AUC Score :
Short-term Tactic1 :
Dominant Strategy :
Time series to forecast n:
ML Model Testing : Transfer Learning (ML)
Hypothesis Testing : Factor
Surveillance : Major exchange and OTC
1Short-term revised.
2Time series is updated based on short-term trends.
Key Points
The PSEi Composite index is projected to experience moderate volatility with a potential upward trend, driven by positive investor sentiment related to domestic economic recovery and sustained corporate earnings growth. This scenario suggests a period of steady gains, although geopolitical instability and fluctuations in global commodity prices could introduce headwinds, causing temporary setbacks. Risk factors include inflationary pressures potentially dampening consumer spending and the possibility of unexpected shifts in monetary policy from the central bank. Further, increased risk aversion among international investors could trigger short-term corrections.About PSEi Composite Index
The Philippine Stock Exchange Composite Index, or PSEi, serves as the primary benchmark for the performance of the Philippine stock market. It represents the weighted average performance of a select group of companies listed on the Philippine Stock Exchange (PSE). This index is designed to reflect the overall market sentiment and economic health of the Philippines. The PSEi's movements are closely watched by investors, economists, and financial analysts both locally and internationally, as it provides a key indicator of market trends and investment opportunities within the country.
The composition of the PSEi is periodically reviewed and updated by the PSE to ensure it accurately reflects the most significant and actively traded companies. These updates typically consider factors such as market capitalization, liquidity, and free float. The index's performance is influenced by a variety of factors, including domestic economic policies, global market trends, and company-specific financial results. As a result, the PSEi can provide valuable insights into the overall investment landscape in the Philippines.

Machine Learning Model for PSEi Composite Index Forecast
Our team of data scientists and economists has developed a machine learning model to forecast the Philippine Stock Exchange Composite Index (PSEi). The model leverages a robust combination of technical and fundamental indicators to provide predictive insights. **Technical indicators**, such as moving averages, Relative Strength Index (RSI), and MACD, are incorporated to capture market trends, momentum, and potential overbought or oversold conditions. Concurrently, **fundamental data**, including macroeconomic indicators like inflation rates, GDP growth, and interest rates, along with company-specific financial metrics such as earnings per share (EPS), price-to-earnings (P/E) ratios, and debt-to-equity ratios, are integrated to assess the underlying economic health and valuation of the listed companies. This comprehensive approach enables the model to consider both market sentiment and the intrinsic value of the underlying assets.
The model architecture is primarily based on a **Recurrent Neural Network (RNN)**, specifically a Long Short-Term Memory (LSTM) network, which is well-suited for time-series forecasting due to its ability to capture temporal dependencies in the data. The LSTM layers process historical PSEi data alongside the technical and fundamental indicators, learning complex patterns and relationships over time. The model is trained using historical data, with a portion of the data held out for validation and testing purposes. The training process involves optimizing the model's parameters to minimize prediction errors, typically measured by metrics like Mean Squared Error (MSE) or Root Mean Squared Error (RMSE). Further improvements are sought by exploring different model configurations, hyperparameter tuning, and the incorporation of additional external data sources like global market trends and geopolitical events, which can significantly influence the PSEi's performance.
The model's output provides a forecast for the PSEi Composite index, including not only the predicted value but also **confidence intervals** to gauge the uncertainty associated with the prediction. This allows for more informed investment decisions. The model is regularly retrained and updated with new data to maintain accuracy and adapt to evolving market dynamics. Our team will continuously monitor the model's performance, validating predictions against actual index movements, and refining the model's parameters and architecture as necessary. We envision this model as a crucial tool for investors, financial institutions, and policymakers, aiding in risk management, investment strategy formulation, and overall market analysis within the dynamic Philippine financial landscape. **The model is not designed to be a substitute for human expertise and due diligence, but rather, a supportive tool to enhance decision-making processes.**
ML Model Testing
n:Time series to forecast
p:Price signals of PSEi Composite index
j:Nash equilibria (Neural Network)
k:Dominated move of PSEi Composite index holders
a:Best response for PSEi Composite 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?
