# Sample conditional multivariate random variable?

There's multivariate random variable, future prices of assets, 5 years from now: $$X = [Gold, Silver, SP500]$$

There's historical prices for $$X$$ available for last 50 years. It's possible to fit historical prices to get multivariate probability distribution of future prices

$$P(X)$$

How to fit the multivariate conditional probability distribution? To get better prediction, as (let's suppose it is so) the current prices have predictive power for the future prices.

$$P(X|CurrentX)$$

I don't need the distribution itself, just the ability to sample $$X$$ given $$CurrentX$$. If that helps the individual prices have Pareto distribution.

• Bucket by ranges of currentX – Ezy Feb 1 at 11:47
• @Ezy but CurrentX is a vector, not scalar, how it could be bucketed? – Alex Craft Feb 1 at 11:56
• You can bucket a vector of variables. It’s just more buckets. But you need sufficient amount of data. – Ezy Feb 1 at 12:16