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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, while float-weighted indexing has been the norm in other countries, perhaps because of large cross-holdings or government ownership.
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.
Rendezvous or highest random weight (HRW) hashing [1] [2] is an algorithm that allows clients to achieve distributed agreement on a set of options out of a possible set of options. A typical application is when clients need to agree on which sites (or proxies) objects are assigned to.
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.
Equal-weight funds hold an equal proportion of each stock that makes up an index, which translates into a roughly 0.2 percent holding for each company in the S&P 500, for example.
Fundamentally based index funds have higher expense ratios than the traditional capitalization weighted index funds. For example, the Powershares fundamentally based ETFs have an expense ratio of 0.6% (the U.S. index ETF has an expense ratio of 0.39%) while the PIMCO Fundamental IndexPLUS TR Fund charges 1.14% in annual expenses. [25]
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.
Grigoriadis and Khachiyan [3] applied a randomized variant of "fictitious play" to solve two-player zero-sum games efficiently using the multiplicative weights algorithm. In this case, player allocates higher weight to the actions that had a better outcome and choose his strategy relying on these weights.