowns. One example would be, say,
the closing price of XIV from late April to mid-May in 2010, late 2011,
the
SPY correction in 2011, or the more recent one last month during the China
meltdown.

Does anyone have any R package that they can recommend for detecting such
quick corrections in a systematic manner?

Thanks a lot.

-Ilya

        [[alternative HTML version deleted]]