In 2019, the COVID-19 epidemic swept throughout the globe. The virus was first identified in Wuhan, China. By the time several months had gone by, this virus had spread to numerous locations throughout the world. Consequently, this virus has become a worldwide pandemic. Multiple efforts have been made to limit the transmission of this virus. A possible course of action is to lock down the territory. Unfortunately, this strategy wrecked the economy, worsening the terrible situation. The world health organization (WHO) would breathe a sigh of relief if there were to be no new cases. However, the government should explore employing data from the future in addition to the data it already has. Prediction of time series may be utilized for this purpose. This study indicated that the Gaussian processes method outperformed the least median squared linear regression method (LMSLR). Applying a Pearson VII-based global kernel produces MAE and RMSE values of 23.12 and 53.43, respectively.

Measuring risk of financial institutes and banks plays an important role on managing them. Recent financial turmoil in United States banking system has motivated banking industry to monitor risk factors more closely. In this paper, we present an empirical study to measure the risk of some private banks in Iran called Bank Mellat using Value at Risk (VaR) method. The proposed study collects the necessary information for the fiscal year of 2010 and analyses them using regression analysis. The study divides the financial data into two groups where the financial data of the first half of year is considered in the first group and the remaining information for the second half of year 2010 is considered in the second group. The implementation of VaR method indicates that financial risks increase during the time horizon. The study also uses linear regression method where independent variable is time, dependent variable is the financial risk, and the results confirm what we have found in the previous part of the survey.

During the past few years, there have been tremendous fluctuations on different currencies. For instance, European common currency, Euro, has be fluctuated between 0.60 to 0.9 against US dollar. Therefore, it is important to study the behavior of currency valuations using different techniques. In this paper, we present an empirical study to measure the impact of different items on risk of foreign currency using value at risk (VaR) and regression methods. The proposed model of this paper investigates whether the risk of open positions of six foreign currencies including US dollar, Euro, British Pound, Switzerland Frank, Norwegian Kroner and United Emirate Dirham increase during the time horizon. The proposed study of this paper uses historical daily prices of these currencies for a fiscal year of 2011 in one of private banks located in Iran and measures the relative risk. The results of the implementation of two methods of VaR and linear regression indicate that the risk of open positions increases during the time horizon.