Econophysics of Stock and other Markets: Proceedings of the by Taisei Kaizoji (auth.), Arnab Chatterjee, Bikas K

By Taisei Kaizoji (auth.), Arnab Chatterjee, Bikas K Chakrabarti (eds.)

This ebook reports the most recent econophysics researches at the fluctuations in inventory, currency and different markets. The statistical modeling of markets, utilizing numerous agent-based online game theoretical ways, and their scaling research were discussed.

The best researchers in those fields have stated on their fresh paintings and in addition reviewed the modern literature. a few historic views in addition to a few reviews and debates on contemporary matters in econophysics study have additionally been included.

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Extra resources for Econophysics of Stock and other Markets: Proceedings of the Econophys-Kolkata II

Sample text

We quantify volatility, as the local average of the absolute value of daily returns of indices in an appropriate time window of T days, as an estimate of volatility in that period, see reference [12], Studying Volatility in BSE Using RMT 37 T −1 v(t) = t=1 |G(t)| (2) T −1 We compute monthly volatility for the three year period 2000 − 2002 by taking T = 20 days as there are roughly 20 trading days in a month in BSE. |G(t)| may be considered as a substitute for volatility or ’scaled volatility’ in future.

As is clear, both of these distributions are non-monotonic, and are suggestive of a log-normal form. The fact that these distributions are very similar to each other is not surprising in view of the almost linear relationship between the two (Fig. 6, bottom). This supports previous observation in major US stock markets that statistical properties of the number of shares traded and the number of trades in a given time interval are closely related [13]. For US markets, power law tails have been reported for the distribution of both the number of trades [12] and the volume [13].

6 0 20 40 60 80 100 120 140 Time shift (trading days) Fig. 7. Variation of largest eigenvalue and < |C| >, with the time shift, j. Analysis period is confined to period II. First j was increased in steps of 2 days each time to span a total time of 280 − 500 days (see Figure 3). Volatility has been scaled for convenience. A minute exercise was carried out in Figure 8 by advancing the time windows in steps of 1 day each time, spanning a total time of 333 − 444 days in order to capture the impact of the 9/11 shock.

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