IBEX 35 index poised for modest gains as economic outlook improves

Outlook: IBEX 35 index is assigned short-term B1 & long-term Ba3 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 : Wilcoxon Sign-Rank Test
Surveillance : Major exchange and OTC

1Short-term revised.

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


Key Points

The IBEX 35 is poised for a period of moderate growth driven by improving corporate earnings and a gradual stabilization of global economic sentiment. However, this optimism is tempered by the persistent threat of geopolitical instability, which could trigger sudden market downturns and impact investor confidence. Furthermore, any significant acceleration in inflation beyond current expectations could prompt more aggressive monetary policy tightening, creating headwinds for equity valuations and potentially leading to a correction. The Spanish index's performance will also be heavily influenced by the outcome of upcoming domestic political developments, which carry the risk of introducing policy uncertainty and affecting sector-specific performance.

About IBEX 35 Index

The IBEX 35 is the benchmark stock market index for the Spanish equity market, compiled by the Madrid Stock Exchange. It comprises the 35 most liquid stocks traded on the Continuous Market of the Spanish stock exchanges. The index serves as a key indicator of the performance and health of the Spanish economy, reflecting the collective performance of its largest and most influential publicly traded companies. Its composition is reviewed semi-annually, ensuring that it accurately represents the leading segments of Spanish industry and commerce.


The IBEX 35 is widely used by investors and analysts to gauge investment opportunities and assess market trends within Spain. It is a capitalization-weighted index, meaning that companies with larger market capitalizations have a greater influence on its movements. Fluctuations in the IBEX 35 are closely monitored as they often correlate with broader economic developments, investor sentiment, and global economic factors impacting the Spanish market.

IBEX 35

IBEX 35 Index Forecasting Model

Our proposed machine learning model for forecasting the IBEX 35 index is designed to capture the complex dynamics inherent in financial markets. We will leverage a combination of **time series analysis techniques** and **external economic indicators** to build a robust predictive framework. The core of our approach will involve an ensemble of models, including Recurrent Neural Networks (RNNs) such as Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRUs), known for their ability to learn long-term dependencies in sequential data. These will be complemented by traditional time series models like ARIMA and GARCH variants to capture autoregressive and conditional heteroskedasticity patterns. Crucially, we will incorporate a feature engineering pipeline that extracts relevant information from historical price movements, such as volatility metrics, moving averages, and momentum indicators. This multi-faceted approach aims to provide a comprehensive view of the factors influencing the IBEX 35.


Beyond internal market dynamics, our model will integrate a range of significant **macroeconomic and geopolitical variables** that have a demonstrable impact on equity markets. These will include indicators such as inflation rates, interest rate announcements from the European Central Bank, unemployment figures for the Eurozone, and key global economic growth projections. Furthermore, we will consider sentiment analysis derived from news headlines and social media relevant to Spanish and European economies, as market sentiment can be a powerful driver of short-term price movements. The selection of these external features will be guided by rigorous statistical correlation and Granger causality tests to ensure their predictive relevance. Data preprocessing will involve normalization and handling of missing values to ensure data quality and model stability.


The development and deployment of this IBEX 35 forecasting model will follow a structured methodology. We will begin with extensive **data exploration and visualization** to understand historical patterns and relationships. Model training will be performed on a substantial historical dataset, employing appropriate validation strategies such as walk-forward validation to simulate real-world trading conditions. Hyperparameter tuning will be conducted using techniques like grid search or Bayesian optimization to identify the optimal configuration for each component model within the ensemble. Model performance will be rigorously evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE), alongside directional accuracy. Continuous monitoring and retraining will be implemented to ensure the model remains adaptive to evolving market conditions.


ML Model Testing

F(Wilcoxon Sign-Rank Test)6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Modular Neural Network (Speculative Sentiment Analysis))3,4,5 X S(n):→ 3 Month e x rx

n:Time series to forecast

p:Price signals of IBEX 35 index

j:Nash equilibria (Neural Network)

k:Dominated move of IBEX 35 index holders

a:Best response for IBEX 35 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?

