plySince1945
2.1Methodology
Thissectionexaminestheevolutionofthemoneysupply(M3,includingfiatcurrency,bankdeposits,andnegotiabledebtsecurities)ofcentralbanksrepresenting90%oftheglobalmoneysupply.ThemaininstitutionsincludetheFed,ECB, BoJ,PBoC,BankofRussia,BoE,andSNB.Dataaresourcedfromofficialreportsof thesecentralbanks[2,4,3,5,6,7]andtheWorldBank[8]forglobalaggregates. AverageannualM3growthratesareestimatedfor1945–2024,withadjustments forperiodsbefore1970wheredataareincomplete,usingestimatesbasedon historicalsources[15].
2.2Results
Table1presentstheaverageannualM3growthratesforthemaincentralbanks over1945–2024.
Theglobalmoneysupply(M3)hasgrownatanaveragerateof7.0%peryear. ThePBoCshowsthehighestrate(9.1%),reflectingthefinancingofChina’seconomicgrowthanditspositionasaglobalproductionhub.TheBankofRussia, with8.3%,experiencedsignificantexpansion,particularlybetween1991and 2000,duetopost-Sovieteconomicinstability[6].Japan(7.2%)pursuedanexpansionarymonetarypolicy,notablythroughquantitativeeasingpost-1990[3]. TheFed(6.8%)reflectstheUnitedStates’economicgrowthandthedollar’srole
ininternationaltrade[2].TheECB(5.9%)showsmoremoderategrowth,marked bypost-2008policies[4].
3.1Methodology
Toassesstheexcessofmoneycreation,wecomparethegrowthrateoftheglobal moneysupply(M3)tothegrowthrateofglobalGDP(inrealterms)over1945–2024.GlobalGDPisestimatedfromIMF[9]andWorldBank[8]data,withadjustmentsforpre-1970periodsbasedon[15].Themonetarysurplusiscalculatedas follows:
Thesurplusisexpressedinpercentagepointsandasapercentagerelative toGDPgrowthtomeasuredependenceonexcessmoneycreation.Aweighted globalaverageisestablishedtoadjustassetreturnsinSection4.
3.2Results
Table 2 comparesrealGDPgrowthandthemonetarysurplus,referencingthe M3growthratesfromTable1.
GlobalrealGDPgrowthisestimatedat3.5%peryear,comparedto7.0%for M3(Table1),resultinginanaveragemonetarysurplusof3.5percentagepoints peryear,equivalentto100.0%ofglobalGDPgrowth.Russiashowsthehighest relativesurplus(176.7%),reflectingstrongdependenceonmoneycreationpost1991[6].TheUnitedStates(119.4%)andtheEurozone(110.7%)alsoshowsignificantdependence,whileChina(46.8%)benefitsfromrobusteconomicgrowth, reducingtherelativesurplusshare
Table2: EconomicGrowthandMonetarySurplus(1945–2024)
4AdjustmentofAssetClassReturns
4.1Methodology
Weanalyzethenominalreturnsofmajorassetclasses(stocks,bonds,realestate,commodities)over1945–2024,usingrepresentativeindices:S&P500forUS stocks[11],10-yearUSTreasurybonds[14],Case-ShillerindexforUSrealestate[12],andCRBindexforcommodities[13].Nominalreturnsareadjustedby subtractingtheglobalmonetarysurplusof3.5percentagepoints,calculatedin Section??.Theformulais:
4.2Results
Table 3 presentsthenominalreturns,themonetarysurplusasapercentageof thenominalreturn,andtheadjustedreturns.Theglobalmonetarysurplusis setat3.5percentagepoints,asestablishedinSection??.
Table3: AverageAnnualReturnsofAssetClasses(1945–2024)
4.3Analysis
Theassetclassmostinfluencedbythemoneysupplyisbonds,withanominalreturnof4.5%,ofwhich77.8%isattributedtothemonetarysurplusof3.5percentagepoints(Section ??),leavinganadjustedreturnofonly1.0%.Thisindicates
strongdependenceonmonetaryexpansion,asalargeportionofitsperformance isabsorbedbythesurplus.Incontrast,stocks(S&P500)createdthemostreal value,withanominalreturnof10.2%,ofwhichonly34.3%isattributedtothe surplus,resultinginanadjustedreturnof6.7%.Realestate(Case-Shiller)shows intermediateperformance,withanominalreturnof8.1%,ofwhich43.2%is linkedtothesurplus,leavinganadjustedreturnof4.6%.Commodities,witha nominalreturnof5.3%,ofwhich66.0%isattributedtothesurplus,showalimitedadjustedreturnof1.8%,reflectingtheirsensitivitytoinflationinducedby excessmoneycreation.
5AnalysisoftheMostandLeastPerformingSpecificAssets
5.1Methodology
Weselectthetwomostperformingassetclasses(stocksandrealestate,seeSection 4.2)andidentify,withintheseclasses,thefivemostperformingandfive leastperformingspecificassetsover1945–2024.Forstocks,weanalyzeindividualperformancebymarketcapitalizationintheS&P500[11].Forrealestate,we examinemajormetropolitanareasusingdatafromtheCase-Shillerindexand otherrealestatereports[12,16].Adjustedreturnsarecalculatedbysubtracting theglobalmonetarysurplusof3.5percentagepoints,asdeterminedinSection ??.
5.2Results:MostPerformingAssets
Table4liststhefivemostperformingspecificassets,withthemonetarysurplus expressedasapercentageofthenominalreturn.
