Name: finding turning points with the first derivative
Uploaded: 2026-01-12T12:24:39.000Z
Duration: 1 min 25 s
Channel: JoVE

Bir varlık fiyatının en düşük noktaya düşen, fırsat avcıları devreye girdiğinde keskin bir şekilde toparlandığını ve ardından yavaş yavaş düştüğünü hayal edin.Grafikin yüksek ve düşük noktaları, finansal analizde kullanılan, ilk türev testi kullanılarak belirlenir.Bunu anlamak için, eğriyi bir fonksiyon olarak modelleyin ve ardından çarpım kuralı uygulanarak ilk türev bulunur.Ortak terimler çarpanlara ayrılır ve her terim fonksiyonun kritik noktalarını ve ilgili aralıkları almak için sıfıra ayarlanır.Bundan sonra, her aralıkta test puanları seçilir ve fonksiyonun türevi işareti incelenir.Pozitif türev fonksiyonun arttığını gösterirken, negatif türev fonksiyonun azaldığını gösterir. Türev pozitiften negatife geçtiğinde, fonksiyon artmadan azalmaya geçer ve yerel maksimum elde edilir. Negatiften pozitife geçiş yerel minimumu gösterir.Bu x-değerleri orijinal fonksiyona koymak, onların karşılık gelen fonksiyon değerlerini, yani yerel uç noktayı verir.Bu, varlık değerlemesinin analizi için kritik olan fonksiyonun yerel ekstrema maksimumları ve minimumlarını sağlar.

birinci türev testi: problem Çözümü

First Derivative Test: Problem Solving

Bir varl&#x131;k fiyat&#x131;n&#x131;n d&#xFC;&#x15F;&#xFC;k bir noktaya kadar geriledi&#x11F;ini, d&#xFC;&#x15F;&#xFC;k fiyattan al&#x131;m f&#x131;rsat&#x131; kollayan yat&#x131;r&#x131;mc&#x131;lar&#x131;n devreye girmesiyle keskin bi&#xE7;imde toparland&#x131;&#x11F;&#x131;n&#x131; ve ard&#x131;ndan kademeli olarak d&#xFC;&#x15F;t&#xFC;&#x11F;&#xFC;n&#xFC; hayal edin. Bu t&#xFC;r bir davran&#x131;&#x15F;, d&#xF6;n&#xFC;m noktalar&#x131; yerel olarak a&#x15F;&#x131;r&#x131; de&#x11F;erli ve d&#xFC;&#x15F;&#xFC;k de&#x11F;erlenmi&#x15F; b&#xF6;lgeleri temsil eden p&#xFC;r&#xFC;zs&#xFC;z bir fonksiyonla modellenebilir. Toparlanmay&#x131; izleyen d&#xFC;&#x15F;&#xFC;&#x15F;&#xFC; yans&#x131;tan elveri&#x15F;li bir &#xF6;rnek &#x15F;udur:\begin{equation*} f(x) = (x - 2)^4 e^{-x} \end{equation*}Bu e&#x11F;rinin yerel maksimum ve minimum noktalar&#x131;, fonksiyonun artan bir durumdan azalan bir duruma ya da tersine ge&#xE7;ti&#x11F;i yerleri belirleyen birinci t&#xFC;rev testi kullan&#x131;larak belirlenir. &#x130;lk olarak fonksiyonun birinci t&#xFC;revi hesaplan&#x131;r. Fonksiyon bir polinom terimi ile bir &#xFC;stel terimin &#xE7;arp&#x131;m&#x131; oldu&#x11F;undan, t&#xFC;rev alma i&#x15F;lemi &#xE7;arp&#x131;m kural&#x131;n&#x131;n uygulanmas&#x131;n&#x131; gerektirir. T&#xFC;rev al&#x131;nd&#x131;ktan sonra, elde edilen ifade, t&#xFC;revin t&#xFC;m terimlerinde ortak olan &#xE7;arpanlar parantezine al&#x131;narak sadele&#x15F;tirilir.Daha sonra t&#xFC;rev s&#x131;f&#x131;ra e&#x15F;itlenir ve &#xE7;&#xF6;z&#xFC;m i&#x15F;lemi, t&#xFC;revin s&#x131;f&#x131;r oldu&#x11F;u veya i&#x15F;aret de&#x11F;i&#x15F;iminin incelenmesi gereken kritik noktalar&#x131; verir. Bu kritik noktalar, tan&#x131;m k&#xFC;mesini sonraki analiz i&#xE7;in aral&#x131;klara ay&#x131;r&#x131;r.Ard&#x131;ndan, her bir aral&#x131;k i&#xE7;inde uygun test noktalar&#x131; se&#xE7;ilir ve t&#xFC;revin i&#x15F;areti incelenir. T&#xFC;revin pozitif olmas&#x131;, modellenen varl&#x131;k fiyat&#x131;n&#x131;n ilgili aral&#x131;kta artt&#x131;&#x11F;&#x131;n&#x131;; t&#xFC;revin negatif olmas&#x131; ise azald&#x131;&#x11F;&#x131;n&#x131; g&#xF6;sterir. T&#xFC;revin pozitiften negatife ge&#xE7;mesi, artan durumdan azalan duruma bir ge&#xE7;i&#x15F;i ifade eder ve yerel maksimumu g&#xF6;sterir. Buna kar&#x15F;&#x131;l&#x131;k, t&#xFC;revin negatiften pozitife de&#x11F;i&#x15F;mesi, fiyat e&#x11F;risindeki bir dipe kar&#x15F;&#x131;l&#x131;k gelen yerel minimumu belirler.Son olarak, kritik de&#x11F;erlerin orijinal fonksiyonda yerine konulmas&#x131;yla, bu d&#xF6;n&#xFC;m noktalar&#x131;na kar&#x15F;&#x131;l&#x131;k gelen fiyat seviyeleri elde edilir. Bu yerel ekstremumlar, de&#x11F;erleme analizinde temel &#xF6;nemdedir; &#xE7;&#xFC;nk&#xFC; potansiyel tersine d&#xF6;n&#xFC;&#x15F; b&#xF6;lgelerini g&#xF6;sterir ve ivmenin toparlanmadan d&#xFC;&#x15F;&#xFC;&#x15F;e ya da d&#xFC;&#x15F;&#xFC;&#x15F;ten toparlanmaya nerede kayd&#x131;&#x11F;&#x131;n&#x131; nicel olarak ortaya koymaya yard&#x131;mc&#x131; olur.

