BER

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BER

• VOLATILITY AS AN INDICATOR OF UNCERTAINTY IN AND
  ITS IMPACT ON THE REALIZATION OF INDUSTRIAL
  BUSINESS EXPECTATIONS

- Murray Pellissier
Stellenbosch University, South Africa
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VOLATILITY AS AN INDICATOR OF UNCERTAINTY IN AND
ITS IMPACT ON THE REALIZATION OF INDUSTRIAL
BUSINESS EXPECTATIONS

• Research Objectives
• To provide additional information on the
  elaboration of micro BTS data
• To derive survey expectations volatility
  (uncertainty)
• To derive survey expectations realizations
• To evaluate the impact of uncertainty on the
  realizations of business expectations

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VOLATILITY AS AN INDICATOR OF UNCERTAINTY IN AND
ITS IMPACT ON THE REALIZATION OF INDUSTRIAL
BUSINESS EXPECTATIONS

• Keywords
• Volatility
• Uncertainty
• Business Expectations
• Realization of Expectations

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Volatility/Uncertainty

• Volatility is seen as the quantification of
  historic movements in business expectations and
  radical (true) Uncertainty a subjective
  situations linked to the relevant Volatility
  where no objective classification is possible

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Business Expectations

• Expectations can be described as a subjective
  feeling or perception about an incident to happen
  in future
• One way to measure business expectations on an
  ongoing basis is to ask business people
  Business Tendency Surveys

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BERs survey on Industrial Business Conditions

• The BER evaluates the cyclical stance on business
  conditions within the South African Manufacturing
  sector, by quarterly BT surveys, based on the
  ex-post (survey quarter) and ex-ante (forecast
  quarter) survey questions

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BERs survey question evaluating expectations on
general Industrial Business Conditions

• Compared to the same period a year ago, do you
  expect next quarter general business conditions
  to be ?
• The individual modular responses to each survey
  run are captured as 1 for UP , 2 for
  SAME and 3 for DOWN

Up Same Down
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Comparing relative survey period-on-period
changes in micro survey data

• Movements in individual modular responses over
  adjacent survey periods can be classified in
  micro data terms as

R11 Up ? Up R12 Same ? Up R13 Down ? Up
R21 Up ? same R22 Same ? Same R23 Down ? Same
R31 Up ? Down R32 Same ? Down R33 Down ? Down
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Example Relative survey period-on-period
modular evaluation matrix over five survey runs
Survey Relative Percentage Changes Relative Percentage Changes Relative Percentage Changes Relative Percentage Changes Relative Percentage Changes Relative Percentage Changes Relative Percentage Changes Relative Percentage Changes Relative Percentage Changes Relative Percentage Changes
T T-1 R11 R12 R13 R21 R22 R23 R31 R32 R33 Tot
2 1 2.5 4.1 1.6 3.3 45.9 11.5 1.6 14.8 14.8 100
3 2 1.5 4.6 3.1 4.6 48.9 9.9 0.8 9.9 16.8 100
4 3 8.5 1.9 0.9 7.5 45.3 7.5 1.9 9.4 17.0 100
5 4 5.2 1.0 0.0 5.2 44.8 14.6 2.1 11.5 15.6 100
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BERs survey questions considered for industrial
expectations analysis

• General Business Conditions
• Volume of Production
• Volume of Sales
• Volume of New Orders
• Fixed Investments
• Purchasing Prices

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Deriving Expectations Volatility Expectations
Realization
Survey Question Survey Question Survey Question
Responses Responses
Period T-1 Period T
Survey-Q Survey-Q

Forecast-Q Forecast-Q

Realization
Volatility
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Evaluation of expectations volatility of the
BERs micro survey data on industrial business
conditions

• By analyzing changes in micro survey data in
  period T-1 (Forecast Quarter) compared to period
  T (Forecast Quarter), directional movements in
  individual response expectations (R12, R13, R21,
  R23, R31 and R32) over the sample period
  1992q32005q3 were aggregated as Expectations
  Volatility (EV)

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Evaluation of expectations realizations of the
BERs micro survey data on industrial business
conditions

• By analyzing changes in micro survey data in
  period T-1 (Forecast Quarter) of individual
  response expectations, compared to directional
  realizations in period T (Survey Quarter) of
  individual responses estimations (R11, R22 and
  R33) over the sample period 1992q32005q3 were
  aggregated as Expectations Realization (ER)

