Please use Excel to analyze the statement of cash flows for the table below.
1) What is the correlation between net income and operating cash flow?
2) Explain the trends of cash flow from the table below.
3) What is the free cash flow from the table below?
| Cash Flow | ||||
| All numbers in thousands | ||||
| Period Ending | 1/31/2018 | 1/31/2017 | 1/31/2016 | 1/31/2015 |
| Net Income | 9,862,000 | 13,643,000 | 14,694,000 | 16,363,000 |
| Operating Activities, Cash Flows Provided By or Used In | ||||
| Depreciation | 10,529,000 | 10,080,000 | 9,454,000 | 9,173,000 |
| Adjustments To Net Income | 4,703,000 | 1,617,000 | 1,124,000 | 733,000 |
| Changes In Accounts Receivables | -1,074,000 | -402,000 | -19,000 | -569,000 |
| Changes In Liabilities | 4,086,000 | 3,942,000 | 2,008,000 | 2,678,000 |
| Changes In Inventories | -140,000 | 1,021,000 | -703,000 | -1,229,000 |
| Changes In Other Operating Activities | 928,000 | 1,280,000 | 1,466,000 | 1,249,000 |
| Total Cash Flow From Operating Activities | 28,337,000 | 31,673,000 | 27,552,000 | 28,564,000 |
| Investing Activities, Cash Flows Provided By or Used In | ||||
| Capital Expenditures | -10,051,000 | -10,619,000 | -11,477,000 | -12,174,000 |
| Investments | - | -1,901,000 | -1,901,000 | -1,901,000 |
| Other Cash flows from Investing Activities | -58,000 | -122,000 | -79,000 | 479,000 |
| Total Cash Flows From Investing Activities | -9,060,000 | -13,987,000 | -10,675,000 | -11,125,000 |
| Financing Activities, Cash Flows Provided By or Used In | ||||
| Dividends Paid | -6,124,000 | -6,216,000 | -6,294,000 | -6,185,000 |
| Sale Purchase of Stock | - | - | - | - |
| Net Borrowings | -1,437,000 | -3,591,000 | -3,158,000 | -5,018,000 |
| Other Cash Flows from Financing Activities | -4,018,000 | -967,000 | -2,721,000 | -2,853,000 |
| Total Cash Flows From Financing Activities | -19,875,000 | -19,072,000 | -16,285,000 | -15,071,000 |
| Effect Of Exchange Rate Changes | 487,000 | -452,000 | -1,022,000 | -514,000 |
| Change In Cash and Cash Equivalents | -111,000 | -1,838,000 | -430,000 | 1,854,000 |
In: Accounting
Three years ago, Karen Suez and her brother-in-law Reece Jones opened Gigasales Department Store. For the first 2 years, business was good, but the following condensed income statement results for 2017 were disappointing.
GIGASALES DEPARTMENT STORE
Income Statement
For the Year Ended December 31, 2017
Net sales
$518,000
Cost of goods sold
414,400
Gross profit
103,600
Operating expenses
Selling expenses
$74,000
Administrative expenses
14,800
88,800
Net income
$14,800
Karen believes the problem lies in the relatively low gross profit rate of 20%. Reece believes the problem is that operating expenses are too high. Karen thinks the gross profit rate can be improved by making two changes. (1) Increase average selling prices by 15%; this increase is expected to lower sales volume so that total sales dollars will increase only 4%. (2) Buy merchandise in larger quantities and take all purchase discounts. These changes to purchasing practices are expected to increase the gross profit rate from its current rate of 20% to a new rate of 25%. Karen does not anticipate that these changes will have any effect on operating expenses.
Reece thinks expenses can be cut by making these two changes. (1) Cut 2018 sales salaries of $44,400 in half and give sales personnel a commission of 2% of net sales. (2) Reduce store deliveries to one day per week rather than twice a week; this change will reduce 2018 delivery expenses of $29,600 by 40%. Reece feels that these changes will not have any effect on net sales.
Karen and Reece come to you for help in deciding the best way to improve net income.
Answer the following.
