A Real-Life Example

To start with a very simple example what an option in life can be, let's try to analyze a typical real-life example. Imagine that your favourite ski resorts implemented a dynamic pricing strategy. Let's assume you plan to go skiing in four weeks' time, the price for a one-day card buying now is 75 CHF. Because you are not sure whether you will really go skiing, depending on factors such as weather, snow conditions and personal circumstances, you try to get an option to buy the ticket at a price of 75 CHF for the weekend in four weeks' time. Let's assume the ski resort is willing to sell you that option at a price of 5 CHF - the so called premium.

Fast forward in four weeks' time there are two possible outcomes:

1. Snow conditions are perfect, weather forecast for the weekend is stunning, everybody wants to be on the slope, ticket prices are meanwhile at 95 CHF for the day. Because you have the option to buy at 75 CHF, you will exercise that option and buy the ticket. Your overall costs are 80 CHF (75 CHF for the ski ticket + 5 CHF for the option) and therefore you are better off by 15 CHF compared to buying at 95 CHF.
2. There are very poor snow conditions and weather forecast for the weekend is terrible, demand for going to the slope is very poor and ticket prices are available at a price of 65 CHF. You won't exercise your option to buy at 75 CHF, the option expires without inner value. You still paid the 5 CHF premium.

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Impacts on Pricing

What are the drivers to determine the value of the option? How can the ski resort define the 5 CHF for the price of this option? There are several components that are given to determine pricing:

• ‍Strike price: The ski resort agreed to sell the ticket at 75 CHF. It is relatively easy to understand that if they would have agreed to sell the ticket at 80 CHF, the price of the option would have been lower than the agreed 5 CHF.‍
• Maturity: The agreed option had a term of four weeks, a relatively short maturity. Snow conditions could already have been estimated for that weekend, so uncertainty would probably be higher for longer dated option, and therefore also the costs of the options in case of longer maturity.‍
• Implied Volatility: A major driver of the premium is the expected variability in future ticket prices. The more unpredictable the weather, snow conditions and demand are, the wider the range of potential price outcomes becomes — and the higher the premium needs to be. Higher implied volatility means a higher risk for the resort that market conditions will move unfavorably, which is directly reflected in a higher option price.

The strike price and maturity can be relatively easy determined and calculated with mathematical models. Now the more difficult factor is to calculate the probability based on the expectation of changing weather and snow conditions (implied volatility). There are two components determining the outcome:

• ‍Historical weather and snow conditions: The historical volatility in weather and snow conditions for the agreed weekend can be an indicator for the future. You can expect that if in the past 20 years the snow conditions have been good in that ski resort during the same time with a similar forecast, that it will be also the case this year. The weather will be more difficult to predict, but there may be seasonal patterns. ‍
• Expected weather and snow conditions: Assume this year because of warm temperatures, snow conditions are very poor and led to more windy conditions than in previous years. Would you expect everything to be the same as previous years? Probably not, and because of the shift in expectation you would probably also change pricing expectations for the day-pass and respectively change the willingness of what you pay for the option

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Impact of Implied Volatility

In financial markets, option pricing follows the same general logic as in our ski-ticket example. One of the most influential components is implied volatility – the market’s collective expectation of how much the underlying asset might move over the lifetime of the option. It is distinctly forward-looking.

To put this into context, markets typically reference three types of volatility:

1. ‍Historical volatility – how much the asset has fluctuated in the past‍
2. Realized volatility – how much the asset actually fluctuates over a recent or specific period‍
3. Implied volatility – how much volatility the market expects in the future, embedded in the option price itself

These three measures often differ. Historical and realized volatility look backward, while implied volatility reflects current expectations and sentiment about future uncertainty.

Practitioners use mathematical models such as the Black-Scholes model, the Binomial (Cox-Ross-Rubinstein) model or Monte Carlo simulations to estimate theoretical option prices. Inputs like strike price, maturity and interest rates are straightforward. Implied volatility, however, is not directly observable; it is inferred from the actual market price of the option – the point where buyers and sellers agree. For investors, implied volatility is therefore a crucial reference point. It signals how calm or turbulent markets expect the future path of an asset to be – and directly shapes the premium you pay or receive when trading options.

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Why Volatility Matters Most

Regardless of whether we look at call options (the right to buy) or put options (the right to sell), one principle is universal: higher implied volatility leads to higher option prices. Volatility reflects the uncertainty about an asset’s future price path. For investors, this increased volatility can represent a meaningful risk, since highly volatile assets tend to show larger and more frequent price swings, making drawdowns, unpredictable outcomes and rapidly shifting market dynamics more likely. In such environments, even distant strike prices may be reached more easily, increasing the probability that options are exercised in ways that may be disadvantageous for the seller. At the same time, higher volatility also results in higher option premiums, which some investors may view as a way to monetise uncertainty by generating additional income. From this perspective, volatile assets can be seen as offering opportunities for enhanced premium capture, provided that the higher probability of adverse price movements is taken into account.