K-Means Clustering Approach for Improving Financial Forecasts

The following paper treats both types of forecasting: qualitative and quantitative. It highlightsthe importance of using both of them in order to achieve more accurate forecasts. It shows the flaws of quantitative forecasting when applying simple regression on large sets ofdata. Also, by using advan...

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Main Author:	Țole Alexandru - Adrian
Format:	Article
Language:	English
Published:	Ovidius University Press 2018-01-01
Series:	Ovidius University Annals: Economic Sciences Series
Subjects:	clustering k-means quantitative qualitative forecasting
Online Access:	http://stec.univ-ovidius.ro/html/anale/RO/wp-content/uploads/2018/08/15-2.pdf

id	doaj-b0c2ca915bc94c4f88a5e76b393ed908
record_format	Article
spelling	doaj-b0c2ca915bc94c4f88a5e76b393ed9082020-11-24T22:16:31ZengOvidius University PressOvidius University Annals: Economic Sciences Series2393-31272393-31272018-01-01XVIII1514518K-Means Clustering Approach for Improving Financial ForecastsȚole Alexandru - Adrian0The Romanian - American UniversityThe following paper treats both types of forecasting: qualitative and quantitative. It highlightsthe importance of using both of them in order to achieve more accurate forecasts. It shows the flaws of quantitative forecasting when applying simple regression on large sets ofdata. Also, by using advanced data analysis techniques, such as Big Data algorithms, the results ofthe quantitative forecasting can be drastically improved and it can be worthy of taking intoconsideration when drawing the conclusions. K-means algorithm it proves to be very effective when a quantitative forecast needs to be done. By using it we can successfully execute “drill-down forecasting” into specific activities.http://stec.univ-ovidius.ro/html/anale/RO/wp-content/uploads/2018/08/15-2.pdfclusteringk-meansquantitativequalitativeforecasting
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Țole Alexandru - Adrian
spellingShingle	Țole Alexandru - Adrian K-Means Clustering Approach for Improving Financial Forecasts Ovidius University Annals: Economic Sciences Series clustering k-means quantitative qualitative forecasting
author_facet	Țole Alexandru - Adrian
author_sort	Țole Alexandru - Adrian
title	K-Means Clustering Approach for Improving Financial Forecasts
title_short	K-Means Clustering Approach for Improving Financial Forecasts
title_full	K-Means Clustering Approach for Improving Financial Forecasts
title_fullStr	K-Means Clustering Approach for Improving Financial Forecasts
title_full_unstemmed	K-Means Clustering Approach for Improving Financial Forecasts
title_sort	k-means clustering approach for improving financial forecasts
publisher	Ovidius University Press
series	Ovidius University Annals: Economic Sciences Series
issn	2393-3127 2393-3127
publishDate	2018-01-01
description	The following paper treats both types of forecasting: qualitative and quantitative. It highlightsthe importance of using both of them in order to achieve more accurate forecasts. It shows the flaws of quantitative forecasting when applying simple regression on large sets ofdata. Also, by using advanced data analysis techniques, such as Big Data algorithms, the results ofthe quantitative forecasting can be drastically improved and it can be worthy of taking intoconsideration when drawing the conclusions. K-means algorithm it proves to be very effective when a quantitative forecast needs to be done. By using it we can successfully execute “drill-down forecasting” into specific activities.
topic	clustering k-means quantitative qualitative forecasting
url	http://stec.univ-ovidius.ro/html/anale/RO/wp-content/uploads/2018/08/15-2.pdf
work_keys_str_mv	AT tolealexandruadrian kmeansclusteringapproachforimprovingfinancialforecasts
_version_	1725789372799778816

K-Means Clustering Approach for Improving Financial Forecasts

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