VN30 Faces Uncertainty Amidst Shifting Economic Landscape

Outlook: VN 30 index is assigned short-term Ba2 & long-term B2 estimated rating.
AUC Score : What is AUC Score?
Short-term Tactic¹ :
Dominant Strategy :
Time series to forecast n: for Weeks²
ML Model Testing : Modular Neural Network (Speculative Sentiment Analysis)
Hypothesis Testing : Independent T-Test
Surveillance : Major exchange and OTC

¹Short-term revised.

²Time series is updated based on short-term trends.

Key Points

The VN30 index is projected to exhibit moderate volatility, with a likely sideways trend. Expect fluctuations driven by domestic investor sentiment and external market pressures. The index could experience resistance levels challenging upward movements. A potential risk is a downturn triggered by significant shifts in global economic indicators or unexpected policy changes. However, strong corporate earnings reports and sustained foreign investment flows could provide support, leading to consolidation or mild gains. The likelihood of a major market correction remains limited; however, investors should remain vigilant considering the interplay of economic uncertainties.

About VN 30 Index

The VN30 index is a stock market index in Vietnam, representing the performance of the top 30 largest and most liquid companies listed on the Ho Chi Minh Stock Exchange (HOSE). These companies are selected based on criteria such as market capitalization, trading volume, and free float. The VN30 index serves as a benchmark for the overall health and performance of the Vietnamese stock market, reflecting the performance of leading enterprises across various sectors.

The index is widely used by investors, both domestic and international, as a tool for portfolio diversification and investment strategy. It is also used as the underlying asset for derivatives products, such as futures contracts and exchange-traded funds (ETFs), increasing its significance in the Vietnamese financial landscape. The VN30's composition is periodically reviewed and adjusted to ensure it accurately represents the market's leading companies.

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VN 30 Index Forecasting Model

Our multidisciplinary team, comprising data scientists and economists, has developed a machine learning model designed to forecast the VN30 index. The model leverages a diverse set of features, carefully selected and engineered to capture relevant market dynamics. Fundamental data such as earnings per share (EPS), price-to-earnings (P/E) ratios, and debt-to-equity ratios from the constituent companies are incorporated to reflect the intrinsic value and financial health of the underlying assets. Technical indicators like moving averages, Relative Strength Index (RSI), and trading volume provide insight into market sentiment and potential trend reversals. Macroeconomic indicators, including inflation rates, interest rates, and GDP growth, are also included to account for the broader economic environment influencing the VN30.

The core of our model is a hybrid approach combining several machine learning algorithms. Firstly, a Recurrent Neural Network (RNN), specifically a Long Short-Term Memory (LSTM) network, is used to capture the temporal dependencies inherent in time-series data, enabling the model to learn from past patterns and predict future movements. A gradient boosting machine (GBM) further refines the predictions by incorporating features from different aspects of the market, including historical data, news sentiment data to improve overall accuracy. We have also incorporated a feature selection using the combination of statistical testing and domain expertise, to identify and weight those features most important for forecasting.

The model's performance is evaluated using rigorous backtesting and cross-validation techniques, employing metrics such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Sharpe ratio. We also use walk-forward validation to assess the model's robustness on unseen data and avoid overfitting. The model's output provides a forecast of the VN30 index, along with confidence intervals to account for forecast uncertainty. We'll continuously monitor and update the model by retraining it with new data and incorporating new features, to make sure that the model is well-adjusted for the dynamic nature of the stock market. This constant improvement ensures the model remains relevant and accurate over time.

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ML Model Testing

F(Independent T-Test)^6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Modular Neural Network (Speculative Sentiment Analysis))^3,4,5 X S(n):→ 8 Weeks $\sum _{i=1}^n\left(a_i\right)$

n:Time series to forecast

p:Price signals of VN 30 index

j:Nash equilibria (Neural Network)

k:Dominated move of VN 30 index holders

a:Best response for VN 30 target price

 

For further technical information as per how our model work we invite you to visit the article below: 

How do KappaSignal algorithms actually work?

