FMC and Pondecherry Paper

8/8/2019 FMC and Pondecherry Paper

1/22

Indian Institute of Plantation Management 1

PAPER ON:

Forecasting Commodity Future Prices

Written by;

Mr. Mane Pramod

Student PGD-ABPM,

Indian Institute of Plantation Management,

Jnanabharati campus,

Bangalore -560056

AUGUST-2009

Email: [email protected]


2/22


Executive Summery

Fluctuations in the prices of various commodities are very volatile due to sliding global

economy and uncertain financial happenings, which is generating high risk for commodity

future market participants; hence, it is important to develop accurate price forecasts, which can

work out profit booking calls and keep investors away from losing money.

This paper discus about the forecasting of commodity future starting from basics of

forecasting. And also reveals various type or method generally followed for forecasting with

their considered error correction. Quantitative forecasting method will be discussed in detail in

this paper and also have only overview on qualitative method because of its limited use in

commodity future forecasting. Though these models provide valuable insights into the causes

of price movements, but they are not necessarily the best suited for forecasting given the

multiplicity of known and unknown factors that affect supply and demand conditions in these

markets. There are two main bases for forecasting Fundamental (demand and supply) and

Technical analysis which will discuss in second section of report.

In Indian scenario traders are widely using some technical indicators like MACD, RSI,

BOLLINGER BAND, and RETRACEMENT, which is quantitative forecasting and comes

under econometrics and this, will be discussed further by using CRUDE OIL as an example.

Finally in concluding part paper discuss about difficulties in present methods and reliability,

accuracy, durability and economy of information(data) and its sources available for forecasting

and challenges in forecasting of commodity future in present situation like recession, shrinking

Pricing cycles of commodities, supplier consolidation and pricing volatility.


3/22


Chapter Scheme

Chapter 1 Introduction to forecasting ..04

Definition

Methods of forecasting

Error correction

Chapter 2 Fundamental and technical analysis .09

Fundamental analysis

- Supply

- Demand

Technical analysis

- MACD (moving average)

- SIGNAL LINE

- BOLLINGER BAND

-

RSI

- RETRACEMENT

Chapter 3 Commodity CRUDE OIL..16

Chapter 4 Conclusion..22


4/22


Chapter: 1

INTRODUCTION TO FORECASTING

Definition:

FORECASTING:

Planning tool which helps future analysts in his attempts to cope with the uncertainty of the

future. It starts with certain assumptions based on the persons experience, knowledge, and

judgment. These estimates are projected into the coming months or years using one or more

techniques such as moving averages, regression analysis, candle stick charts and trend

projection. Since any error in the assumptions will result in a similar or magnified error in

forecasting, the technique ofsensitivity analysis is used which assigns a range ofvalues to the

uncertain factors (variables).

TYPES OF FORECASTING METHODS:

1 .QUALITATIVE FORECASTING METHODS

These types of forecasting methods are based on judgments or opinions, and are subjective in

nature. They do not rely on any mathematical computations.

Qualitative Methods

Executive Opinion Market Research Delphi Method

Approach in which a group

of managers and analysts

meet and collectively

develop a forecast.

Approach that uses

surveys and interviews to

determine demand.

