Zero-Lag Exponential Moving Average

Function Prototype

/* Zero-Lag Exponential Moving Average */
/* Type: overlay */
/* Input arrays: 1    Options: 1    Output arrays: 1 */
/* Inputs: real */
/* Options: period */
/* Outputs: zlema */
int ti_zlema_start(TI_REAL const *options);
int ti_zlema(int size,
      TI_REAL const *const *inputs,
      TI_REAL const *options,
      TI_REAL *const *outputs);

Description

This documentation is still a work in progress. It has omissions, and it probably has errors too. If you see any issues, or have any general feedback, please get in touch.

Zero-Lag Exponential Moving Average modifies a Exponential Moving Average to greatly reduce lag.

It takes one parameter, the period n.

It is calculated for each bar as follows:

See Also

• Exponential Moving Average

References

• Wikipedia: Zero Lag Exponential Moving Average
• Stocks & Commodities V. 28:11 (30-35): Zero Lag (Well, Almost) by John Ehlers and Ric Way
• Wikipedia: Exponential Smoothing

Example Usage

Calling From C

/* Example usage of Zero-Lag Exponential Moving Average */
/* Assuming that 'input' is a pre-loaded array of size 'in_size'. */
TI_REAL *inputs[] = {input};
TI_REAL options[] = {5}; /* period */
TI_REAL *outputs[1]; /* zlema */

/* Determine how large the output size is for our options. */
const int out_size = in_size - ti_zlema_start(options);

/* Allocate memory for output. */
outputs[0] = malloc(sizeof(TI_REAL) * out_size); assert(outputs[0] != 0); /* zlema */

/* Run the actual calculation. */
const int ret = ti_zlema(in_size, inputs, options, outputs);
assert(ret == TI_OKAY);

Calling From Lua (with Tulip Chart bindings)

-- Example usage of Zero-Lag Exponential Moving Average
zlema = ti.zlema(input, 5)

Example Calculation

period = 5

Chart

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