User feedback is critical to helping us ensure top-quality tools and data. Answers to common questions will be a series of blog posts with our answers.
What Historical Quotes Available and Pricing?
We offer 15-minute delayed 1-minute snapshots for $99 per month, and offer history back to June 2020 for $499. Here is a large download of a sample of a 1-minute intraday snapshot. Here is a small snippet CSV of the first few rows.
Here is a large download of a sample 2-minute file (raw no greeks) that we have historically back to 2015: Nightly updates are $99 per month and bulk download back to 2015 is $999.
More information on our quotes is here https://info.orats.com/quotes
How does smoothed market values (SMV) process work?
"Are the 3-point quadratic fits described on your website and available in the Data API: 1) the same as the SMV 2) used as starting points for the fits or 3) are they not used at all?"
After the SMV process is complete, ORATS calculates the quadratic fit parameters slope and derivative (skewness and kurtosis) on the smoothed implied volatilities. So the 3-point quadradic fits are not a seed or basis for our theoretical SMVs, but benefit from the SMV process. Here's how the SMV process works:
The SMV process
The first step in the SMV System is cleaning the quotes and applying good inputs to our modified binomial pricing engine. Using ORATS popular dividend feed and option pricing methodologies, a residual yield is solved for based on the put-call parity formula. Applying the residual yield rate process helps with summarizing hard-to-borrow stocks or stocks with differing dividend assumptions. The effect is to line up the call and put implied volatilities.
Next, using the call and put mid-price IVs, a non-arbitrageable smooth curve is fit through the strike implied volatilities.
- We use a proprietary skew generator using bounded flexible spline bands.
- We adjust the skews with another process to account for wings that may be slightly off put-call parity.
- We eliminate calendar or butterfly arbitrage in our theoretical values.
For example, in the Implied Monies endpoint for GameStop (GME) the residual yield represents the borrow rate that short sellers need to pay. The SMV process also calculates a confidence from 0 to 1 based on the amount of options implied volatilities and width of the market. Notice the higher confidence and lower market width in volatility points (mwVol) are related in the table below.
GME's borrow peaked at 93% before coming down and then rising again to today's level of 12% for the expirations around 30 days to expiration.
- SMV volatilities produce theoretical values that are between the bid-ask over 99% of the time.
Benefits of smoothing
Smooth market volatilities (SMV) derived from the options market helps traders make sense of a plethora of exchange quotes. There are three main benefits of smoothing the implied volatility skew:
- Call and put theoretical values can be compared to market bid-ask quotes to see if the options are under or overpriced.
- The smoothed IVs produce more consistent greeks that are important for backtesting, trading and managing risk.
- Smoothing the IVs create better summarizations of the skew.
This smoothing system produces powerful theoretical values and accurate option Greeks. The Strikes Report shows each option's bid-asks, greeks and theoretical values. Delta, Vega, Theta, Rho, Phi and theoretical values are critical for risk management and trading.
Benefits of 3-factor parameters
By parameterizing the smoothed curve, the shape can be evaluated comparing to other tickers, to history and to forecasts of the skew parameters.
We calculate quadratic fit parameters slope and derivative (skewness and kurtosis) but these are a result, not a seed or basis for our theoretical SMVs. Slope and derivative levels can be used as an entry point or exit point trigger in the backester, as can 100s of our historical calculations.
ORATS describes the implied volatility surface as a 3-dimensional surface where the independent variables are time to expiration, and option delta and the dependent variable is implied volatility. To illustrate an implied volatility surface, we have developed a 2-dimensional graph that displays all three axes in the figure below. Summary information about this surface gives the trader a macro view of the implied volatilities for each option chain.
The importance of Slope can be seen in the graph below.
The importance of derivative (sometimes called kurtosis or curvature of the skew) has been seen lately, and in our view is the reason VIX is high compared to other implied volatility measurements. See our blog post here about that.
Question about wings, far OTM options
“Are the wings were simply capped at strikes far closer to ATM than should be capped? Where can I see the SMV skews with the Data API or in Wheel, the backtester interface?
As can be seen below, the SMV volatilities are not capped until approaching the 1.00 or 0.00 delta wings. This can be seen in the strikes endpoint in our Data API or in Chain at wheel.orats.com
ORATS SMV also differentiates itself is by producing meaningful analytics on thinly traded securities and far out of the money options. The SMV incorporates historical information when the current confidence in the market summarization is low.
Moreover, the SMV treatment of the wings, the small delta out of the money calls and puts, produces more realistic implied volatilities than unadjusted IVs based on bid-ask prices with little premium.
ORATS data including skew information can be accessed via instructions at docs.orats.io and our API Explorer is a handy tool and can be found here.
We create second-order calculations like constant maturity volatilities, best ETF IV ratios, and others too numerous to state here (for example, five delta implied volatility 20 days to maturity with earnings effects taken out), but all are integrated into a trigger system where the data point or ratios of data points can be used to time trading in our backtest and live scanning at wheel.orats.com
We think our data has the best summarizations out there. You can check ours against others at this site https://quantpedia.com/links-tools/?category=historical-data
See our blog and others here on Feedspot.com's options trading blogs.