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Today's Featured Article
There seems to be a great deal of confusion amongst new and even experienced traders when it comes to options. I speak to clients every day that want to incorporate commodity options into their strategies but are struggling with the basic mechanics of the trade. It does take time to become familiar with options and a lot of the available material is either grossly over simplified and misleading or too rigorous for most investors lacking an advanced understanding of statistical analysis and probability theory.
Here is an all too common scenario. You are expecting that a key report for a particular market is going to be bullish and push prices higher. The idea of buying a call option as opposed to buying the underlying futures seems appealing because of the limited risk and cheaper cost to hold the position versus margin on an underlying future.
So you buy out of the money calls and wait for the news. A day or two later the report comes out bullish and prices rally. There is some profit on your option but it is not the windfall you were expecting. Perhaps you have gotten as far in your option analysis as to keep an eye on Delta (rate of change in premium for movement in the price of the underlying) when entering your trade. You bought an option at thirty Deltas and after a twenty five point rally you were expecting to have about nine or ten points of profit on your position. Now the market is only bid three points higher then your entry price.
It is results like this that lead many traders to the agoraphobic assumption that they just cannot make money with options and that the odds are stacked against them. So what went wrong? The problem with the above trade is that the trader failed to analyze volatility before taking the position.
The same report that you were looking at was also on the minds of other market participants. That expectation of a near term increase in volatility was already priced into the call options you bought. After the report was released and the market moved higher expectation for future volatility was reduced. So though Delta worked in your favor; Vega (rate of change in option premium from movement in implied volatility) worked against you.
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Once you get beyond the basic mechanics of the trade; pricing models and the introduction of the "Greeks" seems to be just that, speaking Greek. But it is possible to glean a conceptual understanding of the "Greeks" without delving into advanced mathematics. There are also numerous off the shelf software products that will do the heavy lifting for you.
The sooner you get familiar with the concept of volatility the sooner you will see positive results in your option trading. I've found that the easiest way to teach this to new traders is through application of strategy. The first step is to figure out what strategies work when volatility is high and what strategies work when volatility is low. Fortunately this part of the picture is easy to see. The old adage buy low and sell high applies. Sell inflated volatility premium and buy low volatility.
This goes hand in hand with a growing understanding of short option strategies. A common misconception amongst retail traders is that "I don't have the capital in my account to sell options and I can't swing the risk so I just want to buy calls and puts." Limited risk selling strategies go completely overlooked. We have already demonstrated that this is not a smart approach.
Now that we have our list of strategies broken down into high volatility and low volatility categories the obvious question becomes how is it possible to determine if volatility is low or high? This is where things can start to get tricky. If you are very astute you may have seen that in the analysis of the previously mentioned call option trade I wrote that Vega worked against the position. And that Vega was a measure of the rate of change in option premium due to changes in implied volatility. This should lead us to assume that there are different types of volatility.
There are typically three key figures we are concerned with; historical volatility; implied volatility; and Vega. The mathematics involved in calculating these values would go well beyond the scope of this article; fortunately though as was stated earlier off the shelf software can do all the heavy lifting for us! Still we can understand these figures conceptually and how they are related to each other through application of an option pricing model such as Black-Scholes.
Much effort in the field of quantitative finance is directed towards finding more accurate pricing models then what Fischer Black and Myron Scholes came up with in 1973. By developing our understanding of volatility we will soon see the need some traders may have for more accurate implied pricing models. That is not to say that there is no practical purpose for Black-Scholes. I would liken it to making a cross country road trip with a folding map versus a GPS device. Either way is better then using nothing at all.
Without getting too deep into the mathematics what we can say about the Black-Scholes model is that it takes as inputs; the current price of the underlying instrument; time to expiration; option strike price; the risk-free interest rate; and historical volatility from that the Black-Scholes model derives a theoretical fair value option price.
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Historical volatility is an input into our option pricing model but other then that what is it and where does it come from? There isn't a single best method for finding historical volatility but basically what we are looking at is some kind of formula for calculating a standard deviation from the mean price of an instrument over time.
Our software pulls all this data together and runs it through an algorithm and spits out a fair value price for our option. If you have spent any time looking at these various software analytics packages you have probably seen that the theoretical price is rarely in line with the bid; offer; and market price of an option. In the trade example above it is likely that our analytics software would have shown theoretical value to be well below the price paid.
Historical volatility is a measure of past events. Options by their very nature are forward looking instruments. This anomaly leads us to the definition of our second type of volatility; implied volatility. Implied volatility is the measure of volatility which satisfies our pricing model for the current market price rather then deriving a theoretical market price from historical volatility.
From this we can now evaluate option prices in terms of volatility to determine if an option is "cheap" relative to historical volatility or "expensive" relative to the underlying historical volatility. If historical volatility is high and implied volatility is higher still this is the ideal set up for option selling strategies. If historical volatility is low and IV is lower we may benefit from buying options.
Finally we can apply our newly acquired knowledge of the role of volatility in option pricing back to our pricing model by considering the role of Vega. Generally speaking Vega is highest at near the money strikes and further out in time. This is fairly logical.
A near the money long dated option is more likely to move into the money then a short dated far away option because with the long dated the underlying instrument doesn't have to move very far and it has a long time to make that move. Naturally if we were to sell those near the money deferred options we would want to collect good premium for doing so. As such these are the option strikes that are most sensitive to changes in implied volatility. This sensitivity to change in implied volatility is quantified as Vega.
This is by no means the end of the volatility story. Hopefully though this article has whet your appetite for learning more about option trading. I've always been a learn by doing type of person. Putting ideas to work in the market is a great way to learn by doing. However lessons learned in the market are often accompanied by trading losses. That is why I started the Electronic Trading Center at PFG. I wanted to give traders a way to learn about trading in the markets by actually participating in live trades but with the support of an experienced market professional to assist in strategy development and execution. I've helped numerous traders on their way to becoming options market
veterans. If it is something you are considering, learn more by
signing up for complimentary access to PFGBEST ETC (Electronic Trading Center).
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About the Author
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Erik Voit has lived at the forefront of technology since writing his first applications on his Deskpro 386 in the late 80's. Though he has formal training as a network engineer he attributes much of his skill set to his time spent as a technical analyst with the Bank of New York. After leaving BNY, Erik became involved with a proprietary derivatives trading firm in Chicago's financial district. Erik provides regular webinars, workshops and consultation on all trading and technology matters; from the most basic to the most advanced.
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Special Message from Our Author
Complimentary Access to PFGBEST ETC
These days, it seems there are as many trading systems as there are traders. Each has strengths and weaknesses, and what works for one trader may be unsuitable for another. That's why we created PFGBEST ETC (Electronic Trading Center), a unique service catering to your individual trading needs. You have questions, PFGBEST ETC has answers. Learn More Here! |
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