Earful.info
May 30, 2005
Quantitative Portfolio Optimization for Record Labels & Music Publishers
Higher profits, with less risk and a smaller capital investment
Labels and publishers can reduce their risk and increase their returns with less capital using quantitative finance. Portfolio theory challenges the assumption that it takes ten artists to break one. Instead, it argues that the same results are attainable with fewer artists through the deliberate selection and removal of assets based on (1) risk, (2) return and (3) how assets move in relation to one another. Weighting asset sectors (artists, masters or song catalogs by musical genres, for example) in a quantitatively structured manner can yield portfolios with far fewer assets and better expected risk-return properties. Our methodology is based on the fact that record labels and music publishers are purchasers of risk. Music companies pay advances to recording artists and writers for their creative output. In these transactions, artist sell their risk of failing along with the intellectual property. Music companies perform a speculative function, similar to the commodities markets: They purchase risk, and they profit by reducing the risk through marketing and diversification. Our goal is to provide a mix of artists, masters and publishing catalogs that delivers the maximum attainable return for a given level of volatility (risk). Three basic elements need to be tracked: risk, return and covariance. Each term is defined in the following three sections.
Key benefits: • Higher returns • Lower risk • Less capital • Lower cost of capital • Lower marketing expenses • Reduced staffing • Ability to identify and reward your best executives • Predictive power
“Our goal is to provide a mix of artists, masters and publishing catalogs that delivers the maximum attainable return for a given level of volatility (risk).”
Returns Financial returns can be decomposed into two portions: expected returns (e.g., risk-free rate, target return, etc.) and unexpected returns — any profit above, or loss below, the expected return. Our approach maximizes unexpected returns at a given level of risk. Risk and Diversification Risk is the variation in returns. The greater the frequency and the magnitude of changes in results, the higher the risk. Risk is an inescapable part of business. It is the opportunity cost for seeking profits. This is why risk and return tend to rise and fall together. Asset risk can be divided into two categories:
Inside this report: Benefits Biographies
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Systematic risk: market-related risk that influences a large number of assets. For example, piracy’s impact on total music industry sales. Unsystematic risk: residual, asset-specific or diversifiable risk. example, the death of an artist. For
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Unsystematic risk can be reduced, even eliminated, through diversification: the spreading of an investment across two or more assets. In a well diversified portfolio, the positive and negative asset-specific outcomes tend to cancel each other out. Therefore, large portfolios essentially do not have unsystematic risk, only systematic risk: The risk associated with individual assets is eliminated. A minimum level of risk, the systematic risk, cannot be eliminated through diversification. Therefore, systematic risk is referred to as non-diversifiable risk. Only the systematic risk is relevant in determining the expected return and risk premium for a properly diversified portfolio. The systematic risk is inescapable and must be borne by all investors; unsystematic risk is carried because of inefficient diversification. Covariance and The Power of Portfolios Variance is a measure of risk: how returns fluctuate relative to the mean. Covariance is a measure of the correlation between fluctuations in one asset’s returns and the fluctuations in returns of the other assets in the portfolio. Returns can be maximized for any level of risk (conversely, risk can be minimized for any return) using a portfolio optimization methodology. Covariance is the most important factor to consider when adding an asset to a portfolio. Allocating among assets with a high level of covariance helps offset individual risks against each other. As a result, portfolio risk tends to be less than the individual assets that comprise the portfolio, including its least risky asset. The best known portfolio management tool is the capital asset pricing model (CAPM). It establishes a proportional relationship between the return on an asset and the return on the market (quantified by Beta; β) to derive asset returns on a single factor—the market return. The higher the covariance, the higher the Beta, and the higher the required return . CAPM is valuable, but the excess return may be explained by sensitivity to a number of factors. The Arbitrage Pricing Theory (APT) produces forecasts that are more accurate than CAPM because it includes many variables. The additional factors add complexity, but improve the explanatory power. The permutations of asset covariances increases exponentially as additional assets and factors are added. Matrices must be used to ease calculations. This yields the following general formula for portfolio optimization:
Covariance considers how asset returns fluctuate in relation to one another.
“Covariance is the most important factor to consider when adding an asset to a portfolio.”
σ
Diversification drives down unsystematic risk so only the systematic risk remains.
