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To find critical points, compute the first derivative of the function using differentiation rules like the product rule. Factor out common terms from the derivative expression, then set it equal to zero and solve for x-values. These x-values are the critical points where the function's slope is zero, partitioning the domain into intervals for further analysis.

When the derivative changes from positive to negative, the function transitions from increasing to decreasing, indicating a local maximum. Conversely, a change from negative to positive shows the function shifts from decreasing to increasing, identifying a local minimum. These sign changes reveal where the function's behavior reverses, critical for understanding first derivatives and the shape of a graph.

The product rule is required when differentiating functions composed of multiple terms multiplied together, such as a polynomial multiplied by an exponential term. It ensures each component is correctly differentiated and combined. After applying the product rule, simplifying by factoring out common terms makes solving for critical points more manageable.

After identifying critical points, select test points within each interval created by those critical points. Evaluate the derivative's sign at each test point to determine if the function is increasing or decreasing. Finally, substitute the critical x-values into the original function to find the corresponding y-values, which are the local extrema representing the function's local maximum and minimum points.

Asset prices can be modeled as smooth functions where turning points represent locally overvalued and undervalued regions. The first derivative test identifies where prices shift from rising to falling or vice versa, revealing potential reversal points. These local extrema mark where momentum changes from recovery to decline, helping quantify critical valuation regions for investment decisions.

Critical points divide the domain into distinct intervals. Within each interval, a test point is chosen and substituted into the derivative to determine its sign. A positive derivative indicates the function is increasing over that interval, while a negative derivative shows it is decreasing. This systematic interval analysis reveals the complete behavior pattern of the function.

A local maximum occurs where the derivative changes from positive to negative, representing a peak in the function. A local minimum occurs where the derivative changes from negative to positive, representing a valley. Both are identified by analyzing derivative sign changes across critical numbers and the closed interval method to confirm their exact locations and values.