Transcription

FORECASTING THE MACROECONOMIC RISKOF INDUSTRIES AND THE PROBABILITY OFDEFAULT FOR COMPANIES IN EUROPEDr. Jakob MargolisFirst EViews User Meeting, FrankfurtOctober 22, 2014

AGENDA21Target: Connect a Generic Scorecard (SAS) with a Macroeconomic Model (EViews)2Important terms: Scorecard, Risk of Industries (RI), Probability of Default (PD) and Rating3Generic Scorecard for prediction of PD and Rating using SAS4Macroeconomic Model for forecast of RI using EViews5Connection between macroeconomic indicators and RI, PD, Rating6Simulation of Scenarios and Stresstest06.11.2014PRÄSENTATIONSNAME REDNER

TARGET: CONNECT A GENERIC SCORECARD (SAS)WITH A MACROECONOMIC MODEL (EVIEWS)Scorecard for prediction of probability of default (PD)with risk of industries (RI) using SASRisk of industriesMacroeconomic model (MEM) for forecastingthe risk of industries using EViewsRisk of industries f (GDP, DAX, i ECB, Oil price, )Final Raw Score for each company within a country PD Rating3

MEM for risk ofindustry (EViews)Scorecard for prediction ofPD and rating (SAS)IMPORTANT TERMS: WHAT IS RISK OF INDUSTRY (RI)AND PROBABILITY OF DEFAULT (PD) FOR A COMPANY?4PROBABILITY OF DEFAULT FOR A COMPANY (USING SAS):PD F(DEM; FIN; TRD; NEG; MEM); DEM variables: legal form, number of employees, age of company etc.; FIN variables: revenue, profit, liabilities, etc.; TRD variables: late payment, sum of invoices, paydex etc.; NEG variables: audit remarks, blocked accounts etc.; MEM variables: RI (Bad Rate of industry) RI F( macroeconomic indicators )FORECASTING THE RISK OF INDUSTRY PER QUARTER (USING EVIEWS):RI q Bad rate q bankruptcy in industry q / active company q F (GDP(t), Interest Rate of ECB(t), Inflation rate(t), DAX-30(t), Euro/USD(t); Oil price(t), .)

MEM for risk ofindustry (EViews)Scorecard for prediction ofPD and rating (SAS)TARGET: CONNECT A GENERIC SCORECARD (SAS)WITH A MACROECONOMIC MODEL (EVIEWS)Country-Database with all available information (microeconomic variables)SAS: Risk-Model split (e.g. based on “number of employees”)1: Small companies: 1-9 ore14Score small: D1;F1;T1;N12: Big companies: 10 ore24Score big: D2;F2;T2;N2We use Eviews for modelling Risk of industry (RI):Macroeconomic modul: RI f(GDP, DAX-30, i ECB, Oil price, )Raw Score smallRaw Score bigStatistical based overridesFinal Raw Score for each company within a country PD Rating5

EXAMPLE-1: MICRO-ECONOMIC INDICATOR (E.G. AGE OF COMPANY)IN GENERIC SCORECARD:UNIVARIATE ANALYSIS FOR DEMOGRAPHIC INDICATOR - AGE OF COMPANY (YEARS)Demographic Modul: age of company% Bad Rate in small groups% Bad Rate after grouping adjustment6,32%MISSING1,31%0 - 24,10%2 - 34 - 55 - 66 - 77 - 88 - 99 - 101,00%1,14%11 - 1213 - 1414 - 1616 - 1717 - 1919 - 2020 0,00%2,19%5 - 81,94%1,33%10 - 1112 - 134,10%MIS, 0 - 52,66%2,59%1,93%2,43%2,27%3 - %8 0,00%3,00%4,00%5,00%6,00%1,00%2,00%7,00% Failure risk decreases after 8 years in the market.63,00%4,00%5,00%

EXAMPLE 2 – GENERIC SCORECARD:RISK OF INDUSTRIES IN COUNTRY (CENTRAL EUROPE)Industry NACEABCDEFGHIJKLMNRSTOTAL7Industry er serviceConstructionTradeTransport & LogisticHotels & GastronomieInformation and communicationFinance & InsuranceEstateFreelanceBusiness ServiceArtsOther ServicesGOODSBADS323591335PGOODSPBADSBAD RATEWOEPOP% AVG 424.79%13.84%12.91%0.224.76%3.60%

