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1 year ago

in the gilded age, how did monopolies affect many small businesses? monopolies helped small businesses grow.

1 answer:

7 0

In the Gilded age, monopolies affected the small businesses as the monopolies forced small businesses to shut down. A monopoly arises when a single corporation dominates the market for a given product or service.

Monopolies frequently result in the closure of the smaller businesses. One business can regulate the product prices when it controls a particular market. Due to their size, most the monopolizing businesses can afford to reduce their prices so much that no small business can compete. Because of this, the smaller companies are left with no alternative except to shut down or combine with the monopolizing firm.

To learn more about monopolies, click here

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A bank has written a call option on one stock and a put option on another stock. For the first option the stock price is 50, the

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Answer:

10-Day 99% VaR = 3.61

Explanation:

Data Given:

For First Option:

Stock Price = 50

Strike Price = 51

Volatility = 28% per annum

Time to maturity = 9 months

For Second Option:

Stock Price = 20

Strike Price = 19

Volatility = 25% per annum

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Solution:

First of all we need to refer the DerivaGem Model to dig out the change in price equation for both the options.

So, according to DerivaGem Model, We have following data:

For First Option:

Value = -5.413

Delta Value = -0.589

For Second Option:

Value = -1.014

Delta = -0.284

Change in Price = (Delta value of First Option x Stock Price)Y1 + (Delta value of the second option x Stock Price)Y2

Change in Price = (-0.589 x 50)Y1 + (-0.284 x 20)Y2

So, We will get the Change in Price Linear Equation for both the options.

Change in Price = -29.45Y1 -5.68Y2

Now, we have to calculate the Daily Volatility Percentage.

Formula:

Daily Volatility Percentage = Volatility/ Square root of number of days active in annum

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Volatility for First Option = 28%

Volatility for Second Option = 25%

Daily Volatility Percentage for First Option = 28%/ $\sqrt{252}$

Daily Volatility Percentage for First Option = 0.0176

Similarly,

Daily Volatility Percentage for Second Option = 25%/ $\sqrt{252}$

Daily Volatility Percentage for Second Option = 0.0157

Now, utilizing the above calculated data, we can find the one-day variance of change in price.

1-Day Variance = $(29.45^{2} *0.0176^{2}) + (5.68^{2} * 0.0157^{2}) - (2 * 29.45 * 0.0176 * 5.68 * 0.0157 * 0.4)$

Solving the above equation:

We get:

1-Day Variance = 0.2396

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SD of 1-Day Variance = 0.4895

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Now, in order to find the value of one day 99% VaR from the table, we have all the prerequisites.

So,

Value of One day 99% VaR from table = 2.33

But we need 10-Day 99% VaR.

So, number of days = 10

Hence,

10-Day 99% VaR = $0.4895 * 2.33 * \sqrt{10}$

10-Day 99% VaR = 3.61

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