Problem With Lower And Upper No-Arbitrage Barriers And Inequalities-Financial Mathematics











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EXERCISE




We consider a financial market of one period with two stocks $(S_0,S_1)$.
We further consider a purchase option with repayment $C = (S_1^{1} - K)^+$
with a value of $K> 0$ and maturing time $T = 1$. Let $underline{π}(C)$,$overline{π}(C)$ the lower and upper no-arbitrage barriers for the value of $C$.



a)Show that the following inequality applies
$$underline{π}(C)geq bigg(S_1^{1} - dfrac{k}{1+r}bigg)^+$$



Please also show that the following equality applies
$$underline{π}(C)= bigg(S_1^{1} - dfrac {k}{1+r}bigg)^+$$



if it is further assumed that:
$$P[S_1^{1}=S_0^{1} cdot(1+r)]> 0$$



Hint : Use the probability measure $$Q[·]: = P [·|S_1^{1} =S_0^{1}cdot (1+r)]$$



b) Also show that the following inequality applies
$$underline {π}(C)leq S_0^{1}$$



and that the following equality applies
$$overline{π}(C)=S_0^{1}$$



assuming that $rm ess sup S_1^{1}=infty $ and that $rm ess inf S_1^{1}=0$.




ATTEMPT



a)We have a financial market with no-arbitrage so we have the form:
$$π(C)=E_Qbigg[dfrac{c}{1+r}bigg]<infty$$ for $Qsubset P$



So,$$underline{π}(C)geq inf_{Q in P}E_Qbigg[dfrac{c}{1+r}bigg]=inf_{Q in P}E_Qbigg[dfrac{S_1^{1}-k}{1+r}bigg]=inf_{Q in P}dfrac{1} {1+r}E_Q[S_1^{1}-k]$$



UPDATE



Ι think that i have to use put-call-parity equation:



$$C_t-P_t=S_t-kB(t,T)$$
with $B(t,T)=dfrac{S_0^{0}} {S_0^{1}}=dfrac{1}{1+r}$



Then we rearrange the equation so that C is on the left hand side and use P_t>0 (using 1/(1+r) for the discount factor).So,we have $$C_t=P_t+S_t-k dfrac{1}{1+r}$$



Can anyone help me from here with a thorough solution so to find the question a)?



I don't know if this is right but i want to know if I am in the right way to solve the problem.



Also,I would like to ask if $min=inf$ in this problem



For question b) i know that i have to take this theorem
enter image description here



and this remark but i don't know even how to start!
enter image description here



I would really appreciate any hints/thorough solution because it's the first problem that I have to solve and I don't have any experience in this type of exercise and generally it's my first try in the field of financial mathematics



Thanks, in advance!










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    up vote
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    down vote

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    EXERCISE




    We consider a financial market of one period with two stocks $(S_0,S_1)$.
    We further consider a purchase option with repayment $C = (S_1^{1} - K)^+$
    with a value of $K> 0$ and maturing time $T = 1$. Let $underline{π}(C)$,$overline{π}(C)$ the lower and upper no-arbitrage barriers for the value of $C$.



    a)Show that the following inequality applies
    $$underline{π}(C)geq bigg(S_1^{1} - dfrac{k}{1+r}bigg)^+$$



    Please also show that the following equality applies
    $$underline{π}(C)= bigg(S_1^{1} - dfrac {k}{1+r}bigg)^+$$



    if it is further assumed that:
    $$P[S_1^{1}=S_0^{1} cdot(1+r)]> 0$$



    Hint : Use the probability measure $$Q[·]: = P [·|S_1^{1} =S_0^{1}cdot (1+r)]$$



    b) Also show that the following inequality applies
    $$underline {π}(C)leq S_0^{1}$$



    and that the following equality applies
    $$overline{π}(C)=S_0^{1}$$



    assuming that $rm ess sup S_1^{1}=infty $ and that $rm ess inf S_1^{1}=0$.




