I. Problem definition:

Ms. Salinas Savings & Loan has bucked the trend of financial and liquidity problems that has plagued the industry since 1985. Ms. Salinas believes it is necessary to have a long range strategic plan for her firm including a 1 year forecast and preferably even a 5 year forecast of deposits.

Objective:1.To determine what would be a successful forecasting tool for the strategic plan of Ms. Salinas.2. To compare different forecasting tool with its Pros and Cons. | II. Review of Background Information: |

In this case study, we should also focus the discussion on the 1980s concurrent crisis in the savings and loan (S&L) industry even though it was stated that Salinas has bucked the trend of financial problems during this period. A review of the S&L debacle (as it is commonly known today) provides several important lessons for financial-institution regulators. Moreover, legislation enacted in response to the crisis substantially reformed both bank and thrift regulation and dramatically altered the FDIC’s operations.

The causes of this debacle and the events surrounding its resolution have been documented and analysed in great detail by academics, governmental bodies, former bank and thrift regulators, and journalists. Although the FDIC had a role in monitoring events as they unfolded and, indeed, played an important part in the eventual cleanup, until 1989 S&Ls were regulated by the Federal Home Loan Bank Board (FHLBB, or Bank Board) and insured by the Federal Savings and Loan Insurance Corporation (FSLIC) within a legislative and historical framework separate from the one that surrounded commercial banks.
.
The causes can be named as follows by the FDIC government: 1. Tax Reform Act of 1986 2. The deregulation of S&Ls in 1980 3. End of inflation 4. Forbearance III. Analysis of Facts and Data: The facts stated by the problem are the data of the past deposit data from 1959-2002 and peruses the Kansas GSP over the same 44 years which we could use for the computation of the desired forecasting strategy. The case also stated that recessions had been a factor in the slow deposits throughout the history of the company namely the year 1960,1983,1988,1991 and 2001. Despite the liquidity problems experienced in 1980’s, it only took a little of the growth of the company by slowly increasing its deposit during this time frame. The data also showed an increasing trend both for the GSP of Kansas and the Deposit. a. Naive Approach: Answer: Year | Deposit | GSP | 2003 | 108.9 million | 5.3 billion |

b. Moving Average: For Ma =3

Year | Deposit | GSP | 2003 | 81.3 million | 4.76 billion |

For Ma=5

Year | Deposit | GSP | 2003 | 73.98 million | 4.68 billion |

c. Exponential smoothing:

A=.3

Year | Deposit | 2003 | 64.35893 million |

A=.5

Year | Deposit | 2003 | 72.35413 million |

A=.7 Year | Deposit | 2003 | 76.11639 million |

d. Linear Trend analysis

Year | Deposit | 2003 | 54.7 million | 2004 | 56.336 million | 2005 | 57.97 million | 2006 | 59.068 million | 2007 | 61.24 million |

e. f. e. Linear regression:

DEPOSIT = -17.64 + 13.596 (gsp)

Year | Deposit | GSP | 2003 | 53.05 | 5.2 | 2004 | 59.86 | 5.7 | 2005 | 68.01 | 6.3 | 2006 | 77.532 | 7.0 | 2007 | 81.72 | 7.3 |

IV. Alternative courses of action to be taken: Naive Approach:

Advantage: 1. Easy to do, and not time consuming.

Disadvantage: 1. Too simple, not all factors are considered. 2. Only one value can be forecasted.

Moving Average:

Advantage: 1. Helps to clear out noise from the data and helps the observer make a clearer idea of any changes that are actually occurring in the long term. 2. Discounts the value of the oldest data.

Disadvantage: 1. Can only forecast one value, limited only to the next data set. 2. Too large or too small value can greatly affect the result and also then sometimes significant long term changes in the data could be masked.

Exponential Smoothing:
Advantage:
1. Easy to implement, more efficient to compute. 2. The effect of the unusual data fades uniformly.
Disadvantage:
1. Can only forecast one value, limited only to the next data set. 2. Not advisable to use for systematic trend data.
Linear Trend Equation:
Advantage:
1. Uses all of the data or variables that can give significant result for the forecast. 2. Useful for period forecasting.
Disadvantage:
1. Use of multiple variables.
Regression Analysis:
Advantage:
1. Looks at linear relationships.
Disadvantage:
1. Sensitive to Outliers 2. Data must be dependent.