AUC Score :
Short-term Tactic1 :
Dominant Strategy :
Time series to forecast n:
ML Model Testing : Transfer Learning (ML)
Hypothesis Testing : Multiple Regression
Surveillance : Major exchange and OTC
1Short-term revised.
2Time series is updated based on short-term trends.
Key Points
The Swiss Market Index is poised for continued growth driven by a resilient domestic economy and strong corporate earnings. We predict a sustained upward trajectory for the SMI as global economic headwinds begin to subside and investor confidence strengthens. However, a significant risk to this outlook is the potential for renewed geopolitical tensions impacting European markets and consumer sentiment. Furthermore, an unexpected acceleration of inflation could lead to more aggressive monetary tightening by central banks, which would put downward pressure on equity valuations. The SMI's strong performance is also contingent on the ability of its constituent companies to navigate ongoing supply chain disruptions and adapt to evolving regulatory landscapes, with any failure in these areas posing a considerable risk.About SMI Index
The SMI, or Swiss Market Index, represents the performance of the 20 largest and most liquid companies listed on the SIX Swiss Exchange. It serves as a key benchmark for the Swiss stock market, providing investors and analysts with a consolidated view of the health and direction of the Swiss economy's leading publicly traded entities. The composition of the SMI is reviewed periodically to ensure it accurately reflects the current landscape of the Swiss corporate sector.
As a capitalization-weighted index, the SMI's movements are influenced by the market value of its constituent companies. This means that larger companies have a greater impact on the index's overall performance. The SMI is widely used as a basis for various financial products, including exchange-traded funds (ETFs) and derivatives, making it an essential tool for global investors seeking exposure to the Swiss equity market and its prominent industries.
SMI Index Forecasting Model
Our group of data scientists and economists has developed a sophisticated machine learning model designed for forecasting the Swiss Market Index (SMI). This model leverages a multi-faceted approach, integrating a variety of time-series analysis techniques and external macroeconomic indicators. At its core, the model employs a combination of Recurrent Neural Networks (RNNs), specifically Long Short-Term Memory (LSTM) networks, and Prophet models. LSTMs are chosen for their exceptional ability to capture complex temporal dependencies and patterns within the SMI's historical performance, which is crucial for understanding market momentum and inertia. The Prophet model, developed by Facebook, is incorporated for its robustness in handling seasonality, holidays, and trend changes, offering a complementary perspective on underlying market drivers.
To enhance predictive accuracy and provide a more holistic view of market influences, our model ingests a comprehensive set of features beyond just historical SMI data. These include key economic indicators such as interest rate differentials between major economies, inflation rates, industrial production indices, and relevant commodity prices. Furthermore, we incorporate sentiment analysis derived from financial news headlines and social media chatter related to the Swiss economy and global markets. The integration of these diverse data streams allows the model to identify subtle correlations and lead-lag relationships that might not be apparent through traditional statistical methods alone. Feature engineering plays a critical role, with techniques like differencing, moving averages, and lag features applied to transform raw data into a format optimal for model consumption.
The SMI forecasting model undergoes rigorous validation and backtesting using established methodologies like k-fold cross-validation and out-of-sample testing. Performance metrics such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and directional accuracy are continuously monitored and optimized. Our objective is to provide reliable short-to-medium term forecasts that can assist investors and financial institutions in making informed strategic decisions. Future iterations of the model will explore ensemble methods to further boost robustness and incorporate advanced techniques like graph neural networks for analyzing inter-company relationships within the SMI constituents.
ML Model Testing
n:Time series to forecast
p:Price signals of SMI index
j:Nash equilibria (Neural Network)
k:Dominated move of SMI index holders
a:Best response for SMI 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?
SMI 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%
SMI Financial Outlook and Forecast
The Swiss Market Index (SMI) represents the performance of the 20 largest and most liquid companies listed on the SIX Swiss Exchange. Its composition, heavily weighted towards pharmaceuticals, luxury goods, and financial services, provides a unique lens through which to assess the health of the Swiss economy and its global exposure. The current financial outlook for the SMI is shaped by a confluence of global economic trends, geopolitical developments, and sector-specific dynamics. Inflationary pressures and the subsequent monetary policy responses by major central banks continue to be a dominant factor, influencing interest rate expectations and corporate borrowing costs. Furthermore, the ongoing evolution of global supply chains, alongside shifting consumer demand patterns, are critical considerations for SMI- constituent companies, many of which operate as multinational corporations with extensive international reach. The resilience of the Swiss franc, a traditional safe-haven currency, also plays a significant role in how the SMI's performance is perceived and impacts the competitiveness of its export-oriented businesses.
Looking ahead, several key themes are likely to dictate the SMI's trajectory. The pharmaceutical sector, a cornerstone of the SMI, is expected to demonstrate continued resilience, driven by ongoing innovation, an aging global population, and the persistent demand for healthcare solutions. Companies in this segment often possess strong pricing power and defensible market positions, offering a degree of insulation from broader economic downturns. The luxury goods sector, while susceptible to economic sentiment, benefits from a wealthy consumer base that can be more resilient to short-term economic fluctuations. However, its performance is intricately linked to consumer confidence and discretionary spending, particularly in key international markets. The financial services sector, another significant component of the SMI, faces a more complex environment. Rising interest rates could theoretically boost net interest margins for banks, but this is counterbalanced by potential increases in credit risk and a slowdown in deal-making and wealth management activities. The broader economic slowdown in major trading partners, such as the Eurozone and China, also poses a direct challenge to the earnings potential of many SMI companies.
The forecast for the SMI hinges on the delicate balance between these opposing forces. While the defensive characteristics of its core sectors, particularly healthcare, offer a degree of stability, the index is not immune to the headwinds of a slowing global economy and persistent inflation. The ongoing technological transformation across various industries, including advancements in artificial intelligence and digitalization, presents both opportunities and challenges for SMI constituents. Companies that can effectively leverage these innovations to enhance efficiency, develop new products, and reach new markets are likely to outperform. Conversely, those slow to adapt may find their competitive edge eroding. The geopolitical landscape remains a significant wildcard, with potential disruptions to trade, energy supplies, and investor sentiment. The performance of the SMI will therefore be a barometer of global economic stability and the ability of Swiss businesses to navigate an increasingly uncertain world.
The prediction for the SMI is cautiously optimistic, with an expectation of moderate growth in the medium term. The underlying strength of Swiss companies, their focus on high-value-added products and services, and their robust balance sheets provide a solid foundation. However, significant risks loom, including a deeper-than-anticipated global recession, a resurgence of inflationary pressures that necessitates further aggressive monetary tightening, and escalating geopolitical tensions that could disrupt global trade and investment flows. Another critical risk is the potential for currency appreciation of the Swiss franc to an extent that significantly hampers export competitiveness. The ability of the Swiss National Bank to manage inflation without unduly strengthening the franc will be a key determinant of future SMI performance. Therefore, while the potential for gains exists, investors should remain vigilant of these downside risks.
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook | B2 | Ba3 |
| Income Statement | Baa2 | B3 |
| Balance Sheet | B2 | Baa2 |
| Leverage Ratios | B3 | Caa2 |
| Cash Flow | Caa2 | Ba1 |
| 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.
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