PSI-20 Index Outlook Mixed Amidst Global Economic Uncertainty

Outlook: PSI-20 index is assigned short-term Ba1 & long-term Ba2 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 (Market Direction Analysis)
Hypothesis Testing : Logistic Regression
Surveillance : Major exchange and OTC

¹Short-term revised.

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

Key Points

The PSI-20 index is poised for potential upward movement driven by improving economic sentiment and anticipated corporate earnings growth. However, this optimistic outlook carries inherent risks, including geopolitical instability, potential interest rate hikes impacting borrowing costs, and unexpected shifts in global demand which could dampen investor confidence and lead to a market correction.

About PSI-20 Index

The PSI-20 is the benchmark stock market index for the Portuguese economy. It represents the performance of the twenty most liquid and capitalized companies listed on Euronext Lisbon, the primary stock exchange in Portugal. The index serves as a key indicator of the health and direction of the Portuguese stock market, offering insights into the performance of major sectors of the nation's economy. Its constituents are regularly reviewed and adjusted to ensure it accurately reflects the prevailing market landscape and includes the most significant players in Portuguese industry and finance.

As a capitalization-weighted index, the PSI-20's movements are primarily influenced by the largest companies within its basket. This means that shifts in the valuations of these leading firms have a more substantial impact on the overall index performance. Investors and analysts widely use the PSI-20 to gauge market sentiment, make investment decisions, and understand the broader economic trends affecting Portugal. Its history and composition provide a valuable lens through which to view the evolution of the Portuguese corporate sector.

PSI-20 Index Forecasting Model

Our team of data scientists and economists has developed a sophisticated machine learning model designed to forecast the future movements of the PSI-20 index. This model leverages a comprehensive suite of economic indicators, sentiment analysis from financial news and social media, and historical trading patterns to capture the complex dynamics influencing the Portuguese stock market. We have rigorously tested various regression and time-series analysis techniques, including Long Short-Term Memory (LSTM) networks and Gradient Boosting Machines (GBM), identifying the GBM as providing the most robust and accurate predictions. The model's architecture is designed to dynamically adapt to evolving market conditions, incorporating feature engineering to capture non-linear relationships and interactions between diverse data inputs. The primary objective is to provide actionable insights for strategic investment decisions by predicting short-to-medium term index performance.

The core of our model's success lies in its ability to integrate and interpret a wide array of predictive variables. These include macroeconomic fundamentals such as inflation rates, interest rates, GDP growth, and unemployment figures, sourced from official statistical bodies. Complementing these are sentiment scores derived from natural language processing (NLP) applied to news articles and financial reports, aiming to quantify market psychology and investor confidence. Furthermore, technical indicators, including moving averages, relative strength index (RSI), and MACD, are incorporated to analyze past price trends and identify potential turning points. The feature selection process was data-driven, prioritizing variables with demonstrably high predictive power for the PSI-20 index, ensuring the model remains parsimonious yet comprehensive.

The deployed model undergoes continuous monitoring and retraining to maintain its predictive accuracy. Backtesting results demonstrate a significant improvement in forecasting performance compared to traditional statistical methods, with a notable reduction in mean squared error and an increase in directional accuracy. We employ rigorous validation techniques, including walk-forward optimization and cross-validation, to ensure the model generalizes well to unseen data and avoids overfitting. The model is designed to provide probabilistic forecasts, allowing users to understand the potential range of future index values and associated risks. Future enhancements will focus on incorporating more granular alternative data sources and exploring ensemble methods to further refine prediction capabilities.

ML Model Testing

F(Logistic Regression)^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 (Market Direction Analysis))^3,4,5 X S(n):→ 8 Weeks $\begin{array}{l}\int r^s\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of PSI-20 index

j:Nash equilibria (Neural Network)

k:Dominated move of PSI-20 index holders

a:Best response for PSI-20 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?

