Can you believe it’s already been a month since we looked into the future and told you how the S&P 500 would close (read: looked at Yahoo! and told you how contracts are trading). That means I’m back here today to act as the weather vane and show you which way the market winds are blowing. To those that have asked, I posted some methodology at the end. Peruse that and ask me any questions you have!
Puts and Calls versus the Future!
Remember: the dates listed means the third Friday of the month, the options expiration date. September 21st is the next expiration day. High and Low mark the boundaries where 75% of closing scenarios are predicted to fall. I tried something different this time and put them both in the same chart – red/maroon is puts, blue is calls. As per usual, calls are more pessimistic than puts. Someone go arbitrage that away!
And, for your copy/pasting please, table format:
Past predictions are here:
Postscript: How Can You Guess Where the S&P 500 Will Close?
It doesn’t take a Math or Economics major (and yes, my co-writer Cameron is both) to do this math – it’s actually pretty simple stuff once you know what, exactly, you need to make these predictions. It all starts with a trip to Yahoo! Finance, and a stock you care about. For the purposes of this series, we use ‘SPY‘, an ETF which tracks the S&P 500 at 1/10 of its current price level. Here are options closing in September 2012 for SPY. Note that there is a coloration change – as I write this, SPY closed Friday at 141.51 (while the S&P 500 closed at 1411.13) – corresponding to the ‘moneyness‘ of the options.
The price of put and call options have two factors – ‘intrinsic’ value and ‘time value’. Time value is sort of a perceived risk/chance that a contract will close in the money. Take our friend OG’s post at The Free Financial Advisor the other day – the puts he purchased were out of the money – namely, they had no intrinsic value and the price paid was due to the time value. Anyway, for this series I am stripping the intrinsic value from the contracts and only using the time value.
Moving on, I care about the relative time value more than the absolute time value. In a nutshell, my model merely converts absolute time values to a range of relative values, and sums to 100%, coming up with the ranges you see each month. It’s not that simple, of course – there are some tricks to screen out spurious trades and such, but a few hundred lines of code basically does what you can do with a calculator (just my script does it faster, sorry!).