14. Introduction to Modern Portfolio Theory

Modern portfolio theory (MPT) is a framework for constructing investment portfolios that aims to maximize expected returns for a given level of risk. The theory was first introduced by Harry Markowitz in 1952 and is based on the principle of diversification.

MPT assumes that investors are risk-averse and seek to minimize the risk of their portfolio. The theory proposes that by investing in a diverse set of assets with low correlations, an investor can reduce the overall risk of their portfolio without sacrificing returns.

The main concepts of Modern Portfolio Theory (MPT) are:

1. Efficient Frontier: The efficient frontier is a set of portfolios that offer the highest expected return for a given level of risk. It is a line that represents a combination of portfolios that have the maximum expected return for a given level of risk. Portfolios that lie on the efficient frontier are considered to be optimal as they offer the best return for a given level of risk.
2. Risk and Return: MPT is based on the principle that higher returns are associated with higher risk. The risk of a portfolio is measured by its standard deviation or variance of returns. The theory assumes that investors are rational and risk-averse, and they seek to maximize their expected return for a given level of risk.
3. Portfolio Diversification: MPT emphasizes the importance of diversification in reducing portfolio risk. Diversification means spreading investments across different asset classes and securities to minimize the impact of any single security on the portfolio’s overall performance.
4. Capital Asset Pricing Model (CAPM): The Capital Asset Pricing Model is a theory that explains how the market prices assets and predicts the expected returns of assets based on their risk. CAPM provides a framework for calculating the expected return of an asset based on its beta, which measures the asset’s sensitivity to market movements.
5. Beta: Beta is a measure of the volatility of an asset in relation to the overall market. It measures the degree to which an asset’s returns move in response to changes in the market. A beta of 1 indicates that the asset’s returns move in line with the market, while a beta of less than 1 indicates that the asset’s returns are less volatile than the market, and a beta of greater than 1 indicates that the asset’s returns are more volatile than the market.
6. Portfolio Optimization: MPT provides a framework for optimizing portfolios by selecting the combination of assets that offer the highest expected return for a given level of risk. Portfolio optimization involves determining the optimal allocation of assets to achieve a desired risk-return tradeoff.
7. Asset Allocation: Asset allocation is the process of dividing a portfolio among different asset classes, such as stocks, bonds, and cash. Asset allocation is an important component of portfolio management as it can have a significant impact on a portfolio’s risk and return.

Definition of risk averse, risk seeking and risk neutral investor

A risk averse investor is someone who is cautious and prefers investments with lower risk even if it means accepting lower returns. They are willing to pay a premium to reduce risk and prefer to avoid investments that have a higher probability of loss.

A risk-seeking investor is someone who is willing to take on higher levels of risk in the pursuit of higher returns. They are willing to accept higher levels of risk and volatility in their investments and are comfortable with the possibility of losing money in pursuit of higher returns.

A risk-neutral investor is someone who is indifferent to risk and makes investment decisions based solely on expected returns. They do not consider risk when making investment decisions and are not influenced by the possibility of gain or loss.

Calculation of expected rate of return for individual security

The expected rate of return for individual security can be calculated using the following formula:

Expected Rate of Return = (Probability of a positive return x Potential positive return) + (Probability of a negative return x Potential negative return)

Where:

• Probability of a positive return: the likelihood that the security’s price will increase
• Potential positive return: the potential gain from holding the security
• Probability of a negative return: the likelihood that the security’s price will decrease
• Potential negative return: the potential loss from holding the security

For example, let’s assume a stock has a 60% chance of generating a positive return of 15% and a 40% chance of generating a negative return of 5%. The expected rate of return for this stock would be:

Expected Rate of Return = (0.60 x 0.15) + (0.40 x -0.05) = 0.09 – 0.02 = 0.07 or 7%

So, the expected rate of return for this stock is 7%.

Graphical presentation of portfolio risk/return of two securities

A graphical presentation of portfolio risk/return for two securities can be done using a scatter plot. Here’s how:

1. On the x-axis, plot the expected return for security A.
2. On the y-axis, plot the expected return for security B.
3. For each possible combination of weights of security A and security B, calculate the expected return and standard deviation of the portfolio.
4. Plot each combination of weights as a point on the scatter plot, with the expected return on the x-axis and the standard deviation on the y-axis.
5. Connect the dots to create a line that represents the efficient frontier, which shows the combinations of securities that offer the highest expected return for a given level of risk.

