A robust filter in stock networks analysis

Stock Selection as a Problem in Phylogenetics—Evidence from the ASX

“…where d ij is the distance corresponding to the the estimated correlation, ρ ij , between stocks i and j, see [14] or [21] for details. A typical stock market correlation matrix for n stocks is of full rank which means that after converting to a distance matrix according to Equation (1), the location of the points, here stocks, can only be fully represented in (n − 1)-dimensional space.…”

“…In recent years a significant number of papers have appeared in the econophysics literature which apply graph theoretical methods to the study of a stock or other financial markets, see for example, [14][15][16][17][18][19][20][21][22] among others. Much of this literature uses correlations, partial correlations, or both in their analysis.…”

Network Topological Property of English Dialects Similarity: A Robust Filter Approach

“…Then, Djauhari (2012) for the proof, ∆ is the adjacency matrix that corresponds to the forest. Thus, the forest is defined by all pairs (i, j) where i > j and δ(i, j) = 1.…”

Optimality problem of network topology in stocks market analysis

“…Thus, if there is more than one MST, it might produce misleading economic interpretation. This is due to the fact that the algorithms provide only one MST among all possible MSTs that might exist in the network [34]. In the next section, (i) a preliminary study on New York Stock Exchange (NYSE) data, which shows that an MST issued from Kruskal's algorithm might not be optimal, will be reported and (ii) a hypothetical example will show that the result of Kruskal's algorithm depends on the way we order the stocks to define the row and column of the network C .…”