Financial Engineering is a multidisciplinary field drawing from finance and economics, mathematics, statistics, engineering and computational methods. The emphasis of FE & RM Part I will be on the use of simple stochastic models to price derivative securities in various asset classes including equities, fixed income, credit and mortgage-backed securities. We will also consider the role that some of these asset classes played during the financial crisis. A notable feature of this course will be an interview module with Emanuel Derman, the renowned ``quant'' and best-selling author of "My Life as a Quant". We hope that students who complete the course will begin to understand the "rocket science" behind financial engineering but perhaps more importantly, we hope they will also understand the limitations of this theory in practice and why financial models should always be treated with a healthy degree of skepticism. The follow-on course FE & RM Part II will continue to develop derivatives pricing models but it will also focus on asset allocation and portfolio optimization as well as other applications of financial engineering such as real options, commodity and energy derivatives and algorithmic trading.
Including Dividends
Loading...
From the course by Columbia University
Financial Engineering and Risk Management Part I
1484 ratings
Explore Related Videos
At Coursera, you will find the best lectures in the world. Here are some of our personalized recommendations for you
From the lesson
Option Pricing in the Multi-Period Binomial Model
Derivatives pricing in the binomial model including European and American options; handling dividends; pricing forwards and futures; convergence of the binomial model to Black-Scholes.
Meet the Instructors
Martin HaughCo-Director, Center for Financial Engineering
Industrial Engineering & Operations Research
Garud IyengarProfessor
Industrial Engineering and Operations Research Department
>> So far we've discussed option pricing and derivatives pricing in the binomial
model, but we've made no mention of dividends.
In this module we're going to discuss dividends and point out that it's actually
include, easy to include dividends, in the binomial model.
So here's our one period binomial model again.
We start off with t equals 0, the security price of S0.
We have a probability of p, a true probability of p, and a true probability
of 1 minus p of an up move and down move respectively.
We're going to assume that if the security goes up, the value of the stock goes to
uS0 and if it goes down it goes to dS0. But we're also going to assume that the
security pays a proportional dividend of C times S0.
And at C times S0's what get pays out, paid out as a dividend at time t equals 1,
regardless of whether the stock has gone up or down.
So you'll see that CS0's here and CS0's down here as well.
So this is the dividend that gets paid out, to the shareholders.
Okay, as before we have a cash account which pays out a gross risk-free rate of
four, we assume the cash account is worth one dollar or one euro or one whatever at
time t equals 0 and its worth R at time t equals 1.
So it's easy to check again that there are no-arbitrage conditions for this one
period binomial model and in particular the no-arbitrage conditions are given to
us by here. And this is the direct analog of the
no-arbitrage conditions we saw when there were no dividends.
So d plus c is the total return of the stock if the stock falls from S0 to dS0.
And u plus c is the total return of the stock, if the stock raises, or rises, from
S0 to uS0. So, clearly, R cannot be less than d plus
c, otherwise there would be an arbitrage. You could buy the stock and sell the cash
account. Likewise, if R was greater than u plus c,
then you could short sell the stock and buy the cash account and again create an
arbitrage. Okay.
So what we can do is that suppose we want to price the derivative security with
value C1 of S1 at time 1. It pays off Cu in this upper state here,
and it pays off Cd in this lower state over here.
So what we can do is we can again construct our one period replicating
strategy to replicate the payoff of this option.
So, in particular, we're going to let x be the number of units of the stock that we
purchase at time 0, and y be the number of units of the cash account that we purchase
at time 0. Well then the replicating aspect of this
portfolio means that we must have these two linear equations.
In particular, the value of the portfolio here on the left-hand side if the stock
goes up is uS0 times x plus cS0 times x. So this is the dividend piece, this is the
value of the stock. Plus R times y, this is the position of
the cash account. And that must be equal to C0, if the stock
price goes up. If the stock price goes down, then we have
dS0x plus cS0x plus Ry equals Cd. So these are the two equations that we
have. If we can find x and y so that these two
equations are satisfied, then the portfolio xy, which is purchased at time
0, replicates the payoff C0 and Cd. So therefore the value of this portfolio
at time 0 must be the arbitrage-free value of this derivative security.
