sequence/
sequence.rs

1//! Rolling multi-date rebalance through the `PortfolioSequence` API.
2//!
3//! One fixed factor structure, ten dates of new expected returns anchored on
4//! the previous date's weights. The sequence reuses the equilibration and the
5//! reduced factorizations across dates and chains warm starts internally.
6
7use std::error::Error;
8
9use ledge::{FactorCovariance, Matrix, PortfolioProblem, RebalanceStep, SolveStatus};
10
11const ASSETS: usize = 40;
12const FACTORS: usize = 4;
13const DATES: usize = 10;
14
15/// Deterministic pseudo-returns so the example needs no RNG dependency.
16fn expected_returns(date: usize) -> Vec<f64> {
17    (0..ASSETS)
18        .map(|asset| 0.05 + 0.02 * ((asset + 3 * date) as f64 * 0.61).sin())
19        .collect()
20}
21
22fn main() -> Result<(), Box<dyn Error>> {
23    let exposures: Vec<f64> = (0..ASSETS * FACTORS)
24        .map(|index| 0.3 * (index as f64 * 12.9898).sin())
25        .collect();
26    let problem = PortfolioProblem::new(
27        Matrix::new(ASSETS, FACTORS, exposures)?,
28        FactorCovariance::Diagonal(vec![0.06; FACTORS]),
29        vec![0.1; ASSETS],
30        expected_returns(0),
31    )?
32    .with_risk_aversion(6.0)?
33    .with_bounds(vec![0.0; ASSETS], vec![0.2; ASSETS])?
34    .with_quadratic_turnover(vec![1.0 / ASSETS as f64; ASSETS], 0.5)?;
35
36    let mut sequence = problem.sequence()?;
37    let mut previous_weights: Option<Vec<f64>> = None;
38
39    println!("date | status | iterations | new factorizations | one-way turnover");
40    println!("---|---|---|---|---");
41    for date in 0..DATES {
42        let factorizations_before = sequence.factorizations();
43        let step = RebalanceStep {
44            expected_returns: (date > 0).then(|| expected_returns(date)),
45            previous_weights: previous_weights.clone(),
46            ..RebalanceStep::default()
47        };
48        let solution = sequence.solve_next(&step)?;
49        if solution.status != SolveStatus::Solved {
50            return Err(format!(
51                "date {date} stopped with status '{}' after {} iterations",
52                solution.status, solution.iterations
53            )
54            .into());
55        }
56
57        let turnover = previous_weights.as_ref().map_or(0.0, |previous| {
58            solution
59                .x
60                .iter()
61                .zip(previous)
62                .map(|(new, old)| (new - old).abs())
63                .sum::<f64>()
64                / 2.0
65        });
66        println!(
67            "{date} | {} | {} | {} | {turnover:.6}",
68            solution.status,
69            solution.iterations,
70            sequence.factorizations() - factorizations_before,
71        );
72        previous_weights = Some(solution.x);
73    }
74    println!(
75        "total reduced factorizations across {DATES} dates: {}",
76        sequence.factorizations()
77    );
78    Ok(())
79}
sequence/sequence.rs

sequence/
sequence.rs
