MySQL query optimization

I am mid way through a personal web development project and have a MySQL query I need help with.

I have two tables:

CREATE TABLE `share_prices` (
`price_id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`price_date` date NOT NULL,
`company_id` int(10) NOT NULL,
`high` decimal(20,2) DEFAULT NULL,
`low` decimal(20,2) DEFAULT NULL,
`close` decimal(20,2) DEFAULT NULL,
PRIMARY KEY (`price_id`),
UNIQUE KEY `price_date` (`price_date`,`company_id`),
KEY `company_id` (`company_id`),
KEY `price_date_2` (`price_date`)
) ENGINE=InnoDB AUTO_INCREMENT=368586 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

And,

CREATE TABLE `rating_lookup` (
`rating_id` int(11) NOT NULL,
`start_date` date DEFAULT NULL,
`start_price` decimal(10,2) DEFAULT NULL,
`broker_id` int(11) DEFAULT NULL,
`company_id` int(11) DEFAULT NULL,
`end_date` date DEFAULT NULL,
PRIMARY KEY (`rating_id`),
KEY `idx_rating_lookup_company_id` (`company_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;


This is the current query:



SELECT broker_id, count(rating_id)

FROM (

SELECT rating_lookup.*,
share_prices.company_id as correct_company,
share_prices.price_date,
max(high) as peak_gain,
( ( ( max(high) - rating_lookup.start_price ) / rating_lookup.start_price ) * 100 ) as percent_gain

FROM rating_lookup, share_prices

WHERE share_prices.price_date > rating_lookup.start_date
AND share_prices.price_date 5

) correct

GROUP BY broker_id


Currently this query takes 0.391 sec (duration) / 10.438 sec (fetch)


The objective is:

To get the total amount of correct ratings per broker_id

A correct rating is defined as a rating that has a reached + 5% since its start_price.