juliaactuary / learn Goto Github PK

pub fn npv(mortality_rates: &Vec<f64>, lapse_rates: &Vec<f64>, interest_rate: f64, sum_assured: f64, premium: f64, init_pols: f64, term: Option<usize>) -> f64 {
    let term = term.unwrap_or_else(|| mortality_rates.len());
    let mut result = 0.0;
    let mut inforce = init_pols;
    let v: f64 = 1.0 / (1.0 + interest_rate);
    let mut discount_factor: f64 = 1.0;

    for (t, (q, w)) in mortality_rates.iter().zip(lapse_rates).enumerate() {
        let no_deaths = if t < term {inforce * q} else {0.0};
        let no_lapses = if t < term {inforce * w} else {0.0};
        let premiums = inforce * premium;
        let claims = no_deaths * sum_assured;
        let net_cashflow = premiums - claims;
        result += net_cashflow * v.powi(t as i32);
        discount_factor *= v;
        inforce = inforce - no_deaths - no_lapses;
    }

    result
}

Type annotations are optional, but providing them is able to coerce the values to be all plain bits (i.e. simple, non-referenced values like arrays are) when the type is constructed. This makes the whole data be stored in the stack and is an example of data-oriented design. It's much slower (~0.5 million policies per second, ~50x slower)