import type { array, matrix } from "../types";
/**
 * Parametric Conditional Value-At-Risk.
 *
 * Parametric Conditional Value-At-Risk measures the expected loss
 * exceeding the VaR. Also known as Expected Shortfall (ES) or Expected Tail Loss (ETL).
 * It is more sensitive to the shape of the loss distribution in the tails.
 *
 * @param mu mean value (def: 0)
 * @param sigma standard deviation (def: 1)
 * @param p cVaR confidence level in range [0,1] (def: 0.95)
 * @param amount portfolio/asset amount (def: 1)
 * @param period time horizon (def: 1)
 * @return Parametric Conditional Value-At-Risk
 *
 * @example Parametric daily CVaR with mean and std
 * ```ts
 * import { assertEquals } from "jsr:@std/assert";
 *
 * assertEquals(paramcondvar(0.0179, 0.023230487630602065), 0.030017825479120894);
 *
 * ```
 *
 * @example Parametric CVaR with additional parameters
 * ```ts
 * import { assertEquals } from "jsr:@std/assert";
 *
 * assertEquals(paramcondvar(0.0179, 0.023230487630602065, 0.99, 100000, 10), 19578.980844416896);
 *
 * ```
 *
 * @example Different asset parameters
 * ```ts
 * import { assertEquals } from "jsr:@std/assert";
 *
 * assertEquals(paramcondvar(0.01125, 0.04727061065899899, 0.99, 100000, 10), 39840.35893323986);
 * ```
 */
export default function paramcondvar(mu: number, sigma: number, p?: number, amount?: number, period?: number): number;
/**
 * Parametric Conditional Value-At-Risk.
 *
 * Parametric Conditional Value-At-Risk measures the expected loss
 * exceeding the VaR. Also known as Expected Shortfall (ES) or Expected Tail Loss (ETL).
 * It is more sensitive to the shape of the loss distribution in the tails.
 *
 * @param mu mean value (def: 0)
 * @param sigma standard deviation (def: 1)
 * @param p cVaR confidence level in range [0,1] (def: 0.95)
 * @param amount portfolio/asset amount (def: 1)
 * @param period time horizon (def: 1)
 * @return Parametric Conditional Value-At-Risk
 *
 * @example Parametric daily CVaR with mean and std
 * ```ts
 * import { assertEquals } from "jsr:@std/assert";
 *
 * assertEquals(paramcondvar(0.0179, 0.023230487630602065), 0.030017825479120894);
 *
 * ```
 *
 * @example Parametric CVaR with additional parameters
 * ```ts
 * import { assertEquals } from "jsr:@std/assert";
 *
 * assertEquals(paramcondvar(0.0179, 0.023230487630602065, 0.99, 100000, 10), 19578.980844416896);
 *
 * ```
 *
 * @example Different asset parameters
 * ```ts
 * import { assertEquals } from "jsr:@std/assert";
 *
 * assertEquals(paramcondvar(0.01125, 0.04727061065899899, 0.99, 100000, 10), 39840.35893323986);
 * ```
 */
export default function paramcondvar(mu: array, sigma: array, p?: number, amount?: number, period?: number): array;
/**
 * Parametric Conditional Value-At-Risk.
 *
 * Parametric Conditional Value-At-Risk measures the expected loss
 * exceeding the VaR. Also known as Expected Shortfall (ES) or Expected Tail Loss (ETL).
 * It is more sensitive to the shape of the loss distribution in the tails.
 *
 * @param mu mean value (def: 0)
 * @param sigma standard deviation (def: 1)
 * @param p cVaR confidence level in range [0,1] (def: 0.95)
 * @param amount portfolio/asset amount (def: 1)
 * @param period time horizon (def: 1)
 * @return Parametric Conditional Value-At-Risk
 *
 * @example Parametric daily CVaR with mean and std
 * ```ts
 * import { assertEquals } from "jsr:@std/assert";
 *
 * assertEquals(paramcondvar(0.0179, 0.023230487630602065), 0.030017825479120894);
 *
 * ```
 *
 * @example Parametric CVaR with additional parameters
 * ```ts
 * import { assertEquals } from "jsr:@std/assert";
 *
 * assertEquals(paramcondvar(0.0179, 0.023230487630602065, 0.99, 100000, 10), 19578.980844416896);
 *
 * ```
 *
 * @example Different asset parameters
 * ```ts
 * import { assertEquals } from "jsr:@std/assert";
 *
 * assertEquals(paramcondvar(0.01125, 0.04727061065899899, 0.99, 100000, 10), 39840.35893323986);
 * ```
 */
export default function paramcondvar(mu: matrix, sigma: matrix, p?: number, amount?: number, period?: number): array | matrix;
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