Mathematical valuation and risk assessment models can be misleading or inaccurate for several reasons:
* Missing factors in models: Important variables or conditions might be overlooked.
* Bad or wrong data: Incorrect or poor-quality data input can lead to faulty outcomes.
* Misinterpretation of results: Users might not correctly understand or use the results.
* Errors in the derivation of the model: Mistakes in the mathematical formulation or assumptions can lead to errors.
All these factors contribute to the potential inaccuracy or misleading nature of such models.