Question # 1:<\/p>\n
The Gallito Restaurant is located on Torty Island, a resort company near Fort Myers, Florida. The restaurant, which is owned and operated by Kelly Smith, just completed its third year of operations. During this time, Kelly sought to establish a reputation for the restaurant as high-quality dining establishment that specializes in fresh seafood. The effort made by Kelly and her staff proved successful, and her restaurant is currently one of the best and fast growing restaurants on the island. Kelly conclude that, to plan better for the growth of the restaurant in the future, she needs to develop a system that will enable her to forecast food and beverage sales for the coming month in advance. Kelly compiled the following data on total food and beverage sales for the last ear of operation.<\/p>\n
Perform an analysis of the sales data of the Gallito Restaurant. And recommend following;<\/p>\n
A graph of time series. [5 marks]<\/p>\n
Forecast sales for January of next year using<\/p>\n
Four months moving average [10 marks]<\/p>\n
Month Sales 4-month Moving Average Forecast <\/p>\n
January 263 \u00a0<\/p>\n
February 238 \u00a0<\/p>\n
March 247 \u00a0<\/p>\n
April 193 \u00a0<\/p>\n
May 196 284.25<\/p>\n
June 149 255.75<\/p>\n
July 157 235.5<\/p>\n
August 161 214<\/p>\n
September 122 196.25<\/p>\n
October 130 179.75<\/p>\n
November 167 184.25<\/p>\n
December 230 202.5<\/p>\n
January ? 162.25<\/p>\n
Thus the predicted sell for January next year is $162.25<\/p>\n
Three months weight moving average, using weight of 0.5 for the most recent period, 0.3 for the second most recent period and 0.2 for the third most recent period. [10 marks]<\/p>\n
Month Sales 3-month moving Average Forecast<\/p>\n
January 263 February 238 March 247 April 193 May 196 June 149 July 157 August 161 September 122 October 130 26<\/p>\n
November 167 50.1<\/p>\n
December 230 115<\/p>\n
January ? 191.1<\/p>\n
Use Alpha of 0.3 and use Exponential smoothing method for forecast. [10 marks] <\/p>\n
Exponential smoothing method<\/p>\n
New Forecast = a.. last actual demand – (1- a) (last forecast)<\/p>\n
Ft+1= aDt + (1- a)Ft<\/p>\n
Exponential smoothing method<\/p>\n
Alpha= 0.3<\/p>\n
Month Sales Forecast January 263 200 February 238 218.9 March 247 224.63 April 193 231.34 May 196 219.84 June 149 212.69 July 157 193.58 August 161 182.61 September 122 176.13 October 130 159.89 November 167 150.92 December 230 155.74 January ? 178.02 Among them (i.e., in in part b) which method you will recommend, give your justification and support work. [10 marks]<\/p>\n
We compare forecasted values with actual values to see how well one model works or to compare models. <\/p>\n
I would use the last one which is exponential smoothing because if gives a very detailed forecast as indicated in the table above and the graph below.<\/p>\n
d) Briefly describe what are the advantages and disadvantages of these methods. [5 marks]<\/p>\n
Advantage and disadvantage of Moving Average <\/p>\n
The SMA is the most straightforward calculation, the average price over a chosen time period. The main advantage of the SMA is that it offers a smoothed line, less prone to whipsawing up and down in response to slight, temporary price swings back and forth. Therefore, it provides a more stable level indicating support or resistance. <\/p>\n
Disadvantage <\/p>\n
The SMA’s weakness is that it is slower to respond to rapid price changes that often occur at market reversal points. The SMA is often favored by traders or analysts operating on longer time frames, such as daily or weekly charts.<\/p>\n
Advantage and disadvantage of Exponential Moving Average <\/p>\n
The advantage of the HYPERLINK “http:\/\/www.investopedia.com\/terms\/e\/ema.asp” EMA is that by being weighted to the most recent price changes, it responds more quickly to price changes than the SMA does. This is particularly helpful to traders attempting to trade intraday swing highs and lows, since the EMA signals trend change more rapidly than the SMA does.<\/p>\n
Disadvantage <\/p>\n
The concurrent disadvantage of the greater sensitivity of the EMA is that it is more vulnerable to false signals and getting whipsawed back and forth. The EMA is commonly used by intraday traders who are trading on shorter time frame charts, such as the 15-minute or hourly charts.<\/p>\n
Advantage and disadvantage of Weighted Moving Average <\/p>\n
A trader using a WMA is less likely to pick a trend change early but is also less likely to mistake a minor correction for a trend change. The advantage of using WMAs is that they pick up trends more quickly than simple moving averages. Some traders prefer to use WMAs for shorter time periods to capture changes quicker. <\/p>\n
Disadvantage <\/p>\n
The disadvantage of WMAs is that more false signals are likely to be generated than with simple moving averages. Some investors prefer simple moving averages over long time periods to identify long-term trend changes.<\/p>\n
Question # 2:<\/p>\n
In January, a car dealer predicted February demand for 142 Ford Mustang. Actual February demand 153 autos. <\/p>\n
(a). Using a smoothing constant chosen by management of Alpha = 0.2, how can you forecast Marchdemand? [6 marks]<\/p>\n
Ft+1= aDt + (1- a)Ft t = 1F1\u00a0= 142t = 2Ft\u00a0= \u03b1Dt – 1\u00a0+ (1 – \u03b1)Ft – 1F2\u00a0= \u03b1D2 – 1\u00a0+ (1 – \u03b1)F2 – 1F2\u00a0= 0.2(D1) + (1 – 0.2)F1F2\u00a0= 0.2(D1) + (0.8)F1F2\u00a0= 0.2(153) + (0.8)142F2\u00a0= 30.4 + 113.6F2\u00a0= 144 <\/p>\n
Or as below <\/p>\n
Time Demand Exponential Smoothing Forecast Na\u00efve Approach Alpha 0.2<\/p>\n
January February 153 142 March ? 144 142 b) If you use Na\u00efve Approach, what would be forecast of March demand? [1 mark]<\/p>\n
The demand for march will be 142<\/p>\n
c). Which one, (a) or (b), gives a better forecast and why? [3 marks].<\/p>\n
The first which is the exponential is the best method to determine the forecast for March as compared to na\u00efve. The na\u00efve one is far away from the real value for March. <\/p>\n","protected":false},"excerpt":{"rendered":"
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