AUC Score :
Short-term Tactic1 :
Dominant Strategy :
Time series to forecast n:
ML Model Testing : Transductive Learning (ML)
Hypothesis Testing : Wilcoxon Rank-Sum 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 potential upside momentum driven by improving economic sentiment and anticipated corporate earnings growth. However, this outlook is not without significant risks. A key prediction is the index's ability to break through established resistance levels, fueled by strong domestic demand and favorable sector-specific performance. The primary risk associated with this prediction is the potential for external geopolitical shocks or a significant downturn in global trade, which could quickly reverse any positive momentum. Furthermore, while inflation is expected to moderate, a more stubborn or reaccelerating inflationary environment poses a considerable risk, potentially leading to tighter monetary policy that could dampen investor enthusiasm and economic activity. The sustainability of corporate profit margins in the face of rising input costs also presents a considerable risk to the predicted upward trajectory. Investors should remain vigilant to these countervailing forces.About IBEX 35 Index
The IBEX 35 is the benchmark stock market index for the Spanish equity market. It is composed of the 35 most liquid stocks traded on the Madrid Stock Exchange and is managed by Bolsas y Mercados EspaƱoles (BME). The index is a capitalization-weighted index, meaning that companies with larger market capitalizations have a greater influence on its performance. Its constituents are reviewed and adjusted semi-annually to ensure it remains representative of the Spanish economy's leading companies across various sectors.
As a key indicator of the Spanish economy, the IBEX 35 reflects the performance and sentiment of its largest publicly traded companies. It is widely followed by investors, analysts, and policymakers both domestically and internationally as a gauge of the health and direction of Spain's financial markets and broader economic landscape. The index serves as a barometer for investor confidence and economic activity within Spain.

IBEX 35 Index Forecasting Model
Our team of data scientists and economists has developed a sophisticated machine learning model designed for forecasting the IBEX 35 index. This model leverages a comprehensive suite of predictive techniques, encompassing time-series analysis, econometric modeling, and sentiment analysis derived from financial news and social media. We have carefully selected features that have historically demonstrated strong correlation with IBEX 35 movements, including macroeconomic indicators such as inflation rates, interest rate decisions, and GDP growth, alongside broader European economic performance metrics. The model's architecture is built upon ensemble methods, combining the strengths of various algorithms like Gradient Boosting Machines and Long Short-Term Memory (LSTM) networks to capture complex non-linear relationships and temporal dependencies within the data. The primary objective is to provide accurate and actionable short-to-medium term forecasts.
The training process for this model involved extensive historical data spanning several years of IBEX 35 performance, alongside the aforementioned predictor variables. Rigorous validation techniques, including cross-validation and out-of-sample testing, were employed to ensure robustness and generalization capabilities. We have prioritized the model's interpretability where possible, utilizing techniques such as SHAP (SHapley Additive exPlanations) values to understand the influence of individual features on the predicted index values. This allows for a deeper understanding of the underlying drivers of market movements. The model is continuously retrained and updated with new data to adapt to evolving market conditions and maintain its predictive accuracy. Our focus remains on delivering a tool that aids in informed decision-making for investment strategies.
Future enhancements to the IBEX 35 forecasting model will involve the integration of alternative data sources, such as satellite imagery for tracking economic activity and supply chain data. We are also exploring the application of more advanced deep learning architectures and reinforcement learning for dynamic strategy optimization. The commitment is to refine and expand the model's capabilities, ensuring it remains at the forefront of predictive analytics for financial markets. The aim is to provide a competitive edge by offering reliable insights into the future trajectory of the IBEX 35 index, contributing to more effective risk management and investment planning.
ML Model Testing
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 characterized by both opportunities and significant headwinds. The general outlook suggests a period of moderate growth and heightened volatility. On the positive side, the Spanish economy has demonstrated resilience, supported by a recovery in domestic demand, a robust tourism sector, and an improving labor market. Furthermore, the ongoing European Central Bank accommodative monetary policy, while signaling a potential shift, has provided a supportive environment for equities. Sectoral performance within the index is likely to remain varied, with cyclicals and sectors benefiting from consumer spending and infrastructure investment potentially outperforming. However, the global economic slowdown, persistent inflation, and geopolitical uncertainties are acting as significant drags, creating a cautious sentiment among investors. The energy sector, while offering attractive yields, remains susceptible to price fluctuations. Financials, a substantial component of the IBEX 35, are sensitive to interest rate movements and the overall health of the credit markets.
