Search results

  1. D

    Exam Feedback May 2022 Part 2 Exam Feedback

    I cleared part 2! Thank you for high quality prep:) Now it is time to get some professional experience to obtain certification.
  2. D

    P2.T8. Liquidity and Treasury Risk Measurement and Management

    Hello @David Harper CFA FRM It is clear right now. Thank you for the good explanation from several perspectives.
  3. D

    P2.T8. Liquidity and Treasury Risk Measurement and Management

    I am not sure about the offer price... When the financial institution tries to liquidate the large position [n] let's say n > 10, the spread widens. I understand why the bid price widens, as there is a surplus, a lot of supply in the market. But I can't get why the offer price widens.
  4. D

    Exam Feedback November 2021 Part 1 Exam Feedback

    Passed 2,1,1,1. Very happy go get the first quartiles in the most difficult books.
  5. D

    YouTube T3-13: Par yields are swap rates

    Can't understand why the swap rates and the par rates are equal. What are swap rates and why they are not equal to spot rates(why spot rates are a little bit higher than swap rates). Spot rates are the rates observed in the market? Thanks!
  6. D

    Chapter 14: Trading strategies

    Thank you very much. The key sentence for me: 'In the p-c parity context, in addition to the naked put, we are just investing at the risk-free rate, which does not alter the payoff function (curve) yet satisfies the equality.'
  7. D

    Chapter 14: Trading strategies

    The quoted sentence is from your note. I just was confused with K*exp(-rt). So in the quote above, we can say, using put-call parity +S0 -c = +K*exp(-rT) -p. So, +S0-c = covered call = K*exp(-rt) - p = naked put?
  8. D

    Chapter 14: Trading strategies

    Quote: 'put-call parity shows that the price exposure from writing a covered call is the same as the exposure from writing a naked put.'. Put-call parity is c+Ke -rt = p+S0. We know that S0 - c is a covered call and -S0 + c is naked put but what about Ke-rt. I know that we don't have it in the...
  9. D

    Distribution of rates of return Chapter 15 Black Scholes

    Hello! May someone explain how to get the distribution like below. We cancel out T in the mean by dividing by 1/t but we also should cancel the T out in the variance part but after canceling we still have sigma/T but why not just sigma. So we have (mu - sigma2 / 2) * T, sigma2 * T and all this...
  10. D

    Chapter 1 Measure of financial risk

    I got it! Sorry for this. I will ask only those questions which I will not figure out by myself! I am still a student, so I love asking too many questions but I see your point. Thank you!
  11. D

    Chapter 1 Measure of financial risk

    Why is 'When μ = 0, the VaR rises with the square root of the holding period'?
  12. D

    Chapter 1 Measure of financial risk

    Why 'The more illiquid the market, the longer the relevant holding period' is so?[VaR]
  13. D

    Chapter 1 Measure of financial risk

    Thanks for the reply! To tell the truth, I am still not comfortable with it. If it is possible, may you explain it in detail, please Also, some good notes about the picture I attached, if you somewhat extend your explanation on this point as well I will be happy. Thanks
  14. D

    Chapter 1 Measure of financial risk

    Why the VaR (y axis) increases with the confidence level (x axis) for a standard normal distribution.?
  15. D

    Chapter 5 MPT,CAPM

    What does 'There is no cost involved in the reduction of risk exposures through diversification. Consequently, there is no compensation for taking asset-specific risk. ' mean?
  16. D

    Chapter 1 Measure of financial risk

    What does 'If a normal distribution is time-varying, then its unconditional distribution will be heavy-tailed.' mean?
  17. D

    Chapter 5 Sample moments

    What does asymptotically unbiased mean?
  18. D

    Chapter 5 Sample moments

    I got it. Thank you!
  19. D

    Chapter 5 Sample moments

    I just can't understand. E[mu-hat]. Why mu-hat? As I understand mu-hat is for sample mean.But here I have E[mu-hat(sample mean)] = population mean
  20. D

    Chapter 5 Sample moments

    May someone explain how to interpret this part: see picture.
Top