Editing Safran SA (section)

== Monte Carlo Simulations ==

=== Data ===
Introducing our cutting-edge Monte Carlo simulation for Safran's stock price analysis! By harnessing the power of this advanced computational method, we aim to provide you with invaluable insights into the potential behavior of Safran's stocks over time.
[[File:Sfran stock.png|none|thumb|500x500px|Historical price of Safran's equity]]
Our Monte Carlo simulation involves running thousands of random simulations based on a variety of input variables, including historical price data, volatility, and other essential market factors. Through this approach, we generate a comprehensive probability distribution of possible outcomes, enabling you to assess the potential risk and returns associated with investing in Safran.
[[File:Log distr.png|none|thumb|400x400px|Logarithmic distribution of past prices]]

=== Simulations ===
With our simulation, you can make data-driven decisions and gain a deeper understanding of the uncertainty surrounding the stock's performance. Embrace the future of equity research and explore the vast range of possibilities to optimize your investment strategies effectively.
[[File:MC simu.png|none|thumb|500x500px|Price paths of Safran's stock 50 days in the future for 100 simulations]]
Through our Monte Carlo simulations, we have the ability to visualize numerous paths for 100 simulations, offering a glimpse into the potential outcomes. However, to gain a deeper and more comprehensive understanding of the results, we recommend running a larger number of simulations. By doing so, we can effectively construct probability distributions that highlight the likelihood of Safran's stock price being at certain levels. This will provide a more accurate and insightful analysis, enabling you to make informed decisions with confidence.
[[File:SImu dis.png|none|thumb|500x500px|Final stock price distribution in 50 days for 1,000,000 simulations]]
From this analysis, it becomes evident that the current valuation on the 28th of July 2023, at 147.98€, appears to be somewhat inflated when we examine the Gaussian curve. The distribution of prices is skewed towards the left side of the curve, indicating a higher concentration of lower price points.

Please note that we utilized the article "''Monte Carlo Simulations for Stock Price Predictions [Python]''" authored by ''Elias Melul'' as a reference to develop our Python code for running the simulations. You can find the complete Python code in the appendix section.<ref>https://medium.com/analytics-vidhya/monte-carlo-simulations-for-predicting-stock-prices-python-a64f53585662</ref>