Approach in which a

forecast is the product of

a consensus among a

group of experts.
http://www.businessdictionary.com/definition/planning.htmlhttp://www.businessdictionary.com/definition/tool.htmlhttp://www.businessdictionary.com/definition/attempt.htmlhttp://www.businessdictionary.com/definition/uncertainty.htmlhttp://www.businessdictionary.com/definition/assumptions.htmlhttp://www.businessdictionary.com/definition/experience.htmlhttp://www.businessdictionary.com/definition/knowledge.htmlhttp://www.businessdictionary.com/definition/judgment.htmlhttp://www.businessdictionary.com/definition/estimate.htmlhttp://www.businessdictionary.com/definition/month.htmlhttp://www.businessdictionary.com/definition/technique.htmlhttp://www.businessdictionary.com/definition/moving-average.htmlhttp://www.businessdictionary.com/definition/regression-analysis-RA.htmlhttp://www.businessdictionary.com/definition/trend.htmlhttp://www.businessdictionary.com/definition/projection.htmlhttp://www.businessdictionary.com/definition/error.htmlhttp://www.businessdictionary.com/definition/result.htmlhttp://www.businessdictionary.com/definition/sensitivity-analysis.htmlhttp://www.businessdictionary.com/definition/assign.htmlhttp://www.businessdictionary.com/definition/range.htmlhttp://www.businessdictionary.com/definition/values.htmlhttp://www.businessdictionary.com/definition/factor.htmlhttp://www.businessdictionary.com/definition/variable.htmlhttp://www.businessdictionary.com/definition/variable.htmlhttp://www.businessdictionary.com/definition/factor.htmlhttp://www.businessdictionary.com/definition/values.htmlhttp://www.businessdictionary.com/definition/range.htmlhttp://www.businessdictionary.com/definition/assign.htmlhttp://www.businessdictionary.com/definition/sensitivity-analysis.htmlhttp://www.businessdictionary.com/definition/result.htmlhttp://www.businessdictionary.com/definition/error.htmlhttp://www.businessdictionary.com/definition/projection.htmlhttp://www.businessdictionary.com/definition/trend.htmlhttp://www.businessdictionary.com/definition/regression-analysis-RA.htmlhttp://www.businessdictionary.com/definition/moving-average.htmlhttp://www.businessdictionary.com/definition/technique.htmlhttp://www.businessdictionary.com/definition/month.htmlhttp://www.businessdictionary.com/definition/estimate.htmlhttp://www.businessdictionary.com/definition/judgment.htmlhttp://www.businessdictionary.com/definition/knowledge.htmlhttp://www.businessdictionary.com/definition/experience.htmlhttp://www.businessdictionary.com/definition/assumptions.htmlhttp://www.businessdictionary.com/definition/uncertainty.htmlhttp://www.businessdictionary.com/definition/attempt.htmlhttp://www.businessdictionary.com/definition/tool.htmlhttp://www.businessdictionary.com/definition/planning.html


5/22


2 .QUANTITATIVE FORECASTING METHODS

Quantitative forecasting methods can be divided into two categories: time series models and

causal models.

Quantitative Methods

Time Series Models Causal Models

Time series models look at

past patterns of data and

attempt to predict the future

based upon the underlying

patterns contained within

those data.

Causal models assume that the

variable being forecasted is

related to other variables in the

environment. They try to

project based upon those

associations.

2.1 TIME SERIES MODEL

Time series is a series of observations collected over evenly spaced intervals of some quantity

of interest. e.g. prices per hour, volume per day

Let

yi= observed value i of a time series (i = 1,2,,t)

yhati = forecasted value of yi

ei = error for case i = yiyhati


6/22


7/22


2.2 PATTERNS THAT MAY BE PRESENT IN A TIME SERIES

Level or horizontal: Data are relatively constant over time, with no growth or decline.

Trend: Data exhibit a steady growth or decline over time.

Seasonality: Data exhibit upward and downward swings in a short to intermediate time frame

(most notably during a year).

Cycles: Data exhibit upward and downward swings in over a very long time frame.

Random: Erratic and unpredictable variation in the data over time.

2.3 ERROR CORRECTION:

Sometimes the forecast is too high (negative error) and sometimes it is too low (positive

error).

The accuracy of the forecasting method is measured by the forecasting errors. There are two

popular methods for assessing forecasting accuracy:

Mean Absolute Deviation

(MAD)

To eliminate the problem of positive errors canceling negative errors, a simple measure is one

that looks at the absolute value of the error (size of the deviation, regardless of sign). When

we disregard the sign and only consider the size of the error, we refer to this deviation as the

absolute deviation. If we accumulate these absolute deviations over time and find the average

value of these absolute deviations, we refer to this measure as the mean absolute deviation .

MAD = ( | ei | )/n

Where n is the number of periods in the forecast

Units of MAD are same as units of yi


8/22


Mean Squared Error (MSE)

MSE = (

ei

2

)/nUnits squared

Tracking Signal

A tracking signal (T.S.) is a tool used to continually monitor the quality of our forecasting

method as we progress through time. Each period a tracking signal value is calculated, and a

determination is made as to whether it falls into an acceptable range (much like we saw with

control charts). If it drifts outside of the acceptable range, that is an indication that the

forecasting method being used is no longer providing accurate forecasts. Tracking signals

help to indicate whether there is bias creeping into the forecasting process. Bias is a tendency

for the forecast to be persistently under or persistently over the actual value of the data.

Tracking signal is calculated as follows:

Tracking signal =

algebraic sum of forecast errors (ASFE)

MAD


9/22


Chapter: 2

FUNDAMENTAL AND TECHNICAL ANALYSIS

There are two basic approaches to forecasting prices in commodity markets: fundamental

analysis and technical analysis. While they are often presented as substitutes or competitors

in price forecasting, the two can be complimentary. Most market analysts pay attention to

both fundamental and technical factors even though they may emphasize one over the other.

