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Closely related to the problem of financial analysis

2021-09-01 来源: 51Due教员组 类别: Essay范文

各位留学生大家好!今天100due教员组给大家分享的是一篇会计essay代写范文,主要内容是讲:本财务分析基于随附excel文件中计算的20个密切相关的问题,本节包括对结果的详细解释和分析。

This financial analysis is bases on twenty closely related questions as calculated in the accompanying excel file and this section includes detailed explanation and analysis of the results.

Three key variables are calculated based on the last two digits of my student number which is 49, and these three variables include number of hotel rooms 249, number of seats in the restaurant 324, and number of seats in the banquet hall 498. The first key information is the purchase price of this hotel, which is calculated use the simple and straightforward formula: Number of roomsⅹ€ 45,000 + Number of seats in restaurantⅹ€ 14,000 + Number of seats in banquet roomⅹ€ 3,700. Using the variables indicated, the purchase price for the hotel adds up to € 17,583,600. This purchase price is a critical factor in calculating the payback period and internal rate of return of the purchase of the hotel as an investment.

Apart from the rooms, the restaurant also has the capacity to hold various functions thanks to the large banquet hall it has. The desirable profit margin on banquet dinners is 17% and in order to determine the price charged on this function, a number of factors need to be taken into consideration. Profit margin on this function is calculated as revenue divided by revenue less by cost of sales as a percentage figure. As the number of attendees 249 is given, the food and beverage costs are variable costs charged on a per capita basis at € 23.50 and € 19.50 respectively. Other direct costs include the wages for additional part-time waitresses add up to € 720. Estimated fixed cost is at € 3,600 per function. Therefore, to achieve a profit margin of 17%, the total cost, € 15,027, is going to comprise 83% of the revenue, so the price for this banquet is € 18,105. However, the lowest possible price for the banquet means the breakeven price, at which the restaurant makes no profit or loss. So when the price for the banquet equals to the costs of banquet, at € 15,027, restaurant will achieve break-even for this banquet.

Pricing is ultimately part of the restaurant’s strategy and it should reflect the restaurant’s purpose, self-perception and its position in the market. Perceiving itself to be ‘up-market’, the restaurant might have to charge high prices to project quality and exclusivity. To make a profit, revenue has to exceed all costs. For guests attend this function, I suggest a 75% off room pricing strategy for those who choose to stay with us for one night, which means rack rate for single room is € 24 and rack rate for double one € 33. The expected hotel occupancy is estimated to be 45% and this forecast projects revenue at € 13,664.50. For the rest 55% room capacity, the suggested rack rates would increase the profit margin approximately from 21% to 40%.

Moving on to the analysis of general operational performance, an important factor is the average daily rate. This rate is calculated as actual room occupied divided by room revenue. At an occupancy rate 77%, the number of actual room occupied is 192, the number of single and double rooms are 44 and 148 respectively. According to these factors, the ADR for last year is € 121.95. But assuming all rooms are of the same size and a double room is charged 22% more compared to a single room, the new room rate for single ones is € 54.93, for double one is € 67.02.

Break-even rooms’ revenue and break-even occupancy are critical figures in order to determine the potential profit and loss of the operation of hotel. It is assume that all costs of hotel rooms are fixed costs, including direct expenses of operating the rooms are € 2,200,000, administration and general expenses € 167,000, sales and marketing expenses € 434,000, POM € 369,000, interest € 476,000, insurance € 49,000, other expenses € 240,000. All these direct expense and overhead costs determine that the break-even revenue equals the sum of costs, at € 10,781. Using the ADR in previous analysis, to achieve the targeted break-even revenue, 88 out of the total 249 rooms must be occupied. This means in order to achieve break-even, the occupancy percentage need to reach 35.5%.

Another important factor in forecasting the performance of the restaurant is the analysis of guests. Breakfast service is included in the double room price, so if we need to know the number of guests on an average day taking breakfast, we need to use the average occupancy rate to determine the average number of guests. Therefore, given that 92% of guests have breakfast, the expected figure would be 272. But if all rooms are occupied, there is no need to take the average occupancy rate into account and this means that the number of breakfast guests will increase to 383.