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BERs Industry survey question on general
business conditions Expectations Volatility (EV)
vs Expectations Realization (ER)
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General Business Conditions Comparison between
Expectations Volatility Realization
Volatility Realization
Obs BCEV BCER
1993 32.1 67.8
1994 30.6 68.0
1995 30.6 68.1
1996 40.1 61.4
1997 42.5 51.6
1998 33.0 59.4
1999 42.3 61.1
2000 47.3 51.9
2001 45.2 52.8
2002 45.2 57.0
2003 46.6 52.5
2004 45.4 52.7
Mean 40.1 58.7
Std.D 6.6 6.6
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New Orders Expectations Volatility (EV)
vs Expectations Realization (ER)
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New Orders Comparison between Expectations
Volatility Realization
Volatility Realization
Obs OREV ORER
1993 48.9 50.0
1994 45.3 61.1
1995 39.1 54.5
1996 43.2 55.3
1997 47.8 47.7
1998 49.6 57.8
1999 47.0 48.7
2000 48.0 51.8
2001 46.4 51.6
2002 45.6 53.4
2003 48.2 51.0
2004 46.8 50.6
Mean 46.3 52.8
Std.D 2.9 3.9
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Ascending order indications of Expectations
Volatility
Expectations Expectations
BTS Evaluation Volatility EV Realization ER
1 IV (Investment) 32.4 68.1
2 PP (Prices) 36.9 64.4
3 BC (Buss Conditions) 40.1 58.7
4 PO (Production) 45.7 54.5
5 SL (Sales) 46.3 53.4
6 OR (Orders) 46.3 52.8
Mean 41.3 58.6
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Correlations between Expectations Volatility
Realizations
Evaluation Relationship R t- value
Buss Conditions BCEV BCER -0.85 -11.56
Fixed Investment IVEV IVER -0.88 -13.04
New Orders OREV ORER -0.16 -1.11
Production POEV POER -0.69 -6.78
Prices PPEV PPER -0.77 -8.43
Sales SLEV SLER -0.75 -8.04
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Causality between Expectations Volatility
Realizations

• Granger causality analysis was implemented to
  test the hypothesis, which comes first during the
  forecast survey assessment of an industrial
  economic variable, prevailing uncertainty or
  expected realization of outcome
• Granger causality establishes precedence and
  information content, although it does not imply
  causality in the more common use of the term

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Directional Causality between Expectations
Volatility Realizations
Evaluation Granger Causality
Buss Conditions Uncertainty Realization
Fixed Investment Uncertainty Realization
New Orders Uncertainty Realization
Production Uncertainty Realization
Prices Uncertainty Realization
Sales Uncertainty Realization
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Research Findings

• That uncertainty does impact negatively on the
  realizations of industrial business expectations
• That directional causality from uncertainty, to
  the corresponding realization of expectations is
  noted in the case of general business conditions,
  production and sales
• That un-directional causality is noted in the
  case of fixed investments and prices
• That strong feedback causality in the case of new
  orders confirms that the directional causality
  goes from realization of historic expectations to
  prevailing uncertainty.

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Component Factor Analysis of expectations
volatility variables

• The six EV variables can be reduced to two main
  components (Eigenvaluesgt1)
• Component1 is mainly loaded by New orders,
  Production and Sales factors.
• Component2 is mainly loaded by Fixed Investments
  and inverted Business Conditions factors
• Component3 also loads relatively high on
  Eigenvalues and mainly embraces inverted Price
  factors

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Composite Uncertainty Indicator

• Accepting Component1 of the Factor Analysis as
  indicative of an un-weighted composite
  uncertainty (EV) indicator, a similar
  expectations realizations (ER) indicator was
  developed for comparison reasons

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Composite Uncertainty vs composite Expectations
Realizations
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Components of expectations volatility variables

• Based on the fact that Component1 only explains
  50 of the variance, the six EV variables load
  quite differently in comparison to each other and
  has to be further investigated in terms of
  weights in compiling an acceptable composite
  Uncertainty indicator

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Conclusions

• It can be concluded that in the South African
  Industrial case, prevailing uncertainty
  surrounding business expectations do impact
  negatively on the realization of expectations
• The possibility exist to compile an industrial
  business uncertainty indicator, provided the
  relevant component weights be further analyzed

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• VOLATILITY AS AN INDICATOR OF UNCERTAINTY IN AND
  ITS IMPACT ON THE REALIZATION OF INDUSTRIAL
  BUSINESS EXPECTATIONS