Estimating Stock Volatility with Returns & Options Prices

In summary, options prices are often based upon the volatility of a stock. To estimate volatility, we can model the current price using a weighted sum of past values and choose r, \sigma_r, and \sigma_y to minimize the expected difference between the actual and predicted price. The Black-Scholes pricing model assumes a constant drift and volatility, but this may not accurately reflect real market conditions. Additionally, the expected rate of return on a stock has no bearing on the value of an option due to arbitrage opportunities.
  • #1
John Creighto
495
2
Options prices are often based upon the volatility of a stock. I'm left to wonder how we might estimate volatility. Let:

[tex]r[/tex] is the yearly expected rate of return
[tex]\sigma_r[/tex] is the uncertainty in the yearly expected rate of return.
[tex]\sigma_y[/tex] the daily volatility.

Then we might model the current price as follows:

[tex]y(n)=\sum_{i=1}^{\infty} w_i (r+\sigma_{r,i})^{(i-n)/365}(y(n-i)+\sigma_{y,i})[/tex]

where:

[tex]w_i[/tex] is how much weight we use each past value to determine the future value

and

[tex]1=\sum_{i=1}^{\infty} w_i[/tex]

Once the [tex]w_i[/tex]'s are chosen then [tex]r[/tex], [tex]\sigma_r[/tex] and [tex]\sigma_y[/tex] are chosen so that they minimize:

[tex]E \left[\left( y(n)-\hat{y}(n) \right)^2\right][/tex]

where:

[tex]\hat{y}(n)=\sum_{i=1}^{\infty} w_i E\left[(r+\sigma_{r,i})^{(i-n)/365}\right]y(n-i)[/tex]
 
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  • #2
  • #3
BWV said:
The standard deviation of the log price change is the standard method

the expected return of a stock has no bearing on the value of an option

http://en.wikipedia.org/wiki/Black–Scholes#Black.E2.80.93Scholes_PDE

the only problem is that price changes, particularly over shorter time horizons, are not normally distributed

The expected rate of return has no bearing on the value of an option under Black-Scholes because of assumption 2.

* It is possible to borrow and lend cash at a known constant risk-free interest rate.
* The price follows a geometric Brownian motion with constant drift and volatility.
* There are no transaction costs.
* The stock does not pay a dividend (see below for extensions to handle dividend payments).
* All securities are perfectly divisible (i.e. it is possible to buy any fraction of a share).
* There are no restrictions on short selling.

On average most stocks do go up in value over time so this assumption isn't completely accurate. However, since the expiry time for an option is about one month this assumption may be okay, because a stock that is expected to increase in value by 8% of the year, will only increase by 0.64% on average in one month.

I just now decided to google long term options. I found a product called:
http://www.investopedia.com/terms/l/leaps.asp

They have a higher premium and in this case the expected rate of return would have a bearing on there value.
 
  • #4
On the topic of Leaps, I believe you can find leaps on exchanges by deriving the symbol as follows:

Symbol:
Normally, symbols for all equity Long-term Equity AnticiPation Securities (LEAPS) expiring in any calendar year are based on the underlying stock symbol, but are modified by either the letter L, V, W, or Z. For example, LEAPS on XYZ might use the symbol "LXY" and LEAPS on PQR might use "LQR"; similarly, LEAPS on XYZ expiring in the next year might use the symbol "WXY", while those expiring in the year following that might use "VYZ". Due to conflicts with pre-existing security symbols, it is not possible to consistently alter the underlying stock symbol in the same manner for every LEAP expiring in a certain year, nor for each LEAP expiration on a specific underlying stock.

http://www.cboe.com/Products/EquityLEAPS.aspx
 
  • #5
John Creighto said:
The expected rate of return has no bearing on the value of an option under Black-Scholes because of assumption 2.



On average most stocks do go up in value over time so this assumption isn't completely accurate. However, since the expiry time for an option is about one month this assumption may be okay, because a stock that is expected to increase in value by 8% of the year, will only increase by 0.64% on average in one month.