In: Accounting
Which of the following indexes is reflecting more clearly price level and inflation trend:
A) The Core Inflation Rate, or Personal Consumption Expenditure (PCE) price index excluding food & energy
B) GDP deflator which is average of the current prices of all goods & services in GDP expressed as percentage of base year prices
C) Consumer Price Index (CPI) - a measure of the average of prices paid by urban consumers for a fixed market basket of consumer goods and services
D) Real income, which is the purchasing power of nominal income measured by quantity of goods and services nominal income will buy
The changes in Aggregate Supply (AS shifters) resulted from:
A) Changes in consumer spending, business investment, government expenditures and net export
B) Changes in input prices, productivity, nominal wages and legal-institutional environment
C) Changes in prices of goods and services produced
D) Business failure, temporary shotdowns and changes in output rate
. The effects of a negative demand shock are:
A) The Aggregate Demand curve shifts leftward with a reduction in price level and in the output that is below the potential GDP and is called recessionary gap
B) Aggregate demand curve shifts rightward with higher prices and bigger output above the potential GDP called inflationary gap
C) Decrease in Aggregate Supply, higher prices and and lower output which generates stagflation (negative supply shock)
D) Increase in Aggregate Supply with lower prices and bigger output, called positive supply shock
To restore the macroeconomic equilibrium with full-employment the supply side theories emphasized:
A) The control of money and interest rates as mechanisms for shifting Aggregate demand
B) The role of government spending and taxes
C) The importance to control both Aggregate Demand and Aggregate Supply by shifting both curves
D) The importance to shift Aggregate Supply by changing costs of resources, government taxes and regulation
In: Economics
Terlingua Transportation Co. (TTC) is a regional shipper. It is most cost efficient for the company’s diesel fuel trucks to refuel at retail outlets along the shipping routes. However, retail prices tend to be volatile. Hence, managers at TTC have decided to hedge future retail purchases of fuel by means of New York Harbor ULSD (ultra low sulphur diesel) futures contracts. Each contract has 42,000 gallons as the underlying asset. You are a financial analyst for TTC. Today is April. Your immediate task is to hedge the price risk of diesel future purchases in three months (i.e., in July). You expect that TTC trucks will need to buy a total of 700,000 gallons of diesel fuel in July. You plan to apply dynamic hedging. Based on calculations for a 3-month hedge, you determine that your company needs to take a long position in 20 of the August futures contracts today. Time passes. Today now is May. Forecast for quantity of the July purchase of diesel fuel is unchanged. You plan to continue hedging with August contracts. You have the following statistical data. All spot prices are retail prices for diesel fuel. All futures prices are for the New York Harbor ULSD futures. Standard deviations are in cents per gallon. standard deviation of 1-month changes in spot prices: 14 standard deviation of 2-month changes in spot prices: 24 standard deviation of 3-month changes in spot prices: 34 standard deviation of 1-month changes in futures prices: 15 standard deviation of 2-month changes in futures prices: 27 standard deviation of 3-month changes in futures prices: 36 1-month correlation between spot and futures prices: 1.10 2-month correlation between spot and futures prices: 1.17 3-month correlation between spot and futures prices: 1.23 In your calculations for optimal number of futures contracts, you optimize using the formulas for cross hedging. Calculate the change in optimal number of futures contracts that your company should be long. Report the change as an integer value. If you decrease the number of contracts, report a negative number. (When you calculate the new value for N*, round to the nearest integer.)
In: Finance
tudies have shown that people who suffer sudden cardiac arrest (SCA) have a better chance of survival if a defibrillator is administered very soon after cardiac arrest. How is survival rate related to the time between when cardiac arrest occurs and when the defibrillator shock is delivered? This question is addressed in the paper “Improving Survival from Sudden Cardiac Arrest: The Role of Home Defibrillators” (by J.K. Stross, University of Michigan, February 2002). The accompanying data give y = survival rate (percent) and x = mean call-to-shock time (minutes) for a cardiac rehabilitative center (where cardiac arrests occurred while victims were hospitalized and so the call-to-shock time tended to be short) and for four communities of different sizes.
|
Mean call-to-shock time,x |
2 |
6 |
7 |
9 |
12 |
|
Survival Rate, y |
90 |
45 |
30 |
5 |
2 |
Do the following by hand and on Minitab.
Construct a scatter plot.
Calculate the Pearson correlation coefficient.
Determine equation of least squares line that can be used for predicting a value of y based on a value of x.
