Introduction To Price Analysis And Forecasting

Question 1

What is meant by Forecasting?

Answer 1

Forecasting is a prediction about future. In economics and business, forecasting is the estimates of future events typically produced for the prices and quantities.

Question 2

What is Price Analysis?

Answer 2

Price analysis refers to the study of demand-supply and price relationships.

Question 3

What is meant by Outlook?

Answer 3

Outlook is a combination of situation description and price analysis to produce forecasts for agricultural decision makers.

Question 4

How is Forecasting Classified?

Answer 4

Forecasting procedures are classified as to whether they are quantitative (numerical) or qualitative (judgemental).

Question 5

What is Good Forecasting?

Answer 5

Good forecasting is a combination of both quantitative and qualitative, as common sense and judgement should be used when analysing or manipulating data.

Question 6

What is Assumption Of Continuity?

Answer 6

It can be assumed that some aspects of the past pattern will continue into the future .

Question 7

What do Explanatory (or Structural) models assume?

Answer 7

Explanatory (or structural) models assume that the variable to be forecasted (i.e. the dependent variable) exhibits an explanatory relationship with one or more of the independent variables.

Question 8

What process of developing a model is involved?

Answer 8

The process of developing a model usually involves

regression analysis. The simplest and most common procedure is the Ordinary Least Squares (OLS).

Question 9

Name some other models?

Answer 9

Time series models (also known as associational models).

The prediction they make is based on the past behaviour of the variable itself with the aim of discovering patterns in the historical data and extrapolating into the future.

Question 10

What are the Basic Steps In Forecasting?

Answer 10

Problem definition
Gathering information Exploratory analysis
Choosing and fitting models Validating the model
Verifying the models performance

Question 11

What is a simple extrapolation of data series called?

Answer 11

A simple extrapolation of time series data is called projection (more sophisticated analyses can examine the data for seasonal movements, cycles or trends).

Question 12

What do Time Series Models Forecast?

Answer 12

Time series models forecast future prices or quantities on the basis of past movements in the given series alone.

Question 13

What are the components of Time Series Data?

Answer 13

Time series forecasting assumes that within each data set there is a systematic pattern that can be identified and a residual variation due to random irregular movements or noise.
The irregular component is the least predictable (occur due to one off events like disease outbreaks).

Question 14

What are the systematic components of Time Series Data?

Answer 14

The systematic components are trends, cycles and seasonality and Noise. The variability in a time series is a
product of all four elements

Question 15

What are the 4 Cycles of Time Series Data?

Answer 15

Trends (T) - underlying long term movement in a time series. Eg: demand for wool decline over time.
Cycles (C) - regular oscillations around the trend at intervals longer than a year. Eg: Markets tend to exhibit cyclical behaviour.
Seasonality (S) - regular movements occurring at the same time each year. Eg: blueberries are expensive prior to Christmas.
Noise (I) - erratic or random variations.

Question 16

What is a Trend?

Answer 16

A trend is a long-term relatively smooth pattern or direction that the series exhibits.
Majority of time series are not stationary (and not completely random) but exhibit an underlying
trend. Trend is not always linear and may take other forms but theoretical basis is important.

Question 17

What is the Coefficient Of Determination?

Answer 17

(R Squared value)The coefficient of determination is the proportion of variation of the dependent variable which is taken up by fitting the regression line

Question 18

What are the values of R Squared?

Answer 18

R squared value has a maximum of 1 and a minimum of 0. For example, if this is 0.36 then the function explains 36% of the variation in data.

Question 19

What is meant by Moving Average?

Answer 19

Moving average is a forecasting technique that averages past values in computing
the forecast.
Moving averages smooths out fluctuations.

Question 20

What is meant by Cycles?

Answer 20

Cycles are regular fluctuations about the trend. Typically occur over medium to long term at intervals greater than 12 months.
Difficult or impossible to predict.

Question 21

What is a Business Cycle?

Answer 21

Trade cycle - tendency for alternating periods of upward and downward movements in aggregate level of output and employment relative to
the long-term trend. Also known as business cycles.

Question 22

What are business fluctuations?

Answer 22

Business fluctuations are fluctuations of supply, demand and prices that occur in a specific segments of the economy.
The rest of the economy is unaffected.

Question 23

What is meant by Seasonality?

Answer 23

Seasonality is regular patterns that occur at the same time each year. Type of cyclical movement common in agricultural markets (particularly for perishable goods & goods with high storage costs).

Question 24

What is Validation and Verification mean?

Answer 24

Validation is testing a model against historical data.

Verification is comparing the actual forecast against the observed conditions.

Question 25

Key Terms

Answer 25

•Decision making •Forecasting
•Price analysis
•Time lag
•Outlook
•Quantitative forecasts •Qualitative forecasts •Assumption of continuity •Explanatory models
•Time series models
Components of time series:
(Trend, Cycle, Seasonal, and Irregular)
•Finding trends
•Linear trend forecasting
•Example: EMI = 1.432x + 382.43 (explain?) •Functional forms (linear/log models) •R-square values
•Moving average
•Forecast accuracy
(validation and verification) •Forecast error