What is Volatility?

What is Volatility & How it Affects You?

Financial market volatility is defined as the rate at which the price of an asset rises, or falls, given a particular set of returns. It is often measured by looking at the standard deviation of annual returns over a set period of time. At its core, volatility is a measure of how risky a particular investment is, and it is used in the pricing of assets to gauge fluctuations in returns. That is, when the volatility is high, the trading risks are higher and vice versa. When volatility is used in the pricing of financial assets, it can help to estimate fluctuations that are likely to occur over the short term. If an asset’s price fluctuates quickly within a short timeframe, then it is considered highly volatile. An asset whose price moves slower over a longer time period is said to have low volatility.

Types of Volatility

Volatility is one of the factors that investors in the financial markets analyse when making trading decisions. There are two key approaches to volatility, each with its pros and cons:

• Implied Volatility:
  The term implied volatility describes the estimated volatility of an asset and it is a common feature of options trading. Implied volatility reflects how the marketplace views where volatility should be in the future, but it does not forecast the direction that the asset’s price will move. Generally, an asset’s implied volatility rises in a bear market because most investors predict that its price will continue to drop over time. It decreases in a bull market since traders believe that the price is bound to rise over time. This is down to the common belief that bear markets are inherently riskier compared to bullish markets. Implied Volatility is one of the measures that traders use to estimate future fluctuations of an asset price on the basis of several predictive factors.
• Realised / Historical Volatility:
  Realised volatility, also known as historical volatility, is a way of statistically measuring how the returns from a particular asset or market index are dispersed when analysed over a given timeframe. Normally, historical volatility is measured by establishing the average deviation of a financial instrument from its average price over a given period of time. Standard deviation tends to be the most common measure of realised volatility, though there are other methods used to calculate this metric. Risky security is one that has a high historical volatility value though, in certain types of trades, it is not necessarily a negative factor since both bullish and bearish conditions could be risky. In relation to these two metrics, historical volatility (backward looking) serves as a baseline measure, with implied volatility (forward-looking) defining the relative values of asset prices.

If the two metrics show similar values, then an asset is considered to be fairly priced on the basis of historical norms. For this reason, traders look for deviations from this equilibrium to establish if assets are overvalued or undervalued.

The Standard Deviation Model of Assessing Financial Volatility

Standard deviation is a measure used to statistically determine the level of dispersion or variability around the average price of a financial asset, making it a suitable way to measure market volatility. In general terms, dispersion is the differential between an asset’s average value and its actual value. The higher the dispersion or variability, the higher the standard deviation is. The lower the variation is, the lower the standard deviation. Analysts often use standard deviation as a means of measuring expected risk and determining how significant a price movement is.

When calculating the standard deviation of volatility, the variance of a data set of prices of an underlying asset must be derived. The standard deviation is the square root of variance. For purposes of illustration, we will consider the price of an underlying asset that has rallied uniformly from $1 to $10 in 10 trading periods. Standard deviation will be derived in the following steps:

1. Calculate the mean for the 10 trading days. This is done by adding the prices together ($1, $2….to $10) and then dividing it by 10 (in this case, the total number of prices). The sum of 55 divided by 10 will be $5.5.
2. Determine the deviation from the mean at each period. This is the difference between the closing price and the mean. For instance, on the 7^th day, the price of $7 deviates from the $5.5 mean by 2.5.
3. Square the deviation of each period. All the periods with negative deviations will be eliminated by squaring them.
4. Sum the squared deviations. As per our example, the sum is $82.5
5. Divide the sum by the number of periods, in this case, 10. This will be $8.25.
6. The standard deviation is the square root of this number. In this case, the standard deviation is $2.75 which reflects how values are spread out around the average price, giving traders insight as to how far the asset price may deviate from the average.

As the calculation above shows, standard deviation as a measure of risk assumes that the data set follows a normal distribution, or what is referred to as a bell curve. In such a scenario, as above, 68% of data will fall within one standard deviation; 95% will fall within two standard deviations, and 99.7% of data will fall within three standard deviations. But there are a few limitations to using standard deviation as a measure of volatility. To start with, prices or returns are never uniform, and they are punctuated by periods of sharp spikes in either direction. This will mean that the standard deviation itself may experience fluctuations depending on the periods that are taken into consideration during the calculation.

