Options Trading Strategies – Wrong Use of Historical Volatility and Implied Volatility Crossovers
Historical Volatility (HV) and Implied Volatility (IV) are structurally different types of volatilities. It makes no sen...
Options Trading Strategies – Wrong Use of Historical Volatility and Implied Volatility Crossovers Not all volatilities are constructed equal. It is critical to differentiate between Historical Volatility and Implied Volatility, so retail traders learn how to trade options focused on what is material to theoretically price option spreads forward. Historical Volatility (HV) measures past price movements of the underlying asset recording the asset's actual or realized volatility. The more commonly known type of HV is Statistical Volatility, which computes the underlying assets return over a finite but adjustable number of days. Let me explain what “finite but adjustable” means. You can vary the number of days to measure the Statistical Volatility: for example, 5-1050-200 days, that’s how time-based moving averages and momentum/oscillator studies are built. Though, it is not the case with Implied Volatility. Implied Volatility measures expected values by repetitively refining bid-ask estimates. These estimates are based on the expectations of buyers and sellers. The buyers and sellers (85+% of floor traded volume is driven by institutions, floor traders and market makers) behind the bid and ask values, who do change their estimates within the day, as new information be it macro-economic news or micro-economic data impacting the underlying product becomes available. What is being estimated is the underlying asset’s future fluctuation with certain assumptions embedded into the changes in information of the underlying. That refinement of bid-ask estimates must be completed within finite time-bound option expiration periods. That’s why there are monthly and quarterly option expiration cycles. You cannot change these expiration periods, either by shortening or lengthening the number of days, to “construct” a time period that gives you faster or slower crossover indicators. Why point out the wrong use of Historical Volatility and Implied Volatiity Crossovers? It is to caution you against the defective use of HV-IV crossovers, which is not a reliable trading signal. Remember, for a given expiration month, there can only be one volatility over that specific period. Implied Volatility must leave from where it is currently trading at, to converge at zero on expiration date. Implied Volatility (be it IV for ITM, ATM or OTM strikes) must return to zero on expiry; but, price can go anywhere (up, down or stay flat). To continually sell “overpriced” and buy “under priced” options would eventually cause the implied volatility of every single non-zero bid option to line up exactly. Meaning the phenomenon of IV’s “smiling” skew disappears, as IV becomes perfectly flat. This hardly happens, especially in highly liquid products. Take for example, the SPY, a broad-based Index; or, GLD – the SPDR Shares ETF in a fast market like Gold. With open interest at the non-zero bid strikes going into the thousands and tens of thousands, do you really think a retail off the floor trader is going to be allowed to “out price” the professional hedger on the floor? Unlikely. Calls and Puts in highly liquid products, are like items in an inventory with high supply because there is high demand. This type of inventory does not get “mispriced” because floor traders have to make a daily living from trading the Calls and Puts –they will refuse to carry the risk of mispricing overnight. So, what are the key considerations to banking in your edge as a retail trader? IV’s percentage impact on an option’s extrinsic value is much more sizeable for ATM and OTM strikes, versus ITM strikes which are laden with intrinsic value but lack extrinsic value. Most retail option traders with an account size USD $25-$50K (or less), gravitate towards ATM and OTM strikes for reasons of affordability. The deeper the ITM you go, the wider the Bid-Ask spread becomes compared to the narrower Bid-Ask spread differences in the ATM or OTM strikes, making ITM strikes more costly to trade. When you trade IV, you are buying time decay for a rise in IV at a % point below; or, selling time premium for a drop in IV at a % point above the theoretical price of market value, that participants are willing to pay or sell for. Depending on the market ranges of that day, price debit spreads to get filled at 0.10-0.15 below the Theoretical Price of the spread. With credit spreads, raise the credit to sell the spread by 0.100.15 above the Theoretical Price of the spread. The price you pay below; or, receive above the Theoretical Price of a spread is your edge, purely based on price-performance of Implied Volatility alone. Remember, you Theoretically Price a spread to fill the order for its forward value, never backward. Where can I learn how to trade options with consistent profits focused on Implied Volatility without Historical Volatility? Follow the link below, entitled “Consistent Results” to see a model retail option trader’s portfolio that excludes the use of HV and focuses on trading only IV. I’ll cite these actual historical events, to bolster the argument for removing Historical Volatility from your trading process altogether. 27 Feb, 2007: Widespread Panic from the sizeable China sell-off in equities. If you were trading the options of an index like the FXI which is the iShares product of China’s 25 largest and most liquid Chinese companies though listed in the US; but they are headquartered in China, you would have been impacted.
While you can argue it’s possible to have market events recreate the ranges of the Dow, Nasdaq & S&P, how do you recreate the scenario of the VIX and VXN soaring 59% and 39%? 22Jan, 2008: Fed cuts rates by 75 basis points prior to the scheduled policy meeting on Jan 30th, whereby the FOMC cut another 50 basis points on the date of the meeting. If you were trading interest-rate sensitive sectors using the options on a Financial ETF or a Banking Index like the BKX; or, the Housing Index like the HGX, you would have been impacted. And in the current environment of rates being near zero, the FOMC while they still have a rate policy tool, they are unable to cut rates by the same number of basis points like before. What was a historical event is not successively repeatable going forward, not until rates are raised again and subsequently they get cut again. Question: How do you reconstruct history? That is the history of events forming Historical Volatility. The answer is in the real examples cited, as with any other financially related historical event - you cannot reconstruct history. You may be able to mimic parts of HV but you cannot repeat it in its entirety. So, if you continue using HV-IV crossovers, you visually confuse yourself by searching for volatility “mispricing” patterns that you would like to see; but, you will end up with poor profit performance instead. It makes more practical trading sense to focus purely on IV; then, diversify the trading of volatilities across multiple asset classes beyond equities. Where can I learn more about trading IV across multiple asset classes using only options, without having to own stock? Follow the link below (video-based course), that uses IV Mean Reversion/Mean Repulsion and IV Forecasting, as reliable methods to trade the implied volatilities across broad-based Equity Indexes, Commodity ETFs, Currency ETFs and Emerging Market ETFs. ---------------------Thanks for reading my article, Clinton Lee. Founder, Home Options Trading: a uniquely retail-focused option-centric trading firm. Please see Consistent Results at http://www.homeoptionstrading.com/consistent_results/, displaying the Model Portfolio's Performance YTD, updated each month-end. The portfolio models a typical retail option trader's account up to USD $50,000. Here's the stats in summary: Return: Profit/Start of Year Cash Balance = $91,593/$58,380 = UP 157%. Win/Loss Probability = 60/68 = 88.24%. Performance Ratio = (Win/Loss Probability) x (Average Win/Average Loss) = 88.24% x $2.99 = 2.64. Positive Expectancy = (Win Probability x Average Win) - (Loss Probability x Average Loss) = $1,347 per trade. Preview an original 55 hour video-based course for online options trading from home, at http://www.homeoptionstrading.com/original_curriculum.html Purchase the curriculum and receive an $800 options basic course as a Bonus! Clinton's career spans 16 years of treasury, finance and banking across Hewlett Packard, JP Morgan Chase, Citibank, Royal Bank of Scotland (previously ABN Amro); and, is currently a Senior Liquidity Advisor at Bank of America in its Global Treasury Services division. Despite the years in the finance/banking industry, it did not help him directly grasp online options trading from home.