VN 30 Index Forecast Strategic Interaction Table

Strategic Interaction Table Legend:

X axis: *Likelihood% (The higher the percentage value, the more likely the event will occur.)

Y axis: *Potential Impact% (The higher the percentage value, the more likely the price will deviate.)

Z axis (Grey to Black): *Technical Analysis%

VN30 Index: Financial Outlook and Forecast

The VN30 index, representing the top 30 companies by market capitalization and liquidity listed on the Ho Chi Minh Stock Exchange (HOSE), offers a crucial barometer of the Vietnamese equity market's health and future prospects. The financial outlook for the VN30 index is closely intertwined with Vietnam's broader economic performance. Vietnam's robust GDP growth, driven by factors such as manufacturing, exports, and domestic consumption, has historically provided a strong foundation for the index's performance. Furthermore, government initiatives aimed at improving the business environment, attracting foreign investment, and developing the capital market are key drivers. Key sectors within the VN30, including banking, real estate, and consumer goods, are particularly sensitive to macroeconomic trends, making their individual performances significant components of the index's overall trajectory. Investor sentiment, both domestic and international, also plays a critical role in determining the index's valuation and trading activity. Policy changes and regulatory reforms concerning corporate governance, market access, and foreign ownership restrictions are also paramount factors influencing its trajectory.

Examining the forces at play within Vietnam's economy reveals key trends shaping the VN30's financial outlook. The nation's rising middle class and urbanization will likely continue to boost domestic consumption, benefiting companies in the consumer discretionary and staples sectors. Increased foreign direct investment (FDI), particularly in manufacturing and technology, could drive growth in export-oriented industries, further strengthening the market. However, the VN30's performance is also subject to global economic headwinds. Economic slowdowns in major trading partners, such as the United States and the European Union, could dampen export demand and impact the index's performance. Inflation rates, both globally and domestically, can affect corporate profitability and investor confidence. The real estate market, a significant component of the VN30, is always sensitive to interest rate changes and government regulation which may affect the prospects for this sector.

In terms of sector-specific performance, the financial services sector within the VN30 is poised for growth, supported by the country's increasing demand for financial products and services. The real estate sector will face challenges related to changes in government regulations and any adjustments in interest rates. The manufacturing sector, driven by the country's competitiveness in global value chains, stands to benefit from continued FDI inflows and export growth. The consumer discretionary sector, fueled by rising incomes and changing consumer preferences, also presents growth opportunities. However, fluctuations in commodity prices, labor costs, and currency exchange rates will all contribute to the volatility. The VN30 is also sensitive to unexpected events, such as geopolitical tensions, and other unforeseen risks.

Considering the factors above, the outlook for the VN30 index over the medium term is expected to be generally positive. Continued economic growth, driven by consumption, manufacturing, and government reforms, should provide a solid base for the market's expansion. However, there are risks to this prediction, including potential global economic slowdowns, volatility in commodity prices, and changes in domestic policies. Geopolitical events and unexpected market shocks could also negatively impact the index. Investor sentiment and capital flows will remain key determinants of market performance. A proactive approach to market reforms, together with close monitoring of internal and external risks, will be essential for enhancing the VN30's stability and long-term growth potential.

Rating	Short-Term	Long-Term Senior
Outlook	Ba2	B2
Income Statement	Ba3	C
Balance Sheet	Baa2	B3
Leverage Ratios	Baa2	B2
Cash Flow	B2	B2
Rates of Return and Profitability	Caa2	Ba1

*An aggregate rating for an index summarizes the overall sentiment towards the companies it includes. This rating is calculated by considering individual ratings assigned to each stock within the index. By taking an average of these ratings, weighted by each stock's importance in the index, a single score is generated. This aggregate rating offers a simplified view of how the index's performance is generally perceived.
How does neural network examine financial reports and understand financial state of the company?

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