FUNDAMENTAL ANALYSIS

Fundamental price analysis is based on the notion that the underlying supply/demand

conditions in a given market ultimately determine price. Since the futures market is

attempting to discover prices that will balance supply and demand in some future time period,

there is uncertainty in initially establishing an equilibrium price. The market may be

shocked by new information; resulting in traders changing their assessments of what the

equilibrium price will be in the future. Fundamental analysis is attempts to both anticipate

changes in supply/demand information, and to evaluate the direction and range of pricemovement resulting from new information.

Fundamental analysis may be simple (intuitive), or complicated (using quantitative statistical

or mathematical models), In both cases, analysts are attempting to asses price implications of

economic variables including:

1) Seasonal use patterns

2) Seasonal supply patterns

3) Prices of substitute goods

4) Prices of compliment goods

5) Market structure

Intuitive analysis uses a basic understanding of economic principles to hypothesize about

price changes. Quantitative analysis combines knowledge of economic theory with

mathematics and statistics to establish explicit relationships between economic variables and

price.


10/22


Price movements in commodities using fundamental analysis can be broken down into these

simple formulas:

Demand > Supply = Higher Prices

Supply > Demand = Lower Prices

Supply of Commodities:

The supply of a commodity is the amount that is carried over from previous year(s) of

production and the amount that is being produced during the current year. For example, the

current supplies of soybeans would include the amount of crops in the ground and the amountthat is left over from the previous season. Typically, the more that is carried over from the

previous season, the lower the prices will fall.

There are many factors that can impact the supply of commodities like weather, amount of

acres planted, production strikes, crop diseases and technology. The main thing to remember

when using fundamental analysis is that high prices for commodities will lead to an increase

in production, as it is more profitable to produce commodities when prices are higher. As you

might expect, demand will typically drop as prices move higher.

Demand for Commodities:

Demand for commodities is the amount that is consumed at a given price level. The rule of

thumb is that demand will increase when the price of a commodity moves lower. Oppositely,

demand will decrease as the price of a commodity increases. There is an old saying among

commodity traders that low prices cure low prices. This means that more of a commodity will

be consumed at lower prices, which lowers the supply and thus prices will eventually

increase.

Using Fundamental Analysis to Forecast Future Prices of Commodities:

Prices will fluctuate in the short term, so it is not easy to make fundamental forecasts of

commodities prices and make short-term trades. It is even more difficult for new commodity

traders to do this. I recommend that new traders, and even experienced traders, use a long-

term strategy when using fundamental analysis to forecast commodity prices. You shouldlook for trends that are developing that will cause a shift supply and demand factors.


11/22


It may seem like a daunting task to find all the current data and compare it to previous years

and see how prices reacted under those conditions. Worse yet, you have to forecast in the

future as to what the supply and demand scenario will be. I can tell you it is almost

impossible to do this.

What you want to do is look for trends in production and consumption and trade with that

bias. For example, if the supplies of chana are at a five-year high and we just planted a record

amount of acres of chana for this season; it is likely that chana future will trade with a

downward bias. You would be likely want to trade from the short side.

Now, at some point, the price of chana will get too low and demand will increase. Or, there

might be weather problems during the growing season that will lower the production of

chana. In these cases you have to be flexible and realize that prices wont go down forever.

The longer-term trends in commodities are easier to spot with fundamental analysis, but I

prefer to use technical analysis to capture shorter-term movements in commodities prices.

Most professional commodity traders like to know what the big picture is with commodities

using fundamental analysis and then they use technical analysis to time their entries and exits.

TECHNICAL ANALYSIS:

Technical analysis is a method of evaluating commodity future prices by analyzing the

statistics generated by market activity, such as past prices and volume. Technical analysts do

not attempt to measure a commodities intrinsic value, but instead use charts and other tools to

identify patterns that can suggest future activity. Technical analysis takes a completely

different approach; it doesnt care one bit about the value of a commodity. Technicians

(sometimes called chartists) are only interested in the price movements in the market.

Despite the entire fancy and exotic tool it employs technical analysis really just studies supply

and demand in a market in an attempt to determine what direction, or trend, will continue in

the future. In other words, technical analysis attempts to understand the emotions in the

market by studying the market itself, as opposed to its components. If you understand the

benefits and limitations of technical analysis, it can give you a new set of tools or skills that

will enable you to be a better trader or investor.
http://commodities.about.com/od/profilesofcommodities/p/corn_futures.htmhttp://www.investopedia.com/terms/v/volume.asphttp://www.investopedia.com/terms/i/intrinsicvalue.asphttp://www.investopedia.com/terms/p/pattern.asphttp://www.investopedia.com/terms/c/chartist.asphttp://www.investopedia.com/terms/s/supply.asphttp://www.investopedia.com/terms/d/demand.asphttp://www.investopedia.com/terms/t/trend.asphttp://www.investopedia.com/terms/t/trend.asphttp://www.investopedia.com/terms/d/demand.asphttp://www.investopedia.com/terms/s/supply.asphttp://www.investopedia.com/terms/c/chartist.asphttp://www.investopedia.com/terms/p/pattern.asphttp://www.investopedia.com/terms/i/intrinsicvalue.asphttp://www.investopedia.com/terms/v/volume.asphttp://commodities.about.com/od/profilesofcommodities/p/corn_futures.htm