I just now decided to google long term options. I found a product called:
http://www.investopedia.com/terms/l/leaps.asp

They have a higher premium and in this case the expected rate of return would have a bearing on there value.

No, the expected return has no bearing on option prices because of arbitrage opportunities. If the expectation of return within the option price varies from the risk-free rate there is an arbitrage using some combination of cash, a going short or long the underlying and going short or long the option. The basic formula is put-call parity - Stock + Put = Call + Cash

if you price options based upon an 8% discount rate based on the expected return on the underlying instead of the risk free rate then the call will have a higher price than in BS and the put will have a lower. Per put call parity you could buy the stock, put on a costless collar (short call and long put) and achieve the 8% return risk-free - this of course cannot exist in a competitive financial market therefore the options have to be priced to the risk free rate

The geometric brownian motion with a constant drift could be a positie rate of return - the 8% in your example is the drift
 
  • #6
BWV said:
No, the expected return has no bearing on option prices because of arbitrage opportunities. If the expectation of return within the option price varies from the risk-free rate there is an arbitrage using some combination of cash, a going short or long the underlying and going short or long the option. The basic formula is put-call parity - Stock + Put = Call + Cash

if you price options based upon an 8% discount rate based on the expected return on the underlying instead of the risk free rate then the call will have a higher price than in BS and the put will have a lower. Per put call parity you could buy the stock, put on a costless collar (short call and long put) and achieve the 8% return risk-free - this of course cannot exist in a competitive financial market therefore the options have to be priced to the risk free rate

The geometric brownian motion with a constant drift could be a positie rate of return - the 8% in your example is the drift

Interesting. So how about this strategy.

-Sell a call (European Style) which will give the buyer the risk free rate of return
-Buy a put that represents how much loss you are willing to take. (Strike price equal to stock value or some percentage less (say 20%).
-Buy the underlying stock.

-If the stock tanks your losses are limited to the stock price you paid for the stock minus the strike price of the put.
-If the stock price performance is marginal, your losses are limited to the risk free rate of return.
-If the stock does awesome the upside potential is infinite.
 
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  • #7
John Creighto said:
Interesting. So how about this strategy.

-Sell a call which will give the buyer the risk free rate of return
-Buy a put that represents how much loss you are willing to take. (Strike price equal to stock value or some percentage less (say 20%).
-Buy the underlying stock.

-If the stock tanks your losses are limited to the stock price you paid for the stock minus the strike price of the put.
-If the stock price performance is marginal, your losses are limited to the risk free rate of return.
-If the stock does awesome the upside potential is infinite.

That strategy is called a collar

you have capped your upside by selling the call - say the stock price is $10 and you buy a put and sell a call both with a $10 strike price. Then the position should give you the risk free rate (excluding any transaction costs). By selling the call, you have to pay the difference between the stock price and the strike price if S>X so without being long the underlying your potential loss in selling a call is infinite

phrased another way, at the same strike price:
Long put + short call = synthetic short position
Long call + short put = synthetic long position
 

1. What is stock volatility?

Stock volatility is a measure of the rate and magnitude of a stock's price changes over a certain period of time. It is a statistical measure used to assess the risk associated with a particular stock or market.

2. Why is it important to estimate stock volatility?

Estimating stock volatility is important for investors and traders as it helps them make informed decisions about their investments. High volatility can indicate a higher risk, while low volatility can suggest a more stable investment.

3. How is stock volatility calculated?

Stock volatility is typically calculated using standard deviation, which measures the dispersion of a set of data from its mean. It can also be calculated using the historical prices of a stock or by using statistical models such as the Black-Scholes model.

4. What is the relationship between returns and stock volatility?

Returns and stock volatility have an inverse relationship, meaning that as stock volatility increases, returns tend to decrease and vice versa. This is because higher volatility can lead to larger price movements, which can result in higher potential gains or losses.

5. How can options prices be used to estimate stock volatility?

Options prices can be used to estimate stock volatility by inputting them into mathematical models, such as the Black-Scholes model, which can calculate the implied volatility of a stock. This can then be compared to the historical volatility of the stock to gain insights into potential future volatility.

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