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Following Adaptive Moving Average (FAMA)

Install and import#

bash
npm install fintech-algorithms
ts
import { followingAdaptiveMovingAverageFama } from "fintech-algorithms/technical-indicators/trend-smoothing/following-adaptive-moving-average-fama";

Signature#

followingAdaptiveMovingAverageFama(input)

Runs an efficiency-ratio adaptive average over close and its slower follower: net movement across period bars divided by the summed absolute bar-to-bar movement sets the smoothing constant, and FAMA tracks MAMA at half that constant.

Parameters#

NameTypeNotes
inputTopicInputbars is a non-empty array of OHLCV records with strictly increasing timestamp, finite open, high, low, close and non-negative volume, all sharing one adjustment basis. From parameters this topic reads period, an integer of at least 2, default 14, plus fast_alpha, default 0.5, and slow_alpha, default 0.05, both finite numbers between 0 and 1.

Returns#

TopicResult

series and latest carry two keys, mama and fama. Both are null for the first period bars, are seeded with the close at index period, and thereafter recurse, so with the default period ready_at is 14.

Warm-up#

The first period bars (14 at the default period of 14) positions are null. The efficiency ratio needs a period-bar lookback, so the loop starts at index period and both series are seeded there with the close. ready_at is that index. A window with zero total movement is treated as an efficiency ratio of 0 rather than dividing by zero.

Errors#

  • When parameters.fast_alpha or parameters.slow_alpha is not a finite number between 0 and 1 — throws Error
  • When parameters.period is not an integer of at least 2 — throws Error
  • When bars is empty or a bar violates the OHLCV contract — throws Error

Complexity: time O(n * period), space O(n).

Worked example#

executed Captured by running this function on the input its own test provides. Real output of real code — but not asserted against a published figure.

Input#

input
{
  "bars": [
    {
      "timestamp": "2024-01-02",
      "basis": "synthetic-unadjusted",
      "open": 100,
      "high": 101.45,
      "low": 98.695,
      "close": 100,
      "volume": 750000,
      "benchmark": 200
    },
    {
      "timestamp": "2024-01-03",
      "basis": "synthetic-unadjusted",
      "open": 101.49111452,
      "high": 103.38381693,
      "low": 100.05480022,
      "close": 101.78791214,
      "volume": 795117,
      "benchmark": 200.56326135
    },
    {
      "timestamp": "2024-01-04",
      "basis": "synthetic-unadjusted",
      "open": 102.45519048,
      "high": 104.6701838,
      "low": 100.91147007,
      "close": 102.9549389,
      "volume": 840234,
      "benchmark": 201.11020913
    }
  ],
  "parameters": {}
}

Call#

followingAdaptiveMovingAverageFama(input)

Returns#

object with 9 fields: topic_id, title, state, ready, ready_at, series, latest, parameters, …

{
  "topic_id": "D07-F01-A12",
  "title": "Following Adaptive Moving Average (FAMA)",
  "state": "calculated",
  "ready": true,
  "ready_at": 14,
  "series": {
    "mama": [null, null, null, null, null, null],
    "fama": [null, null, null, null, null, null]
  },
  "latest": {
    "mama": 103.83007356524162,
    "fama": 104.7546779146645
  },
  "parameters": {},
  "diagnostics": {
    "causal": true,
    "input_count": 96
  }
}

Diagrams#

Following Adaptive Moving Average (FAMA) — article hero
Following Adaptive Moving Average (FAMA) — concept map
Following Adaptive Moving Average (FAMA) — decision comparison
Following Adaptive Moving Average (FAMA) — worked example

Calculation flow#

Following Adaptive Moving Average (FAMA) calculation flow 
flowchart LR
    A["an oldest-to-newest finite price series, declared price so"] --> B["Validate order, basis, and finite values"]
    B --> C["Apply the selected Following Adaptive Moving Average (FAMA) convention"]
    C --> D["Emit value, readiness, and diagnostics"]
    D --> E["Interpret descriptively; test outcomes separately"]
    B -->|invalid or insufficient| X["Withhold output with a reason"]
Following Adaptive Moving Average (FAMA) readiness and evidence states 
stateDiagram-v2
    [*] --> Waiting
    Waiting --> Ready: enough valid causal observations
    Waiting --> Rejected: malformed or unsupported input
    Ready --> Calculated: selected formula applied
    Calculated --> Interpreted: diagnostic and limitation retained
    Interpreted --> Ready: next observation arrives
    Rejected --> Waiting: corrected input and deterministic reset

How it works#

This page states the contract — how to call it correctly. The article explains the concept: why it works, and where it breaks.

Read the article →

References#

  • TA-Lib function groups — see linked primary or authoritative record
  • TA-Lib C/C++ API — see linked primary or authoritative record
  • TA-Lib maintained source — see linked primary or authoritative record
  • Evidence decision
  • Level 1 evidence map

The rest of the Trend Smoothing family#