Enum MonteCarloMethod 

#[non_exhaustive]
pub enum MonteCarloMethod {
    IidShuffle,
    BlockBootstrap {
        block_size: usize,
    },
    StationaryBootstrap {
        mean_block_size: usize,
    },
    Parametric,
}

Resampling method used for Monte Carlo simulation.

Each method makes different assumptions about trade return structure. Choose based on your strategy’s autocorrelation characteristics.

Variants (Non-exhaustive)

Non-exhaustive enums could have additional variants added in future. Therefore, when matching against variants of non-exhaustive enums, an extra wildcard arm must be added to account for any future variants.

IidShuffle

Random IID shuffle (Fisher-Yates). Default.

Treats every trade return as an independent, identically distributed draw and randomises the sequence. Fast and appropriate for mean-reversion strategies whose trades are mostly independent. Destroys autocorrelation, which may underestimate the probability of sustained drawdowns for trend-following strategies.

BlockBootstrap

Fixed-size block bootstrap.

Samples consecutive blocks of block_size trades (with circular wrap-around) and reassembles them in random order. Preserves short-range autocorrelation and regime structure better than IID shuffle. A good default block size is sqrt(n_trades). More conservative than IID for trending strategies.

Fields

block_size: usize

Number of consecutive trades per block.

StationaryBootstrap

Stationary bootstrap with geometrically-distributed block lengths.

Like BlockBootstrap but block length is drawn from Geometric(1 / mean_block_size) at each step. Less sensitive to the choice of block size than the fixed variant — a good default when you are uncertain about the true autocorrelation length.

Fields

mean_block_size: usize

Expected (average) number of trades per block.

Parametric

Parametric simulation assuming normally-distributed trade returns.

Fits N(μ, σ) to the observed trade returns and generates synthetic sequences by sampling from that distribution (Box-Muller transform). Useful when the observed trade count is very small and non-parametric resampling would produce near-identical sequences. Assumes normality, which may not hold in fat-tailed markets.

Trait Implementations

impl Clone for MonteCarloMethod

fn clone(&self) -> MonteCarloMethod

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for MonteCarloMethod

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for MonteCarloMethod

fn default() -> MonteCarloMethod

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for MonteCarloMethod

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for MonteCarloMethod

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.