    ATTEMPT



    a)We have a financial market with no-arbitrage so we have the form:
    $$π(C)=E_Qbigg[dfrac{c}{1+r}bigg]<infty$$ for $Qsubset P$



    So,$$underline{π}(C)geq inf_{Q in P}E_Qbigg[dfrac{c}{1+r}bigg]=inf_{Q in P}E_Qbigg[dfrac{S_1^{1}-k}{1+r}bigg]=inf_{Q in P}dfrac{1} {1+r}E_Q[S_1^{1}-k]$$



    UPDATE



    Ι think that i have to use put-call-parity equation:



    $$C_t-P_t=S_t-kB(t,T)$$
    with $B(t,T)=dfrac{S_0^{0}} {S_0^{1}}=dfrac{1}{1+r}$



    Then we rearrange the equation so that C is on the left hand side and use P_t>0 (using 1/(1+r) for the discount factor).So,we have $$C_t=P_t+S_t-k dfrac{1}{1+r}$$



    Can anyone help me from here with a thorough solution so to find the question a)?



    I don't know if this is right but i want to know if I am in the right way to solve the problem.



    Also,I would like to ask if $min=inf$ in this problem



    For question b) i know that i have to take this theorem
    enter image description here



    and this remark but i don't know even how to start!
    enter image description here



    I would really appreciate any hints/thorough solution because it's the first problem that I have to solve and I don't have any experience in this type of exercise and generally it's my first try in the field of financial mathematics



    Thanks, in advance!










    share|cite|improve this question


























      up vote
      2
      down vote

      favorite
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      up vote
      2
      down vote

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      1





      EXERCISE




      We consider a financial market of one period with two stocks $(S_0,S_1)$.
      We further consider a purchase option with repayment $C = (S_1^{1} - K)^+$
      with a value of $K> 0$ and maturing time $T = 1$. Let $underline{π}(C)$,$overline{π}(C)$ the lower and upper no-arbitrage barriers for the value of $C$.



      a)Show that the following inequality applies
      $$underline{π}(C)geq bigg(S_1^{1} - dfrac{k}{1+r}bigg)^+$$



      Please also show that the following equality applies
      $$underline{π}(C)= bigg(S_1^{1} - dfrac {k}{1+r}bigg)^+$$



      if it is further assumed that:
      $$P[S_1^{1}=S_0^{1} cdot(1+r)]> 0$$



      Hint : Use the probability measure $$Q[·]: = P [·|S_1^{1} =S_0^{1}cdot (1+r)]$$



      b) Also show that the following inequality applies
      $$underline {π}(C)leq S_0^{1}$$



      and that the following equality applies
      $$overline{π}(C)=S_0^{1}$$



      assuming that $rm ess sup S_1^{1}=infty $ and that $rm ess inf S_1^{1}=0$.




      ATTEMPT



      a)We have a financial market with no-arbitrage so we have the form:
      $$π(C)=E_Qbigg[dfrac{c}{1+r}bigg]<infty$$ for $Qsubset P$



      So,$$underline{π}(C)geq inf_{Q in P}E_Qbigg[dfrac{c}{1+r}bigg]=inf_{Q in P}E_Qbigg[dfrac{S_1^{1}-k}{1+r}bigg]=inf_{Q in P}dfrac{1} {1+r}E_Q[S_1^{1}-k]$$



      UPDATE



      Ι think that i have to use put-call-parity equation:



      $$C_t-P_t=S_t-kB(t,T)$$
      with $B(t,T)=dfrac{S_0^{0}} {S_0^{1}}=dfrac{1}{1+r}$



      Then we rearrange the equation so that C is on the left hand side and use P_t>0 (using 1/(1+r) for the discount factor).So,we have $$C_t=P_t+S_t-k dfrac{1}{1+r}$$



      Can anyone help me from here with a thorough solution so to find the question a)?



