Portfolio Management Unit – II Session No. 13 Topic: Introduction to Asset Allocation Unit – II Session No. 13 Topic: Introduction to Asset Allocation

Session Plan Recap the Previous Session Asset Allocation Steps involved in Asset Allocation Monte Carlo Simulation Summarizing and Q & A

Asset Allocation In establishing and to finding a set of asset class weights that produce a portfolio consistent with the individual investor’s return objective, risk tolerance, and constraints. This task must be completed from a taxable perspective, taking into consideration – (1) after-tax returns – (2) the tax consequences of any shift from current portfolio allocations – (3) the impact of future rebalancing, and – (4) asset ‘‘location.’’

Asset Allocation Steps in Asset Allocation: – Determination of Investors return requirements – Elimination of risk objectives – Elimination of investors constraints – Evaluation of expected risk-adjusted performance and diversification

Asset Allocation Determination of Investors return requirements The investment adviser should compare expected returns for the different asset allocations on a basis consistent with the IPS. Example: Return requirements in real, after-tax terms. In that case, the adviser would adjust for the effects of taxes and expected inflation before deciding which allocations meet the investor’s return requirement.

Asset Allocation Elimination of risk objectives: Eliminate asset allocations that fail to meet quantitative risk objectives or are otherwise inconsistent with the investor’s risk tolerance. For example, an investor may have risk objectives related to the expected standard deviation of return, worst-case return, or any of several other downside risk concepts. On a long-term basis, an individual investor will be unable to apply an asset allocation that violates a risk objective.

Asset Allocation Elimination of investors constraints Eliminate asset allocations that fail to satisfy the investor’s stated constraints. For example, an investor may have a liquidity requirement that is appropriately met by holding a certain level of cash equivalents, and allocations must satisfy that constraint. Unique circumstances may also make certain allocations unacceptable to the investor.

Asset Allocation Evaluation of expected risk-adjusted performance and diversification Evaluate the expected risk-adjusted performance and diversification attributes of the asset allocations that remain after Steps 1 through 3 to select the allocation that is expected to be most rewarding for the investor. Monitoring the market movement and diversification is an important part of the Asset Allocation.

Monte Carlo Simulation Monte Carlo simulation is a mathematical technique that allows people to account for risk in quantitative analysis and decision making. The technique is used by professionals in such widely disparate fields as finance, project management, energy, manufacturing, engineering, research and development, insurance, oil & gas, transportation, and the environment. Monte Carlo simulation furnishes the decision-maker with a range of possible outcomes and the probabilities they will occur for any choice of action. It shows the extreme possibilities—the outcomes of going for broke and for the most conservative decision—along with all possible consequences for middle-of-the-road decisions. The technique was first used by scientists working on the atom bomb; it was named for Monte Carlo, the Monaco resort town renowned for its casinos. Since its introduction in World War II, Monte Carlo simulation has been used to model a variety of physical and conceptual systems

Monte Carlo Simulation Monte Carlo Simulation in Personal Retirement Planning Here, we focus on its applicability to personal retirement planning. Monte Carlo simulation is the process by which probability ‘‘distributions’’ are arrayed It helps in predict end-stage results even though with various degrees of volatility. Its use in projecting retirement wealth is valuable based on multiple factors (investment returns, inflation, etc.) The resulting path is dependency effect on wealth accumulation.

Monte Carlo Simulation Objective of Probabilistic approaches Investment planning is to improve the quality of managers’ recommendations and investors’ decisions. The distinction between traditional deterministic analysis and probabilistic analysis. In both approaches, the individual supplies a similar set of personal information but in a Monte Carlo or probabilistic analysis, a probability distribution of possible values is specified for economic variables, reflecting the real-life uncertainty about those variables’ future values are highly considered on computing the returns.

Monte Carlo Simulation Advantages of Probabilistic approach – a probabilistic forecast more accurately portrays the risk – simulation can give information on the possible trade-off between short-term risk and the risk of not meeting a long-term goal. – taxes complicate investment planning considerably by creating a sequential problem in which buy and sell decisions. – an expected value of future returns is more complicated than an expected value of concurrent returns

Summarizing How asset allocation used in managing individual investor’s portfolio? How to determine the investor’s return requirements? How to eliminate quantitative risk objectives? On what basis the strategic asset allocation measured? What is Monte Carlo Analysis? How Monte Carlo simulation helps for effective investment planning?