Yes, it is possible but the array type should be JuMP.VariableRef. Here zeros(100) creates an array of Float64 and JuMP.VariableRef is not convertible to Float64.
You can try

using JuMP
model = Model()
@variable(model, x)
arr = Vector{JuMP.VariableRef}(undef, 100)
arr[1] = x

@variable(m, delta0)
amort = delta0/T
bal = Vector{JuMP.VariableRef}(undef, 100)
bal[1] = delta0
for i = 2:100
bal[i] = bal[i-1] - amort
end

I can now assign a decision variable to the first array position bal[1], but for the following positions from [2] onwards, I need to deduct a certain value amort. But I get an error MethodError: Cannot convert an object of type GenericAffExpr{Float64,VariableRef} to an object of type VariableRef
So I asked about this in a previous post and someone advised to use regular zeros array, and that allowed me to subtract amort from bal[1]. So I have this dilemma, where I need a JuMP array for decision variable storage, but also need the properties of a zeros array, and am not sure what to do.
If someone can please help, it would be greatly appreciated. This is the link to my other related question: https://discourse.julialang.org/t/for-loop-error/26210/7