###### The Individual Balance Sheet

Economic (Holistic) Balance Sheet An economic balance sheet builds on the idea of... **Read More**

Heuristics, also known as **rules of thumb**, are simplistic and generic rules that investors use to satisfice. Satisficing, as covered in the behavioral economics section, reflects an attempt to reach a satisfactory economic decision at the expense of an optimal decision in the face of limited skills, understanding, resources, and/or information on behalf of the investor. While heuristics may contain some common sense and are not likely the absolute worst route an investor could take, it is essential to understand their limitations and why financial professionals do not use them.

This rule calculates a percentage dedicated to equity holdings in any investor’s portfolio by the equation 120 – Investor age. For example, a 30-year-old investor would allocate 120 – 30 = 90, or 90% of their portfolio to stocks.

Ultimately, this rule of thumb is a one-size-fits-all approach and considers no facets of an investor’s life other than age. This would not be suitable for financial professionals to rely upon in practice. Furthermore, there is no theoretical basis for this rule. However, it ends to approximate the relationship between human and financial capital over time. As investors age, they tend to convert their human capital into financial capital, which calls for a more conservative investment allocation.

Another similar approach would be investing in target date or lifecycle funds. These funds often have a target retirement date (at which the investor is also assumed to turn 65) and adjust allocations to become more and more conservative as the date approaches (higher allocations to fixed income, less to equity).

This even simpler heuristic skips the age-related calculation and goes directly for a static split of 60% stocks and 40% bonds for a truly one-size-fits-all approach. There is some evidence that the global market portfolio is close to the exact makeup of 60-40. However, this varies over time. A 60/40 split could be an excellent place to start, but it lacks the rigor of a professional recommendation.

This model has worked well for some large institutional investors, such as Yale, as these institutions are in an excellent position to earn the illiquidity premiums in these investments due to their ability to meet the minimum investment amounts and lockup periods. The same approach may not be at all feasible for smaller retail investors.

The risk parity approach seeks to rectify a criticism of MVO in that while it diversifies risk across asset classes, it does not necessarily diversify across the sources of risk. The risk parity approach states that each asset class should contribute equal risk to the overall portfolio. A significant criticism of this approach is that it does not consider return.

The risk parity approach, which is somewhat contentious, has several variations. However, the most widely used version can be mathematically expressed as follows:

$$ w_i\times Cov\left(r_i,r_p\right)=\frac{1}{n}\delta^2p $$

Where;

\(w_i\)=Weight of asset i

\(Cov\left(r_i,r_p\right)\)=Covariance of asset i with the portfolio

\(n\)=Number of assets

\(\delta^2p\)=Variance of the portfolio

Typically, the problem has no closed-form solution and must be solved using optimization techniques such as mathematical programming. Before Markowitz introduced mean-variance optimization, which considers risk and return, most asset allocation methods only focused on return. They ignored risk or dealt with it in an ad hoc way. The main criticism of risk parity is that it ignores expected returns, a shortcoming shared by most rules-based risk approaches such as other forms of volatility weighting, minimum volatility, and target volatility.

The composition of the opportunity mainly influences the risk contribution in risk parity. For instance, if the opportunity set comprises seven equity asset classes and three fixed-income asset classes, 70% of the risk is expected to come from equities and 30% from fixed income. On the other hand, if the opportunity set comprises three equity asset classes and seven fixed-income asset classes, 70% of the risk will come from fixed-income and 30% from equities. Therefore, risk parity practitioners must know how their opportunity set is formed.

The 1/N rule is a simple asset allocation approach where wealth is equally distributed among N assets. Despite being theoretically dominated by methods that optimize asset class weights, empirical studies have found the 1/N rule to perform considerably better than expected. One possible explanation is that it avoids problems caused by input estimation errors.

The formula is \(\frac {1}{(\text{Number of assets in the portfolio})}\).

## Question

According to the ‘120 minus your age’ heuristic, investor portfolio durations will

most likely:

- decrease over time.
- increase over time.
- remain constant.
## Solution

The correct answer is B:Calculate the percentage dedicated to equity holdings in any investor’s portfolio using the equation 120 – Investor age. For example, a 30-year-old investor would allocate 120 – 30 = 90, or 90% of their portfolio to stocks. A 60-year-old investor would allocate 120 – 60 = 60, or 60% of their portfolio to stocks, with the remaining 40% to fixed income.

Higher allocations to fixed income increase portfolio duration (interest rate risk).

A is incorrect.It suggests that investor portfolio durations will decrease over time. As the percentage of fixed income in a portfolio increases, the portfolio’s duration also increases.

C is incorrect.It suggests that investor portfolio durations will remain constant over time. The ‘120 minus your age’ heuristic changes allocation between equities and fixed income as an investor ages, affecting the portfolio’s duration. So, the duration of the portfolio does not remain constant over time.

Reading 5: Principles of Asset Allocation

Los 5 (n) Describe and evaluate heuristic and other approaches to asset allocation