What is Alpha and Beta in investing
- Ethan Noel
- 4 days ago
- 5 min read
Imagine if you bought Nvidia stock last year. It went up 40%: congratulations, you may just be the next Warren Buffet! However, upon glancing at your portfolio, you note that the S&P 500 also went up 25% in the same period. So how much of your 40% return was actually you (your research, your belief, your timing) and how much was just the entire market dragging everything upward, like a rising tide lifting all the boats in the sea? The key to exploring whether natural market movement or your unique trading acumen determines the performance of your investments lies in two important concepts: alpha (how your investment performs relative to a benchmark) and beta (how much your investment's price moves compared with the broader market).
These words may all sound like Greek to you, but their primary significance to investors is quite simple: they are metrics that gauge asset performance and risk.
IMPORTANT NOTE: Whenever ‘the market’ is referred to anywhere in this article, it
symbolises a major stock market index (for all intents and purposes I will stick to the S&P (500).
Beta: an asset volatility indicator
Every stock in existence sits somewhere on a spectrum. At one end, there are stocks that are highly sensitive to market activity (examples including AMD, Tesla and Nvidia), and at the other end are stocks that are indifferent to market trends (such as Berkshire Hathaway, Pfizer and ExxonMobil). Beta is simply a numerical score that indicates where on this spectrum any given stock exists.
A beta of 1.0 (the benchmark) indicates that the investment is in perfect correlation with the market; if the market rises 5%, the investment’s share price rises 5%. Index funds tracking the S&P 500, like Vanguard's VOO and iShares’ IVV, have a beta of exactly 1.0.
Investments with a beta above 1.0 are considered volatile (a stock with a beta of 1.7 means that for every 10% the market moves, it will move 17% in the same direction), so both gains and losses are amplified. On the other hand, an investment with a beta below 1.0 is considered less volatile than the market (a stock with a beta of 0.5 means that for every 10% the market moves, it only moves 5%).
Various factors can affect the beta of an investment: as a general rule of thumb, essential services and consumer staples (things that have low price elasticity of demand, or PED)tend to have low beta, while technology and software companies tend to have high beta. Case in point: Nvidia, whose fortunes are tied to investor speculation and growth-focused AI spending, has a beta of around 1.7. On the other hand, Coca-Cola, whose product is purchased in recessions and in booms without much variation in consumption, has a beta of roughly 0.55. Its share price reflects the stability and predictability of its revenues.
Neither a high or low beta is inherently superior, and deciding between them ultimately depends on your risk appetite and investment horizon. If you have a high risk tolerance and are hoping to quickly profit off of growth-focused stocks, then curating a high-beta portfolio is right along your lane. However, if you are just hoping to build up a consistent investing habit and steadily build wealth, then a low-beta portfolio is more suited for you.
Alpha: measuring the excess return on your investments
You’ve probably heard that it’s almost impossible to beat the market. In fact, 92%
of actively-managed US funds underperform the S&P 500. However, the investment managers of the other 8% have what is known as ‘positive alpha’; they have managed to extract extra returns on top of what the market has already produced. A fund with a beta of 1.0 and an alpha of 3% is not just matching the market but outperforming it by 3 percentage points even after accounting for the overall market direction. That excess return cannot be explained by riding the market wave (but has to come from somewhere), and can range from superior stock selection, better timing, deeper research, structural advantages in execution, or insight about mispriced assets that the rest of the market has missed.
The alpha figure indicates the percentage above or below a benchmark index that the stock or fund price achieved. It is also historical, so it can only be used to model past alpha figures and not predict what future values might be like.
As attractive as having higher alpha sounds, it is notoriously difficult to sustain gains in the long term. In 2007, Warren Buffett publicly wagered $1 million that a simple S&P 500 index fund (like VOO) would outperform any collection of hedge funds over the subsequent decade. A fund-of-funds manager named Ted Seides accepted the challenge, selecting five funds of hedge funds representing dozens of underlying managers. After ten years, the index fund had returned 85.4% cumulatively, while Seides’ average hedge fund portfolio returned 22%. The lesson is not that hedge fund managers are incompetent, but that the fees, trading costs, and the fundamental difficulty of sustaining alpha over long periods mean that even skilled managers frequently destroy more value than they create.
Making use of alpha and beta to improve investing decisions
If you hold an S&P 500 index fund, you are mostly accepted that your returns will be determined almost entirely by beta and are comfortable with that because over long periods, the market has consistently risen, and capturing its return at minimal cost beats the vast majority of professional strategies. It is a strategy that outperforms 92% of professional managers over 15 years and is recommended by Warren Buffett himself. Arguably, it is also the most rational choice for you , the inexperienced, young investor who does not have access to the informational advantages that generate sustained positive alpha.
If you choose to dabble in individual stocks, you are asserting that you have identified something about this company, this valuation, this moment, that the rest of the market has missed and you have not. Sometimes you will be right. However, keep in mind that an immense quantity of in-depth research (and time) is usually required to consistently make moves that generate genuine alpha, something that is not usually available to the majority of retail investors. If you find yourself making decisions based on FOMO or gut-feel and are attempting to pass it off as being a high-alpha investor, remember that you’re not trading, you’re just gambling.
Fun expansion: visualising everything using linear regression
To summarise, this graph will show how alpha and beta intertwine to explain stock returns.
(Rp is the portfolio return, Rm is the market return and Rf is the risk-free rate.)
The formula for stock returns is this: Rp - Rf = α + β(Rm-Rf) + ε
y is your stock's return in a given period.
x is the market benchmark's return in that same period.
β (beta) is the slope of the regression line. If the line is steep, beta is high, meaning your stock amplifies market movements strongly. If the line is nearly flat, beta is low, meaning your stock barely reacts.
α (alpha) is the y-intercept: where the line crosses the y-axis, i.e., the stock's predicted return when the market return (x) is exactly zero. This is the portion of the stock's return that exists independently of whatever the market is doing.
ε (epsilon) is the error term (the residuals) and is represented by the vertical distance from each actual dot to the regression line. Some weeks, Nvidia dramatically outperformed what its beta would have predicted; some weeks it dramatically underperformed. These deviations are caused by events that no model can forecast: a surprise earnings beat, a regulatory ruling, a product recall, a CEO resigning. This is called idiosyncratic risk (the risk that is specific to the company), as opposed to systematic risk , which comes from beta and is shared by everything in the market.
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