This guide explains how market signals are generated.
If one has entered the market long by issuing a buy, this is what a sell with StopTrail and trailamount does: If no price is specified, the latest close price is used trailamount is substracted from the price to find the stop (or trigger) price The next iteration of the broker checks if the trigger price has been reached
If Yes: the order is executed with a Market execution type approach
If No, the stop price is recalculated by using the latest close price and substracting the trailamount distance
If the new price goes up, it is updated
If the new price would go down (or not change at all), it is discarded
That is: the trailing stop price follows the price upwards, but remains fixed if the prices start falling, to potentially secure a profit.
If one had entered the market with a sell, then issuing a buy order with StopTrail simply does the opposite, i.e.: prices are followed downwards.
Example:
EMA CrossOver
Results will match records with the terms EMA
or CrossOver in any field. Note that stemming
is applied so e.g. EMA will also match
CrossOver. Search results are ranked according to an algorithm
that takes your query terms into account.
You can require presence of both terms using either the
+ or AND operator:
Examples:
+business +services
or
business AND services
You can require absence of one or more terms using either the
- or NOT operator:
Examples:
-EMA +CrossOver
or
NOT EMA AND CrossOver
Example:
"business services"
Results will match records with the phrase
business services in any field.
Example:
metadata.title:Broadcom
Results will match records with the term Broadcom in the
field metadata.title. If you want to search for multiple terms
in the title you must group the terms using parenthesis:
Example:
metadata.title:(Broadcom Microsoft)
Example:
metadata.publication_date:[2022-01-01 TO 2022-02-01]
(note, you must capitalize TO).
Results will match any record with a publication date between 2021-01-01 and 2022-01-01 (both dates inclusive).
Note that, partial dates are expanded to full dates, e.g.:
Use square brackets ([]) for inclusive ranges and use
curly brackets ({}) for exclusive ranges, e.g.:
[2017 TO 2018} is equivalent to
[2017-01-01 TO 2017-12-31] because of date expansion and
exclusive upper bound.
Examples of other ranges:
metadata.publication_date:{* TO 2022-01-01}: All days until 2022.
metadata.publication_date:[2022-01-01 TO *]: All days from 2022.
By default all searches are sorted according to an internal ranking algorithm that scores each match against your query. In both the user interface and REST API, it's possible to sort the results by:
You can use the boost operator ^ when one term is more relevant
than another. For instance, you can search for all records with the phrase
business services in either title or
description field, but rank records with the phrase in the
title field higher:
Example:
metadata.title:"corporation"^5 metadata.description:"business services"