By United States. National Aeronautics and Space Administration.; Goddard Space Flight Center

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44 V. Kulkarni and N. 3 ‘Last’ eigenmode and the variability index The eigenstates of C deviating from RMT predictions bring out the collective response of the market to perturbations. Collective motion of all the assets in the portfolio is significantly high, or the stocks are highly correlated in regimes marked by occasional or persisting bursts of activity. The degree of such synchronization is indicated by the eigenvector corresponding to the largest eigenvalue, through the evolution of its structure and components, seen in a.

Note that, both of the above-mentioned studies looked at low-resolution data, namely, the daily closing time series. In this study, we have looked at the high-frequency transaction by transaction stock price data, as well as taken a fresh look at the low-frequency daily data. We conclude that, far from being different, the distribution of price fluctuations in Indian markets is quantitatively almost identical to that of developed markets. However, the distributions for trading volume and number of trades seem to be market-specific, with the Indian data being consistent with a log-normal distribution for both of these quantities.

Hence, when θ = 0, we have the minimum risk portfolio, and when θ = 1, we have the maximum return (maximum risk) portfolio. The higher the value of θ, the higher the expected portfolio return rP,θ and, consequently, the higher the risk the investor is willing to absorb. We define a single measure, the weighted portfolio layer as wi lev(vit ), lP (t, θ) = (4) i∈P(t,θ) N where i=1 wi = 1 and further, as a starting point, the constraint wi ≥ 0 for all i, which is equivalent to assuming that there is no short-selling.

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Total Ozone Mapping Spectrometer by United States. National Aeronautics and Space Administration.; Goddard Space Flight Center


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