Birinci Türev Testi: Problem Çözümü

Bir varl&#x131;k fiyat&#x131;n&#x131;n d&#xFC;&#x15F;&#xFC;k bir noktaya kadar geriledi&#x11F;ini, d&#xFC;&#x15F;&#xFC;k fiyattan al&#x131;m ...

Education

JoVE Core

Calculus

Kalkülüs

Unit

Birim

Applications of Differentiation

Türevin Uygulamaları

KEY TERMS AND CONCEPTS

TEMEL TERİMLER VE KAVRAMLAR

finding turning points with the first derivative

The first derivative test is used to find turning points on a smooth curve. It shows where a function changes from increasing to decreasing, or from decreasing to increasing. In this example, the curve can model an asset price that falls to a low point, rebounds, and then gradually declines again.

The process starts by finding the first derivative of the function. Because the function is a product of a polynomial term and an exponential term, the product rule is needed. After differentiating, the expression is simplified by factoring out the terms that are common to every part of the derivative.

Next, the derivative is set equal to zero. Solving this equation gives the critical points, which are inputs where the slope is zero or where the slope test must still be checked. These critical points split the domain into separate intervals for further analysis.

Test points are then chosen from each interval, and the sign of the derivative is checked. A positive derivative means the function is increasing on that interval. A negative derivative means the function is decreasing. When the sign changes from positive to negative, the curve has a local maximum. When the sign changes from negative to positive, the curve has a local minimum.

Finally, the critical inputs are substituted back into the original function to find the corresponding output values at those turning points. These local extrema are important in valuation analysis because they show where momentum changes from recovery to decline, or from decline to recovery. They help identify possible reversal regions on the curve.