There is also the beta (β) method for measuring or calculating volatility. In this method, an underlying asset’s volatility is measured against other related assets. For instance, the volatility of Apple stock can be measured against the overall volatility of other technology sector stocks or even an entire benchmark stock index. Learn more about how this model of volatility assessment is calculated as well as its significance in our risk management guide.

Volatility Across Asset Classes

Volatility is a universal market feature — but its nature and impact differ dramatically across asset classes.

Understanding how volatility behaves in different markets is key to building strategies that are both adaptable and resilient.

1. Equities

Equity markets are often the poster child for volatility. Earnings reports, macroeconomic news, and investor sentiment can swing stock prices sharply within hours.

High-beta stocks like tech companies typically see greater price fluctuations, offering both opportunity and risk.

What to watch:

• Earnings season: Expect sharp price movements.
• Geopolitical events: Global tensions often hit equities first.

Strategy Tip:
Long-term investors may ride out stock volatility, while short-term traders can use tools like stop-loss orders or volatility-based indicators (e.g. Bollinger Bands) to manage positions more actively.

2. Forex

Currency markets tend to experience lower absolute volatility than equities, but leverage amplifies the risk. Political developments, central bank decisions, and macro data are common volatility triggers.

What to watch:

• Interest rate changes and central bank policy shifts.
• Cross-currency influence — a volatile USD impacts many forex pairs.

Strategy Tip:
Pair selection matters. Exotic or emerging market currencies tend to be more volatile than majors like EUR/USD or USD/JPY.

3. Commodities

Volatility in commodities often stems from supply shocks, seasonality, and speculation. Crude oil, for example, can experience sudden price swings due to geopolitical conflicts or OPEC decisions.

What to watch:

• Inventory reports (e.g. EIA, API) for oil.
• Weather forecasts in agricultural markets.

Strategy Tip:
Commodities traders should monitor futures contracts’ rollovers and news cycles closely. Position sizing is crucial to withstand large price moves.

4. Cryptocurrencies

Few markets are as inherently volatile as crypto. Thin liquidity, speculative behaviour, and decentralised governance mean prices can swing 10–20% in a day without major news.

What to watch:

• Exchange-specific news (e.g., hacks, outages).
• Regulatory announcements in key markets.

Strategy Tip:
Use tight risk management rules — never risk more than 1–2% of capital per trade. Consider pairing crypto exposure with less volatile assets for balance.

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Volatility Metrics Explained: Comparing the Tools

Volatility isn’t a single number — it’s measured in several ways, each offering different insights. Traders and investors use a range of volatility metrics to assess risk, anticipate price movement, and choose the right trading strategies.

1. Historical Volatility (HV)

This measures the actual past price fluctuations of an asset over a defined period — often 20, 30, or 90 days.

• Use case: Ideal for technical traders to assess past behaviour.
• Limitations: Backward-looking; may not reflect current sentiment or upcoming events.

2. Implied Volatility (IV)

IV is derived from options pricing and reflects the market’s expectations of future volatility.

• Use case: Options traders rely on this to price premiums and identify high-risk environments.
• Limitations: Sensitive to supply-demand imbalances in options markets, not purely predictive.

3. VIX (Volatility Index)

Often dubbed the “fear index”, the VIX measures expected 30-day volatility in the S&P 500, derived from options pricing.

• Use case: Market-wide sentiment gauge, especially useful during financial crises or major announcements.
• Limitations: US-focused; may not reflect volatility in forex, crypto, or commodities.

4. Average True Range (ATR)

A technical indicator that tracks the average range of price movement over time.

• Use case: Day and swing traders use ATR to set stop-losses and target levels.
• Limitations: Doesn’t distinguish between upside or downside movement — just the range.

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Why Volatility Matters?

Volatility Affects Trader Sentiment

Analysing market sentiment is an essential part of financial data analysis. Prices of assets traded on the financial markets will usually move up and down on a daily basis – a natural effect of the stochastic behaviour of the financial market. In spite of these price movements, hundreds of millions of investors worldwide continue to risk their money in the financial market, hoping to make returns in the future. The volatility of the financial markets is of interest to investors since high levels of volatility often come with the chance of huge profits or significant losses at the expense of higher uncertainty. If volatility is extremely high, investors may choose to stay away from the markets in fear of losing their funds. Others might engage in riskier trading in the hope of earning higher profits.

