What's are some go-to packages in R/Finance for detecting shocks in financial time series?
It should, we tested the package for illiquid stocks with 1-2 trades a day. The models would require sufficient warm-up period. Since this is not a HF dataset, I would also suggest switching off market microstructure noise detection <https://www.portfolioeffect.com/docs/platform/quant/manuals/portfolio-settings/model-pipeline#noise_model> - the estimated HF noise at EOD frequency is close to zero for liquid stocks anyway. If you want to give intraday data a try - SPY, GOOG & C sample history is available through the package. Best, Alex 2015-09-28 19:26 GMT-04:00 Ilya Kipnis <ilya.kipnis at gmail.com>:
Alexey, As someone who works independently, unfortunately I don't have access to intraday data at all. Does that work with daily-frequency data, like the kind I use on my blog? -Ilya On Mon, Sep 28, 2015 at 7:24 PM, Alexey Zemnitskiy < alexzemnitskiy at gmail.com> 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
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