15.5 Using Excel to Make Investment Decisions
4 min read•june 18, 2024
Excel is a powerful tool for analyzing stocks and portfolios. It helps calculate key metrics like average returns and standard deviations, giving investors insights into performance and risk. These calculations are crucial for making informed investment decisions and understanding the .
Excel also shines in portfolio analysis, allowing investors to calculate overall returns and assess risk through and . The , calculated using Excel's regression functions, measures a stock's sensitivity to market movements, aiding in portfolio construction and risk management.
Using Excel for Stock and Portfolio Analysis
Stock return and risk calculations
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- Measures the historical performance of a stock over a given time period (1 year, 5 years)
- Calculate using the AVERAGE function in Excel
- Input: series of periodic returns (daily, monthly, or annual returns)
- Output: the mean return over the specified period
- Provides insight into the stock's past performance and potential future returns
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- Measures the dispersion of returns around the average return
- Indicates the level of risk associated with the stock (volatility)
- Calculate using the or function in Excel
- STDEV.P: use when data represents the entire population (all trading days)
- STDEV.S: use when data is a sample of the population (selected trading days)
- Higher standard deviation implies higher risk
- Helps investors assess the potential fluctuations in the stock's price
- Crucial for understanding the risk-return tradeoff in
Portfolio performance metrics
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- The weighted average of the individual stock returns in the portfolio
- Calculate using the function in Excel
- Multiply each stock's weight by its corresponding return (0.25 x 0.05)
- Sum the products to obtain the portfolio return
- Provides an overall measure of the portfolio's performance
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- Measures the risk of the portfolio
- Calculated using the weighted average of individual stock variances and the between stocks
- Calculate individual stock variances using the or function
- Calculate covariances between stocks using the or COVARIANCE.S function
- Combine variances and covariances based on the portfolio weights
- Use the function to find the square root of the portfolio variance
- Helps assess the overall risk of the portfolio
- Covariance
- Measures how two stocks move together (Microsoft and Apple)
- Calculate using the COVARIANCE.P or COVARIANCE.S function in Excel
- COVARIANCE.P: use when data represents the entire population
- COVARIANCE.S: use when data is a sample of the population
- Positive covariance: stocks tend to move in the same direction
- Negative covariance: stocks tend to move in opposite directions
- Important for diversification, as combining stocks with low or negative covariance can reduce portfolio risk
Beta coefficient regression analysis
- Beta coefficient
- Measures the sensitivity of a stock's returns to market movements (S&P 500)
- Represents that cannot be diversified away
- Calculate using the function in Excel
- Input: stock returns (dependent variable) and market returns (independent variable)
- Output: the stock's beta coefficient
- Helps investors understand how the stock is likely to perform relative to the market
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- A statistical method to estimate the relationship between a dependent variable (stock return) and an independent variable (market return)
- Perform using the , , and functions in Excel
- SLOPE: calculates the beta coefficient
- INTERCEPT: calculates the alpha (the expected return when the market return is zero)
- RSQ: measures the goodness of fit of the regression line (R-squared)
- Provides a framework for understanding the relationship between a stock and the market
- Interpreting beta
- : stock moves in line with the market
- : stock is more volatile than the market (aggressive)
- Example: means the stock is 50% more volatile than the market
- : stock is less volatile than the market (defensive)
- Example: means the stock is 50% less volatile than the market
- : stock moves in the opposite direction of the market (rare)
Excel for Financial Analysis and Investment Decision-Making
- : Essential tools for performing complex calculations and automating financial analysis tasks
- : Creating mathematical representations of financial situations to forecast future performance and evaluate investment opportunities
- : Utilizing Excel's built-in tools to process and interpret large datasets, enabling more informed investment decisions
Key Terms to Review (33)
AAPL (Apple): AAPL is the ticker symbol for Apple Inc., one of the largest technology companies in the world. It is widely traded on the NASDAQ stock exchange and a major component of various financial indices such as the S&P 500 and Dow Jones Industrial Average.
AMZN (Amazon): AMZN (Amazon) is the stock ticker symbol for Amazon.com, Inc., a multinational technology company focusing on e-commerce, cloud computing, digital streaming, and artificial intelligence. It is one of the largest companies in the world by market capitalization and revenue.
Arithmetic average return: Arithmetic average return is the sum of a series of returns divided by the number of observations in the series. It provides a simple average that indicates the typical return over a given period.
Average Return: Average return is a measure of the central tendency of a set of returns, calculated by summing the individual returns and dividing by the number of observations. It provides a general indication of the typical or expected return an investor can anticipate from an asset or investment over a given period of time.
Beta Coefficient: The beta coefficient, or simply beta, is a measure of the volatility or systematic risk of an individual asset or security in relation to the overall market. It quantifies the sensitivity of an asset's returns to changes in the broader market's returns.
Covariance: Covariance is a statistical measure that indicates the degree to which two random variables move in relation to each other. It quantifies the strength and direction of the linear relationship between two variables, providing insight into their joint behavior.
COVARIANCE: Covariance is a statistical measure that indicates the degree to which two random variables vary together. It quantifies the relationship between two variables, showing how changes in one variable are associated with changes in another variable.
COVARIANCE.P: Covariance.P is a statistical measure that quantifies the relationship between two random variables. It represents the degree to which the variables move together, indicating the strength and direction of their linear association.
Data Analysis: Data analysis is the process of examining, transforming, and modeling data to extract meaningful insights and support informed decision-making. It involves the application of various statistical and computational techniques to uncover patterns, trends, and relationships within a dataset.