MEM: COLLECTION OF MACROECONOMIC INDICATORS ON 5 LEVELS1. INDUSTRY LEVEL (SIC OR NACE OR WZ): INDUSTRY RISK, PRODUCTION INDEX, TURNOVER PERINDUSTRY, GROSS VALUE ADDED 2. STATE LEVEL: BUNDESLAND IN GERMANY, WOJWODZTWO IN POLAND, KANTON IN SWITZERLAND,MEGYE IN HUNGARY; e.g. UNEMPLOYMENT PER STATE;3. COUNTRY LEVEL: TIME SERIES ANALYSIS: TIME (t) 42 QUARTERS (the more the merrier:) GDP(t); DAX-30(t); Inflation rate(t); Government deficit(t) -3% (Basel III) unemployment(t); etc.4. EUROPA LEVEL: INTEREST RATE (t) OF EUROPE CENTRAL BANK (ECB)5. GLOBAL LEVEL: EURO/USD (t), OIL PRICE (t), DOW JONES INDEX(t) 8

EXAMPLE 3 – MEM: GDP FOR GERMANY IN BILLION PER QUARTERFinancial crisisSource: German Statistical Office9

EXAMPLE 4 – RISK OF INDUSTRY:FAILURE RATE (BR) PER YEAR FOR MINING & ENERGY IN GERMANYSIC-CODES10-14: MINING& ENERGY(OIL,GAS);Source: Bisnode Data1010.14 Mining1011 Iron ores1021 Copper ores1031 Lead & zinc ores1041 Gold ores1044 Silver ores1061 Ferroalloy ores exc. vanadium1081 Metal mining services1094 Uranium, radium & vanadium ores1099 Miscellaneous metal ores N.E.C.12Coal Mining1221 Bituminous coal & lignite surface mining1222 Bituminous coal underground mining1231 Anthracite mining1241 Coal mining services13Oil and Gas Extraction1311 Crude petroleum & natural gas1321 Natural gas liquids1381 Drilling oil & gas wells1382 Oil & gas field exploration services1389 Oil & gas field services N.E.C.Mining & Quarrying of Non-metallic Minerals exc.14Fuels1411 Dimension stone1422 Crushed & broken limestone1423 Crushed & broken granite1429 Crushed & broken stone N.E.C.1442 Construction sand & gravel1446 Industrial sand1455 Kaolin & ball clay1459 Clay, ceramic & refractory minerals N.E.C1474 Potash, soda & borate minerals1475 Phosphate rock1479 Chemical & fertilizer mineral N.E.C.1481 Non-metallic mineral services exc. fuels1499 Misc. non-metallic minerals exc. fuels

EXAMPLE 4 – RISK OF INDUSTRY:FAILURE RATE (BR) PER YEAR FOR MINING & ENERGY IN GERMANYSIC 10 14 Mining & Energy(Oil, Gas, without Electricity)3,00%2,50%2,00%1,50%Failure rate (BR) per 7Source: Bisnode DataRisk of mining & energy industry has increased1120082009

EXAMPLE 4 – RISK OF INDUSTRY:FAILURE RATE (BR) PER YEAR FOR MINING & ENERGY IN GERMANYEXTRACTIONOF INDIVIDUALINDUSTRIESPOSSIBLESource: Bisnode Data1210.14 Mining1011 Iron ores1021 Copper ores1031 Lead & zinc ores1041 Gold ores1044 Silver ores1061 Ferroalloy ores exc. vanadium1081 Metal mining services1094 Uranium, radium & vanadium ores1099 Miscellaneous metal ores N.E.C.12Coal Mining1221 Bituminous coal & lignite surface mining1222 Bituminous coal underground mining1231 Anthracite mining1241 Coal mining services13Oil and Gas Extraction1311 Crude petroleum & natural gas1321 Natural gas liquids1381 Drilling oil & gas wells1382 Oil & gas field exploration services1389 Oil & gas field services N.E.C.Mining & Quarrying of Non-metallic Minerals exc.14Fuels1411 Dimension stone1422 Crushed & broken limestone1423 Crushed & broken granite1429 Crushed & broken stone N.E.C.1442 Construction sand & gravel1446 Industrial sand1455 Kaolin & ball clay1459 Clay, ceramic & refractory minerals N.E.C1474 Potash, soda & borate minerals1475 Phosphate rock1479 Chemical & fertilizer mineral N.E.C.1481 Non-metallic mineral services exc. fuels1499 Misc. non-metallic minerals exc. fuels

EXAMPLE 5: ELECTRICITY PROVIDERS IN GERMANYExamples from SIC 4931: WHAT IS THE POTENTIAL OF ELECTRICITY PROVIDERS IN GERMANY?SIC44931 Elektrizitäts- u. LZORTPremicon Bio-Raffinerie GmbHEinsteinstr. 381675MünchenStadtwerk Külsheim GmbHAm E-Werk 897900KülsheimStadtwerke Zeulenroda GmbHMarkt 807937Zeulenroda-TriebesStadtwerke Forchheim GmbHHaidfeldstr. 891301ForchheimStadtwerke Elbtal GmbHNeubrunnstr. 801445RadebeulWärmeversorgung Bergstraße GmbHDammstr. 6864625BensheimStadtwerke Bad Vilbel GmbHTheodor-Heuss-Str. 5161118Bad VilbelStadtwerke Aschersleben GmbHMagdeburger Str. 2606449AscherslebenBahnhofstr. 1758540MeinerzhagenLadestr. 575323Bad WildbadStadtwerke MeinerzhagenGesellschaft mit beschränkterHaftungStadtwerke Bad Wildbad GmbH &Co. KG1306.11.2014STORM VERSORGER JAKOB MARGOLIS