Volatility Affects Trading Costs

Volatility is a fact of investing life, and it guides or affects various decisions that investors have to make in the market. In general, high volatility implies high inherent risk, but it also means high reward opportunity. Money is made out of price changes in the markets, but high volatility carries additional risks as well. In CFD markets such as Forex, high volatility typically widens the spreads of underlying assets. This can directly impact overall profit potential or investing goals. The high volatility witnessed during the release of major economic news and events of underlying assets is a testament to this. In options trading, high volatility has the effect of increasing premiums (which is essentially the cost of an option contract). This is because of the perceived higher likelihood that a highly volatile asset has of hitting any relevant strike price and thus, expire in the money. Additionally, volatility can influence decisions on capital allocation and portfolio rebalancing. Typically, less volatile assets will be allocated a higher proportion of capital than more volatile ones. This can trickle down to position sizes with investors likely to trade more volatile assets with smaller lot sizes. Volatile assets can also skew the performance of an overall portfolio, and this may prompt investors to rebalance to achieve stability.

How Different Traders Respond to Volatility

Volatility affects every trader differently. Whether you’re managing a long-term portfolio or executing scalps on short timeframes, your success depends on how well you adapt.

Here’s how various trader types typically respond to volatility — and what you can learn from each.

1. The Day Trader: Thriving in Fast Markets

Volatility Response:
Day traders often embrace high volatility, as it increases the number of tradeable setups in a short period.

• Tools used: Tight stop-losses, 1–5 minute charts, ATR, and Bollinger Bands.
• Typical asset focus: Forex majors, stock indices, crypto.

Pro Tip:
Volatility can bring opportunity — but only with discipline. Use volatility filters and trade only during active market hours.

2. The Swing Trader: Selective Momentum Catcher

Volatility Response:
Swing traders look for controlled volatility, often waiting for breakouts or pullbacks that follow volatile spikes.

• Tools used: Moving averages, RSI, volatility contraction setups.
• Typical asset focus: Stocks, commodities, FX pairs.

Pro Tip:
Use volatility to your advantage by entering during consolidations and exiting into spikes. Avoid trading during earnings reports or economic releases unless prepared.

3. The Long-Term Investor: Volatility as a Stress Test

Volatility Response:
Investors often view market drops as buying opportunities, especially when driven by emotion rather than fundamentals.

• Tools used: Volatility-adjusted position sizing, dollar-cost averaging, diversification.
• Typical asset focus: Equities, ETFs, indices.

Pro Tip:
Rather than reacting emotionally, use volatility to rebalance portfolios and reassess risk tolerance.

4. The Options Trader: Volatility is the Edge

Volatility Response:
Options traders can profit from volatility itself      by choosing strategies that align with expectations for high or low IV.

• Tools used: Implied volatility charts, VIX, straddles, strangles.
• Typical asset focus: Equities and indices with deep options markets.

Pro Tip:
When IV is high, sell premium (e.g., credit spreads). When IV is low, buy premium (e.g., long calls/puts).

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Strategies to Manage and Leverage Volatility

Volatility is a double-edged sword. While it can magnify gains, it also increases risk — especially for unprepared traders.

Here’s how to manage volatility smartly and, when the opportunity arises, turn it to your advantage.

1. Adjust Your Position Size

Volatility expands potential price swings, so scaling down your position is a simple but powerful adjustment.

• In high-volatility conditions, reduce your exposure to preserve capital.
• Consider using a percentage of capital or volatility-adjusted position sizing tools (e.g. based on ATR).

2. Use Volatility-Based Stop-Losses

Fixed stop-loss distances don’t work well in volatile markets. Instead, use dynamic stops that adjust with volatility.

• Common methods: ATR-based stops, percentage volatility bands.
• Avoid stop placements that are too tight in choppy markets — you’ll be stopped out prematurely.

3. Diversify Across Asset Classes

Different assets respond differently to macroeconomic shocks. Use diversification to mitigate concentrated volatility risk.

• Mix in less volatile instruments (e.g. bonds, large-cap indices) during turbulent periods.
• Consider non-correlated assets — when stocks drop, gold or USD may rise.

4. Trade Volatility Itself

You can also trade the expectation or realisation of volatility:

• Use options strategies like straddles or strangles.
• Trade VIX derivatives or volatility-focused ETFs where available.

