The study investigates the asymmetric effect of exchange rate changes on stock prices in Vietnam. We use the nonlinear autoregressivedistributed lag (ARDL) analysis for monthly data from 2001:01 to 2018:05, based on VN-Index stock price collected from Ho Chi Minh Stock Exchange (HOSE); the nominal exchange rate is separated into currency depreciation and appreciation through a partial sum decomposition process. Asymmetry is estimated both in the long-run relationship and the short-run error correction mechanism. The research results show that the effect of exchange rate changes on stock prices is asymmetrical, both in the short run and in long run. Accordingly, the stock prices react to different levels to depreciation and appreciation. However, the currency appreciation affects a stronger transmission of stock prices when compared to the long-run currency depreciation. In the absence of asymmetry, the exchange rate only has a short-run impact on stock prices. This implies a symmetrical assumption that underestimates the impact of exchange rate changes on stock prices in Vietnam. This study points to an important implication for regulators in Vietnam. They should consider the relationship between exchange rate changes and stock prices in both the long run and the short run to manage the stock and foreign exchange market.

Multi-criteria stock selection is a critical issue for effective investment since the improper stock investment might cause many problems affecting investors negatively. Investors need a range of financial indicators while they are choosing the optimal set of stocks to invest. This study aims to rank the stock of agriculture companies indexed on the Vietnam Stock Exchange Market. The data of 13 agriculture companies during the 2016-2019 periods was analyzed by analytical hierarchy process (AHP) integrated with grey relational analysis (GRA), multiobjective optimization ratio analysis (MOORA), and technique for order performance by similarity to ideal solution (TOPSIS). The AHP method is employed to determine the weights of the proposed financial ratios, and GRA, TOPSIS, and MOORA approaches are used to obtain final ranking. The results indicated that HSL is the top stock with the highest rank and GRA, MOORA, and TOPSIS rankings have strong correlation values between 0.78-1. The findings suggest that the integrated model could be implemented effectively to specific analysis of industries such as oil and gas, textiles, food, and electronics in future research. Further, other techniques like COPRAS, KEMIRA, and EDAS could be employed to evaluate the financial performance of other companies to solve investment problems.

The study aims to examine the impact of productivity in addition to the policy of increasing the foreign investors’ ownership rate on the performance of businesses which were listed on Vietnam's stock exchange market from 2010 to 2017. With the database of 3.961 observations, the study employs a statistical method – multiple regression to estimate the relationship between labor productivity, foreign ownership as well as other firm-level characteristics and firm performance. Research findings show that increasing labor productivity and increasing foreign ownership rates help increase firm performance. In addition, except for financial leverage, variables such as liquidity and firm size have positive effects on firm performance measured by Tobin’s Q. These findings have theoretical contributions and practical implications for managers, investors and government in Vietnam. Managers should pay attention to improving labor productivity through employing incentive mechanisms, building a good working environment, investing in technology, etc. in order to enhance the firm performance. Investors could utilize the labor productivity and foreign ownership indicators to select stocks of good companies for investment. For Vietnamese government, relaxing the limit of foreign ownership and accelerating the divesting of State capital in Stateowned enterprises could help increase the investment scale of foreign investors and resulting in positive effects on the firm performance.

Building a target capital structure is one of the most important decisions in corporate financial management. The purpose of this article is to identify the determinants of capital structure and adjustment mechanism toward the target leverage. The partial adjustment model was applied on a sample of 306 non-financial companies listed on Vietnam stock exchange market during the period of 2008-2017. By the fixed effect model estimation method, the research results have discovered the factors of growth opportunities, firm size, tangible fixed assets and firm’s unique characteristics have a positive effect on the target capital structure of enterprises. Besides, profitability and dividend payment have a negative effect on the target capital structure of enterprises. Accordingly, the research results show that the average adjustment speed toward target leverage of the firms is 90.03%. Research results also demonstrate firms have higher or lower debt ratio than the target debt ratio, capital surplus or capital deficit also have an impact on the adjustment rate toward the target capital structure. The research results are consistent with the Dynamic Trade-off Theory. From this result, this article has provided policy implications for non-financial companies listed on Vietnam’s stock market in building a reasonable target capital structure according to operating timeline to maximize enterprise value.

The paper aims to measure stock price volatility on Ho Chi Minh stock exchange (HSX). We apply symmetric models (GARCH, GARCH-M) and asymmetry (EGARCH and TGARCH) to measure stock price volatility on HSX. We used time series data including the daily closed price of VN-Index during 1/03/2001–1/03/2019 with 4375 observations. The results show that GARCH (1,1) and EGARCH (1,1) models are the most suitable models to measure both symmetry and asymmetry volatility level of VN-Index. The study also provides evidence for the existence of asymmetric effects (leverage) through the parameters of TGARCH model (1,1), showing that positive shocks have a significant effect on the conditional variance (volatility). This result implies that the volatility of stock returns has a big impact on future market movements under the impact of shocks, while asymmetric volatility increase market risk, thus increase the attractiveness of the stock market. The research results are useful reference information to help investors in forecasting the expected profit rate of the HSX, and also the risks along with market fluctuations in order to take appropriate adjust to the portfolios. From this study’s results, we can see risk prediction models such as GARCH can be better used in risk forecasting especially.