In mathematical finance, the sensitivities of option prices to various market parameters, also known as the “Greeks”, reflect the exposure to different sources of risk. Computing these is essential to predict the impact of market moves on portfolios and to hedge them adequately. This is commonly done using Monte Carlo simulations. However, obtaining accurate estimates of the Greeks can be computationally costly. Multilevel Monte Carlo offers complexity improvements over standard Monte Carlo techniques. However the idea has never been used for the computation of Greeks. In this work we answer the following questions: can multilevel Monte Carlo be useful in this setting? If so, how can we construct efficient estimators? Finally, what computational savings can we expect from these new estimators? We develop multilevel Monte Carlo estimators for the Greeks of a range of options: European options with Lipschitz payoffs (e.g. call options), European options with discontinuous payoffs (e.g. digital options), Asian options, barrier options and lookback options. Special care is taken to construct efficient estimators for non-smooth and exotic payoffs. We obtain numerical results that demonstrate the computational benefits of our algorithms. We discuss the issues of convergence of pathwise sensitivities estimators. We show rigorously that the differentiation of common discretisation schemes for Ito processes does result in satisfactory estimators of the the exact solutions’ sensitivities. We also prove that pathwise sensitivities estimators can be used under some regularity conditions to compute the Greeks of options whose underlying asset’s price is modelled as an Ito process. We present several important results on the moments of the solutions of stochastic differential equations and their discretisations as well as the principles of the so-called “extreme path analysis”. We use these to develop a rigorous analysis of the complexity of the multilevel Monte Carlo Greeks estimators constructed earlier. The resulting complexity bounds appear to be sharp and prove that our multilevel algorithms are more efficient than those derived from standard Monte Carlo.

Optioner säljs och köps idag flitigt av många olika anledningar. En av dessa kan vara spekulation kring framtida händelser för aktiepriser där optioner har fördelar jämfört med aktier i form av en hävstångseffekt. En annan anledning för optionshandel är för att hedga (säkra) risker vilket ställer krav på att innehavet av optionen ska kompensera den negativa effekt som riskerna bidrar till. Med andra ord, om det finns en risk för ett negativt framtida scenario som man inte vill riskera att utsätta sig för så kan optioner vara rätt verktyg att använda sig av.   Risker finns idag överallt, i olika former, vilket har bidragit till att efterfrågan av optioner har ökat enormt de senaste årtiondena. Dock kan risker vara både komplexa och varierande vilket har lett till att mer komplexa optioner har utvecklats för att mätta den efterfrågan som utvecklats på marknaden. Dessa, mer komplexa optioner, kallas exotiska optioner och de skiljer sig från de vanliga europeiska och amerikanska köp- och säljoptionerna. Däribland hittar vi bland annat lookback-optioner i form av bland annat köpoptioner på maximum och kvantiloptioner vilka är två av de huvudsakliga optionerna som diskuteras i uppsatsen.   Det har länge varit känt hur man prissätter europeiska köp- och säljoptioner via Black-Scholes-Mertons modell men desto fler komplexa optioner som tillkommer på marknaden desto mer komplicerade prissättningsmodeller utvecklas. Till skillnad från europeiska köp- och säljoptioner vars utdelning beror på aktiepriset på lösendagen så är lookback-optioner beroende av aktieprisets rörelse under hela kontraktstiden. Detta medför att prissättningen av dessa beror av fler parametrar än i Black-Scholes-Mertons modell, bland annat ockupationstiden för den stokastiska process som beskriver aktiepriset, vilket bidrar till andra prissättningsmodeller.   Uppsatsen har som syfte att redogöra för modellen som används vid prissättningen av kvantiloptioner samt presentera hur deras egenskaper förhåller sig till andra typer av lookback-optioners egenskaper. Det presenteras i rapporten att kvantiloptioner liknar vissa typer av lookback-optioner, mer bestämt köpoptioner på maximum, och att kvantiloptioners egenskaper faktiskt konvergerar mot köpoptioner på maximums egenskaper då kvantilen närmar sig 1. Utifrån detta resonemang så kan det finnas fördelar i att använda kvantiloptioner snarare än köpoptioner på maximum vilket investerare bör ta i hänsyn när, och om, kvantiloptioner introduceras på marknaden. / Options are today used by investors for multiple reasons. One of these are speculation about future market movements, here ownership of options is advantageous over usual ownership of shares in the underlying stock in terms of a leverage effect. Furthermore, investors use options to hedge different kinds of risks that they are exposed to, this demands that the option compensates the possible negative effect that the risk brings to the table. In other words, if there is a risk of a future negative scenario which the investor is risk averse to, then owning specific options which neutralize this risk could be the perfect tool to use.   Risks are today seen all over the market in different shapes which have created a great demand for options over the last decades. However, since risks can be both complex and range over multiple business areas, investors have demanded more complex options which can neutralize the risk exposures. These, more complex options, are called exotic options, and they differ from the regular American and European options in the way they behave with respect to the underlying stock. Amongst these exotic options, we can find different kind of lookback options as well as quantile options which are two of the main options that are discussed in this thesis.   It has been known for a while how to price European call and put options by the Black-Scholes-Merton model. However, with more complex options also comes more complex pricing models and unlike the European options’ payoff which depend on the underlying stock price at time of maturity, the lookback option’s and quantile option’s payoff depend on the stock price movement over the total life span of the option contract. Hence, the pricing of these options depends on more variables than the classic Black-Scholes-Merton model include. One of these variables is the occupation time of the stochastic process which describes the stock price movement, this leads to a more complex and extensive pricing model than the general Black-Scholes-Merton’s model.   The objective of this thesis is to derive the pricing model that is used for quantile options and prove that the properties of quantile options are advantageous when compared to some specific lookback options, viz. call options on maximum.  It is concluded in the thesis that quantile options in fact converges to the call option on maximum for quantiles approaching 1. However, quantile options come with some different properties which potentially makes them a good substitute for the call option on maximum. This is a relevant factor for investors to consider when, and if, quantile options are introduced to the market.