Lévy Processes
This quiz covers fundamental concepts of Lévy processes including definitions, properties, characteristic functions, Lévy measures, generators, and semigroups.
Questions
What is the defining characteristic of a Lévy process?
- Independent and stationary increments
- Continuous sample paths
- Gaussian distribution
- Finite variance
Which of the following is an example of a Lévy process?
- Brownian motion
- Poisson process
- Geometric Brownian motion
- Ornstein-Uhlenbeck process
What is the characteristic function of a Lévy process?
- $$\phi(u) = \exp\left(\int_\mathbb{R} \left(e^{iux} - 1 - iux\right)\,\nu(dx)\right)$$
- $$\phi(u) = \exp\left(\int_\mathbb{R} \left(e^{iux} - 1\right)\,\nu(dx)\right)$$
- $$\phi(u) = \exp\left(\int_\mathbb{R} \left(e^{iux} - 1 + iux\right)\,\nu(dx)\right)$$
- $$\phi(u) = \exp\left(\int_\mathbb{R} \left(e^{iux} + 1 - iux\right)\,\nu(dx)\right)$$
What is the relationship between a Lévy process and its Lévy measure?
- The Lévy measure is the distribution of the jumps of the process.
- The Lévy measure is the distribution of the increments of the process.
- The Lévy measure is the distribution of the sample paths of the process.
- The Lévy measure is the distribution of the characteristic function of the process.
Which of the following properties is not satisfied by a Lévy process?
- Independent increments
- Stationary increments
- Gaussian distribution
- Infinitely divisible distribution
What is the relationship between a Lévy process and its drift and diffusion coefficients?
- The drift coefficient is the mean of the increments of the process.
- The diffusion coefficient is the variance of the increments of the process.
- The drift coefficient is the rate of change of the mean of the process.
- The diffusion coefficient is the rate of change of the variance of the process.
Which of the following is an application of Lévy processes?
- Modeling financial asset prices
- Modeling the arrival of customers in a queue
- Modeling the spread of diseases
- All of the above
What is the relationship between a Lévy process and a Wiener process?
- A Wiener process is a special case of a Lévy process.
- A Lévy process is a special case of a Wiener process.
- A Wiener process and a Lévy process are independent.
- A Wiener process and a Lévy process are mutually exclusive.
What is the characteristic function of a compound Poisson process?
- $$\phi(u) = \exp\left(\int_\mathbb{R} \left(e^{iux} - 1\right)\,\nu(dx)\right)$$
- $$\phi(u) = \exp\left(\int_\mathbb{R} \left(e^{iux} - 1 - iux\right)\,\nu(dx)\right)$$
- $$\phi(u) = \exp\left(\int_\mathbb{R} \left(e^{iux} + 1 - iux\right)\,\nu(dx)\right)$$
- $$\phi(u) = \exp\left(\int_\mathbb{R} \left(e^{iux} + 1 + iux\right)\,\nu(dx)\right)$$
What is the relationship between a Lévy process and its generator?
- The generator is the infinitesimal generator of the process.
- The generator is the characteristic function of the process.
- The generator is the Lévy measure of the process.
- The generator is the distribution of the process.
Which of the following is a property of the generator of a Lévy process?
- It is a linear operator.
- It is a bounded operator.
- It is a positive operator.
- All of the above
What is the relationship between a Lévy process and its semigroup?
- The semigroup is the collection of transition probabilities of the process.
- The semigroup is the collection of characteristic functions of the process.
- The semigroup is the collection of generators of the process.
- The semigroup is the collection of Lévy measures of the process.
Which of the following is a property of the semigroup of a Lévy process?
- It is a strongly continuous semigroup.
- It is a Markov semigroup.
- It is a Feller semigroup.
- All of the above
What is the relationship between a Lévy process and its associated measure?
- The associated measure is the distribution of the process.
- The associated measure is the characteristic function of the process.
- The associated measure is the Lévy measure of the process.
- The associated measure is the generator of the process.