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

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

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

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 possibleVolatility 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

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

BER’s 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 questionsThe 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

BER’s 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 :The individual modular responses to each survey run are captured as : ‘1’ for UP, ‘2’ for SAME and ‘3’ for DOWN UpSameDown

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 :Movements in individual modular responses over adjacent survey periods can be classified in micro data terms as : R11 Up  UpR12 Same  UpR13 Down  Up R21 Up  sameR22 Same  SameR23 Down  Same R31 Up  DownR32 Same  DownR33 Down  Down

Example : Relative survey period- on-period modular evaluation matrix over five survey runs Survey Relative Percentage Changes T : T-1 R11R12R13R21R22R23R31R32R33Tot 2 : : : :

BER’s survey questions considered for industrial expectations analysis General Business Conditions General Business Conditions Volume of Production Volume of Production Volume of Sales Volume of Sales Volume of New Orders Volume of New Orders Fixed Investments Fixed Investments Purchasing Prices Purchasing Prices

Deriving Expectations Volatility & Expectations Realization Survey Question ResponsesResponses Period T-1 Period T Survey-QSurvey-Q Forecast-QForecast-Q Volatility Realization

Evaluation of expectations volatility of the BER’s 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 1992q3:2005q3 were aggregated as Expectations Volatility (EV)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 1992q3:2005q3 were aggregated as Expectations Volatility (EV)

Evaluation of expectations realizations of the BER’s 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 1992q3:2005q3 were aggregated as Expectations Realization (ER)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 1992q3:2005q3 were aggregated as Expectations Realization (ER)

BER’s Industry survey question on general business conditions Expectations Volatility (EV) vs Expectations Realization (ER)

General Business Conditions : Comparison between Expectations Volatility & Realization VolatilityRealization ObsBCEVBCER # 68.1 * # * Mean Std.D6.6

New Orders : Expectations Volatility (EV) vs Expectations Realization (ER)

New Orders : Comparison between Expectations Volatility & Realization VolatilityRealization ObsOREVORER * # # * Mean Std.D2.93.9

Ascending order indications of Expectations Volatility Expectations BTS Evaluation VolatilityEV RealizationER 1 IV (Investment) PP (Prices) BC (Buss Conditions) PO (Production) SL (Sales) OR (Orders) Mean

Correlation s between Expectations Volatility & Realizations EvaluationRelationshipR t- value Buss Conditions BCEV : BCER Fixed Investment IVEV : IVER New Orders OREV : ORER Production POEV : POER Prices PPEV : PPER Sales SLEV : SLER

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 outcomeGranger 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 Granger causality establishes precedence and information content, although it does not imply causality in the more common use of the term

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

Research Findings That uncertainty does impact negatively on the realizations of industrial business expectationsThat 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 salesThat 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 pricesThat 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.That strong feedback causality in the case of new orders confirms that the directional causality goes from realization of historic expectations to prevailing uncertainty.

Component Factor Analysis of expectations volatility variables The six EV variables can be reduced to two main components (Eigenvalues>’1’)The six EV variables can be reduced to two main components (Eigenvalues>’1’) Component1 is mainly loaded by New orders, Production and Sales factors.Component1 is mainly loaded by New orders, Production and Sales factors. Component2 is mainly loaded by Fixed Investments and inverted Business Conditions factorsComponent2 is mainly loaded by Fixed Investments and inverted Business Conditions factors Component3 also loads relatively high on Eigenvalues and mainly embraces inverted Price factorsComponent3 also loads relatively high on Eigenvalues and mainly embraces inverted Price factors

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 reasonsAccepting 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

Composite Uncertainty vs composite Expectations Realizations

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’ indicatorBased 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

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

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