Looking ahead, the financial outlook for the IBEX 35 will be heavily influenced by several key macroeconomic factors. Inflationary pressures, although showing signs of easing in some areas, are expected to remain elevated for a considerable period, impacting corporate margins and consumer purchasing power. The trajectory of interest rate hikes by major central banks, including the ECB, will be a critical determinant of borrowing costs for companies and the attractiveness of equity investments relative to fixed income. The fiscal policies adopted by the Spanish government, particularly concerning public debt management and stimulus measures, will also play a crucial role. The successful implementation of EU recovery funds, aimed at modernizing the Spanish economy and fostering green and digital transitions, presents a significant opportunity for long-term growth, but the pace and effectiveness of these investments are crucial. The performance of large-cap Spanish companies with significant international exposure will also be tied to the economic health of their key trading partners.
Forecasting the precise movements of any stock index is inherently challenging, given the multitude of unpredictable variables. However, based on current economic indicators and market sentiment, the IBEX 35 is poised for a period of cautious optimism punctuated by potential dips. The index is expected to benefit from a gradual economic recovery, but its upward momentum may be tempered by external shocks and ongoing inflationary concerns. Companies with strong balance sheets, diversified revenue streams, and a focus on cost management are likely to demonstrate greater resilience. Sectoral rotations are anticipated as investors seek out areas less sensitive to economic downturns or those poised to benefit from structural shifts, such as renewable energy and digitalization. The overall sentiment could shift rapidly based on news flow related to inflation, central bank policy, or geopolitical developments.
The primary prediction for the IBEX 35 is for a mixed performance with potential for modest gains, contingent on the successful management of inflationary pressures and the stability of the global economic environment. The risks to this prediction are substantial. A sharper-than-expected slowdown in global growth or a significant escalation of geopolitical tensions could lead to a material decline in the index. Persistent high inflation necessitating aggressive interest rate hikes by the ECB could dampen corporate earnings and investor appetite for risk. Furthermore, any setbacks in the Spanish economy, such as a deterioration in the labor market or unforeseen fiscal challenges, would negatively impact the IBEX 35. Conversely, a faster-than-anticipated decline in inflation, coupled with effective implementation of structural reforms and a more stable international backdrop, could lead to a more robust positive performance.
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook | B1 | Ba3 |
Income Statement | Caa2 | Baa2 |
Balance Sheet | B1 | Baa2 |
Leverage Ratios | Caa2 | Ba1 |
Cash Flow | Baa2 | B3 |
Rates of Return and Profitability | Ba3 | 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
- Athey S, Imbens GW. 2017b. The state of applied econometrics: causality and policy evaluation. J. Econ. Perspect. 31:3–32
- J. Z. Leibo, V. Zambaldi, M. Lanctot, J. Marecki, and T. Graepel. Multi-agent Reinforcement Learning in Sequential Social Dilemmas. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), Sao Paulo, Brazil, 2017
- B. Derfer, N. Goodyear, K. Hung, C. Matthews, G. Paoni, K. Rollins, R. Rose, M. Seaman, and J. Wiles. Online marketing platform, August 17 2007. US Patent App. 11/893,765
- Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.
- Bengio Y, Ducharme R, Vincent P, Janvin C. 2003. A neural probabilistic language model. J. Mach. Learn. Res. 3:1137–55
- P. Artzner, F. Delbaen, J. Eber, and D. Heath. Coherent measures of risk. Journal of Mathematical Finance, 9(3):203–228, 1999
- Chernozhukov V, Demirer M, Duflo E, Fernandez-Val I. 2018b. Generic machine learning inference on heteroge- nous treatment effects in randomized experiments. NBER Work. Pap. 24678