Time Series Analysis of Housing Demand: A Forecasting Model for Ankara, Turkey

The property boom in Ankara surrounded by urban arrangements, calls for complicated forecasting approaches so that stakeholders can benefit from logical decision-making. The researchers apply up-to-date time series analysis methodology to forecast the housing demand in the area. It implicates the historical sales of housing and economic indicators combined with demographic factors are the sources that develop a comprehensive model of forecasting which allows to explore and track the intrinsic dynamics of the housing market. The methodology, in turn, is the application of cutting-edge statistical models and machine learning algorithms in the process of capturing the complex trend that is explicit in the time series data. In terms of our approach, we will include seasonality as well as trend components as well as those external factors, which affect the level of houses' demands. The study also analyzes the outcomes caused by economic shocks, public policies, and urban planning on housing market equilibrium. The study carried out demand forecasting concerning the sale of houses in Turkey which is supported by the data. The study is based on TURKSTAT numbers on the number of houses sold within the year 2021 (S.O.D) by Turkish provinces that cover Ankara province where the data is retrieved from. Considering the sales of houses in Ankara from 2014-2018 as a basis, this study intends to find a numerical forecasting model that is most suited to the observed dataset and thus, determine the number of houses sold in Ankara in the year 2019 using this particular method. Output from time series analysis provides the developers and investors with significant information by the way of anticipating market fluctuations, improving their investment strategies, and choosing the right policies according to the markets' needs. Moreover, an accurate model needs to be analyzed through serious validation techniques to identify its authenticity in its real-life examples. This research is, at the same time, an attempt to make progress in the field of demand forecasting in the real estate market as well as an attempt to provide stakeholders working in Ankara Province with a comprehensive guide while moving through a changing housing market. The utilization of technology and a careful investigation of relevant factors lends this study credibility as well as makes it a necessary literary component for those pursuing a deeper comprehension of housing demand in the region.