Option Research & Technology Services

Options Earnings Data Modeling & Forecasting

ORATS' proprietary, innovative approach to earnings data modeling and forecasting gives options traders a depth, breadth, and clarity of visualization that no other data provider can offer. This readily translates into trading advantage, whether you seek alpha by trading earnings explicitly or you are simply looking to successfully negotiate unexpected moves in the markets.

Every experienced options trader understands the major impact of earnings announcements on option prices. ORATS earnings data allows traders to navigate the earnings cycle by presenting data from multiple, distinct vantage points. The ORATS Earnings file contains approximately 120 different quantities that work together to describe forecast, implied, and historical earnings effects. While these metrics cover a very broad spectrum, some of the most interesting ones fall into categories relating to "earnings moves" and "earnings effect". The most important such quantities are explained below, with an appeal to an example involving a hypothetical stock.

"Earnings Move" Values

  • Earnings Move - the percentage realized move in the stock on earnings.
  • Historical Earnings Move - the average of past Earnings Moves, in percents. (For example, our stock may have a Historical Earnings Move of 3%.)
  • Fair Volatility - the volatility level that traders should be willing to pay for an earnings month. This includes levels to which implied volatilities are projected to fall after earnings, plus an adjustment for the forecast earnings move.
    • For example, assume the implied volatility of the earnings month is 57.4%. The earnings month has 11 days to expiration and the earnings fall within this period.
    • The implied volatility after earnings is estimated to fall to 37.8% -- based on the Implied Earnings Effect (see below).
    • The forecasted earnings move is 3% -- based on a historical average of the earnings moves on the day of earnings.
    • Thus, the Fair Volatility for the earnings month with 11 days to go is the average of 10 days at 37.8% volatility and a one day move of 3% on earnings day, which equates to a Fair Volatility of 39.1%. We can say the implied is far (57.4% - 39.1% = 18.3%) overvalued vs. the Fair Volatility estimate.
    • Another way to think about it by working this situation backwards, the stock would have to move 8% on earnings to make the 57.4% fairly valued. The 8% implied earnings move is overvalued compared to the Forecasted Earnings Move of 3%.
  • Implied Earnings Move - the difference in Earnings Move projected by comparing implied volatility with Fair Volatility.

The most common useful comparisons of Earnings Move values include:

  • Comparing Fair Volatility to Implied Volatility - to detect over-/under-valued situations, as in the example under the definition of Fair Volatility above.
  • Comparing Historical Earnings Move to the Implied Earnings Move - to compare market predictions for upcoming earnings against the historical norm.
  • A more general comparision is the Earnings Move average to the spread price as a percent of stock price. Since a straddle or strangle break even price is the amount the stock has to move this comparison offers a reasonableness test of the pricing of the spread to the expected move in the stock.

"Earnings Effect" Values

  • Earnings Effect - the Earnings Move compared to the expected move as derived from the implied volatility. Earnings Effect is measured as a percentage of the actual move on earnings vs. the expected move on a normal trading day. So an Earnings Effect of 100% means there is no move directly attributable to earnings, 200% would mean the move on earnings day is twice the normal magnitude, and 50% would mean the move was half the normal magnitude (which would be unusual).
  • Forecasted Earnings Effect - forecast based on seasonally averaged historic Earnings Effects, weighted by recency. (For example, the Forecast Earnings Effect might be 256%, meaning that the stock moves 256% of normal on earnings day.)
  • Implied Earnings Effect - derived by isolating the additional implied volatility in the earnings months. (For example, the Implied Earnings Effect might be 283%. This example indicates an overvaluation by 27%. Notice how the overvaluation in Earnings Effect agrees with the overvaluation in Earnings Move from the examples above.)
  • Historic Volatility Ex-Earnings - the realized volatility of the stock taking out that component of volatility directly attributable to Earnings Effects, i.e. with the volatility measured on earnings days taken out.

Valuable comparisons based on Earnings Effect values include:

  • Comparing Forecasted Earnings Effect vs. Implied Earnings Effect, as per the example above.
  • Comparing realized historic volatility to Historic Volatility Ex-Earnings - gives traders another method for assessing how a stock might behave during the upcoming earnings announcement.

ORATS earnings data is both available as a data file and presented in the ORATS Dashboard.

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Testimonials

"ORATS gives us solid earnings data other vendors simply can't deliver. They provide earnings dates information and their innovative approach to viewing the earnings history gives us an advantage in timing our trades around earnings announcements."

-Myron Wood, Quant Developer, KCM Management LLC.

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