Risk-neutral probabilities (FRM T5-07)

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  • čas přidán 5. 11. 2019
  • One of the harder ideas in fixed income is risk-neutral probabilities. In this video, I'd like to specifically illustrate, and define, what we mean by risk-neutral probabilities. I will do this in three steps. The first one is just a simple example of a coin toss, where my objective is to illustrate what we mean by risk-neutral probabilities. These are the probabilities that equate the expected discounted value to the market price of the instrument. Then, having defined the concept, in the second sheet I've replicated Bruce Tuckman's example in Chapter 7 where he retrieves the risk-neutral probabilities that are implied by a 1 year zero coupon bond. We'll take those risk-neutral probabilities and go to the third sheet and use them to price or value an option on that same bond so that's a contingent claim. Then we'll see why there is some magic to these risk-neutral probabilities because we're going to be able to use them to price the option and we'll get a price that's necessarily equal to the price if we were to value the option with a replicating portfolio, which is something of an unambiguous value that would be indifferent to our risk preferences. So, I look forward to that illustration of risk-neutral probabilities.
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Komentáře • 26

  • @shree4403
    @shree4403 Před 4 lety +15

    The best explanation I've encountered for risk neutral probabilities definition. To summarize in my own words :- Risk neutral probabilities are the implied probabilities, when the market price of your instrument, equals the expected payoff

    • @bionicturtle
      @bionicturtle  Před 4 lety +9

      Thank you very much, it's a hard idea so I am thrilled you like it. And your summary is EXCELLENT, can i just add a single word (discounted): "Risk neutral probabilities are the implied probabilities, when the market price of your instrument, equals the discounted expected payoff" .... of course you already get that, as the price implies current/discounted. Thank you!

    • @kathirkamanathan7407
      @kathirkamanathan7407 Před 4 lety +2

      @@bionicturtle Great explanation. I was just thinking it should be called Implied Probability, and immediately thereafter saw your comment. Wonder why they had to use a difficult term - evaded my understanding for a long time.

    • @mathtick
      @mathtick Před 3 lety

      This is basically wrong. What is the probability distribution when you have one price? Probability distribution is a monontonic function. Nonsense explanation I see a lot. See transformation of random variables is what to look at.

    • @shree4403
      @shree4403 Před 3 lety

      @@mathtick I was like you in my very early learning stages of probability theory, but you'll eventually get it if you spend enough time and effort. Btw - PDFs are not always monotonic (e.g Normal dist's PDF for x between -Inf to 0, it is increasing and 0 and Inf, it is decreasing) and CDFs are monotonic (Every CDF has to be monotonically increasing as PDF's values are always greater than zero). Further more, here you are dealing with stochastic processes, i.e a set of random variables and not just one random variable. So things are a little more complicated here. Performing operations like addition, etc. on a set of random variables, i.e., on a stochastic process is very different from adding states of a random variable.

    • @mathtick
      @mathtick Před 3 lety

      @shreejyot no you are not understanding but you are illustrating point that these kind of explanations mislead and confuse. They are not *wrong* per se, but the context is limited and they don't extrapolate to the general problem which is actually simpler that this special case.
      First, by "prob dist" I mean CDF, not PDF.
      The infintessimal generator of certain kinds of stochastic process can probably be determined by a single data point (price). But that is not at all what these kinds of demos are saying.
      If you have one price, you 100% can not determine the probability distribution in general.
      See en.wikipedia.org/wiki/Probability_density_function section on Function of random variables and change of variables in the probability density function for instance.
      So trick is to write down the price as an expectation of a payoff. This is a functional of the probability distribution. How are you going so solve for this using one price?
      If you have many prices across a set of payoff functions (i.e. options) you can start to do something. You can assume paramtric forms for the probability distribution and this can make some sense in the infinitessimal limit under some conditions. But that is academic.

  • @mohammedsaeed7241
    @mohammedsaeed7241 Před rokem +2

    The risk-neutral probs are derived from the market price, and the discount rate is used to derive them is the RISK-FREE rate. Thank you this was very informative.

  • @michalcertik249
    @michalcertik249 Před 2 lety

    Working for over 10 years in quantitative finance, this is so far the best explanation on real-world vs risk-neutral pricing.

  • @SzTz100
    @SzTz100 Před 10 měsíci

    Hay the Bionic man, great to see you are still around.

  • @jiqi353
    @jiqi353 Před 4 lety

    Thank you! It is an intuitive way to understand risk neutral probability finally

  • @johnsonwayne9279
    @johnsonwayne9279 Před 4 měsíci

    I wish I could understand your language better. It is not your fault - it is mine.
    I am mathematically trained but not economically or financially. Some of the
    words and phrases you use to describe a term or an equation throw me but I
    will try to learn more about this economic/financial language. Great video
    though since I can understand a lot of this which explains debt market activity
    and demystifies what "expectations" means. Also, as I consume this kind of material
    it becomes foundationaly clear that human emotion and mom and pop are not
    market drivers but suckers in the debt markets. And another thing. Although
    many pundits swear that the central banks do not have the power to set interest
    rates, this kind of information shows that they absolutely do and are doing it every second.
    Their close competition would be the hedge fund people who are using the same
    formulations to pursue CB policy to "front run" the market, then followed by the
    pension funds and the others.
    This was a great video for me.

  • @excelisfun
    @excelisfun Před 4 lety +5

    You make such great videos! Thanks, Bionic Turtle!!!

    • @bionicturtle
      @bionicturtle  Před 4 lety +1

      Thank you, support from a genuine CZcams legend is deeply appreciated!

  • @AugustNocturne
    @AugustNocturne Před 2 lety

    Thank you for your explanation for a hard concept!

  • @d0718
    @d0718 Před 4 lety

    Knew how to calculate and work with risk neutral probabilities but now I actually finally understand what it means :D thank you

    • @bionicturtle
      @bionicturtle  Před 4 lety

      You're welcome! Glad that we could help :)

  • @kathirkamanathan7407
    @kathirkamanathan7407 Před 4 lety

    In the bond pricing example, the 1 year risk free rate is available (=5.15%) from the curve. So why should we try to estimate it from the 6-month risk free rate (=5%)?

  • @mayoorbhatt2549
    @mayoorbhatt2549 Před 3 lety

    Best explain by you🇮🇳🙏🇮🇳🙏🇮🇳🙏👌

  • @Silvertestrun
    @Silvertestrun Před rokem +1

    Ty

  • @investwithvincent6329
    @investwithvincent6329 Před 2 lety

    7:15
    It is at this point do i say that reminds me of the blackscholes model because of the concept of implied discount rate being incorporated in this example

  • @investwithvincent6329
    @investwithvincent6329 Před 2 lety

    20:17
    I see two different discounted prices 1.46 and .58 .... From my understanding these two prices create a no arbritrage opportunity. How would an investor explore this opportunity?

  • @mathtick
    @mathtick Před 3 lety

    Please always explain risk neutral properly in terms of transformations of probability distributions. It is not possible to determing the Q from a single observation.
    The Q is determined from P *and* a transformation function (utility). So under some conditions you can write E_P(f(X)) as E_Q(X) where Q is the f-transformed probability distribution.
    If f is linear it is called risk-neutral.
    Please correct me if anything I am saying is wrong.
    All of the examples with binary events are nice but they are just confusing people or tricking people into thinking they understand something.

  • @sakuranooka
    @sakuranooka Před 2 lety

    Why bother with RN probabilities if we could instead use a risk-adapted discount rate (eg 16.3%) together with the real-world probs?