      I don't know if this is right but i want to know if I am in the right way to solve the problem.



      Also,I would like to ask if $min=inf$ in this problem



      For question b) i know that i have to take this theorem
      enter image description here



      and this remark but i don't know even how to start!
      enter image description here



      I would really appreciate any hints/thorough solution because it's the first problem that I have to solve and I don't have any experience in this type of exercise and generally it's my first try in the field of financial mathematics



      Thanks, in advance!










      share|cite|improve this question















      EXERCISE




      We consider a financial market of one period with two stocks $(S_0,S_1)$.
      We further consider a purchase option with repayment $C = (S_1^{1} - K)^+$
      with a value of $K> 0$ and maturing time $T = 1$. Let $underline{π}(C)$,$overline{π}(C)$ the lower and upper no-arbitrage barriers for the value of $C$.



      a)Show that the following inequality applies
      $$underline{π}(C)geq bigg(S_1^{1} - dfrac{k}{1+r}bigg)^+$$



      Please also show that the following equality applies
      $$underline{π}(C)= bigg(S_1^{1} - dfrac {k}{1+r}bigg)^+$$



      if it is further assumed that:
      $$P[S_1^{1}=S_0^{1} cdot(1+r)]> 0$$



      Hint : Use the probability measure $$Q[·]: = P [·|S_1^{1} =S_0^{1}cdot (1+r)]$$



      b) Also show that the following inequality applies
      $$underline {π}(C)leq S_0^{1}$$



      and that the following equality applies
      $$overline{π}(C)=S_0^{1}$$



      assuming that $rm ess sup S_1^{1}=infty $ and that $rm ess inf S_1^{1}=0$.




      ATTEMPT



      a)We have a financial market with no-arbitrage so we have the form:
      $$π(C)=E_Qbigg[dfrac{c}{1+r}bigg]<infty$$ for $Qsubset P$



      So,$$underline{π}(C)geq inf_{Q in P}E_Qbigg[dfrac{c}{1+r}bigg]=inf_{Q in P}E_Qbigg[dfrac{S_1^{1}-k}{1+r}bigg]=inf_{Q in P}dfrac{1} {1+r}E_Q[S_1^{1}-k]$$



      UPDATE



      Ι think that i have to use put-call-parity equation:



      $$C_t-P_t=S_t-kB(t,T)$$
      with $B(t,T)=dfrac{S_0^{0}} {S_0^{1}}=dfrac{1}{1+r}$



      Then we rearrange the equation so that C is on the left hand side and use P_t>0 (using 1/(1+r) for the discount factor).So,we have $$C_t=P_t+S_t-k dfrac{1}{1+r}$$



      Can anyone help me from here with a thorough solution so to find the question a)?



      I don't know if this is right but i want to know if I am in the right way to solve the problem.



      Also,I would like to ask if $min=inf$ in this problem



      For question b) i know that i have to take this theorem
      enter image description here



      and this remark but i don't know even how to start!
      enter image description here



      I would really appreciate any hints/thorough solution because it's the first problem that I have to solve and I don't have any experience in this type of exercise and generally it's my first try in the field of financial mathematics



      Thanks, in advance!







      probability inequality stochastic-processes martingales finance






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      edited Nov 15 at 11:10

























      asked Nov 14 at 17:31









      Magic K. Mamba

      305113




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          2 Answers
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          $mathbf{(a)}$ From the extension of the Theorem hinted, the lower no-arbitrage bound is :
          $$underline{pi}(C) = inf_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{C}{1+r}bigg]=inf_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg]$$



          The Jenses inequality in context of probability theory, says thati f $X$ is a random variable and $varphi$ is a convex function, then it is : $varphibig(mathbb{E}[X]big) leq mathbb{E}[varphi(X)]$. The function $f(x) = (x-K)^+, ; K>0$ is convex, thus :



          $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] geqfrac{1}{1+r}big[mathbb{E}_mathbb{Q}(S_1^1 - K)big]^+ $$
          $$= frac{1}{1+r}big[mathbb{E}_mathbb{Q}(S_1^1) - mathbb{E}_mathbb{Q}(K)big]^+= frac{1}{1+r}bigg[S_0^1(1+r) - Kbigg]^+$$
          $$implies$$
          $$underline{pi}(C) geq bigg(S_0^1 - frac{K}{1+r}bigg)^+$$
          where the probability measure $mathbb{Q}[cdot] := mathbb{P}[cdot | S_1^1 = S_0^1(1+r)]$ was used.