Financial modeling: Financial modeling is the process of creating a numerical representation of a financial situation or scenario, often used to forecast a company's financial performance. It involves the use of spreadsheets and formulas to analyze data and make informed decisions regarding investments, budgets, and strategic planning.
Intercept: The intercept is a statistical term that represents the value of the dependent variable when the independent variable is equal to zero. It is a crucial parameter in linear regression analysis, providing insight into the starting point or baseline of the relationship between two variables.
Investment Decision-Making: Investment decision-making is the process of analyzing and evaluating various investment options to determine the most suitable course of action that aligns with an individual's or organization's financial goals and risk tolerance. It involves carefully considering factors such as expected returns, associated risks, and the overall fit within a diversified investment portfolio.
NFLX (Netflix): NFLX (Netflix) is the stock ticker symbol for Netflix, Inc., a leading global streaming entertainment service and production company. Investors analyze NFLX to assess its financial performance and growth potential in the highly competitive streaming industry.
Portfolio Return: Portfolio return is the overall rate of return earned on an investment portfolio, which is a collection of different assets such as stocks, bonds, and other financial instruments. It represents the total gain or loss experienced by an investor over a specific period of time, taking into account the performance of all the assets within the portfolio.
Portfolio Standard Deviation: Portfolio standard deviation is a measure of the dispersion or variability of the returns of a portfolio of investments. It quantifies the risk associated with a portfolio by calculating the average deviation of individual asset returns from the portfolio's overall return.
Regression Analysis: Regression analysis is a statistical technique used to model and analyze the relationship between a dependent variable and one or more independent variables. It allows for the estimation of the strength and direction of the association between these variables, providing insights that can be used for prediction, forecasting, and decision-making.
Risk-Return Tradeoff: The risk-return tradeoff is a fundamental concept in finance that describes the relationship between the level of risk associated with an investment and the potential return it can generate. It suggests that higher-risk investments typically offer the potential for higher returns, while lower-risk investments generally provide lower returns.
RSQ: RSQ, or the coefficient of determination, is a statistical measure that represents the proportion of the variance in the dependent variable that is predictable from the independent variable(s) in a regression model. It is a widely used metric in the context of investment decisions and portfolio analysis to assess the goodness of fit of a regression line and the strength of the relationship between variables.
Slope: Slope measures the rate of change between two variables, typically represented as the ratio of the vertical change (rise) to the horizontal change (run). In finance, it is crucial for understanding relationships in regression analysis, such as how a dependent variable responds to changes in an independent variable.
Slope: Slope is a measure of the steepness or incline of a line or curve. It represents the rate of change between two variables, typically the dependent and independent variables in a linear relationship.
Spreadsheet Formulas: Spreadsheet formulas are mathematical expressions used within a spreadsheet application, such as Microsoft Excel or Google Sheets, to perform calculations, manipulate data, and automate various tasks. These formulas are the building blocks that enable spreadsheets to become powerful tools for financial analysis, data modeling, and decision-making.
SPY: SPY is the ticker symbol for the SPDR S&P 500 ETF, which tracks the performance of the S&P 500 Index. It is commonly used as a benchmark for U.S. large-cap stocks.
SQRT: SQRT, or square root, is a mathematical operation that finds the positive value that, when multiplied by itself, results in the original number. It is a fundamental function used in various financial and investment calculations to determine values such as the present value of future cash flows, the risk-adjusted rate of return, and the standard deviation of investment returns.
Standard deviation: Standard deviation is a statistical measure that quantifies the amount of variation or dispersion in a set of data values. It is used to assess the risk and volatility of an investment's returns in finance.
Standard Deviation: Standard deviation is a statistical measure that quantifies the amount of variation or dispersion of a set of data values around the mean or average. It provides a way to understand how spread out a group of numbers is from the central tendency.
State Street Global Advisors: State Street Global Advisors (SSGA) is the investment management division of State Street Corporation, specializing in asset management and investment advisory services. SSGA is known for its role as a pioneer in exchange-traded funds (ETFs) and index investing.
STDEV.P: STDEV.P is a statistical function in Excel that calculates the standard deviation of a population. It is a measure of the spread or dispersion of a set of data points around the population mean, providing insight into the variability within the entire population.
STDEV.S: STDEV.S is a statistical function in Microsoft Excel that calculates the sample standard deviation of a dataset. The sample standard deviation is a measure of the spread or dispersion of the data points around the mean value, and it is used to quantify the variability or risk associated with a set of investment returns or other financial data.
SUMPRODUCT: SUMPRODUCT is an Excel function that multiplies corresponding elements in two or more arrays and then sums the products. It is a powerful tool for performing complex calculations and analyses in the context of investment decisions.
Systematic risk: Systematic risk is the risk inherent to the entire market or a market segment. It cannot be eliminated through diversification and is influenced by factors such as economic changes, political events, and natural disasters.
Systematic Risk: Systematic risk, also known as market risk or undiversifiable risk, is the risk inherent to the entire market or market segment, which cannot be mitigated through diversification. It is the risk that affects all assets and cannot be eliminated by holding a diversified portfolio.
VAR.P: VAR.P, or Variance of a Portfolio, is a statistical measure that quantifies the variability or dispersion of the returns of a portfolio of investments. It is a crucial metric in modern portfolio theory, as it helps investors understand the risk associated with their investment portfolios.
VAR.S: VAR.S, or Sample Variance, is a statistical measure that quantifies the spread or dispersion of a set of data points around their mean or average value. It is a fundamental concept in the field of investment analysis, as it helps investors understand the risk and volatility associated with different investment options.