Skip to contents

Changelog

Source: NEWS.md

R4GoodPersonalFinances (development version)

R4GoodPersonalFinances 1.0.0

CRAN release: 2025-06-04

This major release introduces probably first in the world (open-sourced) implementation of a new multilevel life-cycle modeling of a household finances. It connects life-cycle models with single-period net-worth Markowitz optimization models and allows for high degree of personalization. The implementation is based on a novel theoretical framework, described by Thomas M. Idzorek and Paul D. Kaplan in “Lifetime Financial Advice: A Personalized Optimal Multilevel Approach” (2024).

Major changes

  • Added Household R6 class that aggregates information about a household and its members and HouseholdMember class that aggregates information about a single member of a household.
  • Added functions responsible for setting, resetting and getting information about disk cache for caching the results of the simulations: set_cache(), reset_cache() and get_cache().
  • Added calc_life_expectancy() function to calculate the life expectancy of a person based on the Gompertz model.
  • Added plot_life_expectancy() function to visualize the probability of dying and life expectancy of every member of a Household object and similar plot_survival() function for visualizing the probability of survival of each of the members of a Household and the probability of at least one member of a Household to survive.
  • Added create_portfolio_template() function to create an exemplary Portoflio object - a template for default portfolio with two asset classes: GlobalStocksIndexFund and InflationProtectedBonds and with some reasonable default values that should be updated and customised further.
  • Added calc_portfolio_parameters() function to calculate the parameters of a Portfolio object like current value, weights of assets, expected return and standard deviation of the whole portfolio.
  • Added calc_optimal_asset_allocation() function to calculate optimal allocation for a particular Household and Portfolio objects.
  • Added plot_optimal_portfolio() function to visualize the current and optimal allocation to assets for a particular Portfolio object.
  • Added simulate_scenario() function to simulate a single scenario of cash flows for a particular Household and Portfolio objects using expected returns of the assets in portfolio or random returns in multiple Monte Carlo samples.
  • Added simulate_scenarios() function to simulate multiple scenarios of cash flows for a particular Household and Portfolio objects. The scenarios parameters can triggered by different events like different years of retirement.
  • Added plot_scenarios() function to visualize the scenarios metrics that help with choosing the optimal parameters for the best scenario, e.g. the optimal year for retirement.
  • Added plot_expected_allocation() function to visualize the expected allocation of assets for a particular scenario over the household life cycle.
  • Added plot_expected_capital() function to visualize the expected financial, human, and total capital, as well as liabilities for a particular scenario over the household life cycle.
  • Added plot_future_income() and plot_future_spending() functions to visualize the future income and spending for a particular scenario over the household life cycle. The plot_future_spending() function allows to plot the relation of discretionary and non-discretionary spending, structure of non-discretionary spending and possible levels of discretionary spending over time based on Monte Carlo simulations.

R4GoodPersonalFinances 0.2.0

CRAN release: 2025-03-13

This release provides functions for calculating probability of retirement ruin and functions for calibrating the underlying Gompertz model with the use of the mortality rates.

Major changes

R4GoodPersonalFinances 0.1.1

Bugfixes

  • Fixed apps errors while executing locally.

R4GoodPersonalFinances 0.1.0

Initial release of the package includes functions designed to support the optimal allocation of your investment portfolio with the use of the ‘Merton Share’ formula.