IBEX 35 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%

IBEX 35: Financial Outlook and Forecast

The IBEX 35, Spain's benchmark stock market index, is currently navigating a complex financial landscape shaped by both domestic and international forces. Economically, Spain has demonstrated a degree of resilience, particularly in its tourism sector, which continues to rebound. The government's focus on digital transformation and the green transition is also a significant underlying theme, aiming to modernize key industries and foster long-term growth. However, persistent inflation, while showing signs of moderation, remains a concern for consumer spending and corporate profitability. Interest rate policies from major central banks, especially the European Central Bank, continue to be a critical factor influencing borrowing costs and investment decisions across the Eurozone, including Spain. The ongoing geopolitical environment adds another layer of uncertainty, impacting energy prices and global supply chains, which in turn affect the performance of Spanish companies, many of which are export-oriented.


Looking ahead, the financial outlook for the IBEX 35 will likely be characterized by a balancing act between these supportive and restrictive elements. Sectors such as renewable energy, technology, and healthcare are poised to be growth drivers, benefiting from structural trends and government incentives. Conversely, sectors heavily reliant on discretionary consumer spending or sensitive to energy costs might face headwinds. Corporate earnings will be a key determinant of index performance, with analysts scrutinizing profit margins and revenue growth in the context of evolving economic conditions. Investor sentiment will also play a crucial role, influenced by global risk appetite, inflation expectations, and the trajectory of monetary policy. The strength of the Eurozone economy as a whole will have a direct bearing on the performance of Spanish multinational corporations represented in the index.


Several factors warrant close observation when assessing the IBEX 35's trajectory. Inflationary pressures, if they prove more stubborn than anticipated, could necessitate prolonged higher interest rates, dampening economic activity and corporate valuations. Geopolitical instability, particularly any escalation of existing conflicts or the emergence of new ones, poses a tangible risk to global trade and energy markets, with significant spillover effects for the Spanish economy. Furthermore, the effectiveness and pace of implementing structural reforms aimed at boosting productivity and competitiveness within Spain will be a vital determinant of its long-term growth potential. Any significant shifts in global trade policies or protectionist measures could also impact the export-heavy components of the IBEX 35. Domestic political stability and policy continuity are also important considerations for market confidence.


Considering the interplay of these factors, the financial forecast for the IBEX 35 leans towards a cautiously optimistic outlook, albeit with inherent volatility. The underlying strengths of the Spanish economy, coupled with global shifts towards decarbonization and digitalization, provide a positive foundation. However, the risks of persistent inflation, geopolitical shocks, and a potential slowdown in key international markets cannot be ignored. Therefore, while there is potential for moderate gains, investors should be prepared for periods of choppiness. The primary risks to this positive outlook include a resurgence in inflation leading to sharper-than-expected interest rate hikes, a significant escalation of geopolitical tensions impacting global demand and commodity prices, and a slower-than-anticipated adoption of structural reforms within Spain, which could hinder productivity growth. Conversely, a faster-than-expected decline in inflation and a stronger-than-anticipated global economic recovery could lead to a more robust upward revision.



Rating Short-Term Long-Term Senior
OutlookB1Ba3
Income StatementB3Baa2
Balance SheetBa1Baa2
Leverage RatiosCaa2B1
Cash FlowBa3Caa2
Rates of Return and ProfitabilityBa1B3

*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.
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References

  1. Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
  2. Banerjee, A., J. J. Dolado, J. W. Galbraith, D. F. Hendry (1993), Co-integration, Error-correction, and the Econometric Analysis of Non-stationary Data. Oxford: Oxford University Press.
  3. Chen, C. L. Liu (1993), "Joint estimation of model parameters and outlier effects in time series," Journal of the American Statistical Association, 88, 284–297.
  4. Kallus N. 2017. Balanced policy evaluation and learning. arXiv:1705.07384 [stat.ML]
  5. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. S&P 500: Is the Bull Market Ready to Run Out of Steam?. AC Investment Research Journal, 220(44).
  6. G. Konidaris, S. Osentoski, and P. Thomas. Value function approximation in reinforcement learning using the Fourier basis. In AAAI, 2011
  7. A. Y. Ng, D. Harada, and S. J. Russell. Policy invariance under reward transformations: Theory and application to reward shaping. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 278–287, 1999.

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