Posts Tagged ‘price index’

PRICE INDEX “The Score Card”

The price index is an indicator of the average price movement over time of a fixed basket of goods and services. The objective is to monitor & measure the retail, wholesale or producer prices etc.

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Base Year for calculation: Presently WPI series compiled are — Assam (base 1993-94), Bihar (1991-92), Haryana (1980-81), Karnataka (1981-82), Punjab (1979-82), U.P.(1970- 71) and West Bengal (1980-81). The National Statistical Commission has recommended that base year should be revised every five year and not later than ten years. Step-wise introduction to compilation of WPI: Like most of the price indices, WPI is based on “Laspeyres formula” for reason of practical convenience. These steps are discussed in detail in the following sections:

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1) Concept of Wholesale Prices: It is the rate at which relatively large transaction of purchase, usually for further sale, is effected. The price pertaining to bulk transaction of agricultural commodities may be farm harvest prices, or prices at the village mandi /market of the Agricultural Marketing Produce Committee/ procurement prices, support prices.

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2) Choice of Base Year: The criteria for the selection of base year are (i) a normal year i.e. a year in which there are no abnormalities in the level of production, trade and in the price level and price variations, (ii) a year for which reliable production, price and other required data are available and (iii) a year as recent possible and comparable with other data series at national and state level.

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3) Selection of Items, Varieties/ Grades, Markets: The importance of an item in the free market will depend on its traded value during the base year. In agriculture commodities the selection of new items in the basket is done on the basis of increased importance in wholesale markets. In the existing WPI series, items, their specifications and markets have been finalized in consultation of with the Directorate of E&S (M/O Agriculture), National Horticulture Board, Spices Board,Tea board, Coffee Board and Rubber Board, Silk Board, Directorate Of Tobacco, Cotton Corporation of India etc.

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4) Derivation of Weighting Diagram: Weights of Agriculture commodities: These weights are based on the Marketed value (MV) arrived at by multiplying Marketed Surplus Ratio (MSR) to the estimates of Value of Production (VOP) of agricultural commodities.

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5) Collection of Prices: The collection of base prices is done concurrently while the work on finalization of index basket is on. Therefore, price collection is normally done for larger number of items pending finalization. Once the basket is ready, current prices are collected only as per the final basket from the designated sources. Weekly prices need to be collected for pre-determined day of the week. For the current series prices are quoted on the basis of the prevailing prices of every Friday.

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6) Treatment of prices collected from open market & administered prices: The issue of using administered prices for index compilation is resolved by taking into account appropriate ratio between the levy and non-levy portions. Where these ratios are not available, the issues can be resolved through taking the appropriate number of price quotations of the administered prices and the open market prices after periodic review.

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7) Classification structure: The classification is based on NIC renders the WPI data amenable to comparison with the Index of Industrial Production (IIP) and National Income data.

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8) Methodology of Index Calculation: In the first stage, once the price data are scrutinized, price relative for each price quote is calculated. Price relative is calculated as the ratio of the current price to the base price multiplied by 100 i.e. (P1/Po) X100. In the next stage, commodity/item level index is arrived at as the simple arithmetic average of the price relatives of all the varieties (each quote) included under that commodity. Next, the indices for the sub groups/groups/ major groups are compiled and the aggregationmethod is based on Laspeyres formula.

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9) Provisional Vs Final: The weekly indices are compiled after a short gap of two weeks only as compared to other indices, which are compiled on monthly basis. The WPI are, therefore released provisionally and final revised indices, incorporating all possible quotations, are released after a gap of two months.

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10) Data collection mechanism : At present data collection for WPI is solely based on voluntary basis. Price data pertaining to Primary articles and Fuel & petroleum products are mainly collected through administrative Ministries/ Department’s, PSU’s and state government departments. For ‘Manufactured products’, apart from some government sources, data collection is done through Chambers of Commerce, Trade Associations, Business Houses and leading Manufacturing Units.