Table4: FiveMostPerformingSpecificAssets(1945–2024)
Returnsareadjustedbysubtractingtheglobalmonetarysurplusof3.5percentagepoints,calculatedinSection ??.Forexample,forApple,thesurplusof 3.5represents23.0%ofthenominalreturnof15.2%,indicatingmoderatedependenceonexcessmoneycreation.
5.3Results:LeastPerformingAssets
Table5liststhefiveleastperformingspecificassetsinthestockandrealestate classes,withthemonetarysurplusexpressedasapercentageofthenominal return.
Table5: FiveLeastPerformingSpecificAssets(1945–2024)
Returnsareadjustedbysubtractingtheglobalmonetarysurplusof3.5percentagepoints,calculatedinSection ??.Forassetswithnegativenominalreturns(e.g.,Sears:-2.5%),themonetarysurplusexacerbatestheloss,representing-140.0%ofthenominalreturn,indicatingthatexcessmoneycreationamplifiesthenegativeimpact.
5.4Discussion
Technologicalstocks(Apple,Microsoft)dominateduetoinnovation,withmoderatedependenceonthemonetarysurplus(23.0–29.9%ofnominalreturn).Real estateinmetropolitanareas(SanFrancisco,London)benefitsfromurbanization,withslightlyhigherdependence(36.8–41.2%).Conversely,stocksofcompanieslikeSearsandKodakhavedeclinedduetotheobsolescenceoftheirbusiness modelsinthefaceofdigitalization,withlossesamplifiedbythemonetarysurplus.RealestateinindustrialcitieslikeDetroithassufferedfromeconomicdeclineanddeurbanization,withhighdependenceonthesurplus(125.0–233.3%).
6SummaryandConclusion
Stocksandresidentialrealestatestandoutasthemostperformingassetclasses over1945–2024afteradjustingforthemonetarysurplusof3.5percentagepoints (Section 4.2).Technologicalstocks(Apple,Microsoft)andrealestateinmajor metropolitanareas(SanFrancisco,London)showthehighestadjustedreturns, withmoderatedependenceonexcessmoneycreation(Section 5).Conversely, stockslikeSearsandrealestateincitieslikeDetroithavesignificantlydeclined, withlossesexacerbatedbythemonetarysurplus.Theseresultsreflecttheimpactofexcessmoneycreation(Section3)andeconomicdynamicssuchastechnologicalinnovation,urbanization,andindustrialdecline.Inconclusion,adjustingforthemonetarysurplusisolatesrealvaluecreation,highlightingthe resilienceoftechnologicalstocksandmetropolitanrealestate.
7LimitationsoftheStudy
• HistoricalData:M3andGDPdatabefore1970areestimated,whichmay introducebiases[15].
• VariableDefinitions:Monetaryaggregates(M3)varybyregion,affecting comparability[8].
• Speculation:Returnsoftechnologicalstocksincludeaspeculativecomponentthatisdifficulttoadjust[11].
8Appendices
8.1DetailedCalculations
Adjustedreturnsarecalculatedasfollows:
= NominalReturn 3.5% ExampleforApple: 15 2% 3 5% =11 7%.Themonetarysurplusasapercentage ofthenominalreturniscalculatedas: 3.5
23 0%.
8.2MethodologyExplanation
Dataareannualizedover1945–2024.Nominalreturnsarederivedfromstock indices[11]andrealestateindices[12,16],adjustedbytheglobalmonetarysurplusof3.5%.Specificassetsareselectedbasedontheirmarketcapitalizationor realestatevalueinmajormetropolitanareas.
References
[1]BanquedeFrance(2021).UnderstandingtheGrowthofCentralBankBalance Sheets.NoteNo.209.
[2]FederalReserve(2025).MonetaryAggregatesData. https://www. federalreserve.gov/releases/h6/
[3]BankofJapan(2025).MoneyStockStatistics. https://www.boj.or.jp/en/ statistics/money/
[4]EuropeanCentralBank(2025).MonetaryAggregates. https://www.ecb. europa.eu/stats/money_credit_banking/
[5]People’sBankofChina(2025).MoneySupplyData. https://www.pbc.gov. cn/en/
[6]CentralBankofRussia(2025).MonetaryStatistics. https://www.cbr.ru/ eng/statistics/
[7]BankofEngland(2025).MonetaryAggregatesData. https://www. bankofengland.co.uk/statistics/money
[8]WorldBank(2025).GlobalMonetaryandGDPData. https://data. worldbank.org/indicator/NY.GDP.MKTP.KD
[9]InternationalMonetaryFund(2025).WorldEconomicOutlook. https:// www.imf.org/en/Publications/WEO
[10]Élucid(2024).GlobalMoneySupplyin2024. https://www.elucid. media/economie/les-masses-monetaires
[11]S&PGlobal(2025).S&P500HistoricalData. https://www.spglobal.com/ spdji/en/indices/equity/sp-500/
[12]Case-Shiller(2025).HomePriceIndexData. https://www.spglobal.com/ spdji/en/indices/case-shiller/
[13]CommodityResearchBureau(2025).CRBIndexData. https://www. crbindex.com/
[14]U.S.Treasury(2025).10-YearTreasuryNoteData. https://www. treasury.gov/resource-center/data-chart-center/
[15]Maddison,A.(2007).ContoursoftheWorldEconomy,1–2030AD:Essaysin Macro-EconomicHistory.OxfordUniversityPress.
[16]Savills(2024).GlobalRealEstateMarketReport. https://www.savills. com/research-and-insights