Efficient way to reconstruct base table from changes - postgresql

Question

I have a table consisting of products (with ID's, ~15k records) and another table price_changes (~88m records) recording a change in the price for a given productID at a given changedate.
I'm now interested in the price for each product at given points in time (say every 2 hours for a year, so altogether ~ 4300 points; altogether resulting in ~64m data points of interest). While it's very straight forward to determine the price for a given product at a given time, it seems to be quite time-consuming to determine all 64m data points.
My approach is to pre-populate a new target table fullprices with the data points of interest:
insert into fullprices(obsdate,productID)
select obsdate, productID from targetdates, products
and then update each price observation in this new table like this:
update fullprices f set price = (select price from price_changes where
productID = f.productID and date < f.obsdate
order by date desc
limit 1)
which should give me the most recent price change in each point in time.
Unfortunately, this takes ... well, ages. Is there any better way to do it?
== Edit: My tables are created as follows: ==
CREATE TABLE products
(
productID uuid NOT NULL,
name text NOT NULL,
CONSTRAINT products_pkey PRIMARY KEY (productID )
);
CREATE TABLE price_changes
(
id integer NOT NULL,
productID uuid NOT NULL,
price smallint,
date timestamp NOT NULL
);
CREATE INDEX idx_pc_date
ON price_changes USING btree
(date);
CREATE INDEX idx_pc_productID
ON price_changes USING btree
(productID);
CREATE TABLE targetdates
(
obsdate timestamp
);
CREATE TABLE fullprices
(
obsdate timestamp NOT NULL,
productID uuid NOT NULL,
price smallint
);