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Can someone give an overview or literature on Intraday Data Stylized Facts?

In particular for equity market returns or exchange rates.

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    $\begingroup$ Here is one: Currencies trade 24/5 and equities are traded from market open till market close. And not even that is a stylized fact, take a look at the Hong Kong equity market and you will encounter numerous unannounced (sometimes multi day/weeks) trading halts. Or consider the many locked markets or stocks in opening auctions that can last hours if not throughout the whole session (see Tokyo stock exchange for plenty examples). In summary nothing is stylized which is why risk taking approaches need to be dynamic and adaptive. $\endgroup$ – Matt Sep 29 '14 at 6:11
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  1. Stationarity. The distribution of returns is non-stationary. Moreover, standard deviation of returns is not constant over time.

  2. Symmetry. The distribution of returns is approximately symmetric with increasing leptokurtosis as sampling frequency increases. However, large drawdowns are not matched with equally large upward movements.

  3. Gaussian behavior. Returns become increasingly normal with decreasing frequency. Long horizon returns are approximately normal

  4. Serial correlation. There exist anomalies in the serial correlation of returns, which are nevertheless impossibly difficult to forecast.

  5. Scaling properties and asymmetry in time scale. Time scaling is nontrivial as returns are not iid, but there is documented evidence for fairly stable, empirical scaling properties.

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    $\begingroup$ Could you please provide any reference for this? Then one would have a starting point for further research of the literature. $\endgroup$ – Richard Sep 30 '14 at 7:00
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This reminds me of a paper by Rama Cont: "Empirical properties of asset returns: stylized facts and statistical issues.". You can download here:

http://www.cmap.polytechnique.fr/~rama/papers/empirical.pdf

He also has a paper on volatility clustering: "Volatility clustering in financial markets: empirical facts and agent-based models.", which may be of your interest.

http://www.cmap.polytechnique.fr/~rama/papers/clustering.pdf

Hope this help.

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  • $\begingroup$ Thanks very much, the papers are quite old though, I believe intraday characteristics changed since the upcoming of high frequency trading algorithms... $\endgroup$ – emcor Oct 3 '14 at 7:37

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