Relative Strength Index Wikipedia.
Gain and loss averages use Wilder's smoothing (an RMA seeded with the
SMA of the first period changes), matching TA-Lib. nil is returned
when there is not enough data or the window has no movement (RSI is
undefined). See TAlib for the input conventions.
Summary
Functions
Wilder-smoothed average gain over the period newest price changes.
Wilder-smoothed average loss over the period newest price changes.
Sum of gains across consecutive prices, oldest first.
Warm up streaming RSI state from history.
Sum of losses across consecutive prices, oldest first.
Advance streaming RSI state by one price, in O(1).
Calculate RSI over the period newest price changes, with Wilder's
smoothing (matching TA-Lib).
Calculate RSI for each point of a price series in a single pass (Wilder-smoothed gain/loss averages).
Functions
@spec average_gain([number()], pos_integer()) :: float() | nil
Wilder-smoothed average gain over the period newest price changes.
Parameters
- prices: list of prices, oldest first.
- period: lookback window, a positive integer (default 14).
Examples
iex> TAlib.Indicators.RSI.average_gain([1, 2, 3, 4, 5, 6], 3) |> Float.round(4)
1.0@spec average_loss([number()], pos_integer()) :: float() | nil
Wilder-smoothed average loss over the period newest price changes.
Parameters
- prices: list of prices, oldest first.
- period: lookback window, a positive integer (default 14).
Examples
iex> TAlib.Indicators.RSI.average_loss([6, 1, 4, 2, 5, 3], 3) |> Float.round(4)
1.7037Sum of gains across consecutive prices, oldest first.
Examples
iex> TAlib.Indicators.RSI.gain([0, 10, 20, 30])
30@spec init([number()], pos_integer()) :: {TAlib.Indicators.RSI.State.t(), [float() | nil]}
Warm up streaming RSI state from history.
Returns {state, values} with values the full RSI series of
history (identical to rsi_list/2), and state ready to continue
it one price at a time in O(1) via next/2. History needs more than
period prices (the first period changes form the seed).
Examples
iex> {state, values} = TAlib.Indicators.RSI.init([1, 2, 3, 4, 5], 3)
iex> values
[nil, nil, nil, 100.0, 100.0]
iex> {_state, 100.0} = TAlib.Indicators.RSI.next(state, 6)Sum of losses across consecutive prices, oldest first.
Examples
iex> TAlib.Indicators.RSI.loss([40, 30, 20, 10])
30@spec next(TAlib.Indicators.RSI.State.t(), number()) :: {TAlib.Indicators.RSI.State.t(), float() | nil}
Advance streaming RSI state by one price, in O(1).
iex> {state, _} = TAlib.Indicators.RSI.init([1, 2, 3, 4, 5], 3)
iex> {_state, value} = TAlib.Indicators.RSI.next(state, 6)
iex> value
100.0@spec rsi([number()], pos_integer()) :: float() | nil
Calculate RSI over the period newest price changes, with Wilder's
smoothing (matching TA-Lib).
Parameters
- prices: list of prices, oldest first.
- period: lookback window, a positive integer (default 14).
Examples
iex> TAlib.Indicators.RSI.rsi([1, 2, 3, 4, 5, 6], 3)
100.0
iex> TAlib.Indicators.RSI.rsi([6, 1, 4, 2, 5, 3], 3) |> Float.round(4)
39.4737@spec rsi_list([number()], pos_integer()) :: [float() | nil]
Calculate RSI for each point of a price series in a single pass (Wilder-smoothed gain/loss averages).
Returns a list aligned with data: the first period entries are nil,
and every later entry is the RSI of the window ending at that point.
Parameters
- data: list of prices, oldest first.
- period: lookback window, a positive integer (default 14).
Examples
iex> TAlib.Indicators.RSI.rsi_list([1, 2, 3, 4, 5], 3)
[nil, nil, nil, 100.0, 100.0]