Det samme gør sig gældende i den stokastiske model som nævnt ovenfor, men her tilføres der en ekstra dimension. I den tilhørende Excel fil ses modellen og udregningerne der er anvendt til at estimere BWS. Der tilføjes 3 variable; olieprisen, USD og EUR.
Her simuleres s˚a den fremtidige udvikling i hver variabel (et kvalificeret gæt).
De 3 variable lægges sammen s˚a det blivet ´et procenttal og trækkes s˚a fra (1−p). Tallet ganges s˚a p˚a omkostningssiden. Det giver et billede af hvordan den systematiske risiko tilhørende de 3 variable kan p˚avirke BWS.
Figur 21: Egen tilvirkning]
De celler der er markeret med gult, er dem der er blevet forklaret og der skal gøres opmærksom p˚a at hvergang der trykkes p˚a F9 s˚a ændre tallene sig fordi det aktiver simuleringerne.
14 Konklusion
Form˚alet med afhandlingen, er at undersøge om det p˚avirker resultatet for værdiansæt-telsen, ved at tilføre 3 variable. Første fase begyndes med en fundamental analyse af Blue Water Shipping. Den næste fase, er s˚a at anvende den deterministiske DCF-model og beregne virksomhedsværdien. Tredje fase er at koble Monte Carlo simuleringer p˚a DCF-modellen og beregne virksomhedsværdien.
Inden anden og tredje fase kunne begyndes blev værdien i basistilstanden estimeret p˚a baggrund af en opstillet proformabudget som tog udgangspunkt i de re-formulerede opgørelser samt rentabilitetsanalysen.
Resultaterne i de 2 modeller sættes s˚a op i mod hinanden. Forskellen p˚a resultaterne er store. Euroen har ikke den store p˚avirkning fordi den Danmark har fastkurspolitik som er opbundet af euroen, men valutaen tages alligevel med fordi regnskaberne fra BWS er opgivet i DKK.
P˚a baggrund af resultaterne, kan der ikke drages en endelig beslutning, i forhold til op-gavens overskrift. Virksomhedens værdi bliver højere n˚ar olien og dollaren stiger fordi det mindsker omkostningerne.
Monte Carlo simuleringen er en godt værktøj og giver en bedre forst˚aelse af risikoen, men modellen kræver korrekte datainput tilført for at kunne virke optimal.
15 Referencer
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