So we can solve these two equations and two unknowns.
If we do that, we'll find that C0 can be written as follows.
The fair value C0 is equal to xS0 plus y, and we can write it like this.
Again, we can write it in the form of having risk-neutral probabilities and now
Q is equal to this quantity here. Which is the same as our original one
period risk-neutral probability, except now, we have this additional minus c.
1 minus q is equal to u plus c minus R divided by u minus d, and that's that term
there. So, again, when the security pays a
proportional dividend, we can still construct a replicating strategy.
And we can compute the price of a derivative security as the discounted
expected term or payoff of the derivative security using these risk-neutral
probabilities. Okay.
In the multi-period binomial model we can assume a proportional dividend is paid in
each period. In particular we would assume a
proportinal dividend of cSi is paid at t equals i plus 1.
Then each embedded one period model has identical risk-neutral probabilities.
They're given to us by these quantities here, and derivative securities are priced
as before. We can work backwards in the binomial
lattice using these risk-neutral probabilities, to calculate the va-, fair
value, or arbitrage-free value, of the derivative at each time period.
Until we get back to t equals 0, which gives us the initial price, arbitrage-free
price, of the security. In practice dividends are not paid in
every di-, period. They're often paid every six months or
every year, and so they're a little more awkward to handle in practice.
We might discuss that later in the course, but for now we'll, we'll, we'll leave it
at that point. Another point to keep in mind is, is the
following. Suppose the underlying security does not
pay dividends. Then it's easy to check that this is true.
The initial value of the stock is equal to the expected value, using the risk-neutral
probabilities of the terminal value of the stock discounted.
And of course, that follows easily from our risk-neutral pricing, because we know
the stock price Is equal to Sn minus 0, 0. Take the max of these two.
So in fact this is just a call option with K equal to 0.
So the stock price is equal to a call option on this stock with its strike K
equal to 0, and so this just follows from the pricing of call options.
But of course, every security must be priced like this.
Okay. Suppose now that the underlying security
pays dividends in each time period. Then you can check that eight no longer
holds. Instead what holds actually is the
following, the initial value of the stock, S0 is equal to the expected value at time
0 using the risk-neutral probabilities of Sn divided by R to the n, which is what we
have here, plus the sum of the dividends, which we'll call Di, discounted
appropriately. Okay.
We're assuming Sn is the x dividend security price at time n.
So Sn is the price at time n immediately after the dividend at time n is paid.
And you don't need any new theory to prove this.
We can just use what we've seen already. It follows from this mutual pricing, and
observing the dividends and Sn may be viewed as a portfolio of securities.
So, to see this we can view the ith dividend as a separate security with value
equal to this quantity here. So if we view the ith dividend which is
paid at time i as a security that pays at cash flow only at time i, then our
risk-neutral pricing tells us that the value of this dividend is Pi.
And it's equal to this quantity here. Now we can view the owner of the
underlying security as owning a portfolio of securities at times 0.
The value of this portfolio is the value of the securities within the portfolio.
Those securities are each of the n dividends.
Okay, and each of those n dividends is value Pi for i equals 1 to n, plus the
terminal value of the stock, or if you like, the, the value at time n.
And that's Sn discounted by R to the n taking its expectation with respect to the
risk-neutral probabilities. But of course we also note the value of
the underlying security is S0, so S0 must be equal to this quantity here.
Okay. And so we get S0 equals to the sum of the
Pi's plus this quantity and that is just equation nine.
Explore our Catalog
Join for free and get personalized recommendations, updates and offers.
Coursera provides universal access to the world’s best education,
partnering with top universities and organizations to offer courses online.
© 2019 Coursera Inc. All rights reserved.
