import vola
fa = vola.makeFactoryAnalytics()
fp = 'AEX_20160622-160000.000-CET_ocpf-eq.json.gz' # serialized price fitter
ocpf = fa.makeOptionChainPricerFitterEquity(fp) # create fitter from serialized instance
oc = ocpf.optionChain # the option chain with contract information
ps = ocpf.priceSnapshot # price snapshot with price information
vcts = [vola.VCT.C6, vola.VCT.C10M] # curve types to use for fitting prices
rf = ocpf.fit(ps, vcts) # fit price snapshot
vs = rf.volSurface # use the volsurface for pricing
ocp = fa.makeOptionChainPricerEquity(oc, vs) # create pricer
rp = ocp.price() # compute prices and greeks for all options in the option chain
vola.df.rp(rp) # print prices and greeks in pandas dataframe
vola.plot.var(vs) # plot total variances for the fitted vol surface
Vola Dynamics offers the world's leading options pricer and volatility fitter.
Trade any equity, ETF, futures, or index options off auto-fitted curves and/or easily create your own. Price and hedge vol derivatives consistent with vanillas.
Relying on decades worth of research and trading, implemented in a modern Bayesian framework, using superior numerics. Automated trading even around high vol/opportunity events.
Drop-in replacement for the critical pricer and fitter components of your infrastructure (C++, Python, Java, C#).
Our clients trust Vola Dynamics to maintain their core valuation and risk analytics (pricing, greeks, volatility surface fitting, scenario analysis) for equity, futures and index options.