POTENTIAL FOR ELECTRIC & OTHER SERVICES COMBINEDExample 5: Potential of Electricity Providers in Germany 690 companiesSIC4BEZEICHNUNGElektrizitäts- u. andere öffentliche100%4931 VersorgungsbetriebeErzeugung u. Verteilung von4925 Misch-, Stadt- u. Flüssiggas90%Elektrizitätsgesellschaften u. -80%ANZAHL68814911 Systeme13593 Zylinder, Stellantriebe0Zweitschmelzen u. Läutern von70%3341 Nichteisenmetallen60%6081 ausländischer Banken02652 Zusammensetzbare Kartons050%Zweigstellen u. Vertretungen99,7%Zugeschnittene Steine u.40%03281 Steinprodukte, Kalkstein, Marmor00133 Zuckerpflanzen (-rohr, -rüben)00174 Zitrusfrüchte030%20%10%0,1% 0,1% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%0%49311406.11.20144925491135933341STORM VERSORGER JAKOB MARGOLIS60812652328101330174

DISTRIBUTION OF ELECTRIC COMPANIES PER EMPLOYEESExample 5: Most Electricity providers in Germany have between 20 and 99 employeesA) 1 - 4B) 5 - 95%C) 10 - 199%D) 20 - 4920%E) 50 - 9923%F) 100 - 19912%G) 200 - 4996%H) 500 - 9992%I) 10002%0%1506.11.2014GRÖßE NACHMITARBEITERN18%5%10%15%Anteil der UnternehmenSTORM VERSORGER JAKOB MARGOLIS20%25%ANZAHLANTEILA) 1 - 412318%B) 5 - 9335%C) 10 - 19599%D) 20 - 4914120%E) 50 - 9915723%F) 100 - 1998112%G) 200 - 499436%H) 500 - 999152%I) 1000122%J) k.A.264%

REVENUE DISTRIBUTION OF ELECTRICITY PROVIDERSExample 5: 64% electricity providers in Germany have revenue more than 10 Mio. A) 250 (k) GRÖßE NACHUMSATZ10%B) 250 - 500 (k) 5%C) 500 - 1.000 (k) 2%D) 1.000 - 2.000 (k) 2%E) 2.000 - 5.000 (k) 5%F) 5.000 - 10.000 (k) 9%G) 10.000 - 25.000 (k) 22%H) 25.000 - 50.000 (k) 18%I) 50.000 (k) 24%0%5%10%15%Anteil der Unternehmen1606.11.2014STORM VERSORGER JAKOB MARGOLIS20%25%ANZAHLANTEILA) 250 (k) 6710%B) 250 - 500 (k) 335%C) 500 - 1.000 (k) 112%D) 1.000 - 2.000 (k) 142%E) 2.000 - 5.000 (k) 325%F) 5.000 - 10.000 (k) 609%G) 10.000 - 25.000 (k) 15222%H) 25.000 - 50.000 (k) 12318%I) 50.000 (k) 16424%J) k.A.345%

AGE OF COMPANIES (ELECTRICITY PROVIDERS)Example 5: 52% electricity providers have age of comp. between 1 and 9 years (Libiralization law 2005)A) 1 - 2UNTERNEHMENSALTER4%B) 3 - 512%C) 6 - 936%D) 10 -148%E) 15 - 1910%F) 20 - 2913%G) 30 - 494%H) 50 - 996%I) 1004%0%1706.11.20145%10%15%20%25%Anteil der UnternehmenSTORM VERSORGER JAKOB MARGOLIS30%35%40%ANZAHLANTEILA) 1 - 2294%B) 3 - 58512%C) 6 - 924736%D) 10 -14548%E) 15 - 196810%F) 20 - 298813%G) 30 - 49274%H) 50 - 99406%I) 100264%J) k.A.264%

EXAMPLE 5: RISK DISTRIBUTION FOR ELECTRICITY PROVIDERS IN GERMANYAnzahl UnternehmenScore VerteilungANTEIL80OHNE SCORE7711,2%70SCORE 0 INSOLVENT121,7%MIT SCORE60187,1%605040302010001020304050Score60Anzahl Unternehmen18ANZAHL06.11.2014STORM VERSORGER JAKOB MARGOLIS708090100