Finding Turning Points with the First Derivative

finding-turning-points-with-the-first-derivative

absolute and local extreme values

Finding Max and Min on Function Graphs

Absolute and local extreme values show the highest and lowest points on a function graph. Absolute maximum and absolute minimum values describe the highest and lowest values across the entire domain. Local maximum and local minimum values describe the highest and lowest values within a smaller part of the graph. Periodic functions such as sine and cosine can have extreme values at many points. Their repeating pattern creates multiple local extrema. In these cases, the derivative becomes zero...

critical numbers and the closed interval method

critical-numbers-and-the-closed-interval-method

Finding Absolute Extrema on a Closed Interval

Absolute extrema on a closed interval are found by checking critical numbers and the endpoints. A function’s maximum and minimum values help describe its overall behavior across its domain. These values are called extrema, and they can be local or absolute. Local extrema are peaks and valleys in a limited region. Absolute extrema are the highest or lowest points on the entire interval. Critical numbers are the domain values where the derivative is zero or does not exist. According to Fermat’s...

rolle’s theorem

Rolle’s Theorem and Zero Slope Points

Rolle’s Theorem explains when a differentiable function must have a flat tangent inside an interval. It applies to a real-valued function on a closed interval, which means the endpoints are included. The function must also be continuous on the whole interval and differentiable on the open interval, where the interior points lie. The theorem uses one more key condition. The function must have the same value at both endpoints. When that happens, Rolle’s Theorem guarantees at least one point...

the mean value theorem

Mean Change and Instantaneous Slope

The Mean Value Theorem links average change to instantaneous slope. It shows that when a function changes smoothly over an interval, the average change across the whole interval must match the change at one specific point inside it. The theorem is easy to see in a motion example. Imagine a vehicle traveling between two points on a road. Its velocity can change during the trip, beginning slowly, speeding up during acceleration, and slowing down near the end. Even when the speed is not...

first derivatives and the shape of a graph

first-derivatives-and-the-shape-of-a-graph

Using First Derivatives to Find Graph Changes

The first derivative shows how a function changes across its domain. In calculus, the derivative is written as f'(x). It tells us whether the graph is rising, falling, or turning at a given point. A function is increasing on an interval when its derivative is positive. That means the slope of the tangent line is positive. A function is decreasing on an interval when its derivative is negative. In that case, the tangent line slopes downward. These sign changes help describe the overall shape...

first derivative test: problem solving

The first derivative test is used to find turning points on a smooth curve. It shows where a function changes from increasing to decreasing, or from decreasing to increasing. In this example, the curve can model an asset price that falls to a low point, rebounds, and then gradually declines again. The process starts by finding the first derivative of the function. Because the function is a product of a polynomial term and an exponential term, the product rule is needed. After differentiating,...

second derivatives and the shape of a graph

second-derivatives-and-the-shape-of-a-graph

Using Second Derivatives to Read Curvature

The second derivative shows how a graph bends. It gives key information about curvature and how that curvature changes over an interval. These ideas help with graph analysis in math and in real-world settings such as road elevation, population growth, and economic trends. A function f(x) is concave upward on an interval when its graph lies above all of its tangent lines. In this case, the second derivative is positive. That means the slope of the tangent line is increasing, and the graph bends...

second derivative test: problem solving

Classifying Critical Points with the Second Derivative

The second derivative test helps classify critical points of a function. Critical points are places where the first derivative is zero or undefined. They are possible locations for local maxima and local minima, but they do not always become one or the other. The second derivative shows concavity, or whether a graph bends up or down. If f''(x) &gt; 0, the function is concave up, and the critical point is a local minimum. If f''(x) &lt; 0, the function is concave down, and the critical point is...

curve sketching and derivatives

Using Derivatives to Read a Graph

Derivatives help students read the graph of a function by showing where the graph rises, falls, and bends. The first derivative tells the slope of the tangent line at each point. The second derivative shows how the curve changes shape over an interval. Points where the first derivative is zero or undefined are critical points. These points are important because they may mark a local maximum, a local minimum, or no extremum at all. A local minimum appears when the first derivative changes from...

indeterminate forms and l’hôpital’s rule

Using Derivatives to Resolve Limit Ambiguity

Indeterminate forms appear when a limit gives an expression that cannot be read directly. Common examples are 0 divided by 0 and infinity divided by infinity. These results do not show the true behavior of the function near the point of interest, so more analysis is needed. L’Hôpital’s Rule is a useful method for handling these ambiguous limits. It applies when two differentiable functions approach 0 or infinity at the same time near the point being studied. Instead of finding the limit of the...

indeterminate products

Limits of Zero Times Infinity

Limits with a zero-times-infinity product are indeterminate. In this type of limit, one factor approaches zero while the other factor grows toward positive or negative infinity. The result is not obvious at first, because the product may approach zero, infinity, or a finite nonzero value. To evaluate these product limits, the expression is first rewritten as a quotient. This form makes it possible to use L'Hôpital's Rule, which compares the derivatives of the numerator and denominator. A...