Using the seat turnover record for the past twelve months, we can forecast the number of restaurant guests for the current month applying the simple moving average method. This technique requires two variables, which are seat turnover per day and the number of seats in the restaurant. Total number of restaurant guests can be calculated as average turnover times the number of available seats, which gives a total of 841 restaurant guests. Using the same technique, I replace the seat turnover per day for 12 month ago with the turnover of current month, and calculate the new projection for next month, that is 845 restaurant guests. Other useful techniques are linear weights method and exponential weights method. Using excel function, it is straightforward to calculate the forecast results as shown in the table below. Exponential weights method assigns exponentially decreasing weights over time and thus predicts more reliable forecast compared to linear weights that assign similar weight to each period. Regression analysis is another frequently applied forecast method and in this case, it can be used to project the number of breakfast guests for the current month. A regression analysis graph using the hotel occupancy rate for the past twelve months is very straightforward from the linear regression line, that in the current month projected number of guest is 337. The basic assumption in the calculation of number of guests using hotel occupancy rate is that every guest will have breakfast, single and double rooms all included.

 

Number of restaurant guests

Number of breakfast guests

SMA (Current month)

841

-

SMA (Next month)

845

-

Linear Weights

927

-

Exponential Weights

814

-

Regression Analysis

-

337

Time series analysis is based on historic data and cannot always be relied on to give a true indication of future results. This is the inherent shortcoming of this forecasting technique. Simple moving average method is a straightforward way to calculate the forecast for performance, each new variable added will change the forecast result, as the differences shown between the figures for current month and next month. An important factor to consider is the different basis of calculation for these two types of guests. The number of restaurant guests is significantly larger than the breakfast guests, because of the restaurant guests tend to come not only for breakfast, but also lunch or dinner, based primarily on the seat turnover rate record for the past months. However, the number of breakfast guests is based on the hotel occupancy rate.

Variance is an important concept in budget control. To calculate the total rooms’ revenue variance, I need to compare the difference between forecasted room’s revenue and actual rooms’ revenue. This calculation yields a favorable rooms’ revenue variance at € 47. This means that although room rate is lower than ADR forecasted, larger occupancy rate contribute to more revenue than projected. Using the same variance technique, actual and forecasted number of rooms occupied can be calculated. Therefore, the price variance is a negative € 4 and a positive volume variance € 7. A negative price means that the budget controller needs to take a closer look at the current price setting and make it more compliant with the actual result, while a positive volume variance requires the controller to apply a more reliable forecast model on the occupancy rate in future analysis.

As an investment target, it is critical to analyze the payback period, manage the long-term liabilities, be aware of the cost of capital, and gain an understanding of the internal rate of return. These key financial figures are key factors when investor is making a decision on an investment. Based on the annual cash flow provided, when calculate the payback period, I find that during year 8 the last negative net cash flow will be generated, so the resulted payback period is 8.04 years. Without the real-world benchmark, it is difficult to determine whether this period is above average or below. But within this scenario, a large business with an initial investment of seventeen million, that payback within ten years is reasonable.

Mortgage is the main source of capital for the hotel, given that 60% of hotel purchase price comes from long-term bank loan. Total payment includes capital € 10,550,160 and interest € 5,897,539.44. Detail breakdown of annual payment is shown in the excel spreadsheet. Another important factor is weighted average cost of capital is the discount rate used in calculation of net present value (NPV) and other valuations models such as free cash flow valuation model. It is the hurdle rate in the capital budgeting decisions. The weighted average cost of capital for the hotel is approximately 3.65%, compared to the return on investment 10%, therefore, this investment is reasonable. Also, the internal rate of return is promising. As the case background suggested, the risk of the hotel is 20% higher than the average of the market, while other hotels currently return 5.2%. This investment is considered as high risk and high return. It is advisable to invest in this hotel to take advantage of the possibly high return it would yield in the medium term.


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