EXAMPLE 6 - CONNECTION BETWEEN MACROECONOMIC INDICATOR(DAX-30) AND INDUSTRY RISK (BAD RATE) OF CONSTRUCTIONRisk (BR) of construction industry in Germany and 40,0000%20,0000%0,0000%DAX-3019Failure rate (BR)

EXAMPLE 7: GOVERNMENT DEFICIT (IN %) FROM INSOLV. RATE (AVG IN %)FOR ALL COMPANIES IN GERMANYGermany:Govern.deficit of 0082009Government deficit% of GDP*1.3- 2.8- 3.7- 4.0- 3.8- 3.3- 1.60.30.1- 3.0Insolv rate of .052010- 3.31.03Table and Charts of BSG, Bisnode Holding 032004200520062007200820092010- 010,8Staatl.Defizitquote%*Europe Commission, Eurostat 8.07.2011** Statistical office of Germany, 30.03.2011Year20102009200820Insolvency companies solv rate (BR%)of stat.officeGernamyInsolvenzquote StBA%Active companies 3,1 Mio.IR is 20.94%the best0.94%year1.10%1.19%1.26%1.27%Fin.crisis 11.21%1.04%0.91%- 020,6- 030,4- 040,2- 050

EXAMPLE-8: MEM WITH ARIMAX FÜR BR BAU Q MIT BWS BAU NPB(GROSS VALUE ADDED FOR CONSTRUCTION INDUSTRY GERMANY)21

EXAMPLE-9: MEM WITH VECTOR AUTOREGRESSION (VAR)BR FIN Q, BWS FIN, DAX30, BIP, ZINSEN EZB, EURO/USDMAIN PROBLEM IS RELATIONSHIP BETWEEN HISTORY SAMPLE (E.G. 42 Q), 6 VARIABLES AND TERMS IN VAR-MODEL22

EXAMPLE-11: MEM VALIDATION FOR 11 INDUSTRIES IN GERMANY:BR BISNODE VS. BR MEM23

EXAMPLE-12: THE FORECAST BR FOR SIC CONSTRUCTIONFROM Q3 2010 UNTILL Q2 2011WITH MACROECONOMIC MODELforecast24

EXAMPLE-13: GENERIC SCORECARD WITH MICRO- AND MACRO-ECONOMIC INDICATORSFINAL MODEL CONSISTS OF THE FOLLOWING VARIABLES:PD COMPANY F(SCORE TOTAL) (BASED ON MICRO-ECONOMIC INDICATORS: AGE, EMPLOY., REVENUE, PROFIT, TRADE, NEG. REM)RISK OF INDUSTRY (BR OR WOE);STATE UNEMPLOYMENT, ECT.Macro-economic indicators(GDP, DAX-30, Oil prise )Analysis of Maximum Likelihood quare Pr 0110,348303135,41 .0001-55,99score total10,01720,000264237,70 .000165,15SIC/Risk (WoE)10,58780,04650159,52 .000112,64unemployment/state1-0,00430,0006149,12 .0001-7,0225signific.signific.signific.

EXAMPLE 14: SIMULATION OF SCENARIOS AND STRESSTESTSCENARIO 1SCENARIO 2WHAT WILL HAPPEN TO PD AND RATING OFWHAT WILL HAPPEN TO PD AND RATING OFA TRANSPORT COMPANYA FINANCIAL COMPANYIF STRESSTEST (SHOCK):26IF STRESSTEST (SHOCK):OIL PRICE DECREASES TO 60 PER BARREL?THE ECB INTEREST RATE INCREASES TO 4%?OIL PRICE 60 VAR-MODEL RI SCORECARD PD RATING OF COMPANYINTEREST RATE 4% VAR-MODEL RI SCORECARD PD RATING OF COMP. RISK MIGRATION MATRIX FROM NOW TO RISK MIGRATION MATRIX FROM NOW TO 4 QUARTERS FORWARD 4 QUARTERS FORWARD

„FIGURES FIRST, WORDS SECOND“ CONTACT:DR. JAKOB MARGOLISSENIOR MODELERMARKETING & RISKBISNODE DEUTSCHLAND GMBHTEL.: 49 (0)6151 380 628MOBIL: 49 (0)151 58029567E-MAIL: [email protected]: ROBERT-BOSCH-STRAßE 1164293 DARMSTADTWWW.BISNODE.DE27

28

Stadtwerke Bad Vilbel GmbH Theodor-Heuss-Str. 51 61118 Bad Vilbel Stadtwerke Aschersleben GmbH Magdeburger Str. 26 06449 Aschersleben Stadtwerke Meinerzhagen Gesellschaft mit beschränkter Haftung Bahnhofstr. 17 58540 Meinerzhagen Stadtwerke Bad Wildbad GmbH &