Fundraising

Question 1

Ways to find the optimal mix of debt and equity?

Answer 1

1. Operating Income Approach
2. Cost of Capital Approach
3. Adjusted Present Value Approach
4. Comparative Analysis

Question 2

What is a forecast in the context of business?

Answer 2

A prediction about a condition or situation at some future time.

Question 3

Why are forecasts important in business decisions?

Answer 3

They provide essential information for making informed financial and strategic decisions by predicting future events.

Question 4

What does it mean for a forecast to be internally consistent?

Answer 4

The forecast logically flows from the stated assumptions without contradictions.

Question 5

What constitutes relevant and significant assumptions in a financial forecast?

Answer 5

Assumptions are relevant if they are likely to occur and directly impact the financial variable being forecasted. They are significant if they are likely to occur and their impact on the financial variable is substantial. All assumptions should be clearly identified.

Question 6

What are the two key attributes of a good financial forecast?

Answer 6

Inclusion of all relevant and significant assumptions, and internal consistency.

Question 7

Explain the role of sensitivity analysis in financial forecasting.

Answer 7

Sensitivity analysis involves adjusting each assumption to examine how changes impact the forecast. This process helps assess the robustness of the forecast and understand potential variations under different scenarios.

Question 8

What is a judgmental forecast?

Answer 8

A forecast based on experience and judgment rather than on mathematical or statistical models.

Question 9

Describe a time series forecast and its underlying assumption.

Answer 9

A time series forecast assumes that the underlying forces affecting a time series (like economic or behavioral factors) are stable over time. It uses historical patterns to predict future movements, based on the belief that past trends will continue.

Question 10

What characterizes a causal forecast?

Answer 10

It is used when the causal relationships are well-understood, stable over time, and the causal variables are easy to predict.

Question 11

How does a judgmental forecast differ from quantitative forecasting methods?

Answer 11

A judgmental forecast relies on subjective assessments, expertise, and intuition, whereas quantitative methods like time series and causal forecasts use historical data and mathematical models to predict future outcomes.

Question 12

How does internal consistency enhance the reliability of a financial forecast?

Answer 12

By ensuring that all parts of the forecast are logically connected and derived from the same set of assumptions, internal consistency helps maintain the accuracy and credibility of the predictions.

Question 13

Why must assumptions in a forecast be both relevant and significant?

Answer 13

To ensure that the forecast is based on factors that are likely to occur and have a meaningful impact on the financial variables being predicted.

Question 14

Provide an example of how an assumption might be tested for relevance and significance in a forecast.

Answer 14

Suppose a company forecasts sales growth based on an assumption that a new marketing campaign will increase sales by 10%. This assumption is relevant because it directly impacts sales and significant because a 10% change could substantially affect revenue projections.

Question 15

What is “what-if” analysis in the context of forecasting?

Answer 15

A method of varying assumptions to explore different scenarios and assess their impact on the forecasted outcomes.

Question 16

Why is it important to clearly identify assumptions in a forecast?

Answer 16

Clear identification of assumptions allows stakeholders to understand the basis of the forecast, evaluate its validity, and assess the potential risks associated with those assumptions.

Question 17

When would you use a causal forecast over other types of forecasts?

Answer 17

When the relationships between variables are well-understood, stable over time, and the causal variables can be easily predicted.

Question 18

Explain how sensitivity analysis and what-if scenarios are related.

Answer 18

Sensitivity analysis is a type of what-if analysis where each assumption is systematically varied to observe its effect on the forecast. Both approaches help in understanding how changes in assumptions influence outcomes and in identifying critical variables.

Question 19

What type of forecast would you use if you have limited historical data and rely on expert opinions?

Answer 19

A judgmental forecast.

Question 20

Describe a scenario where a time series forecast might not be appropriate.

Answer 20

If the underlying factors affecting the time series are changing rapidly or unpredictably, historical patterns may no longer be indicative of future trends, making a time series forecast unreliable.

Question 21

What distinguishes a causal forecast from a time series forecast?

Answer 21

A causal forecast is based on understanding and modeling the cause-and-effect relationships between variables, whereas a time series forecast relies on historical data patterns without necessarily understanding the underlying causes.