metafolio {metafolio}

metafolio: An R package to simulate metapopulations for portfolio optimization

Description

The metafolio R package is a tool to simulate metapopulations and apply financial portfolio optimization concepts. The package was originally written for salmon simulations, so some of the language refers to salmon-specific terminology, but the package could be used and/or adopted for other taxonomic groups.

Details

The main simulation function is meta_sim. This function takes care of running an individual simulation iteration. The package also contains functions for exploring conservation scenarios with these simulations (see the "Assessing multiple conservation scenarios" section below), and find optimal conservation strategies (see the "Portfolio optimization section" below).

Running a simulation once

To run a single simulation iteration, see the function meta_sim. To plot the output from one of these simulations, see the function plot_sim_ts.

Assessing multiple conservation scenarios

You can use run_cons_plans to run meta_sim for multiple iterations and across multiple conservation strategies. These strategies could focus on the spatial distribution of conservation or on the number of populations conserved.

The function plot_cons_plans can plot the output from run_cons_plans.

Specifying environmental patterns

When you run meta_sim you can specify the environmental signal. One of the arguments is a list of options to pass to generate_env_ts, which controls the environmental pattern.

Diagnostic plots

metafolio contains some additional plotting functions to inspect the spawner-return relationships and the correlation between returns: plot_rickers, and plot_correlation_between_returns.

Portfolio optimization

metafolio also contains some experimental functions for finding optimal conservation strategies (an efficient frontier). This is analogous to financial portfolio where the goal is to find the investment weights that maximizes expected return for a level of expected risk, or vice-versa. Presently, these functions rely on Monte Carlo sampling, and so are rather slow.

For this purpose, the function create_asset_weights can generate a matrix of asset weights, which can then be passed to monte_carlo_portfolios to do the optimization itself. plot_efficient_portfolios can be used to plot the optimization output.

See the package vignette vignette("metafolio") for more extensive explanation of how to use metafolio along with some examples.

Author(s)

Maintainer: Sean C. Anderson [e-mail] (ORCID)

Other contributors:

• Jonathan W. Moore [contributor]

• Michelle M. McClure [contributor]

• Nicholas K. Dulvy [contributor]

• Andrew B. Cooper [contributor]

See Also

Useful links:

• https://github.com/seananderson/metafolio

• Report bugs at https://github.com/seananderson/metafolio/issues