Asset Allocation

Question 1

Higher transaction cost

Answer 1

Wider corridor

Question 2

Higher risk tolerance

Answer 2

Wider corridor

Question 3

Higher correlation of asset class with rest of the portfolio

Answer 3

Wider the corridor

Question 4

Higher volatility

Answer 4

Narrower the corridor

Question 5

What’s forward rate bias?

Answer 5

Forward rate bias is defined as an observed divergence from interest rate parity conditions

Question 6

pretax returns

Answer 6

and hence the lower corridors because more volatility

Question 7

mean variance optimization

Answer 7

• most common asset only allocation based approach
• identifies the portfolio allocations that maximize return for every level of risk

Question 8

criticism of mvo

Answer 8

• GIGO
• Concentrated asset class allocations
• Ignores Skewness and kurtosis (asymmetry and tail risk)
• risk diversification
• Ignores liabilities
• single period framework

Question 9

reverse optimization

Answer 9

instead of starting with expected returns and deriving portfolio weights, start with what should be the ideal portfolio weights and drive the expected return consistent with those weights. then use this answer for the traditional MVO. These implied returns can then be used in a forward-looking optimization.

Question 10

black litterman model

Answer 10

extension of the reverse optimisation model where the implied returns (or rather implied excess returns) from a reverse optimization are subsequently adjusted to reflect the investor’s unique views of future returns

Question 11

resampled MVO

Answer 11

resampling can also be used to address the GIGO and highly concentrated issues by applying Monte Carlo simulation to the MVO and then running multiple scenarios and then doing an average weight of each. also creates more diversified portfolios

Question 12

absolute contribution to total risk

Answer 12

asset classes contribution to total volatility

= MCTR x Asset weight

Question 13

marginal contribution to total risk

Answer 13

Measures how a small change in a specific asset affects the total portfolio risk.

Formula: MCTR = (Beta of asset class relative to portfolio) × (Portfolio return volatility).

Question 14

surplus optimization

Answer 14

Surplus optimization applies the mean-variance optimization (MVO) framework to the surplus (the difference between assets and liabilities) rather than focusing directly on the assets themselves.

Question 15

two portfolio approach

Answer 15

we separate the asset portfolio into 2 sub portfolios: a hedging portfolio and a risk seeking portfolio

Return seeking portfolio: The remaining assets are allocated to a return-seeking portfolio, which aims to generate higher returns but with higher risk. This portfolio typically includes assets such as equities or other riskier investments that provide greater potential for growth but do not directly align with liabilities.

Question 16

integrated asset-liability approach

Answer 16

this approach integrates both the assets and the liabilities in a joint optimization method

Question 17

Liability driven approach

Answer 17

generally encompasses asset allocation that is focused on funding an investor’s liabilities.

Question 18

Objective of asset only and liabilities only approach

Answer 18

Maximize Sharpe ratio
for acceptable level of
volatility

Fund liabilities and invest
excess assets for growth

Question 19

Risk measurements in asset only approach

Answer 19

• standard deviation
• tracking error (towards benchmark)
• tail risk (downside risk)

Question 20

Asset classes criteria

Answer 20

• Assets within an asset class should be relatively homogeneous
• Asset classes should be mutually exclusive
• Asset classes should be diversifying
• asset classes as a group should be made up of world investable wealth
• Asset classes selected for investment should have the capacity to absorb a
  meaningful proportion of an investor’s portfolio.

Question 21

Dynamic asset allocation

Answer 21

A strategy incorporating deviations from the strategic asset
allocation that are motivated by longer-term valuation signals or economic views

Question 22

active risk budgeting

Answer 22

addresses the question of how much benchmark-relative risk an investor is willing to take in seeking to outperform a benchmark.

Question 23

Belief in momentum

Answer 23

Wider corridor

Question 24

belief in mean reversion

Answer 24

narrower corridors

Question 25

taxable portfolio

Answer 25

wider and more asymmetric

Question 26

The efficient mix at the far
left of the frontier with the lowest risk is referred to as the global minimum variance
portfolio, while the portfolio at the far right of the frontier is the maximum expected
return portfolio. In the absence of constraints beyond the budget and non-negativity
constraints, the maximum expected return portfolio consists of a 100% allocation to
the single asset with the highest expected return (which is not necessarily the asset
with the highest level of risk)

Question 27

how do solve for single period framework issue of MVO

Answer 27

Monte carlo simulation. It is particularly useful when an investor’s risk tolerance is uncertain or needs validation.