          Now if $mathbb{P}[S_1^1 = S_0^1(1+r)] >0$, this means that at some point it will be $S_1^1 = S_0^1(1+r)$ and thus :



          $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] = mathbb{E}_mathbb{Q}bigg[frac{(S_0^1(1+r) - K)^+}{1+r}bigg] = mathbb{E}_mathbb{Q}bigg[bigg(S_0^1 - frac{K}{1+r}bigg)^+bigg]$$
          which means that the equality will hold, since $S_0^1$ is just a constant $>0$ :
          $$underline{pi}(C) = bigg(S_0^1 - frac{K}{1+r}bigg)^+$$



          For part $mathbf{(b)}$, again from the extension of the Theorem hinted, we have :
          $$overline{pi}(C) = sup_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{C}{1+r}bigg]=sup_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg]$$



          But, note that simply it is :



          $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] leq mathbb{E}_mathbb{Q}bigg[frac{S_1^1}{1+r}bigg] = frac{mathbb{E}_mathbb{Q}(S_1^1)}{1+r} = S_0^1 $$
          $$implies$$
          $$overline{pi}(C) leq S_0^1 $$
          where the probability measure $mathbb{Q}[cdot] := mathbb{P}[cdot | S_1^1 = S_0^1(1+r)]$ was used.



          Can you figure out a similar approach for the last part now ?






          share|cite|improve this answer




























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            (a) Use put-call parity and the fact that the put price must be +ve. (b) Call price cannot exceed the value of the stock, as otherwise buying the stock and selling the call would generate an arbitrage profit.






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            • Could you elaborate please?I understand that you tell to use the put-call parity equation which is $C_t-P_t=S_t-k cdot B(t,T)$.What does "the put price must be +ve" means?
              – Magic K. Mamba
              Nov 14 at 17:50










            • It means that the put price must be positive.
              – Richard Martin
              Nov 14 at 17:53










            • I can't see how to proceed with this information. Could you provide a thorough solution?
              – Magic K. Mamba
              Nov 14 at 17:57










            • First, learn what the symbols mean. Then rearrange the equation so that $C$ is on the left hand side and use $P>0$ (using $1/(1+r)$ for the discount factor).
              – Richard Martin
              Nov 14 at 18:02












            • And after this?
              – Magic K. Mamba
              Nov 14 at 18:15











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            2 Answers
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            $mathbf{(a)}$ From the extension of the Theorem hinted, the lower no-arbitrage bound is :
            $$underline{pi}(C) = inf_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{C}{1+r}bigg]=inf_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg]$$



            The Jenses inequality in context of probability theory, says thati f $X$ is a random variable and $varphi$ is a convex function, then it is : $varphibig(mathbb{E}[X]big) leq mathbb{E}[varphi(X)]$. The function $f(x) = (x-K)^+, ; K>0$ is convex, thus :



            $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] geqfrac{1}{1+r}big[mathbb{E}_mathbb{Q}(S_1^1 - K)big]^+ $$
            $$= frac{1}{1+r}big[mathbb{E}_mathbb{Q}(S_1^1) - mathbb{E}_mathbb{Q}(K)big]^+= frac{1}{1+r}bigg[S_0^1(1+r) - Kbigg]^+$$
            $$implies$$
            $$underline{pi}(C) geq bigg(S_0^1 - frac{K}{1+r}bigg)^+$$
            where the probability measure $mathbb{Q}[cdot] := mathbb{P}[cdot | S_1^1 = S_0^1(1+r)]$ was used.



