# TDI

##### Trend Detection Index

The Trend Detection Index (TDI) attempts to identify starting and ending trends. Developed by M. H. Pee.

- Keywords
- ts

##### Usage

`TDI(price, n = 20, multiple = 2)`

##### Arguments

- price
Price series that is coercible to xts or matrix.

- n
Number of periods to use.

- multiple
Multiple used to calculate (2).

##### Details

The TDI is the (1) absolute value of the `n`

-day sum of the `n`

-day
momentum, minus the quantity of (2) `multiple`

*`n`

-day sum of the
absolute value of the `n`

-day momentum, minus (3) `n`

-day sum of
the absolute value of the `n`

-day momentum.

I.e. TDI = (1) - [ (2) - (3) ]

The direction indicator is the sum of the `n`

-day momentum over the last
`n`

days.

See URL in references section for further details.

##### Value

A object of the same class as `price`

or a matrix (if
`try.xts`

fails) containing the columns:

- tdi
The Trend Detection Index.

- di
The Direction Indicator.

##### Note

Positive/negative TDI values signal a trend/consolidation. A positive/ negative direction indicator signals a up/down trend. I.e. buy if the TDI and the direction indicator are positive, and sell if the TDI is positive while the direction indicator is negative.

##### References

The following site(s) were used to code/document this indicator: http://www.linnsoft.com/tour/techind/tdi.htm

##### See Also

See `aroon`

, `CCI`

, `ADX`

,
`VHF`

, `GMMA`

for other indicators that measure trend
direction/strength.

##### Examples

`library(TTR)`

```
# NOT RUN {
data(ttrc)
tdi <- TDI(ttrc[,"Close"], n=30)
# }
```

*Documentation reproduced from package TTR, version 0.23-1, License: GPL-2*