Question 28

Key features of MCS

Answer 28

Enhanced Modeling: Can incorporate non-normal returns, correlations, tax rates, evolving asset allocation, non-traditional investments, and human capital.

Practical Issues: Simulates rebalancing costs, tax impacts, and market interactions that are challenging to calculate analytically.

Path Dependency: Evaluates scenarios where terminal wealth depends on the sequence of returns, which is critical for portfolios with cash inflows or outflows.

Question 29

Sensitivity to Inputs in MVO

Answer 29

MVO is more sensitive to expected return estimates than to volatility and correlation estimates.

Question 30

Market portfolio of reverse optimization

Answer 30

To apply reverse optimization, you need a version of the global market portfolio, typically formed using market-capitalization-weighted indexes. These indexes often represent the majority of securities in an asset class. Tey should also be considered of optimal weights.

Question 31

one issue with reverse optimization?

Answer 31

Reverse optimization relies on market-capitalization-based returns, which may not always align with an investor’s own expectations or views.

Question 32

2 ways to incorporate Black litterman

Answer 32

The model offers two ways to incorporate views: absolute return forecasts (where an investor specifies a direct forecast for an asset) and relative return forecasts (where the investor expresses a forecast relative to another asset or group of assets).

Question 33

some of the constraints of MVO

Answer 33

budget constraint (which ensures the total portfolio weight equals 100%)

non-negativity constraint (which prevents negative asset allocations).

Many practical considerations in real-world asset management require constraints to reflect the specific circumstances of an investor’s portfolio or situation. (no alchohol companies)

Overcoming shortcomings of MVO

Question 34

Solving skewness and kurtosis prblem of MVO

Answer 34

More advanced optimization techniques address these shortcomings by incorporating higher moments (skewness and kurtosis) and using measures like Conditional Value-at-Risk (CVaR) to better reflect risk and investor preferences.

Question 35

For illiquid assets, how to approach MVO?

Answer 35

Exclude illiquid assets from the asset allocation decision and consider specific funds for implementation.

Include illiquid assets in the asset allocation decision but model inputs based on the specific characteristics of the implementation vehicles.

Include illiquid assets and model inputs to represent the highly diversified characteristics of the asset classes, possibly using listed real estate or infrastructure indexes to approximate private equity and real estate.

Question 36

Challenges with listed AI

Answer 36

Using listed indexes (e.g., REITs for real estate) can distort asset class separation, leading to higher correlations among asset classes. This can increase sensitivity in mean-variance optimization and lead to less diversified asset allocations.

Question 37

When is the risk budget considered optimal?

Answer 37

The portfolio is considered optimal from a risk-budgeting perspective when the ratio of excess return to MCTR is the same for all assets in the portfolio and matches the Sharpe ratio of the tangency portfolio (a portfolio that maximizes the Sharpe ratio). This ensures that each asset is contributing to the portfolio’s return in proportion to the risk it is taking on.

Question 38

Funding ratio

Answer 38

The funding ratio is calculated as the ratio of assets to liabilities.

Question 39

basis risk for pension funds

Answer 39

This risk arises when the chosen assets (such as bonds) do not perfectly match the timing of liabilities, which may cause funding issues in the future.

Question 40

Steps in surplus optimization

Answer 40

• Select asset categories and planning horizon (usually one year).
• Estimate expected returns and volatilities for assets and liabilities.
• Set constraints on asset allocation.
• Estimate the correlation matrix for assets and liabilities.
• Compute the surplus efficient frontier and compare it with the asset-only frontier.
• Choose the optimal portfolio mix based on risk preferences.

Question 41

The factor-based approach is suited for liabilities dependent on uncertainties like inflation and economic conditions.

Question 42

Representative bias

Answer 42

Representative bias is when people tend to overweigh the most recent
observations and information compared to a longer-dated or more comprehensive set of long-term observations and information.

Question 43

Risk parity allocation approach

Answer 43

A risk parity asset allocation is based on the fact that each asset should contribute equally to the total risk of the portfolio for a diversified portfolio. A limitation of risk parity is that it ignores expected returns.