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Why a Recombining Binomial Price Tree Looks Skewed

Article Quant Q&A · Author: PBD10017

Summary

The document addresses why a Cox–Ross–Rubinstein binomial tree can look different from the symmetric diagrams shown in textbooks when asset prices are plotted on the vertical axis. In the model, each step changes price by a percentage, with an upward factor above one and a downward factor below one. Prices cannot fall below zero, so equal percentage moves do not create equal vertical distances across the tree.

The answer says this makes the plotted tree appear twisted and concentrates many terminal prices at low values in the example. It also describes plotting the maturity-price distribution as a way to see that clustering. The explanation is a visual interpretation of the specified tree and example, not a general evaluation of the model’s pricing accuracy. The supplied code and parameter choices illustrate a calculation, but the document reports no comparison with market data or alternative tree constructions.

Key ideas

  • The tree uses proportional upward and downward price changes at each time step.
  • Asset prices are bounded below by zero, making equal percentage moves unequal in vertical distance.
  • Plotting price levels can make a recombining tree appear twisted compared with textbook diagrams.
  • A maturity-price distribution can help show the clustering implied by the example tree.

Tags

Full text
# Is this the correct shape of Cox-Ross-Rubinstein's recombining binomial tree?


# Is this the correct shape of Cox-Ross-Rubinstein's recombining binomial tree?












Most texts display the binomial tree like this:

However when I run my calculation the tree in reality looks like this:

Does this look correct to you? I am using these standard formulas: $$u=e^{\sigma\sqrt{\Delta t}}~~~~~d = e^{-\sigma\sqrt{\Delta t}}$$ and the probability of the quantity increasing at the next time step is $$p=\frac{e^{r\Delta t}-d}{u-d}$$

## Answer by phdstudent (score 2, accepted)

https://quant.stackexchange.com/a/38870

That looks correct because the price is bounded bellow by zero and decreases/increases are always in percentages.

I have run a quick code in matlab (adaptad from Higham (2002))

```
%
% Vectorized version, uses shifts via colon notation.
%%%%%%%%%% Problem and method parameters %%%%%%%%%%%%%
S = 5;E = 10;T = 1;r = 0.06;sigma = 0.3;M = 256;
dt = T/M;A = 0.5*(exp(-r*dt)+exp((r+sigma^2)*dt));
u=A+ sqrt(A^2-1);d = 1/u;p = (exp(r*dt)-d)/(u-d);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Option values at time T
W = max(E-S*d.^([M:-1:0]').*u.^([0:M]'),0);
histogram(W,50);
title('Underlying Price at Maturity')

% Re-trace to get option value at time zero
q = 1-p;
for i = M:-1:1
W = p*W(2:i+1) + q*W(1:i);
end
W = exp(-r*T)*W;
```

With this results one can plot the distribution of prices at maturity (easier to see it that way):

You can see that there is a much bigger cluster of prices at low values just as your figure implies.

Also the difference between your tree and most textbooks is due to the fact that you are plotting the values of $S_t$ in the y-axis. Most textbooks do not do it. If they did their figures would look twisted just like yours.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.