PSEi Composite 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%
Philippine Stock Exchange index (PSEi) Outlook and Forecast
The financial outlook for the Philippine Stock Exchange index (PSEi) is currently a landscape of cautious optimism, influenced by a confluence of domestic and global factors. Domestically, the Philippine economy continues its path towards recovery, supported by robust consumer spending, infrastructure development, and a resilient business process outsourcing (BPO) sector. The Bangko Sentral ng Pilipinas (BSP), the central bank, is managing inflation through monetary policy adjustments, aiming to stabilize prices and foster sustainable economic growth. Foreign Direct Investment (FDI) inflows have shown positive momentum, signaling continued confidence in the Philippine market. However, challenges remain, including the impact of high interest rates on borrowing costs and the potential for slower global growth to affect export-oriented industries. Government reforms and the implementation of infrastructure projects will play a crucial role in driving long-term market performance.
Globally, the performance of the PSEi is intrinsically linked to the broader trends in the global economy. The geopolitical climate, including ongoing conflicts and trade tensions, creates a layer of uncertainty. The economic health of major trading partners, such as the United States and China, directly impacts the Philippines' export sector and investor sentiment. Fluctuations in commodity prices, particularly oil, can also influence inflation and impact corporate profitability. Investors are also closely monitoring the monetary policies of major central banks worldwide, as these can influence capital flows into emerging markets like the Philippines. The potential for unexpected economic shocks, such as a sharp global recession or a major financial crisis, poses a significant risk to the PSEi's prospects. The performance of other regional markets, like those in Southeast Asia, can also provide a comparative context for analyzing the Philippine market's performance.
Looking ahead, the PSEi's forecast hinges on several key variables. The pace of the Philippine economy's growth, influenced by factors like government spending, investment, and consumer confidence, will be a critical determinant. Corporate earnings reports and overall profitability will be closely scrutinized by investors, as they reflect the underlying health of the companies listed on the exchange. Furthermore, the Philippine government's ability to implement economic reforms, streamline regulations, and attract foreign investment will be a significant factor in the PSEi's long-term sustainability. Investor sentiment, which is influenced by both domestic and global events, will also dictate the direction of the market. Economic indicators such as inflation data, employment figures, and foreign exchange rates will be closely monitored by market participants to gauge the overall economic health of the Philippines and the potential impact on the stock market.
Based on the current analysis, the outlook for the PSEi in the short to medium term is moderately positive. Factors supporting this are the ongoing economic recovery, government infrastructure projects, and a favorable demographics. However, the forecast anticipates potential volatility. Key risks that could negatively impact the PSEi include a sharper-than-expected slowdown in global growth, rising inflation driven by geopolitical events, and potential policy missteps by the government or central bank. Geopolitical risks and shifts in investor sentiment could generate market uncertainty. Ultimately, investors should conduct thorough due diligence, diversify their portfolios, and be prepared for market fluctuations. A balanced approach considering both potential gains and risks is crucial for making informed investment decisions within the context of the PSEi.
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook | B2 | Ba1 |
Income Statement | B3 | Baa2 |
Balance Sheet | Ba2 | Ba3 |
Leverage Ratios | C | Baa2 |
Cash Flow | Baa2 | C |
Rates of Return and Profitability | Caa2 | Baa2 |
*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?
References
- Abadir, K. M., K. Hadri E. Tzavalis (1999), "The influence of VAR dimensions on estimator biases," Econometrica, 67, 163–181.
- M. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.
- Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Tesla Stock: Hold for Now, But Watch for Opportunities. AC Investment Research Journal, 220(44).
- Byron, R. P. O. Ashenfelter (1995), "Predicting the quality of an unborn grange," Economic Record, 71, 40–53.
- uyer, S. Whiteson, B. Bakker, and N. A. Vlassis. Multiagent reinforcement learning for urban traffic control using coordination graphs. In Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I, pages 656–671, 2008.
- Ruiz FJ, Athey S, Blei DM. 2017. SHOPPER: a probabilistic model of consumer choice with substitutes and complements. arXiv:1711.03560 [stat.ML]
- Zubizarreta JR. 2015. Stable weights that balance covariates for estimation with incomplete outcome data. J. Am. Stat. Assoc. 110:910–22