5. Set a Volatility Filter

Avoid overtrading by using a volatility threshold to determine when you’ll trade — and when to sit out.

• For example, only trade if ATR > X, or when price breaks beyond a specific Bollinger Band width.
• This helps avoid chop and frustration during low-volatility ranges.

6. Stay Emotionally Grounded

High volatility triggers impulsive decisions. A clear trading plan, coupled with pre-defined rules, protects you from reactive behaviour.

• Stick to your edge. Don’t widen stops or chase moves.
• Consider journaling trades and reviewing performance in volatile phases.

Derivatives Based On Volatility

Besides investments in stocks, currencies or commodities, some traders opt to invest in the concept of volatility itself through a number of derivative investments. These include exchange-traded notes (ETNs), which are similar to ETFs (exchange-traded funds) but are actually unsecured debt notes.

One of these derivatives is VIX, the ticker symbol for the Chicago Board Options Exchange Market Volatility Index. This index serves as a measure of how much traders are willing to invest in buying or selling of the S&P 500 index options.

The VIX is often referred to as the fear index or the fear gauge. The biggest and most popular VIX-related investments are the iPath S&P 500 VIX Short-Term Futures ETN (VXX) which has long positions in futures contracts. If you would want to trade on financial market volatility or use it as a hedge, then the VIX-related ETNs are acceptable instruments.

Case Studies in Volatility: Lessons from the Real World

Market volatility isn’t just theory — it’s shaped the most memorable chapters in financial history.

These real-world examples highlight how different traders responded to volatility and what we can learn from their actions.

1. The 2020 COVID-19 Crash: A Lesson in Liquidity Risk

In March 2020, global markets experienced historic levels of volatility. The S&P 500 plunged over 30% in weeks, while the VIX spiked above 80 — a level not seen since the 2008 financial crisis.

• Key Insight: Even fundamentally strong assets fell due to panic selling and liquidity shortages.
• Trader Response: Many institutions moved into cash, while seasoned retail traders used the VIX spike to sell high-premium options.

Takeaway: In volatile times, cash can be a position — and extreme volatility can offer premium-selling opportunities in the options market.

2. GBP Flash Crash 2016: Algorithmic Risk in Action

On 7 October 2016, GBP/USD plummeted over 6% in just two minutes during Asian trading hours, triggering widespread stop-losses. Many pointed to algorithmic trading and thin liquidity as key contributors.

• Key Insight: Volatility isn’t always macro-driven — technical and structural market issues matter.
• Trader Response: Traders with tight stops or overnight positions suffered. Those using volatility filters avoided entry during low-liquidity times.

Takeaway: Thin liquidity amplifies volatility. Consider time-of-day filters and avoid holding leveraged overnight trades in sensitive currency pairs.

3. Bitcoin’s Weekend Swings: The Wild West of Volatility

Unlike traditional markets, cryptocurrencies like Bitcoin trade 24/7 — and weekends often bring surprising price moves due to reduced liquidity and fewer institutional participants.

• Key Insight: Lack of weekend oversight can lead to wild volatility spikes.
• Trader Response: Crypto traders often reduce exposure before weekends or set wider stops to account for weekend slippage.

Takeaway: Schedule and structure matter. Build trading rules that reflect when, not just what, you trade.

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Volatility main FAQs

• What causes volatility in financial markets?

  Volatility is driven by factors such as economic news, earnings reports, geopolitical events, and changes in market sentiment. It reflects uncertainty about the future direction of asset prices.

   
• How can traders protect themselves during volatile markets?

  Traders can manage risk by reducing position sizes, using volatility-based stop-losses, diversifying across asset classes, and having a clear trading plan to avoid emotional decisions.

   
• What is the difference between implied and historical volatility?

  Historical volatility measures past price movements, while implied volatility reflects the market’s expectations of future price movement, often derived from options pricing.

• Is high volatility always bad for traders?

  Not necessarily. While high volatility increases risk, it also creates trading opportunities. Skilled traders often use it to capitalise on price swings, provided they use sound risk management.

The Final Word

Although some people have a negative view of volatility within the financial markets, it can actually increase the potential for profit if short-term trades are correctly predicted.

Cryptocurrencies, such as Bitcoin and Ethereum, are extremely volatile, but this is exactly what made trading them so profitable over the last few years.

Once you understand volatility and how it impacts asset prices, you are then able to benefit from these price movements.

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