For Variance Swaps (and Vol swaps with some caveats), the Black Scholes model is the main tool used for pricing. It is just less obvious. Using your example, options are not priced with S-K or K-S either. That is simply an algebraic expression of parts of the contract. Pricing involves finding a value for this. There is no assumption on pricing configuration or even numeraire. Therefore, you cannot simply use Black Scholes. It depends largely on the underlying how you price this. Is it equity, an index, a commodity (mostly futures), an exchange rate, a bond? Or whatever other underlying you can think of. Does the stock pay dividends? In the case of FX, what currency is your notional and premium in ([Garman Kohlhagen][1] assumes notional in ccy1 and premium in ccy2, everything else requires (simple) adjustments to the formula). Just like options where you have the underlying price versus a strike, all swaps share a common payoff, they exchange cashflows (side note, a CDS Swap is a bit of a misnomer as they are really options from a pricing perspective, with upfront payments). Generally with swaps, one distinguishes pricing from valuation: - pricing involves determining the appropriate price (or rate) when initiating the contract which makes the swap typically zero cost at initiation - valuation involves determining the appropriate value of the commitment (typically after it has been initiated) For vanilla fixed float IRS swaps, the par swap rate is the coupon of an interest rate swap that makes the market value of the swap equal to zero (the fixed rate that makes the value of the fixed leg equal to the value of the floating leg). For variance swaps, the fair rate is such that the contract is also zero at the initiation. That is all there is in common though. IRS require interest rate curves built from instruments (cash, FRAs or futures and swaps) to correctly price and value them. Essentially you need discount factors and forward rates, but the actual process of curve building is very involved, and nowadays involve usually multiple curves being stripped simultaneously. Curve selection and the like make this almost more art than science. Variance swaps have a theoretical replication. A vanilla option trader following a delta-hedging strategy is essentially replicating the payoff of a weighted variance swap where the daily squared returns are weighted by the option’s dollar gamma. Taking this argument one step further, a fair variance swap can be shown to equal the integral of weighted prices of out-of-the-money options over all strikes. These weights are being inversely proportional to squared strikes, an application of the BlackScholes closed-form formula for gamma. One obvious problem here is that options markets are composed of a discrete set of option prices for a given maturity. Therefore, it is common to first compute a vol surface, usually using Black Scholes again (ignoring complications involved in creating vol surfaces, like de-Americanizing option prices, finding implied forwards and dividends and the like if we think of index or equity VS, FX, for example, is generally quoted in vol which makes surface construction easier). Practically, you may also want to limit the integration region (strike range) to avoid issues with the weights (especially very small strikes are a concern due to the weighting). Due due to practical difficulties in replicating the actual log payout across strikes, the market for equity index varswaps usually trades at a basis to the replicating portfolio. For Vol Swaps, things are a bit messier. Simplified, a Volswap is a varswap - convexity adjustment and the convexity adjustment can be replicated with a portfolio of options on var. So you essentially have 2 replicating portfolios. There are two documents from JP Morgan [Variance Swaps][2] and [Just what you need to know about Variance Swaps][3] with the latter being more concise. On a side remark, the way delta and gamma are defined here is a simplification. It will only work intraday. Ideally, the Greeks are directly derived from the replicating portfolio. However, such a full decomposition is not something (many) vendors offer and mainly tier 1 banks have implemented. [Towards a Theory of Volatility Trading][4] by Peter Carr et al. is probably the best paper to read. Correlation swaps are a beast of their own. I cannot comment much on them as it's beyond my knowledge. They are frequently priced with MC based on LV or SLV but neither will price them properly for numerous reasons. There are some models like Local Vol Local Correlation (LVLC) that may be a bit better but at the end of the day, these are very exotic. Since you wrote you are very new to derivatives pricing I would avoid looking into them as long as possible. Chances are you will never need to know what goes on here (unless you are a (physics) PhD specifically hired as a quant for these products). There is a good [tweet][5] I stumbled upon some time ago. Many people tend to think if a tool gives a price it works (here Monte Carlo Local Vol). However, that is classic [GIGO][6]. MCLV will not even price a vanilla VS properly (calibration is never perfect; MC time steps are limited...). [1]: https://en.wikipedia.org/wiki/Foreign_exchange_option#Valuation:_the_Garman%E2%80%93Kohlhagen_model [2]: https://fdocuments.net/document/variance-swaps-jp-morgan.html [3]: https://www.sk3w.co/documents/volatility_trading.pdf [4]: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.27.6011&rep=rep1&type=pdf [5]: https://twitter.com/NihilistTrader/status/1336661648598249473 [6]: https://en.wikipedia.org/wiki/Garbage_in,_garbage_out#:~:text=In%20computer%20science%2C%20garbage%20in,out%20(RIRO)%20is%20used.