The technical and quantitative analysis of the Casablanca stock market is being enhanced through an innovative approach that combines stochastic simulations with systematic rules. This model, when applied to the benchmark index of the Casablanca Stock Exchange, known as the MASI, aims to provide a more robust framework for managing risks, identifying the market's directional bias, and making informed allocation decisions.
Unlike traditional forecasting that relies on a single target price, this model generates a multitude of potential trajectories based on the index's historical behavior. It utilizes two complementary tools: the Monte Carlo simulation, which measures uncertainty, and trend following, which is employed to ascertain the market's dominant direction.
Monte Carlo Simulation: Mapping Scenarios Rather Than Predicting Specific Levels
The future trajectory of a stock market index is inherently uncertain, which is why the Monte Carlo simulation does not attempt to pinpoint the exact level the MASI will reach on a specific date. Instead, it generates thousands of possible paths based on historical returns, volatility, and variations of the index. The dispersion of these paths allows for an assessment of potential variances and the construction of a probabilistic corridor around the last observed level.
The primary advantage of this method lies in its risk analysis capabilities. It enables investors to visualize a range of favorable and unfavorable scenarios, estimate potential losses, and measure the widening of uncertainty as the projection horizon extends. However, the results remain dependent on the assumptions made and the market's past behavior; thus, a historical simulation does not guarantee that similar configurations will occur in the future.
Trend Following: Identifying the MASI's Bias
The second component of the model is based on trend following, a methodology that does not aim to predict market lows or highs but rather to detect the establishment of a sufficiently clear dynamic to follow. When the indicator turns green, the model signals a bullish bias, while a switch to red indicates a bearish dynamic or a deterioration in the trend.
This approach contrasts with a passive buy-and-hold strategy, where the investor remains exposed to all market cycles. Trend following can help reduce exposure during reversal phases, but it may also produce false signals when the index moves without a clear direction. The accompanying graph illustrates the trend-following line appearing red in recent sessions, indicating an immediate unfavorable bias despite various simulated rebound trajectories.
This model analyzes the evolution of the MASI from 2013 to 2026, capturing various configurations of the Casablanca market, including bullish phases, corrections, episodes of high volatility, and periods of consolidation. The latest available quotation serves as the starting point for the projection, from which the algorithm deploys a set of trajectories represented by the gray lines in the graph.
These trajectories do not represent independent forecasts but rather illustrate the different paths the index could take based on the statistical characteristics integrated into the model. The graph reveals a cone that gradually widens, depicting an increase in uncertainty over time: the further the projection horizon, the broader the range of potential levels.
The upper bound, marked in green, represents the highest part of the projection corridor, encompassing the most favorable scenarios generated by the model. Conversely, the lower bound, indicated in red, corresponds to the lower part of the envelope and illustrates the most unfavorable risk scenarios. It is crucial to note that these bounds should not be mistaken for guaranteed price targets; rather, they are probabilistic benchmarks calculated from the volatility and historical variations of the MASI.
Projecting over a one-month horizon, the stochastic analysis highlights four primary levels to frame the risks based on the current market configuration. The **extreme bullish scenario** sets the upper limit of the projection at **18,871 points**, representing the most favorable assumption generated by the model considering the selected volatility. An **intermediate favorable scenario** positions the MASI around **18,092 points**, indicating a progression trajectory within the upper part of the probabilistic corridor. Conversely, the **intermediate unfavorable scenario** highlights a level of **17,152 points**, which translates to the assumption of a moderate correction of the index during the projection month. Lastly, the **extreme bearish scenario** establishes the lower risk envelope at **16,518 points**, measuring the most significant decline among the scenarios framed by the model and serving as a benchmark for potential loss evaluations.
The combination of Monte Carlo simulations and trend following offers a structured framework for analyzing the MASI, allowing for the visualization of various trajectories, improved risk assessment, and a reduction in the influence of decisions driven by fear or excessive optimism. However, it is essential to recognize that this model does not eliminate uncertainty or market risk. Its results depend on the quality of the data, the analyzed period, and the statistical assumptions used, and should be supplemented by fundamental analysis, volume studies, market liquidity, and individual investor goals.
As reported by boursenews.ma.
