Analyse trend for aggregate

API Catalog//

Analyse trend for aggregate

Request

Perform linear regression trend analysis on an aggregate's metric (Testing).

Security

HTTPBearer

Bodyapplication/jsonrequired

aggregate_idinteger, > 0(Aggregate Id)required

Aggregate ID

intervalstring(IntervalEnum)

Time interval

Default:"1d"

Enum:"10min""30min""1h""1d""1w""1m""1y"

start_datestring, (date-time)(Start Date)required

Start date

end_datestring, (date-time)(End Date)required

End date

metricstring(Metric)

Metric to analyse

Default:"retail_net_turnover"

asset_classstring(AssetClassEnum)

Asset class

Default:"cash"

Enum:"all""cash""options"

curl -i -X POST \
  https://docs.vanda-analytics.com/_mock/apis/aggregates/vanda-msvc-aggregates/aggregates/analytics/trend \
  -H 'Authorization: Bearer <YOUR_TOKEN_HERE>' \
  -H 'Content-Type: application/json' \
  -d '{
    "aggregate_id": 1,
    "interval": "10min",
    "start_date": "2019-08-24T14:15:22Z",
    "end_date": "2019-08-24T14:15:22Z",
    "metric": "retail_net_turnover",
    "asset_class": "all"
  }'

Responses

Successful Response

Bodyapplication/json

aggregate_idinteger(Aggregate Id)required

Aggregate ID

vanda_idstring(Vanda Id)required

Vanda identifier

trend_directionstring(Trend Direction)^(up|down|neutral)$required

Trend direction (up, down, neutral)

slopenumber(Slope)required

Linear regression slope

r_squarednumber, [ 0 .. 1 ](R Squared)required

R-squared value (0-1)

p_valuenumber, [ 0 .. 1 ](P Value)required

Statistical p-value

data_pointsinteger, >= 0(Data Points)required

Number of data points

start_valuenumber(Start Value)required

First value in series

end_valuenumber(End Value)required

Last value in series

percent_changenumber or null(Percent Change)

Any of:

Percentage change from start to end

number

metricstring(Metric)required

Metric analysed

intervalstring(Interval)required

Time interval

Response

{
  "aggregate_id": 0,
  "vanda_id": "string",
  "trend_direction": "string",
  "slope": 0,
  "r_squared": 0,
  "p_value": 0,
  "data_points": 0,
  "start_value": 0,
  "end_value": 0,
  "percent_change": 0,
  "metric": "string",
  "interval": "string"
}