guidelines for sketching a curve

Using Derivatives to Sketch Function Graphs

Sketching a function graph uses key features of the function to show its overall shape. A function plots as a curve on the coordinate plane, with the input on the horizontal axis and the output on the vertical axis. The first step is to find the domain, which is the set of input values where the function is defined. The domain shows how far the graph can extend left and right. Intercepts are also important reference points. The x-intercept is where the graph crosses the horizontal axis, and...

slant asymptotes

Rational Functions with Slant Asymptotes

Rational functions can follow a slant asymptote when the numerator grows faster than the denominator. In this case, a cubic numerator is divided by a squared denominator. That degree difference creates a linear trend that guides the graph at large input values. The function is only defined where the denominator is not zero. Those excluded x-values split the domain into separate regions and avoid singular points. The graph can still cross the x-axis where the numerator equals zero, so the real...

optimization problems

Pipe Length Around a Corner

Pipe length around a corner is a classic constrained optimization problem. It shows how calculus can find a maximum or minimum value when space is limited by fixed walls and angles. The example used here asks for the longest horizontal pipe that can move around a right-angled turn. One hallway is 3 meters wide and the other is 2 meters wide. The pipe is shown as a straight line that touches the inner corner and reaches the opposite walls of both hallways. The key idea is that the pipe’s...

application of differentiation to business

application-of-differentiation-to-business

Maximizing Bakery Revenue with Calculus

Calculus helps businesses make pricing decisions that can improve revenue. In this example, a bakery uses a cupcake model to find the best price and daily sales volume. The goal is to see how changes in price affect demand and total revenue. The demand function shows the link between price and how many cupcakes are sold each day. In this model, p(x) gives the price per cupcake when x cupcakes are sold. Lower prices lead to higher demand, so the function captures how sales change with price. <br...

newton’s method

Newton’s Method for Finding Roots

Newton’s Method is an iterative way to find the roots of real-valued, differentiable functions. A root is the value of x that makes a function equal to zero. This method is useful when an exact algebraic answer is hard to find. The process starts with an initial guess. Newton’s Method then uses the function value and its derivative, which is the slope of the function at that point, to build a better estimate. The next approximation is found from the recursive formula x n+1 = x n - f(x n) /...

the antiderivative of a function

Finding Original Functions with Antiderivatives

Antiderivatives help reconstruct an original function from its derivative. In calculus, an antiderivative of a function f(x) is a function F(x) whose derivative gives back f(x). This idea works like reversing differentiation to recover the starting form. Antiderivatives are not unique because differentiation removes constant terms. For that reason, the general form includes an arbitrary constant C. That constant represents unknown initial conditions when a function is rebuilt from its...

graphing antiderivatives

Antiderivative Graph Shape and Slope

Antiderivative graphs show how a function accumulates over time. In calculus, an antiderivative tracks that buildup, much like the changing position of a rolling ball as its velocity changes. The graph of the antiderivative reflects the total effect of the original function's values. The sign of the original function helps determine the antiderivative's direction. When the function is positive, the antiderivative rises because the accumulation grows. When the function is negative, the...

application of antiderivatives: linear motion

application-of-antiderivatives-linear-motion

Finding Car Stopping Distance with Integration

Integration connects acceleration, velocity, and displacement in linear motion. It works as the reverse of a derivative, which tells how one quantity changes with another. In physics, this makes it possible to move from a rate of change back to the motion itself. A car provides a clear example. It is moving at a steady 20 meters per second when an obstacle appears 800 meters ahead. To stop in time, the car slows with a constant acceleration. That acceleration tells how the car’s velocity...

key terms and concepts

Use the first derivative test to find critical points, test intervals, and identify local maxima and minima on a smooth curve with an asset price example.

Finding Turning Points with the First Derivative | JoVE K12

The JoVE Core Calculus collection provides a comprehensive visual guide to the entire calculus sequence, seamlessly connecting mathematical theory to real-world applications in physics and economics. Through dynamic animated lessons, the course transitions smoothly from foundational single-variable concepts to advanced multivariable topics. Students will explore everything from standard differentiation and integration to spatial vectors, multi-dimensional derivatives, and complex vector fields. By breaking down abstract coordinate systems, infinite series, and spatial motion, this structured approach builds the robust analytical skills and advanced mastery essential for STEM success.

calculus

Finding Turning Points with the First Derivative

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