TimeScale Queries, aiohttp and asyncpg tutorials
asyncpg and aiohttp video
https://www.youtube.com/watch?v=2utibYV3oxA
TimeScale and PostgreSQL analytics and aggregates video
https://www.youtube.com/watch?v=BrYe-4QWjdc
Queries
Find a Stock We are Interested In
select * from stock where symbol = 'TWTR';
Look at the Price Data We Retrieved, observe that we have 5 minute
select * from stock_price where stock_id = 15117; select * from stock_price where stock_id = 15117 and date(dt) = '2021-01-25';
Delete pre-market and after hours
delete from stock_price where dt::timestamp::time < '06:30:00' or dt::timestamp::time >= '13:00:00';
What was the high and low for Twitter in our database?
select max(high) from stock_price where stock_id = 15117;
select min(low) from stock_price where stock_id = 15117;
What was the price at when it was added to ETF database?
select first(open, dt) from stock_price where stock_id = 15117 and date(dt) = '2021-01-26';
What did it close at?
select last(close, dt) from stock_price where stock_id = 15117;
What are some low volume stocks held by ARK ETFs?
select stock_id, symbol, sum(volume) as total_volume from stock_price join stock on stock.id = stock_price.stock_id where date(dt) = '2021-01-29' group by stock_id, symbol order by total_volume asc LIMIT 10;
Histogram - How many times did Twitter close below 50, above 52, or anywhere in between?
SELECT histogram(close, 50, 52, 4) FROM stock_price WHERE stock_id = 15117;
histogram
{8481,428,272,439,256,2138}
select count() from stock_price where stock_id = 15117 and close < 50; select count() from stock_price where close >= 50 and close < 50.5 and stock_id = 15117; select count(*) from stock_price where stock_id = 15117 and close > 52;
Time bucketing functions - get hourly bars
select time_bucket(INTERVAL '1 hour', dt) AS bucket, first(open, dt), max(high), min(low), last(close, dt) from stock_price where stock_id = 15117 group by bucket order by bucket desc;
select time_bucket(INTERVAL '20 minute', dt) AS bucket, first(open, dt), max(high), min(low), last(close, dt) from stock_price where stock_id = 15117 group by bucket order by bucket desc;
Filling Gaps / Missing Prices
SELECT time_bucket_gapfill('5 min', dt, now() - INTERVAL '5 day', now()) AS bar, avg(close) as close FROM stock_price WHERE stock_id = 7502 and dt > now () - INTERVAL '5 day' group by bar, stock_id order by bar;
Last Observation Carried Forward
SELECT time_bucket_gapfill('5 min', dt, now() - INTERVAL '5 day', now()) AS bar, locf(avg(close)) as close2 FROM stock_price WHERE stock_id = 7502 and dt > now () - INTERVAL '5 day' group by bar, stock_id order by bar;
Materialized Views
CREATE MATERIALIZED VIEW hourly_bars WITH (timescaledb.continuous) AS SELECT stock_id, time_bucket(INTERVAL '1 hour', dt) AS day, first(open, dt) as open, MAX(high) as high, MIN(low) as low, last(close, dt) as close, SUM(volume) as volume FROM stock_price GROUP BY stock_id, day;
CREATE MATERIALIZED VIEW daily_bars WITH (timescaledb.continuous) AS SELECT stock_id, time_bucket(INTERVAL '1 day', dt) AS day, first(open, dt) as open, MAX(high) as high, MIN(low) as low, last(close, dt) as close, SUM(volume) as volume FROM stock_price GROUP BY stock_id, day;
Show hourly bars for a particular stock
SELECT * FROM hourly_bars WHERE stock_id = 15117 ORDER BY hour desc;
Show daily bars for last 21 days
SELECT * FROM daily_bars WHERE day > (now() - interval '21 days') AND stock_id = 15117 ORDER BY day;
20 Day Moving Average
SELECT avg(close) FROM ( SELECT * FROM daily_bars WHERE stock_id = 15117 ORDER BY day DESC LIMIT 20 ) a;
Window Function - performs calculation across a set of table rows that are related to the current row
Moving average with Window Functions
SELECT day, AVG(close) OVER (ORDER BY day ROWS BETWEEN 19 PRECEDING AND CURRENT ROW) AS sma_20 FROM daily_bars WHERE stock_id = 15117 ORDER BY day DESC;
highest daily returns