            Now if $mathbb{P}[S_1^1 = S_0^1(1+r)] >0$, this means that at some point it will be $S_1^1 = S_0^1(1+r)$ and thus :



            $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] = mathbb{E}_mathbb{Q}bigg[frac{(S_0^1(1+r) - K)^+}{1+r}bigg] = mathbb{E}_mathbb{Q}bigg[bigg(S_0^1 - frac{K}{1+r}bigg)^+bigg]$$
            which means that the equality will hold, since $S_0^1$ is just a constant $>0$ :
            $$underline{pi}(C) = bigg(S_0^1 - frac{K}{1+r}bigg)^+$$



            For part $mathbf{(b)}$, again from the extension of the Theorem hinted, we have :
            $$overline{pi}(C) = sup_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{C}{1+r}bigg]=sup_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg]$$



            But, note that simply it is :



            $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] leq mathbb{E}_mathbb{Q}bigg[frac{S_1^1}{1+r}bigg] = frac{mathbb{E}_mathbb{Q}(S_1^1)}{1+r} = S_0^1 $$
            $$implies$$
            $$overline{pi}(C) leq S_0^1 $$
            where the probability measure $mathbb{Q}[cdot] := mathbb{P}[cdot | S_1^1 = S_0^1(1+r)]$ was used.



            Can you figure out a similar approach for the last part now ?






            share|cite|improve this answer

























              up vote
              1
              down vote



              accepted










              $mathbf{(a)}$ From the extension of the Theorem hinted, the lower no-arbitrage bound is :
              $$underline{pi}(C) = inf_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{C}{1+r}bigg]=inf_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg]$$



              The Jenses inequality in context of probability theory, says thati f $X$ is a random variable and $varphi$ is a convex function, then it is : $varphibig(mathbb{E}[X]big) leq mathbb{E}[varphi(X)]$. The function $f(x) = (x-K)^+, ; K>0$ is convex, thus :



              $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] geqfrac{1}{1+r}big[mathbb{E}_mathbb{Q}(S_1^1 - K)big]^+ $$
              $$= frac{1}{1+r}big[mathbb{E}_mathbb{Q}(S_1^1) - mathbb{E}_mathbb{Q}(K)big]^+= frac{1}{1+r}bigg[S_0^1(1+r) - Kbigg]^+$$
              $$implies$$
              $$underline{pi}(C) geq bigg(S_0^1 - frac{K}{1+r}bigg)^+$$
              where the probability measure $mathbb{Q}[cdot] := mathbb{P}[cdot | S_1^1 = S_0^1(1+r)]$ was used.



              Now if $mathbb{P}[S_1^1 = S_0^1(1+r)] >0$, this means that at some point it will be $S_1^1 = S_0^1(1+r)$ and thus :



              $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] = mathbb{E}_mathbb{Q}bigg[frac{(S_0^1(1+r) - K)^+}{1+r}bigg] = mathbb{E}_mathbb{Q}bigg[bigg(S_0^1 - frac{K}{1+r}bigg)^+bigg]$$
              which means that the equality will hold, since $S_0^1$ is just a constant $>0$ :
              $$underline{pi}(C) = bigg(S_0^1 - frac{K}{1+r}bigg)^+$$



              For part $mathbf{(b)}$, again from the extension of the Theorem hinted, we have :
              $$overline{pi}(C) = sup_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{C}{1+r}bigg]=sup_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg]$$



              But, note that simply it is :



              $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] leq mathbb{E}_mathbb{Q}bigg[frac{S_1^1}{1+r}bigg] = frac{mathbb{E}_mathbb{Q}(S_1^1)}{1+r} = S_0^1 $$
              $$implies$$
              $$overline{pi}(C) leq S_0^1 $$
              where the probability measure $mathbb{Q}[cdot] := mathbb{P}[cdot | S_1^1 = S_0^1(1+r)]$ was used.