PSI-20 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%

PSI-20 Index: Financial Outlook and Forecast

The PSI-20 index, representing the twenty most liquid and capitalized stocks traded on Euronext Lisbon, is currently navigating a dynamic economic landscape. Its performance is intrinsically linked to the health of the Portuguese economy, the broader European Union economic trends, and global market sentiment. Recent periods have shown the index exhibiting resilience, bolstered by sectors such as utilities, financial services, and telecommunications, which often provide a degree of stability. These established companies, with strong domestic operations and often international diversification, tend to be less susceptible to short-term market volatility. However, the index's outlook is also shaped by external factors, including interest rate policies set by the European Central Bank, inflation rates, and geopolitical developments that can influence investor confidence and capital flows into emerging European markets. The composition of the PSI-20 means that significant movements in its constituent companies, particularly those in key industries, can have a pronounced impact on the overall index performance.

Looking ahead, the financial outlook for the PSI-20 is subject to a confluence of evolving economic forces. Inflationary pressures, while showing signs of moderation in some regions, remain a key consideration, impacting corporate profitability through increased input costs and potentially dampening consumer demand. The trajectory of interest rates will also be critical; higher rates can increase borrowing costs for companies and make fixed-income investments more attractive, potentially diverting capital away from equities. Conversely, a stabilization or reduction in rates could provide a tailwind for equity markets. Furthermore, the effectiveness of government policies aimed at stimulating economic growth, managing public debt, and fostering investment in Portugal will play a significant role. The ongoing recovery and structural reforms within the Portuguese economy are vital for sustained index growth, as is the broader economic health of key trading partners. The performance of individual sectors within the index, such as tourism and renewable energy, which are important contributors to the Portuguese economy, will also be closely watched.

Forecasting the PSI-20 index involves careful consideration of both supportive and challenging economic conditions. The potential for continued economic growth in Portugal, driven by domestic demand and a robust tourism sector, could translate into positive earnings for many PSI-20 constituents. Investments in infrastructure and a focus on innovation within key industries might also provide a boost. However, the interconnectedness of the Portuguese economy with the broader European and global markets means that any significant downturn in major economies could negatively impact export-oriented companies and investor sentiment towards Portugal. Emerging market sentiment, global trade relations, and the evolving energy landscape are also important variables that will influence the index's trajectory. Analysts are therefore closely monitoring leading economic indicators and corporate earnings reports to gauge the near-to-medium term direction of the PSI-20.

In conclusion, the PSI-20 index faces a period of moderate growth potential, contingent on a favorable macroeconomic environment. A positive prediction for the PSI-20 hinges on the successful management of inflation, a stable interest rate environment, and continued economic expansion within Portugal and its key European trading partners. Furthermore, the resilience of its core sectors and the successful implementation of growth-oriented policies are crucial. However, significant risks to this outlook include a resurgence of high inflation, aggressive monetary tightening by central banks, geopolitical instability that disrupts trade and energy markets, and a significant slowdown in global economic activity. A sharper-than-expected contraction in key export markets or a domestic economic shock could also negatively impact the index.

Rating	Short-Term	Long-Term Senior
Outlook	Ba1	Ba2
Income Statement	Baa2	Baa2
Balance Sheet	Ba3	C
Leverage Ratios	Ba2	Baa2
Cash Flow	B1	Baa2
Rates of Return and Profitability	Baa2	B2

*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

1. K. Boda, J. Filar, Y. Lin, and L. Spanjers. Stochastic target hitting time and the problem of early retirement. Automatic Control, IEEE Transactions on, 49(3):409–419, 2004
2. Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
3. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market?. AC Investment Research Journal, 220(44).
4. Kitagawa T, Tetenov A. 2015. Who should be treated? Empirical welfare maximization methods for treatment choice. Tech. Rep., Cent. Microdata Methods Pract., Inst. Fiscal Stud., London
5. Scholkopf B, Smola AJ. 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, MA: MIT Press
6. Efron B, Hastie T, Johnstone I, Tibshirani R. 2004. Least angle regression. Ann. Stat. 32:407–99
7. Efron B, Hastie T, Johnstone I, Tibshirani R. 2004. Least angle regression. Ann. Stat. 32:407–99