WITH prev_day_closing AS ( SELECT stock_id, day, close, LEAD(close) OVER (PARTITION BY stock_id ORDER BY day DESC) AS prev_day_closing_price FROM daily_bars ), daily_factor AS ( SELECT stock_id, day, close / prev_day_closing_price AS daily_factor FROM prev_day_closing ) SELECT day, LAST(stock_id, daily_factor) AS stock_id, MAX(daily_factor) AS max_daily_factor FROM daily_factor JOIN stock ON stock.id = daily_factor.stock_id GROUP BY day ORDER BY day DESC, max_daily_factor DESC;
select all closes for Friday vs. Previous Close
SELECT stock_id, symbol, day, close, LAG (close,1) OVER (ORDER BY close ASC) AS previous_close FROM daily_bars JOIN stock ON stock.id = daily_bars.stock_id WHERE date(day) = '2021-02-05' ORDER BY stock_id, day;
Stocks that went down yesterday
SELECT * FROM ( SELECT stock_id, day, close, LEAD (close,1) OVER (PARTITION BY stock_id ORDER BY day DESC) AS previous_close FROM daily_bars ) a WHERE close < previous_close AND date(day) = '2021-02-05';
Stocks that sold off into the close (last 5 minutes of trading)
SELECT * FROM ( SELECT stock_id, dt, close, LEAD (close,1) OVER (PARTITION BY stock_id ORDER BY dt DESC) AS previous_close FROM stock_price ) a WHERE close < previous_close AND dt = '2021-02-05 12:55:00';
Bullish Engulfing Pattern
SELECT * FROM (
SELECT
day, open, close, stock_id,
LAG(close, 1) OVER (
PARTITION BY stock_id
ORDER BY day
) previous_close,
LAG(open, 1) OVER (
PARTITION BY stock_id
ORDER BY day
) previous_open
FROM
daily_bars
) a
WHERE previous_close < previous_open
AND close > previous_open AND open < previous_close
AND day = '2021-02-05';
Add Gamestop, Refresh Continous Aggregate
CALL refresh_continuous_aggregate('hourly_bars', '2020-10-01', '2021-03-01'); CALL refresh_continuous_aggregate('daily_bars', '2020-10-01', '2021-03-01');
Closed higher 3 times on higher volume
SELECT * FROM ( SELECT day, close, volume, stock_id, LAG(close, 1) OVER ( PARTITION BY stock_id ORDER BY day ) previous_close, LAG(volume, 1) OVER ( PARTITION BY stock_id ORDER BY day ) previous_volume, LAG(close, 2) OVER ( PARTITION BY stock_id ORDER BY day ) previous_previous_close, LAG(volume, 2) OVER ( PARTITION BY stock_id ORDER BY day ) previous_previous_volume FROM daily_bars ) a WHERE close > previous_close AND previous_close > previous_previous_close AND volume > previous_volume AND previous_volume > previous_previous_volume AND day = '2021-01-22';
Gamestonk Query
SELECT * FROM ( SELECT day, close, volume, stock_id, LAG(close, 1) OVER ( PARTITION BY stock_id ORDER BY day ) previous_close, LAG(volume, 1) OVER ( PARTITION BY stock_id ORDER BY day ) previous_volume, LAG(close, 2) OVER ( PARTITION BY stock_id ORDER BY day ) previous_previous_close, LAG(volume, 2) OVER ( PARTITION BY stock_id ORDER BY day ) previous_previous_volume, LAG(close, 3) OVER ( PARTITION BY stock_id ORDER BY day ) previous_previous_previous_close, LAG(volume, 3) OVER ( PARTITION BY stock_id ORDER BY day ) previous_previous_previous_volume FROM daily_bars ) a WHERE close > previous_close AND previous_close > previous_previous_close AND previous_previous_close > previous_previous_previous_close AND volume > previous_volume AND previous_volume > previous_previous_volume AND previous_previous_volume > previous_previous_previous_volume AND day = '2021-02-05';
Three Bar Breakout
SELECT * FROM ( SELECT day, close, volume, stock_id, LAG(close, 1) OVER ( PARTITION BY stock_id ORDER BY day ) previous_close, LAG(volume, 1) OVER ( PARTITION BY stock_id ORDER BY day ) previous_volume, LAG(close, 2) OVER ( PARTITION BY stock_id ORDER BY day ) previous_previous_close, LAG(volume, 2) OVER ( PARTITION BY stock_id ORDER BY day ) previous_previous_volume, LAG(close, 3) OVER ( PARTITION BY stock_id ORDER BY day ) previous_previous_previous_close, LAG(volume, 3) OVER ( PARTITION BY stock_id ORDER BY day ) previous_previous_previous_volume FROM daily_bars ) a WHERE close > previous_previous_previous_close and previous_close < previous_previous_close and previous_close < previous_previous_previous_close AND volume > previous_volume and previous_volume < previous_previous_volume and previous_previous_volume < previous_previous_previous_volume AND day = '2021-02-05';