              Can you figure out a similar approach for the last part now ?






              share|cite|improve this answer























                up vote
                1
                down vote



                accepted







                up vote
                1
                down vote



                accepted






                $mathbf{(a)}$ From the extension of the Theorem hinted, the lower no-arbitrage bound is :
                $$underline{pi}(C) = inf_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{C}{1+r}bigg]=inf_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg]$$



                The Jenses inequality in context of probability theory, says thati f $X$ is a random variable and $varphi$ is a convex function, then it is : $varphibig(mathbb{E}[X]big) leq mathbb{E}[varphi(X)]$. The function $f(x) = (x-K)^+, ; K>0$ is convex, thus :



                $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] geqfrac{1}{1+r}big[mathbb{E}_mathbb{Q}(S_1^1 - K)big]^+ $$
                $$= frac{1}{1+r}big[mathbb{E}_mathbb{Q}(S_1^1) - mathbb{E}_mathbb{Q}(K)big]^+= frac{1}{1+r}bigg[S_0^1(1+r) - Kbigg]^+$$
                $$implies$$
                $$underline{pi}(C) geq bigg(S_0^1 - frac{K}{1+r}bigg)^+$$
                where the probability measure $mathbb{Q}[cdot] := mathbb{P}[cdot | S_1^1 = S_0^1(1+r)]$ was used.



                Now if $mathbb{P}[S_1^1 = S_0^1(1+r)] >0$, this means that at some point it will be $S_1^1 = S_0^1(1+r)$ and thus :



                $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] = mathbb{E}_mathbb{Q}bigg[frac{(S_0^1(1+r) - K)^+}{1+r}bigg] = mathbb{E}_mathbb{Q}bigg[bigg(S_0^1 - frac{K}{1+r}bigg)^+bigg]$$
                which means that the equality will hold, since $S_0^1$ is just a constant $>0$ :
                $$underline{pi}(C) = bigg(S_0^1 - frac{K}{1+r}bigg)^+$$



                For part $mathbf{(b)}$, again from the extension of the Theorem hinted, we have :
                $$overline{pi}(C) = sup_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{C}{1+r}bigg]=sup_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg]$$



                But, note that simply it is :



                $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] leq mathbb{E}_mathbb{Q}bigg[frac{S_1^1}{1+r}bigg] = frac{mathbb{E}_mathbb{Q}(S_1^1)}{1+r} = S_0^1 $$
                $$implies$$
                $$overline{pi}(C) leq S_0^1 $$
                where the probability measure $mathbb{Q}[cdot] := mathbb{P}[cdot | S_1^1 = S_0^1(1+r)]$ was used.



                Can you figure out a similar approach for the last part now ?






                share|cite|improve this answer












                $mathbf{(a)}$ From the extension of the Theorem hinted, the lower no-arbitrage bound is :
                $$underline{pi}(C) = inf_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{C}{1+r}bigg]=inf_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg]$$



                The Jenses inequality in context of probability theory, says thati f $X$ is a random variable and $varphi$ is a convex function, then it is : $varphibig(mathbb{E}[X]big) leq mathbb{E}[varphi(X)]$. The function $f(x) = (x-K)^+, ; K>0$ is convex, thus :



                $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] geqfrac{1}{1+r}big[mathbb{E}_mathbb{Q}(S_1^1 - K)big]^+ $$
                $$= frac{1}{1+r}big[mathbb{E}_mathbb{Q}(S_1^1) - mathbb{E}_mathbb{Q}(K)big]^+= frac{1}{1+r}bigg[S_0^1(1+r) - Kbigg]^+$$
                $$implies$$
                $$underline{pi}(C) geq bigg(S_0^1 - frac{K}{1+r}bigg)^+$$
                where the probability measure $mathbb{Q}[cdot] := mathbb{P}[cdot | S_1^1 = S_0^1(1+r)]$ was used.



