fintech-algorithms
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Realized Kernel

Install and import#

bash
npm install fintech-algorithms
ts
import { calculate } from "fintech-algorithms/volatility-and-covariance/realized-measures/realized-kernel";

Signature#

calculate(data)

Explain each weighted lag correction to realized variance. Supplied-parameter educational reference; no fitted performance claim.

Parameters#

NameTypeNotes
dataTopicInputSee data-contract/CONTRACT.md.

Returns#

TopicResult

Structured result with readiness, values, parameters, and diagnostics.

Warm-up#

The first depends on window or model order positions are null prefix until minimum history exists.

Errors#

  • When required data is missing, non-finite, malformed, or out of range — raises ContractError / Error

Complexity: time O(nwH), space Full diagnostic trace retained for teaching; see implementation for observation/window/matrix dimensions.

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#

data
{
  "returns": [0.01, -0.02, 0.03, -0.01],
  "parameters": {
    "window": 4,
    "annualization_factor": 1,
    "bandwidth": 1
  }
}

Call#

calculate(data)

Returns#

object with 8 fields: topic_id, title, parameters, series, latest, ready, ready_at, diagnostics

{
  "topic_id": "D10-F02-A05",
  "title": "Realized Kernel",
  "parameters": {
    "window": 4,
    "annualization_factor": 1,
    "bandwidth": 1
  },
  "series": [
    null,
    null,
    null,
    {
      "realized_kernel": 0.0004000000000000002,
      "volatility": 0.020000000000000004,
      "bandwidth": 1,
      "lags": [
        {
          "lag": 0,
          "weight": 1,
          "gamma": 0.0015,
          "contribution": 0.0015
        },
        {
          "lag": 1,
          "weight": 0.5,
          "gamma": -0.0010999999999999998,
          "contribution": -0.0010999999999999998
        }
      ],
      "window_start": 0,
      "window_end": 3
    }
  ],
  "latest": {
    "realized_kernel": 0.0004000000000000002,
    "volatility": 0.020000000000000004,
    "bandwidth": 1,
    "lags": [
      {
        "lag": 0,
        "weight": 1,
        "gamma": 0.0015,
        "contribution": 0.0015
      },
      {
        "lag": 1,
        "weight": 0.5,
        "gamma": -0.0010999999999999998,
        "contribution": -0.0010999999999999998
      }
    ],
    "window_start": 0,
    "window_end": 3
  },
  "ready": true,
  "ready_at": 3,
  "diagnostics": {
    "causal": true,
    "input_count": 4,
    "annualization_factor": 1
  }
}

Diagrams#

Realized Kernel — article hero
Realized Kernel — concept map
Realized Kernel — decision comparison
Realized Kernel — worked example

Calculation flow#

Realized Kernel — calculation-flow
flowchart TD
    N0["Lag zero = realized variance"]
    N1["Compute signed lag products"]
    N2["Apply Bartlett weights and factor two"]
    N3["Sum the quadratic-form contributions"]
    N0 --> N1 --> N2 --> N3
Realized Kernel — decision-boundary
flowchart TD
    A["Supplied observations and parameters"] --> B{"Contract valid?"}
    B -->|No| E["Reject with explicit error"]
    B -->|Yes| C{"Required history available?"}
    C -->|No| W["Withhold; never insert zero"]
    C -->|Yes| D["Realized Kernel calculation"]
    D --> F["Inspect diagnostics and stated limits"]

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#

  • Scope of evidence

The rest of the Realized Measures family#