Compute SSE = ( y yˆ)2 for the least squares line.
Why do we call the least squares line the “best fitting line”?
tudies have shown that people who suffer sudden cardiac arrest (SCA) have a better chance of survival if a defibrillator is administered very soon after cardiac arrest. How is survival rate related to the time between when cardiac arrest occurs and when the defibrillator shock is delivered? This question is addressed in the paper “Improving Survival from Sudden Cardiac Arrest: The Role of Home Defibrillators” (by J.K. Stross, University of Michigan, February 2002). The accompanying data give y = survival rate (percent) and x = mean call-to-shock time (minutes) for a cardiac rehabilitative center (where cardiac arrests occurred while victims were hospitalized and so the call-to-shock time tended to be short) and for four communities of different sizes.
|
Mean call-to-shock time,x |
2 |
6 |
7 |
9 |
12 |
|
Survival Rate, y |
90 |
45 |
30 |
5 |
2 |
Do the following by hand and on Minitab.
Construct a scatter plot.
Calculate the Pearson correlation coefficient.
Determine equation of least squares line that can be used for predicting a value of y based on a value of x.
Compute SSE = ( y yˆ)2 for the least squares line.
Why do we call the least squares line the “best fitting line”?
tudies have shown that people who suffer sudden cardiac arrest (SCA) have a better chance of survival if a defibrillator is administered very soon after cardiac arrest. How is survival rate related to the time between when cardiac arrest occurs and when the defibrillator shock is delivered? This question is addressed in the paper “Improving Survival from Sudden Cardiac Arrest: The Role of Home Defibrillators” (by J.K. Stross, University of Michigan, February 2002). The accompanying data give y = survival rate (percent) and x = mean call-to-shock time (minutes) for a cardiac rehabilitative center (where cardiac arrests occurred while victims were hospitalized and so the call-to-shock time tended to be short) and for four communities of different sizes.
|
Mean call-to-shock time,x |
2 |
6 |
7 |
9 |
12 |
|
Survival Rate, y |
90 |
45 |
30 |
5 |
2 |
Do the following by hand and on Minitab.
Construct a scatter plot.
Calculate the Pearson correlation coefficient.
Determine equation of least squares line that can be used for predicting a value of y based on a value of x.
Compute SSE = ( y yˆ)2 for the least squares line.
Why do we call the least squares line the “best fitting line”?
tudies have shown that people who suffer sudden cardiac arrest (SCA) have a better chance of survival if a defibrillator is administered very soon after cardiac arrest. How is survival rate related to the time between when cardiac arrest occurs and when the defibrillator shock is delivered? This question is addressed in the paper “Improving Survival from Sudden Cardiac Arrest: The Role of Home Defibrillators” (by J.K. Stross, University of Michigan, February 2002). The accompanying data give y = survival rate (percent) and x = mean call-to-shock time (minutes) for a cardiac rehabilitative center (where cardiac arrests occurred while victims were hospitalized and so the call-to-shock time tended to be short) and for four communities of different sizes.
|
Mean call-to-shock time,x |
2 |
6 |
7 |
9 |
12 |
|
Survival Rate, y |
90 |
45 |
30 |
5 |
2 |
Do the following by hand and on Minitab.
Construct a scatter plot.
Calculate the Pearson correlation coefficient.
Determine equation of least squares line that can be used for predicting a value of y based on a value of x.
Compute SSE = ( y yˆ)2 for the least squares line.
Why do we call the least squares line the “best fitting line”?
Calculate r2 using the following formula: r 2
( y y)2 ( y yˆ)2
Interpret the r2 value.
Using your equation in part c, draw the least squares line on the scatterplot you constructed in part a.
Use your prediction equation to predict SCA survival rate for a community with a mean call-to-shock time of 5 min.
In: Statistics and Probability
The nurse prepares to discuss the changes in how the JNC 7 defines hypertension. What ranges and descriptions should the nurse include?
In: Nursing
In: Economics
4. Compare physiological, pathophysiological and clinical changes in patients with Parkinson’s and Alzheimer’s Disease during three years of follow-up.
In: Biology
Mention three different aspects that reflect important changes for individuals who fill out their tax report in Puerto Rico.
In: Economics
In: Economics