Describing an asset, investment, or market that experiences relatively small and infrequent price fluctuations. It signifies stability and predictability in the price behavior over a given period. low-volatility investments are generally considered less risky than high-volatility counterparts but might also offer lower potential returns. This attribute is often sought by risk-averse investors and can be a desirable characteristic in times of economic uncertainty or market downturns. The level of volatility can be measured through various statistical methods, like the standard deviation.
Low-volatility meaning with examples
- Many retirees prefer low-volatility investment portfolios, like bonds and dividend-paying stocks, to protect their nest eggs from significant market swings. This cautious approach prioritizes capital preservation over high-growth potential to provide income with peace of mind. Diversification further reduces volatility within these portfolios.
- In times of economic uncertainty, investors tend to flock towards low-volatility assets, such as government bonds and gold, as 'safe havens.' This flight to safety increases their demand, and in turn, typically boosts their prices, acting as a hedge against market downturns.
- The fund manager aimed for a low-volatility strategy by investing in a diversified range of established blue-chip companies and sectors. The aim was to achieve consistent returns while minimizing the chance of major losses by spreading risk across various investment options.
- A common characteristic of low-volatility ETFs is their ability to track indexes comprised of stocks with historically stable price movements. This helps them offer investors exposure to companies with lower beta values compared to the broader market average.
- Low-volatility currencies, like the Swiss franc, are frequently preferred by global traders looking to minimize exchange-rate risk. Their relative stability makes them appealing for international transactions and as stores of value, providing greater predictability.