In deciding to invest in stocks traded in the capital market, investors need to predict which stocks provide the prospect of return and the risks to be faced. This paper aims to predict the return and risk of stock asymmetry using a time series model approach. Predicting stock returns and risk is based on the Autoregressive Integrated Moving Average-Glosten Jagannatan Runkle-Generalized Autoregressive Conditional Heteroscedasticity (ARIMA-GJR-GARCH) model. In contrast, the largest risk potential measurement is performed using the Value-at-Risk (VaR) model. The data analyzed are the best ten stocks according to the criteria that apply on the IDX, the period between 17 December 2018 to 14 December 2021, which includes the names of stock BBCA, BBNI, BBRI, BMRI, ASII, ICBP, PGAS, PTBA, TLKM, and UNVR. The analysis results show that of the best ten stocks, based on the ratio between the predicted values of the average return and Value-at-Risk, those with relatively better performance are PTBA, TLKM, UNVR and BBCA stocks. Based on the results of this analysis, it can be used as a reference in making investment decisions for investors, specifically investing in the ten stocks analyzed.

The current study analyzed the determinants of the Peruvian coca illegal plantations in the period 2003-2019. Hence, the DEVIDA database variables were gathered at first. Then, a machine learning-based technique is employed to select the most relevant variables for the study. That technique, Lasso, selected as accurate variables eradication of coca plantations and pasta base. Both OLS and VAR are employed to analyze the relevance of the selected variables. OLS finds that eradication was negatively related to the dependent variable. Nonetheless, pb confiscation had a positive relationship with illegal coca crops. Furthermore, VAR encounters that only pb confiscation affected the dependent variable. Supplementary tests are carried to ensure the accuracy of the results. In consequence, it is concluded that eradication policies by themselves were not enough to discourage the coca plantations. Farmers should get instruction about alternative crops and financial help. Furthermore, it has been claimed that pb confiscation generates scarcity of the drug, which elevates its price. Thus, coca farmers are more motivated to plant coca because of the higher prices. Therefore, as long as the international demand, which is disposed to pay high prices, the coca illegal crops and its illicit products will exist.

The study is conducted to examine the impact of real effective exchange rate volatility on the trade balance in Vietnam from 2002 to 2019 by using the VAR (vector autoregression) model. The volatility of real effective exchange rate is calculated through the GARCH (1,1) model based on the quarterly data (collected by Bruegel, Europe) of the Vietnamese currency with 143 major trading partners of Vietnam. The research result shows that the current trade balance was negatively affected by the volatility of the past trade balance with the lag from 1 quarter to 4 quarters. Especially, the study finds that the volatility of real effective exchange rate with the lag of 2 reduced the trade balance in Vietnam. This is the particularity of Vietnam – a country pursuing a floating exchange rate policy under the control of the government.

The coca leaf has many uses in the Peruvian culture. Although there are legal usages, people employ coca for illicit business. The most infamous illegal use is cocaine production. The cocaine business is highly profitable, but it harms human health. Then, what are the determinants of cocaine price? The current analysis aims to get the variables with the capability to explain the cocaine prices in Peru. The period analyzed is 2003-2019. The study gathered variables from DEVIDA and UNDOC databases. The Lasso technique selected the variables with the best capability to predict cocaine price. Those variables were: ENACO acquisition, coca seizures, and coca crops. OLS, VAR, and Granger analyses employed those variables to analyze the relationship between them. According to the OLS analysis, both ENACO acquisition and coca crops had adverse effects on cocaine prices, while coca seizures were positively related to the cocaine price. VAR analysis showed that only ENACO acquisition had a short-term relationship with the dependent variable. Moreover, it showed that the whole set of variables influenced the dependent variable. The Granger analysis proved that there was a cause-effect relationship between ENACO acquisition and cocaine price. Hence, the ENACO purchases expansion can rest the attractiveness of illegal groups to farmers. However, lowering cocaine prices might attract more users. Therefore, educational activities are also required.

Human capital is considered as one of the major factors to promote economic stability, especially in developing countries. Furthermore, one of the most important factors in developing human capital is taking the advantage of facilities and economic capabilities in the Instruction Sector. Development of financial system provides such abilities for the prospective countries. This paper studies the influence of financial development on human capital in Iran over period 1977-2010 with the application of a VAR model. The results show that the cash flow in Iran has a negative effect on human capital, which could be because of the increase in inflation and ends increase in costs of long-term investment and human capital is taken into account as long term investment. However, the facilities provided by the banking system has negative effect on human capital due to the lack of the best financial resource allocation. However, since most of university graduate students in Iran practically have adequate skills and education, they do not have enough capital to start a business. Providing financial assistance for the private sector can lead to a business in which they can use their skills and education towards promoting production.

Measuring liquidity risk plays an important role on any business unit especially financial organizations. Social security systems in most countries around the world are responsible to provide necessary requirements in many countries such as health care, pension plans, etc. Therefore, it is necessary to reduce any risk associated with these systems as much as possible. In this paper, we study liquidity risk in Iranian social security using VaR technique. The proposed model of this paper uses historical information for a fiscal year of 2008-2011. We first divide the information of each year into two groups of first and second half and using VaR technique analyzed whether there was any trend change in these two groups. The results of our survey indicate that the mean of VaR in the second half of the year is greater than the first half of the year. Therefore, we can confirm that VaR maintains an increasing trend over the time horizon. We also study the trend in liquidity using regression analysis for each year, separately and the results of our survey confirm that there was an increasing trend in liquidity over time.