Python for Derivative Analytics

1. PYTHON FOR DERIVATIVE
ANALYTICS
Alicia Guerra

2. WHAT IS A DERIVATIVE?
• In finance, a derivative is a contract that derives its value
from the performance of an underlying entity (i.e. an option,
future, etc.)

3. DX ANALYTICS
• Python library which allows for the modeling of rather
complex derivatives instruments and portfolios.

4. SIMULATION
Simulation classes in DX where relevant risk factors are
modeled:
• geometric_brownian_motion
• jump_diffusion
• square_root_diffusion

5. GEOMETRIC BROWNIAN MOTION
• Used to model option prices in
the Black-Scholes model

6. JUMP DIFFUSION
• Model for price behavior that
incorporates small, day-to-
day “diffusive” movements
together with larger,
randomly occurring jumps.
• Inclusion of jumps allows for
more realistic “crash”
scenarios.

7. SQUARE ROOT DIFFUSION
• Models mean-reverting
quantities like interest rates
and volatility.
• Mean-reverting means it is
assumed that a price will
move to the average
price over time.

8. CALIBRATION

9. HEDGING
• Dynamic delta hedging is
a derivative trading
strategy that attempts to
reduce – or eliminate – the
risk caused by price
changes in the underlying
asset.
• A derivative’s delta is the
relation between the
changes in the
derivative’s price and the
changes in the price of
the underlying asset.

10. CONTACT ME
Email: alicia.developer@aliciaguerra.com
LinkedIn: linkedin.com/in/aliciaisabelguerra
Twitter: @skepchick92
Phone: (619) 519-3805