P
=
r w
T
r • ∑ •w
σp = portfolio volatility for portfolio P r w T = the transposed weighted vector Σ = the variance-covariance matrix
r w = the weighted vector
Quantitative Portfolio Optimization for Record Labels & Music Publishers
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From here the sophistication grows. The best way to express a factor that has variability is in a distribution, not as a single number. Enhancements to portfolio design and asset allocation include advanced statistical methods, such as Quasi-Random Monte Carlo Simulated Asset Allocation (QRMCSAA)). Despite the complexity, covariance lies at the heart of portfolio optimization, controlled by the assets included and their weights. Sophistication with Limitations Most efforts to obtain the highest return for a given level of risk (the lowest risk for a given level of return), use standard formulas and assume that asset returns fit a statistically normal distribution. In reality asset return distributions often are skewed, tilt (leptokurtosis) and have fat tails. To find an allocation that will deliver the desired return for given level of risk with a degree of probability requires considerable quantitative skills and specialized financial acumen. Efficient portfolios cannot be improved upon from a risk-return standpoint. Clients may push for greater returns, but it is not possible to alter an efficient portfolio without increasing risk. Applying a portfolio approach, and then placing a disproportionate emphasis on returns, is a major cause of failure. The expertise needed to control a portfolio increases as the number of included assets grow. Labels have many artists, and publishers have a large catalog of songs. Transaction costs rise the more often a portfolio turns over. This is an issue because of ongoing changes to rosters and catalogs. This may either add to the expense or limit suggested allocation to the genre or subgenre level. Portfolio optimization does not increase by adding more finely defined asset categories. Lowering the aggregation levels adds to the instability of the model, because it will suggest a greater number of changes to a company’s holdings. Our quantitative approach is useful for revealing the impact of return variances on financial performance, without revealing the exact causes of risk. Therefore, the approach has strategic value, but little tactical benefit. Finally, as much as 90 percent of a portfolio’s performance can be explained by the initial asset allocation (Branson, Singer and Beebower 1986 and 1991). Near- and mid-term performance may be partially constrained because we are entering established organizations. The music assets of an existing company may not be structured ideally, and it may be imprudent to rapidly alter them to conform to our model. However, by rigorously optimizing portfolios, returns should rise. The Benefits of Applying Portfolio Management to the Music Industry Approximately nine out of ten new artists fail. To obtain reliable cash flow under the existing industry model requires considerable capital either to absorb the risk of failure or to acquire artists, masters and publishing catalogs with proven, stable histories. Effective portfolio management using quantitative finance can reduce risk to a minimum for a given level of return. It helps labels and publishers target the mix of music assets to sign or acquire to maximize their risk-return ratio.
Plotting risk and returns produces an efficient frontier; a representation of efficient portfolios. CAPM and more sophisticated tools are applied to identify music assets with suitable riskreturn profiles.
“To find an asset allocation … requires considerable quantitative skills and specialized financial acumen.”
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Barry Sosnick, the president and founder of Earful.info, held positions as an equity analyst and as a senior project leader for a political polling and market research company. Mr. Sosnick is on the advisory board for the Music and Entertainment Industry Educators Association (MEIEA), the association for entertainment industry academics. Barry presented two major academic studies: “The Changing Recorded Music Industry” at Loyola University, New Orleans in 2003 and “A Capital Budgeting Approach to Understanding Artist-Label Relationships” at the University of Miami in 2005. Peter Alhadeff is an Associate Professor at the Berklee College of Music. Dr. Alhadeff received his PhD from the University of Oxford, U.K. in economic history. He is a published author in economics journals and books, including St. Antony’s/Macmillan Series, Oxford. Peter also authored the book Algebra de Vectores y de Matrices. He is the editor of Recording Magazine en Español and the associate editor of Músico Pro. Music business articles include publications by the Recording Academy’s Grammy 2000, and Grammy Latino.
Strategic Marketing and Risk Management Solutions for the Recording Industry
An optimized portfolio seeks to minimize the number of assets necessary to reach a risk-reward goal. This reduces costs, and can maximize profits. Fewer advances get paid. Less marketing dollars are wasted, because the probability of success increases. In addition to selecting assets to add, our methodology highlights holdings that do not contribute to improving returns or reducing risk. Some artists or titles may be profitable at the moment, but do not add sufficient risk-adjusted value. Selling them frees up cash. Increasing returns on investment and working capital will reduce the cost of capital. Stronger cash flow and the capital freed from divested holdings shrinks the capital requirement. Financing costs will likely decline as returns increase. For public companies in particular, investors reward consistent profitability with a higher price-to-earnings ratio. Finally, the quality of management improves. Using a quantitative approach prevents managers from pursuing profits recklessly or becoming so risk-adverse that they miss out on profitable opportunities. Benchmarking volatility in addition to benchmarking returns will help find, retain and reward the managers producing above average profits without taking unnecessary risks. Quantitative portfolio management requires sophisticated mathematics. The rewards for record labels and music publishers from this financial discipline are higher returns, less risk, increased marketing efficiency, smaller capital requirements, a lower cost of capital and better management. We look forward to working with your company soon.