Say I want to forecast retail stock for 1 month, on daily basis. The error will be calculated using SMAPE, but I would weight the error using recency, i.e., the nearer the weight from now the higher weight. Is there a good weightage scheme I could I adopt?
What is "good" will depend on what you want to do with your forecast. This has been called the "Cost of Forecast Error".
Another important aspect is whether it needs to be explainable to your (possibly non-technical) audience. (Or whether you want to impress them with your math-fu.)
Something like an exponentially decaying weighting scheme may make sense: weight next week's forecasts with $1$, the week's after with $0.9$, then $0.9^2=0.81$ and so forth.