12/22


The field of technical analysis is based on three assumptions:

1. The Market Discounts Everything

2. Price Moves in Trends

3. History Tends To Repeat Itself

Study of Various Tools Used in Technical Analysis

Technical tools:

Moving Averages

MACD (MovingAverage Convergence Divergence)

One of the most popular technical indicators, the moving average convergence divergence

(MACD) is used by traders to monitor the relationship between two moving averages. It is

generally calculated by subtracting a 26-day exponential moving average from a 12-day

EMA. When the MACD has a positive value, the short-term average is located above the

long-term average. As mentioned earlier, this stacking order of the averages is an indication

of upward momentum. A negative value occurs when the short-term average is below the

long-term average a sign that the current momentum is in the downward direction. Manytraders will also watch for a move above or below the zero line because this signals the

position where the two averages are equal (crossover strategy applies here). A move above

zero would be used as a buy sign, while a cross below zero can be used as a sell signal

Signal/Trigger Line

Moving averages arent limited to just stock or commodity prices; Mas can be created for any

form of data those changes frequently. It is even possible to take a moving average of a

technical indicator such as the MACD. For example, a nine-period EMA of the MACD

values is added to the chart, in an attempt to form transaction signals. Buy signals are

generated when the value of the indicator crosses above the signal line, while short signals

are generated from a cross below the signal line. It is important to note that regardless of the

indicator being used, a move beyond a signal line is interpreted in the same manner; the only

thing that varies is the number of time periods used to create it.


13/22


Bollinger Band

A Bollinger band technical indicator looks similar to the moving average envelope, but

differs in how the outer bands are created. The bands of this indicator are generally placed

two standard deviations away from a simple moving average. In general, a move toward the

upper band can often suggest that the asset is becoming overbought, while a move close to

the lower band can suggest the asset is becoming oversold. Since standard deviation is used

as a statistical measure of volatility, this indicator adjusts itself to market conditions. The

tightening of the bands is often used by traders as an early indication that overall volatility

may be about to increase and that a trader may want to wait for a sharp price move.

Bollinger Band Tactics

The Bollinger Bounce

One thing you should know about Bollinger Bands is that price tends to return to the middle

of the bands. That is the whole idea behind the Bollinger bounce. If this is the case, then by

looking at the chart below we can say, price will go down. As you can see, the price settled

back down towards the middle area of the bands.

Thats all there is to it. What you just saw was a classic Bollinger boun ce. The reason these

bounces occur is because Bollinger Bands act like mini support and resistance levels. The

longer the time frame you are in, the stronger these bands are. Many traders have developed

systems that thrive on these bounces, and this strategy is best used when the market is

ranging and there is no clear trend.
http://www.babypips.com/school/support_and_resistance.htmlhttp://www.babypips.com/school/support_and_resistance.html


14/22


Bollinger Squeeze

The Bollinger squeeze is pretty self explanatory. When the bands squeeze together, it

usually means that a breakout is going to occur. If the candles start to break out above the top

band, then the move will usually continue to go up. If the candles start to break out below the

lower band, then the move will usually continue to go down.

Looking at the chart above, you can see the bands squeezing together. The price has just

started to break out of the top band. Based on this information, we can say price will go up.

This is how a typical Bollinger Squeeze works. This strategy is designed to catch a move as

early as possible. Setups like these dont occur every day, but you can probably spot them a

few times a week if you are looking at a 15 minute chart.


15/22


Relative strength index:

It indicates overbought and oversold conditions.

When RSI is above 80, it means that the market is overbought and we should look to

sell.

When RSI is below 20, it means that the market is oversold and we should look to

buy.

RSI can also be used to confirm trend formations. If you think a trend is forming,

wait for RSI to go above or below 50 (depending on if youre looking at an uptrend or

downtrend) before you enter a trade.

Fibonnaci Retracement:

Traders usually study charts, Fibonacci ratios may be applied to the Price scale, and

also to the time scale of charts. My focus here will be on the price scale for now.

