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The Shapley–Shubik power index was formulated by Lloyd Shapley and Martin Shubik in 1954 to measure the powers of players in a voting game. [ 1 ] The constituents of a voting system, such as legislative bodies, executives, shareholders, individual legislators, and so forth, can be viewed as players in an n -player game .
The difference between the full capitalization, float-adjusted, and equal weight versions is in how the index components are weighted. The full cap index uses the total shares outstanding for each company. The float-adjusted index uses shares adjusted for free float. The equal-weighted index assigns each security in the index the same weight.
An index that is weighted in this manner is said to be "float-adjusted" or "float-weighted", in addition to being cap-weighted. For example, the S&P 500 index is both cap-weighted and float-adjusted. [3] Historically, in the United States, capitalization-weighted indices tended to use full weighting, i.e., all outstanding shares were included ...
The NIFTY 50 index is a free float market capitalisation-weighted index. Stocks are added to the index based on the following criteria: [1] Must have traded at an average impact cost of 0.50% or less during the last six months for 90% of the observations, for the basket size of Rs. 100 Million. The company should have a listing history of 6 months.
Fundamentally based indexes or fundamental indexes, also called fundamentally weighted indexes, are indexes in which stocks are weighted according to factors related to their fundamentals such as earnings, dividends and assets, commonly used when performing corporate valuations. This fundamental weight may be calculated statically, or it may be ...
This algorithm can easily be adapted to compute the variance of a finite population: simply divide by n instead of n − 1 on the last line.. Because SumSq and (Sum×Sum)/n can be very similar numbers, cancellation can lead to the precision of the result to be much less than the inherent precision of the floating-point arithmetic used to perform the computation.
NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
For normally distributed random variables inverse-variance weighted averages can also be derived as the maximum likelihood estimate for the true value. Furthermore, from a Bayesian perspective the posterior distribution for the true value given normally distributed observations and a flat prior is a normal distribution with the inverse-variance weighted average as a mean and variance ().