Income that is needed in retirement can come from many sources.
Here the focus is on investments and other funding that is made over time to reach some target level of retirement wealth goals.
A critically important decision is how to allocate capital among the many asset classes, and within an asset class the individual equities or bond instruments. Innumerable studies and research have been conducted on the topic of portfolio optimization. As a matter of fact, the Nobel Prize in Economics was awarded to person who first came up with the mathematical foundations of modern portfolio theory. Subsequently, several approaches based on that theory have been developed and fortunately we do not have to delve into arcane math to implement practical measures.
All these models allow for several manner of optimization goals which can be specified along with constraints. For example, a common constraint in selecting say among 20 stocks would be to restrain capital invested in any stock not to exceed 10%. This would guard against putting all of ones eggs in a single basket. Techniques used automatically tailor themselves to the goal required. Often it is the individual’s risk tolerance or lack of that determines these values.
An introduction to portfolio optimization and the efficient frontier is provided here:
http://www.its.caltech.edu/~rosentha/courses/BEM103/Readings/JWCh07.pdf.
A more detailed with implementation in R code is provided here:
https://faculty.washington.edu/ezivot/econ424/introductionPortfolioTheory.pdf
The above two papers only discuss a 2 asset scenario, however it is easy to deduce from the math presented that is quite easy to scale it up to any number of assets. These papers describe these more general techniques.
More interesting is that snippets of R-code are generously interspersed throughout these papers and assuming one has setup the R-IDE and has access to some market price data, it is a snap to run these various simulations and arrive at allocation ratios satisfying some user-provided constraint. I will upload some sample market price data later to work through these.
Portfolio optimization, construction and review is basically what financial consultants / hedge fund managers do albeit on a massive scale and with high frequency data. The good news is that in R, there are ready made packages and optimization techniques devoted solely to this matter.