                Now if $mathbb{P}[S_1^1 = S_0^1(1+r)] >0$, this means that at some point it will be $S_1^1 = S_0^1(1+r)$ and thus :



                $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] = mathbb{E}_mathbb{Q}bigg[frac{(S_0^1(1+r) - K)^+}{1+r}bigg] = mathbb{E}_mathbb{Q}bigg[bigg(S_0^1 - frac{K}{1+r}bigg)^+bigg]$$
                which means that the equality will hold, since $S_0^1$ is just a constant $>0$ :
                $$underline{pi}(C) = bigg(S_0^1 - frac{K}{1+r}bigg)^+$$



                For part $mathbf{(b)}$, again from the extension of the Theorem hinted, we have :
                $$overline{pi}(C) = sup_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{C}{1+r}bigg]=sup_{mathbb{Q} in mathcal{P}}mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg]$$



                But, note that simply it is :



                $$mathbb{E}_mathbb{Q}bigg[frac{(S_1^1 - K)^+}{1+r}bigg] leq mathbb{E}_mathbb{Q}bigg[frac{S_1^1}{1+r}bigg] = frac{mathbb{E}_mathbb{Q}(S_1^1)}{1+r} = S_0^1 $$
                $$implies$$
                $$overline{pi}(C) leq S_0^1 $$
                where the probability measure $mathbb{Q}[cdot] := mathbb{P}[cdot | S_1^1 = S_0^1(1+r)]$ was used.



                Can you figure out a similar approach for the last part now ?







                share|cite|improve this answer












                share|cite|improve this answer



                share|cite|improve this answer










                answered Nov 15 at 17:49









                Rebellos

                11.6k21040




                11.6k21040






















                    up vote
                    2
                    down vote













                    (a) Use put-call parity and the fact that the put price must be +ve. (b) Call price cannot exceed the value of the stock, as otherwise buying the stock and selling the call would generate an arbitrage profit.






                    share|cite|improve this answer





















                    • Could you elaborate please?I understand that you tell to use the put-call parity equation which is $C_t-P_t=S_t-k cdot B(t,T)$.What does "the put price must be +ve" means?
                      – Magic K. Mamba
                      Nov 14 at 17:50










                    • It means that the put price must be positive.
                      – Richard Martin
                      Nov 14 at 17:53










                    • I can't see how to proceed with this information. Could you provide a thorough solution?
                      – Magic K. Mamba
                      Nov 14 at 17:57










                    • First, learn what the symbols mean. Then rearrange the equation so that $C$ is on the left hand side and use $P>0$ (using $1/(1+r)$ for the discount factor).
                      – Richard Martin
                      Nov 14 at 18:02












                    • And after this?
                      – Magic K. Mamba
                      Nov 14 at 18:15















                    up vote
                    2
                    down vote













                    (a) Use put-call parity and the fact that the put price must be +ve. (b) Call price cannot exceed the value of the stock, as otherwise buying the stock and selling the call would generate an arbitrage profit.






                    share|cite|improve this answer





















                    • Could you elaborate please?I understand that you tell to use the put-call parity equation which is $C_t-P_t=S_t-k cdot B(t,T)$.What does "the put price must be +ve" means?
                      – Magic K. Mamba
                      Nov 14 at 17:50










                    • It means that the put price must be positive.
                      – Richard Martin
                      Nov 14 at 17:53










                    • I can't see how to proceed with this information. Could you provide a thorough solution?
                      – Magic K. Mamba
                      Nov 14 at 17:57










                    • First, learn what the symbols mean. Then rearrange the equation so that $C$ is on the left hand side and use $P>0$ (using $1/(1+r)$ for the discount factor).
                      – Richard Martin
                      Nov 14 at 18:02












