I'm trying to implement an exponential moving average (EMA) on postgres, but as I check documentation and think about it the more I try the more confused I am.
The formula for EMA(x)
is:
EMA(x1) = x1 EMA(xn) = α * xn + (1 - α) * EMA(xn-1)
It seems to be perfect for an aggregator, keeping the result of the last calculated element is exactly what has to be done here. However an aggregator produces one single result (as reduce, or fold) and here we need a list (a column) of results (as map). I have been checking how procedures and functions work, but AFAIK they produce one single output, not a column. I have seen plenty of procedures and functions, but I can't really figure out how does this interact with relational algebra, especially when doing something like this, an EMA.
I did not have luck searching the Internets so far. But the definition for an EMA is quite simple, I hope it is possible to translate this definition into something that works in postgres and is simple and efficient, because moving to NoSQL is going to be excessive in my context.
Thank you.
PD: here you can see an example:
https://docs.google.com/spreadsheet/ccc?key=0AvfclSzBscS6dDJCNWlrT3NYdDJxbkh3cGJ2S2V0cVE
Finally, the following formula is used to calculate the current EMA: EMA = Closing price x multiplier + EMA (previous day) x (1-multiplier)
For each iteration, the value of @today_ema is set equal to α times the current row's time series value plus (1 – α) times the exponential moving average from the prior row. Then, an update statement revises the ema value for the current row to the value of @today_ema.
The exponential moving average (EMA) is a technical chart indicator that tracks the price of an investment (like a stock or commodity) over time. The EMA is a type of weighted moving average (WMA) that gives more weighting or importance to recent price data.
The second part of the query (in black text) is the calculation of the rolling average. Similarly to the first example, we use the AVG() window function and the clause OVER(ORDER BY day ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) . This applies the AVG() function to the current row and the nine rows before it.
You can define your own aggregate function and then use it with a window specification to get the aggregate output at each stage rather than a single value.
So an aggregate is a piece of state, and a transform function to modify that state for each row, and optionally a finalising function to convert the state to an output value. For a simple case like this, just a transform function should be sufficient.
create function ema_func(numeric, numeric) returns numeric
language plpgsql as $$
declare
alpha numeric := 0.5;
begin
-- uncomment the following line to see what the parameters mean
-- raise info 'ema_func: % %', $1, $2;
return case
when $1 is null then $2
else alpha * $2 + (1 - alpha) * $1
end;
end
$$;
create aggregate ema(basetype = numeric, sfunc = ema_func, stype = numeric);
which gives me:
steve@steve@[local] =# select x, ema(x, 0.1) over(w), ema(x, 0.2) over(w) from data window w as (order by n asc) limit 5;
x | ema | ema
-----------+---------------+---------------
44.988564 | 44.988564 | 44.988564
39.5634 | 44.4460476 | 43.9035312
38.605724 | 43.86201524 | 42.84396976
38.209646 | 43.296778316 | 41.917105008
44.541264 | 43.4212268844 | 42.4419368064
These numbers seem to match up to the spreadsheet you added to the question.
Also, you can define the function to pass alpha as a parameter from the statement:
create or replace function ema_func(state numeric, inval numeric, alpha numeric)
returns numeric
language plpgsql as $$
begin
return case
when state is null then inval
else alpha * inval + (1-alpha) * state
end;
end
$$;
create aggregate ema(numeric, numeric) (sfunc = ema_func, stype = numeric);
select x, ema(x, 0.5 /* alpha */) over (order by n asc) from data
Also, this function is actually so simple that it doesn't need to be in plpgsql at all, but can be just a sql function, although you can't refer to parameters by name in one of those:
create or replace function ema_func(state numeric, inval numeric, alpha numeric)
returns numeric
language sql as $$
select case
when $1 is null then $2
else $3 * $2 + (1-$3) * $1
end
$$;
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