Statistical Techniques Applied to Share Data - Part 1 0
The Need for Statistical Techniques
<!– /* Font Definitions */ @font-face {font-family:Calibri; panose-1:2 15 5 2 2 2 4 3 2 4; mso-font-charset:0; mso-generic-font-family:swiss; mso-font-pitch:variable; mso-font-signature:-1610611985 1073750139 0 0 159 0;} /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-parent:”"; margin-top:0cm; margin-right:0cm; margin-bottom:10.0pt; margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:Calibri; mso-fareast-font-family:”Times New Roman”; mso-bidi-font-family:”Times New Roman”; mso-ansi-language:EN-GB;} @page Section1 {size:612.0pt 792.0pt; margin:72.0pt 90.0pt 72.0pt 90.0pt; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;} div.Section1 {page:Section1;} –> Statistical methods were developed in order to make sense of large amounts of data, to boil that data down into a few meaningful conclusions. Never is this more necessary than in the world of Technical Analysis – the analysis of current share prices and the prediction of future ones. There are a vast number of publicly traded shares and each share price changes frequently, often several times a day. This produces a large amount of data, which is usually plotted as a series of graphs. To the untrained eye, these graphs look pretty meaningless, but by applying statistical methods, the information that they contain can be extracted.