                    • And after this?
                      – Magic K. Mamba
                      Nov 14 at 18:15













                    up vote
                    2
                    down vote










                    up vote
                    2
                    down vote









                    (a) Use put-call parity and the fact that the put price must be +ve. (b) Call price cannot exceed the value of the stock, as otherwise buying the stock and selling the call would generate an arbitrage profit.






                    share|cite|improve this answer












                    (a) Use put-call parity and the fact that the put price must be +ve. (b) Call price cannot exceed the value of the stock, as otherwise buying the stock and selling the call would generate an arbitrage profit.







                    share|cite|improve this answer












                    share|cite|improve this answer



                    share|cite|improve this answer










                    answered Nov 14 at 17:38









                    Richard Martin

                    1,3938




                    1,3938












                    • Could you elaborate please?I understand that you tell to use the put-call parity equation which is $C_t-P_t=S_t-k cdot B(t,T)$.What does "the put price must be +ve" means?
                      – Magic K. Mamba
                      Nov 14 at 17:50










                    • It means that the put price must be positive.
                      – Richard Martin
                      Nov 14 at 17:53










                    • I can't see how to proceed with this information. Could you provide a thorough solution?
                      – Magic K. Mamba
                      Nov 14 at 17:57










                    • First, learn what the symbols mean. Then rearrange the equation so that $C$ is on the left hand side and use $P>0$ (using $1/(1+r)$ for the discount factor).
                      – Richard Martin
                      Nov 14 at 18:02












                    • And after this?
                      – Magic K. Mamba
                      Nov 14 at 18:15


















                    • Could you elaborate please?I understand that you tell to use the put-call parity equation which is $C_t-P_t=S_t-k cdot B(t,T)$.What does "the put price must be +ve" means?
                      – Magic K. Mamba
                      Nov 14 at 17:50










                    • It means that the put price must be positive.
                      – Richard Martin
                      Nov 14 at 17:53










                    • I can't see how to proceed with this information. Could you provide a thorough solution?
                      – Magic K. Mamba
                      Nov 14 at 17:57










                    • First, learn what the symbols mean. Then rearrange the equation so that $C$ is on the left hand side and use $P>0$ (using $1/(1+r)$ for the discount factor).
                      – Richard Martin
                      Nov 14 at 18:02












                    • And after this?
                      – Magic K. Mamba
                      Nov 14 at 18:15
















                    Could you elaborate please?I understand that you tell to use the put-call parity equation which is $C_t-P_t=S_t-k cdot B(t,T)$.What does "the put price must be +ve" means?
                    – Magic K. Mamba
                    Nov 14 at 17:50




                    Could you elaborate please?I understand that you tell to use the put-call parity equation which is $C_t-P_t=S_t-k cdot B(t,T)$.What does "the put price must be +ve" means?
                    – Magic K. Mamba
                    Nov 14 at 17:50












                    It means that the put price must be positive.
                    – Richard Martin
                    Nov 14 at 17:53




                    It means that the put price must be positive.
                    – Richard Martin
                    Nov 14 at 17:53












                    I can't see how to proceed with this information. Could you provide a thorough solution?
                    – Magic K. Mamba
                    Nov 14 at 17:57




                    I can't see how to proceed with this information. Could you provide a thorough solution?
                    – Magic K. Mamba
                    Nov 14 at 17:57












                    First, learn what the symbols mean. Then rearrange the equation so that $C$ is on the left hand side and use $P>0$ (using $1/(1+r)$ for the discount factor).
                    – Richard Martin
                    Nov 14 at 18:02






                    First, learn what the symbols mean. Then rearrange the equation so that $C$ is on the left hand side and use $P>0$ (using $1/(1+r)$ for the discount factor).
                    – Richard Martin
                    Nov 14 at 18:02














                    And after this?
                    – Magic K. Mamba
                    Nov 14 at 18:15




                    And after this?
                    – Magic K. Mamba
                    Nov 14 at 18:15


















                     

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