REPOZYTORIUM UNIWERSYTETU
W BIAŁYMSTOKU

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 Tytuł: Introduction to Stochastic Finance: Random Variables and Arbitrage Theory Autorzy: Jaeger, Peter Słowa kluczowe: random variablearbitrage theoryrisk-neutral measure Data wydania: 2018 Data dodania: 20-sie-2018 Wydawca: DeGruyter Open Źródło: Formalized Mathematics, Volume 26, Issue 1, Pages 1–9 Abstrakt: Using the Mizar system [1], [5], we start to show, that the Call-Option, the Put-Option and the Straddle (more generally defined as in the literature) are random variables ([4], p. 15), see (Def. 1) and (Def. 2). Next we construct and prove the simple random variables ([2], p. 14) in (Def. 8). In the third section, we introduce the definition of arbitrage opportunity, see (Def. 12). Next we show, that this definition can be characterized in a different way (Lemma 1.3. in [4], p. 5), see (17). In our formalization for Lemma 1.3 we make the assumption that ϕ is a sequence of real numbers (there are only finitely many valued of interest, the values of ϕ in Rd). For the definition of almost sure with probability 1 see p. 6 in [2]. Last we introduce the risk-neutral probability (Definition 1.4, p. 6 in [4]), here see (Def. 16). We give an example in real world: Suppose you have some assets like bonds (riskless assets). Then we can fix our price for these bonds with x for today and x · (1 + r) for tomorrow, r is the interest rate. So we simply assume, that in every possible market evolution of tomorrow we have a determinated value. Then every probability measure of Ωfut1 is a risk-neutral measure, see (21). This example shows the existence of some risk-neutral measure. If you find more than one of them, you can determine – with an additional conidition to the probability measures – whether a market model is arbitrage free or not (see Theorem 1.6. in [4], p. 6.) A short graph for (21): Suppose we have a portfolio with many (in this example infinitely many) assets. For asset d we have the price π(d) for today, and the price π(d) (1 + r) for tomorrow with some interest rate r > 0. Let G be a sequence of random variables on Ωfut1, Borel sets. So you have many functions fk : {1, 2, 3, 4}→ R with G(k) = fk and fk is a random variable of Ωfut1, Borel sets. For every fk we have fk(w) = π(k)·(1+r) for w {1, 2, 3, 4}. Today Tomorrow only one scenario {w21={1,2} w22={3,4} for all d∈N holds π(d) {fd(w)=G(d)(w)=π(d)⋅(1+r), w∈w21 or w∈w22, r>0 is the interest rate. Here, every probability measure of Ωfut1 is a risk-neutral measure. Afiliacja: Siegmund-Schacky-Str. 18a, 80993 Munich, Germany URI: http://hdl.handle.net/11320/6829 DOI: 10.2478/forma-2018-0001 ISSN: 1426-2630 e-ISSN: 1898-9934 Typ Dokumentu: Article Występuje w kolekcji(ach): Formalized Mathematics, 2018, Volume 26, Issue 1

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