The efficient frontier represents the set of portfolios that have the maximum return for a given level of risk, or the minimum risk for a given level of return. The slope of the efficient frontier represents the risk-return trade-off: as you move up along the frontier, the expected return increases but so does the risk.

The concept of Efficient Frontier

The Efficient Frontier is a concept in Modern Portfolio Theory (MPT) that refers to a set of optimal portfolios that offer the highest expected return for a given level of risk or the lowest risk for a given level of expected return. In other words, the efficient frontier represents the set of portfolios that provide the maximum return for a given level of risk or the minimum risk for a given level of return.

The efficient frontier is a graph that plots the expected return on the y-axis and the standard deviation or volatility of the portfolio on the x-axis. The line connecting the set of optimal portfolios that lie on the efficient frontier is known as the Capital Market Line (CML). The CML represents the combination of the risk-free asset and the optimal risky portfolio that offers the highest Sharpe ratio (a measure of risk-adjusted return).

The efficient frontier is derived from the statistical concept of covariance between assets. It is based on the assumption that investors are rational and seek to maximize their return for a given level of risk or minimize their risk for a given level of return. By diversifying their portfolio across assets with different expected returns and volatilities, investors can achieve a higher expected return or lower risk than by investing in a single asset. The efficient frontier helps investors to identify the optimal portfolio that balances risk and return and to construct a well-diversified portfolio that maximizes their expected return for a given level of risk or minimizes their risk for a given level of expected return.

Portfolio Optimization process

Portfolio optimization is the process of selecting the best possible combination of assets for an investment portfolio based on certain objectives and constraints. The process typically involves the following steps:

1. Define investment objectives: The investor must first define their investment goals and objectives. This could include factors such as desired return, risk tolerance, time horizon, liquidity requirements, and tax considerations.
2. Determine constraints: The investor must also take into account any constraints that may impact the portfolio, such as legal and regulatory requirements, investment guidelines, and liquidity constraints.
3. Select asset classes: The investor must decide which asset classes to include in the portfolio, such as equities, fixed income, cash, and alternative investments.
4. Select securities: Within each asset class, the investor must choose which individual securities to include in the portfolio. This involves analyzing the fundamentals of each security, such as its financials, growth prospects, and valuation metrics.
5. Construct the portfolio: Once the investor has selected the securities, they must determine the appropriate allocation to each security in the portfolio based on the desired risk-return tradeoff.
6. Monitor and rebalance: The investor must regularly monitor the performance of the portfolio and make adjustments as needed to maintain the desired asset allocation and risk profile. This may involve selling some securities and buying others to bring the portfolio back in line with the target allocation.

The goal of portfolio optimization is to create a well-diversified portfolio that maximizes returns for a given level of risk, or minimizes risk for a given level of return. This is typically achieved by constructing a portfolio along the efficient frontier, which represents the set of optimal portfolios that provide the highest expected return for a given level of risk, or the lowest risk for a given level of return.

Estimation issues

In the process of portfolio optimization, there are several estimation issues that need to be addressed to ensure accurate and reliable results. Some of these estimation issues are:

1. Estimation of expected returns: One of the key inputs in the portfolio optimization process is the expected returns of the assets. However, estimating the expected returns can be challenging as it requires making assumptions about future market conditions and the performance of individual assets.
2. Estimation of asset correlations: Another important input in the portfolio optimization process is the correlation between different assets. However, estimating the correlations can be difficult as they are subject to change over time and can be influenced by a variety of factors.
3. Estimation of asset volatilities: Volatility is a key measure of risk for individual assets and is an important input in the portfolio optimization process. However, estimating the volatilities can be challenging as they are subject to change over time and can be influenced by a variety of factors.
4. Data quality and completeness: The accuracy and completeness of the data used in the portfolio optimization process is critical to the reliability of the results. Missing or inaccurate data can lead to biased and unreliable estimates.
5. Overfitting: Overfitting occurs when a model is too closely fitted to a particular set of data, resulting in poor out-of-sample performance. This can be a problem in portfolio optimization if the model is based on a limited set of historical data that may not be representative of future market conditions.
6. Model specification: The choice of model used in the portfolio optimization process can have a significant impact on the results. It is important to carefully consider the assumptions underlying the model and ensure that it is appropriate for the particular investment problem being addressed.