Prices never move in a straight line. Look at any chart, you will see many wiggles, as

price advances and retraces. Commodity futures, Forex, all instruments which are

liquid, will often retrace in Fibonacci proportions, and advance in Fibonacci

proportions. Not always, and not precisely to the penny. But very often, and

reasonably close. This happens often enough that profitable trades can result.

Use Fibonacci ratios with a few simple indicators to help determine probable price

turning points, optimum entry, exit and stop-loss levels.


16/22


17/22


Forecast:

Major trend is uptrend likely to consolidate in range 3110 to 3200.

Call for tomorrow: sell 3180 Stop loss 3222 target 3110

Here for giving the tomorrows call we need to observe what is major trend and other thing

like any inventory data, unemployment data, housing data, OPEC announcements, GDP of

various countries ,Dollar value against other major currencies, rig count-new oil field, oil

consumption data etc which may be helpful for future calls.


18/22


Long term forecast for crude oil:

WORLD ENERGY TREND

Oil prices:

Oil prices have roller-coastered: starting 2008 at US$92/b, the OPEC Reference Basket rose

to a record $141/b in early July before falling to $33/b by the end of the year, the lowest level

since summer 2004.and smoothing in 2009 starting with US$ 35-40/b and presently trading in

range of 65-75US $.For the first time since the early 1980s, world oil demand contracted in2008, by 0.3 mb/d, and it is expected to further decline by a hefty 1.4 mb/d in 2009,

according to OPECs April Monthly Oil Market Report (MOMR). The rapidly softening

fundamentals, with burgeoning stock levels accompanied by a rise in production capacity in

OPEC Member Countries has clearly contributed to the drop in oil prices. This is in addition

to the now recognized fact that the unsustainably high price levels observed in the middle of

2008 were to a large extent due to significant speculative investment inflows in oil and

product futures and over-the-counter (OTC) markets.

Medium-term economic growth:

All institutions, including OPEC, have revised downward drastically their projections for

Gross Domestic Product (GDP) and oil demand growth in 2009. Following fig, illustrates the

rapid reassessment for short-term economic growth in the OECD. In the July 2008 edition of

the OPEC MOMR, real GDP growth for 2009 in the three OECD regions was in the range

1.31.6%, but by June 2009 the US, the Eurozone and Japanese economies were shrink by

2.8%, 4.2% and 6.4% respectively. Over this period, developing country growth expectations

have also been dramatically lowered.


19/22


Long-term economic growth

Demographics

Population Growth rate of world can be used as major instrument for forecasting long term

futures, because it gives idea about overall consumption and its increase in oil consumption

pattern.


20/22


Annual demand growth:

By considering all things like population growth ,its consumption, GDP rate we can forecast

what is the growth rate which oil can have demand in future.

World oil demand

Present oil consumption is 83mb/d, by analyzing the population growth rate, industrial use

rate, demand supply factors, substitute use pattern we can calculate the demand in three

cases: reference case, lower growth and higher growth.


21/22


Oil rig counts

If the forecasted future demand is growing at low rate then rig count will be go down,

because there will be no demand for the entire field to operate at full capacity.

Main thing is cost of production if, it more than the price of crude oil then there will be no

chance of making profit for oil producers.so result rig count go down.

So, by studying all this factors related to starting from oil prices & its trend, population

growth & consumption pattern globally, demand and supply of oil, rig counts, various

OPEC and non-OPEC oil producing countries policy, available oil inventories at various

countries and substitute for oil in future time etc, all this make the forecast reliable and

provide input for forecasting long term pictures.


22/22


Chapter: 4

CONCLUSION

Forecasting of commodity future is very challenging more than that measuring accuracy &

plausibility of forecast is very difficult. Presently due to global economic recession prices of

fluctuating like anything beyond the imagination in such scenario traders should able to

forecast which can generate true calls .in Indian scene traders are unable to access all the

data released by various organization related to various commodities which results lack of

information for prediction process.

By using econometrics-quantitative technique one can generate good risk: reward ratio call,

Moving averages can be effective tools to identify and confirm trend, identify support andresistance levels, and develop trading systems. However, traders and investors should learn to

identifycommodities and time periodthat are suitable for analysis with moving averages and

how this analysis should be applied. Don't expect to get out at the top and in at the bottom

using moving averages. As with most tools of technical analysis, moving averages should not

be used on their own, but in conjunction with other tools that complement them. Not

necessarily quantitative will always true but traders also have to keep watching on various

fundamental factors.

After all the future commodity trading more affected by market sentiments and traders

psychology one should able to understand this market sentiments come up with own strategy

plan of trading. And remember..

If you fail to plan, you plan to fail.

Documents

FMC and Pondecherry Paper