Data analysis, portfolio selection and portfolio renewal in Turkish capital market.

Küçükçınar, Altan


Data-driven modeling using deep neural networks for power systems demand and locational marginal price forecasting
Jimu, Honest; Fahrioğlu, Murat; Electrical and Electronics Engineering (2022-9)
Forecasting electricity demand and locational marginal prices (LMPs) have become critical components for power system security and management. Electricity Demand Forecasting (EDF) aids the utility in maximizing the use of power-generation plants and scheduling them for both reliability and cost-effectiveness. In this thesis, a novel Deep Neural Network Long Short-Term Memory (DNN-LSTM) forecasting model is suggested to improve accuracy and robustness for predicting hourly day ahead power system load and LMP...
Data Mining Approach for Direct Marketing of Banking Products with Profit/Cost Analysis
Mitik, Merve; Korkmaz, Ozan; Karagöz, Pınar; Toroslu, İsmail Hakkı; Yucel, Ferhat (2017-06-01)
Nowadays, many businesses, such as banks, use direct marketing methods to reach customers to minimize the campaigning cost and maximize the return rate. To achieve this, huge customer data should be analyzed to determine the most appropriate product offer for each customer and the most effective channel to reach her/him. However, since only a very small amount of responses collected from the customers are positive to the offers, the dataset is very imbalanced. This decreases sensitivity ratio of prediction ...
Data mining approach for direct marketing of banking products with profit/cost analysis
Korkmaz, Ozan; Toroslu, İsmail Hakkı; Karagöz, Pınar; Department of Computer Engineering (2017)
Nowadays, direct marketing is widely used advertisement method by many business areas such as banks. The main purposes of direct marketing are to maximize return on investment, minimize cost of promotions and reach to peak number of customers that prefer the offerred campaign. Therefore, it is necessary to collect and process huge amount of customer related data to decide questions of which customer will be offered a product, which product will be suitable to him/her and via which channel the promotion will...
Data Mining Framework for Power Quality Event Characterization of Iron and Steel Plants
Guder, Mennan; Salor, Ozgul; ÇADIRCI, IŞIK; Ozkan, Baris; Altintas, Erinc (2015-07-01)
In this paper, a power quality (PQ) knowledge discovery and modeling framework has been developed for both temporal and spatial PQ event data collected from transformer substations supplying iron and steel (I&S) plants. PQ event characteristics of various I&S plants have been obtained based on clustering and rule discovery techniques. The data are collected by the PQ analyzers, which detect the voltage sags, swells, and interruptions according to the IEC Standard 61000-4-30. The constructed clustering strat...
Data mining analysis of economic indicators of countries
Güngör, Erdem; Yozgatlıgil, Ceylan; Department of Statistics (2020-8)
Data Mining is becoming a famous analysis day by day to reveal the hidden information within big data. In the study, we use data mining techniques on the economic indicators of the countries. The four data mining techniques are to be implemented on the dataset. Making homogenous groups of the countries whose economic characteristics are similar are obtained by the Clustering Algorithm. After the clustering algorithm is performed, we pass to Association Rule Data Mining to investigate the most exported produ...
Citation Formats
A. Küçükçınar, “Data analysis, portfolio selection and portfolio renewal in Turkish capital market.,” Middle East Technical University, 1996.