Basics of Investing & Portfolio Management

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Part I: Risk Metrics

Lesson 11

We will learn some of the most important strategies to measure and control risk.
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Part I: Risk Metrics

In the previous segment of this course (Basics of Investing), we defined risk and started talking about how the main asset classes are affected by it. Now, we will dig deeper into risk and we will learn how to measure and control it.

Just as a quick refresher, investment risk is the possibility of losing money when investing. It is crucial to understand that there is a necessary trade-off between expected returns (what you expect/wish to gain) and risk. This means that the more you expect to gain from your investments, the higher risk you will have to bear to achieve it. The different asset classes we have seen in this course have different risk characteristics: stocks tend to yield higher returns at a higher risk, bonds normally have a lower risk but you can expect to get lower returns in the long run.

Now that we have the abstract idea of risk down and we understand the basic relationship between risk and return, we can start learning how to quantify it.

Risk Metrics

Risk is a difficult characteristic to measure as we must deal with probability, statistics, and the unknown. Therefore, quantifying risk has been the main focus of the finance world for decades. There are many different strategies and formulas that intend to measure risk as accurately as possible; however, most are really far from perfect. In this section, we will take a look at the main metrics we use to try to identify investment risk.

If an investment yields a higher return than another investment, does that make it automatically better? Not necessarily. In order to determine which investment is better, it is important to take into account risk and return, and their relationship. Let’s see how we can do that.

In order to evaluate the quality of an investment or a strategy, we analyze the following key (most important) risk metrics:

Standard Deviation

This is the most commonly used risk metric in the finance world. It is a simple statistic that measures the dispersion of your investment returns from their mean. In other words, it measures the distance between your returns and the average return of your investments. So, if an asset has huge swings in value (both up and down), its standard deviation would be higher than an asset whose value is steadier and fluctuates less.

The calculation has a few steps which can be fairly complex when dealing with a lot of data. Now, we will focus on understanding the essence of the metric. We will explain and analyze the formula in depth in a future segment.

For now, all you need to know about the Standard Deviation measure is the following:

  1. Expressed as a percentage: it measures the volatility of percentage changes in asset prices (returns)
  2. Average distance of the asset prices from their average: it increases when prices fluctuate further from their mean
  3. Daily, monthly or yearly: it is typically used to measure daily, monthly or yearly volatility
  4. Positive and negative volatility:  it doesn’t differentiate between prices that go higher vs prices that go lower, it takes both into consideration.
  5. Normal distribution: it assumes the distribution of the data is normal, which is not always true
  6. Comparison of the volatility of different assets: e.g. Microsoft has a yearly Standard Deviation of 15% vs US Government Bonds had a yearly Standard Deviation of 2% (Microsoft is more volatile than Government Bonds)
  7. Identify unexpected outcomes:
    • E.g. If your average daily return is 1% and one day you get 6%, looking at the standard deviation can help you determine the likelihood of that happening again.
    • Studies show that approximately 68% of your returns will fall within one standard deviation of your average return, 95% will fall within two standard deviations and 99.7% will fall within 3 standard deviations.

Beta

Beta is another volatility measure commonly used to compare an asset’s (or strategy’s) volatility to the risk of the broader market (systematic risk). In other words, if a specific asset or a strategy has higher swings (it is more volatile) than its broader market, its beta will be higher than 1.0; and if it moves less than its broader market, it will have a beta below 1.0. Therefore, if an asset has a beta of 1.5, it will theoretically be more volatile than its market, with higher expected returns but with higher intrinsic risks.

An asset’s broader market refers to the stock market which the asset belongs to. Generally, a market’s index is used as a proxy for the broader market (benchmark); for instance, the S&P500 Index can be used as a proxy for the US market, or the STOXX Europe 600 can represent the European market.

The beta coefficient is a statistical measure that represents the slope of the regression line plotted by inputting an asset’s returns against its market’s. It is also a component of the CAPM (Capital Asset Pricing Model), which intends to assess the return investors can expect to receive based on volatility. We will look into regression and the CAPM in future segments.

Many investors use beta to try to quantify how much risk new investments could add to their portfolios.

For now, all you need to know about the Beta measure is the following:

  1. Asset volatility vs its market’s: it measures the volatility of an asset against its market’s systematic volatility
  2. Its value revolves around 1.0:
    • A beta lower than 1.0 = lower risk and lower return than that of the market
    • A beta equal to 1.0 = similar risk and similar return to that of the market
    • A beta higher than 1.0 = higher risk and higher return
  3. 5 year, monthly: you can easily find an asset’s beta online, many sites report data by analyzing an asset’s 5-year monthly performance vs its market’s
  4. Shorter-term volatility measure: many investment professionals argue that beta is more useful for short-term volatility analysis than for long-term investing

We believe it is a good measure to assess an asset’s level of risk, but investment decisions should not be made just based off of the beta metric.

Alpha

Similarly to beta, alpha also compares an asset to its market. However, beta measures the volatility of that asset compared to the volatility of the market. Alpha is used to measure the risk-adjusted performance of an asset compared to its market.

Ultimately, we use alpha to figure out if we are being compensated for taking on more or less risk than the markets. 

An alpha higher than zero implies that our investment has outperformed its market on a risk-adjusted basis. An alpha of zero means that our investment generated returns that are exactly adequate for our level of volatility if compared to the market. An alpha below zero is a sign that we are taking too much risk for the returns we are getting and we are underperforming the market.

We will further discuss alpha in future segments. 

Beta and Alpha

Imagine you invested $1,000 in SmarPies Co. Last year, you earned a 14% return and you had a beta of 1.3. As a proxy for our market, we will use the S&P 500 Index, which had a 12% return in the same period. Let’s see if our investment is better than the market:

Our 1.3 beta implies that our volatility was 30% higher than that of the market. In order to make our investment worth it, our returns should also be 30% higher than that of the market (to compensate for the higher volatility). The minimum acceptable return would be 15.6%:

 Market return of 12%  x  (1  +  30% for volatility compensation)  =  15.6% minimum acceptable return

However, our return was only 14%, which is 1.6% away from the 15.6% needed. Therefore, we would have a negative alpha of -1.6%, which tells us that our investment is not good compared to the market because its higher return isn’t enough to compensate for the risk.

Both beta and alpha may be difficult to accurately measure in a diversified portfolio since both metrics compare an investment to its market. In order to properly calculate both metrics, we must compare our investment to its actual market; and if your investment is a portfolio with a mix of asset classes, it may be tricky to find a proper proxy for the market measure.

In the next section, we will continue discovering the most important risk metrics. We will see some more advanced ways to assess investment risks.

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