Description: To enhance the accuracy and reliability of Monte Carlo simulations in PL, it is proposed to integrate a drop-down pick list within the software that allows users to select expected investment returns, volatility, and inflation based on the long-term capital market assumptions (LTCMAs) published by leading financial institutions. Each year, these institutions publish LTCMAs, including detailed metrics for expected returns by asset class, volatility, and inflation. Incorporating these could help avoid the problem of “garbage in, garbage out,” where end users may not have a strong understanding of the underlying data or would prefer to rely on expert analysis.

Reputable institutions that publish detailed, publicly available LTCMAs include Morningstar, Vanguard, Fidelity, Schwab, JP Morgan, Blackrock, PWL Capital, Research Affiliates, and Grantham Mayo Van Otterloo. Many of these reports provide sufficient data breakdowns to support the incorporation of such functionality into PL.

Current Challenges: The settings section of the Monte Carlo-based “Chance of Success” feature in PL requires users to manually input data sources, specifying investment returns, volatility, and inflation expectations. Establishing accurate data is critical for credible Monte Carlo analysis and a resulting financial plan that is both reliable and actionable. However, this process can be challenging for users who may not have a strong understanding of the underlying analysis.

One possible solution is for the end user to independently review published LTCMAs from leading institutions on a periodic basis and manually incorporate such data into PL. This is cumbersome, time-consuming, and prone to error. Additionally, the current software configuration does not easily allow users to transfer data from these reports into the data source fields found in the settings. The software requires users to break out “Investment Returns”, along with expected volatility, and “Dividend Yield” with expected volatility. Most published market assumptions provide an aggregate return expectation for stocks along with expected volatility, rather than breaking out stock returns into investment growth and dividends.

Key Benefits:

Reliability and Accuracy: Users can rely on well-established financial institutions for their LTCMAs, ensuring that their simulations are based on credible and up-to-date analysis.

Customization: Users can choose which institution’s assumptions they prefer to rely on, allowing for tailored simulations that match their trust and comfort levels with different sources.

Efficiency: Streamlines the process of incorporating LTCMAs into Monte Carlo simulations, saving users time and effort in manually updating these assumptions.

Flexibility: PL could aggregate and average assumptions from multiple authorities, offering a comprehensive view of market expectations.

It is important that the planning process be data-driven and adaptable over time. Integrating the insights and analysis from leading institutions in a straightforward manner would be a valuable and unique feature. Please upvote if you support the integration of LTCMAs into the Monte Carlo analysis tool, and share any thoughts on how this idea can be further refined to meet the needs of the PL community.