Search Results for forecasting-model
Abstract
This research aims to analyze the role of crisis management strategies in supporting Iraqi economic security in the post-2016 period, within an economic environment characterized by rentierism, a single source of income, and fragile infrastructure. The research seeks to analyze the main threats to national stability, such as public debt crises, unemployment, and inflation, while focusing on the theoretical foundations of crisis management concepts as a leadership and administrative system based on forecasting and proactivity. One of the most important objectives of the research is to focus on economic security and its management through successful crisis management strategies, and how to manage crises in a way that can reveal errors before they occur or address them after they occur. The research also relied on a quantitative analytical approach using time series data (2016-2025) and employed advanced statistical and econometric tools, including the ARIMA forecasting model and the Early Warning System (EWS) using Logit and Probit models. The study concluded with several key findings, most notably a positive but very weak and statistically insignificant correlation (p < 0.005) between crisis management strategies and short-term economic security. This weakness is attributed to the Iraqi economy's greater vulnerability to global oil price shocks and external financial fluctuations than to the effectiveness of current internal management mechanisms.
Abstract
The current study aims to predict the failure of companies through the use of financial ratios derived from cash flow disclosure and then categorize them into two categories, the safe category means that the company is in a secure financial position capable of providing cash and fulfilling financial obligations, and the second category is the unsafe category where the company is In a troubled financial situation unable to meet the financial obligations, as (11) financial ratios derived from the cash flow statement were used, and the study was applied in the Iraq Stock Exchange, as the sample consisted of (42) companies listed in it and for the period 2016-2020. Through the use of logistic regression analysis to the prediction model that works to classify companies, with an accuracy rate of 52.4%, the model consists of (4) financial ratios, which are (the ratio of operational activity, the ratio of operating cash to sales, the ratio of operating cash return to total assets, and finally the percentage of cash return operating to total liabilities)