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Seasonal Index – “Time is Money” Final Part

Hello Friends here we come up with an extension of our previous blog, “Seasonal Index……“Time is Money” Part 2

In previous Blog, we had touched upon the aspect like analysis part of seasonal patterns in predicting the future prices of the commodity.

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Seasonal Index - “Time is Money” Final Part

In this Blog, we would read about that how an annual average method can be used to generate a seasonal pattern in predicting the future prices of the commodity and seasonal pattern in the year 2009.

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Annual Average Method

The annual average method can be used to generate a seasonal pattern as well as predicting the future prices of the commodity.

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This seasonal price index is derived by calculating the annual average price, and then by expressing the price for each month during the year as a percent of the annual average.

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Here, the data which is used to derive the seasonal price patterns are the monthly prices taken between the year April’2004 & November’2009.

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The monthly indexes over the years are averaged to derive a price index that represents those years.

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An example of the technique is presented in Table 1.

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The seasonal price index table suggests that the index increases from the month of June, the time the buyers enter the market with full potential & reaches the highest till the end of the year.

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In The Year 2009

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The prices movement of this year almost followed the seasonal pattern, except few months.

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The supply constraints of lower output, as farmers opted for cotton, worked as a high base effect for the futures with a flat production figure of 8.5 lakh tonnes in 2008-09.

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The recovery in prices was noticed owing to the unforeseen failure of monsoons & comfortable stocks of 25-30 lakh bags from last year for which guar prices traded higher all through-out the year.

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This commodity created a history as it made a life time high, since the date of launch at national bourse, on reports that the output is estimated at 30-35 lakh quintals, down 62% due to factors like scanty rains in the major growing areas.

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Stronger Rupee along-with volatile Crude oil prices brought some corrections in export earnings from Guargum markets in Europe/US.

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However, upcoming demand for by-products such as churi & korma from international markets kept the millers interested in processing guar.

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In a nutshell, if investors want to spin their money safely & stabilize their net returns, using seasonal Index can prove to be a fair advantage.

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Note : For More Latest Industry, Stock Market and Economy News and updates, please click here

“Seasonal Index – “Time is Money” Part 2

Hello Friends here we come up with an extension of our previous blog, Seasonal Index……“Time is Money” Part 1

In previous Blog, we had touched upon the aspect like what is seasonal pattern and reasons for studying seasonal variation.

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Seasonal Index……“Time is Money”


Now we would see the analysis part of seasonal patterns in predicting the future prices of the commodity.

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The Analysis

Crop prices tend to follow a general seasonal pattern of their own, identifying the major turning points in prices, setting their seasonal low at harvest followed by a post-harvest rally, where the supply of the crop is fixed and consumption gradually takes that supply, causing prices to rise.

However, major market shocks or powerful influencing factors like monsoon, production figures, stock levels & demand may significantly alter seasonal patterns & the prices may experience the special condition.

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This is what happened with the Guar prices.

The ‘Guar’ legume plant is rain-fed monsoon crop.

Monsoon has been the decisive factor for the trend in guar futures.

The sowing period is July and August right after the first shower of the monsoon and the harvesting period is September and November.

Fresh arrivals of the crop from Haryana and Punjab begin immediately after the first week of September and continue till the month of December.

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One example would be redeploying capital in Guar futures in two phases by taking selling positions from April as monsoon sets in – boosting the production levels, and buying in the month of June when the rally begins.

If we follow the price index & compare it with the actual, then it is seen that the prices have followed the path of the seasonal trend many times in this year & have given their best highs from month of June to August.

The seasonality shown in the below graphs depicts that the positive wave has given a satisfying return on investment in both of these commodities, & the strategy adopted of “Sell in April” makes this clear.


Guar Seed Seasonal Index vs Actual

Guar Seed Seasonal Index vs Actual



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Again, the investors taking fresh buying positions from the end of June & holding till the end of the year have had always hard-earned profits.

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Stay Tuned for more on this.

In next blog we would read about that how an annual average method can be used to generate a seasonal pattern in predicting the future prices of the commodity and seasonal pattern in the year 2009.

🙂

Note : For More Latest Industry, Stock Market and Economy News and Updates, please click here