Timeline for Deep calibration in the Heston Model
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Apr 8 at 8:28 | vote | accept | sxminho | ||
| Mar 17 at 6:44 | comment | added | THATS MY QUANT MY QUANTITATIVE | @sxminho yes. Most papers use synthetic data to show it’s possible, rather than having to deal with robustness and the inconsistencies of real-time data. | |
| Mar 16 at 12:12 | answer | added | Achrbot | timeline score: 1 | |
| Mar 16 at 10:32 | comment | added | sxminho | Thanks, so for you there is no need to generate synthetic data to train the neural network ? I can directly train it using the market implied volatilities ? | |
| Mar 16 at 10:01 | comment | added | user70573 | Equity? If so, thee are price quoted. You usually compute a vol surface using black scholes (applying techniques like de-americanization) and calibrate your heston model to IV, not prices. What you are calibrating are the parameters that model the shape of the volatility. Once you fit vanilla options you can use Heston to price exotic derivatives (often in combination with local vol). | |
| S Mar 16 at 9:40 | review | First questions | |||
| Mar 16 at 10:24 | |||||
| S Mar 16 at 9:40 | history | asked | sxminho | CC BY-SA 4.0 |