An Overview of Probabilistic and Time Series Models in Finance

Question

1. What are the contributions mentioned in the paper "An overview of probabilistic and time series models in finance" ?

2. What future works have the authors mentioned in the paper "An overview of probabilistic and time series models in finance" ?

3. What are the key when designing these pricing models?

4. What is the GMM procedure used in Hansen and Singleton (1982)?

Accepted Answer

In this paper, the authors partially review probabilistic and time series models in finance.. The characterization of the No-Arbitrage paradigm is extensively studied in several financial market contexts.

Accepted Answer

However, there are still many open problems that will merit future research.. Time Series and Econometric Models are the key when designing these pricing models and calibrating or evaluating its empirical possibilities.. For imperfect markets the authors will never have a unique risk-neutral measure and it is also necessary to find appropriate instruments in order to relate risk-neutral measures and hedging or efficient strategies.

Accepted Answer

Time Series and Econometric Models are the key when designing these pricing models and calibrating or evaluating its empirical possibilities.

Accepted Answer

GMM procedure to estimate time-varying term premia and a consumption based asset pricing model are used in Hansen and Singleton (1982) and Hansen and Scheikman (1995).

Accepted Answer

Multivariate models have been often used to represent financial series of returns related, for example, with the Asset Pricing Theory (APT), asset allocation, estimation of time-varying betas or Value at Risk (VaR).

Accepted Answer

Another extension of SV models considered in the literature is to allow for long memory in volatility; see Harvey (1998) and Breidt et al. (1998).

Accepted Answer

Because of its computational simplicity, the constant correlation model of Bollerslev (1990) has been widely used in the empirical analysis of financial data.

Accepted Answer

probabilistic and time series approaches play a crucial role in finance, and it is emphasized if one focuses on arbitrage pricing theory.

Accepted Answer

the likelihood function for a continuous record can be obtained by means of a classical absolutely continuous change of measure.

Accepted Answer

Since most market models with frictions can fit in the model with flows for a specific convex cone of available investments, the model in Jouini and Napp (2002) provides a unified framework for the study of the characterization of the absence of FL in such imperfect market models.

Accepted Answer

More recently, Jouini and Napp (2002) generalize existing results in the following ways: first, they do not assume that there exists a numéraire available to investors and allowing them to transfer money from one date to another; this enables to consider any type of friction on the numéraire-like no borrowing, different borrowing and lending rates, bonds with default risk, etc.

Accepted Answer

the two main motivations to use time series models to analyze financial data are to represent the empirical properties often observed in real prices and to estimate and test the financial models described in section 2.

An Overview of Probabilistic and Time Series Models in Finance

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Most frequently asked questions

1. What are the contributions mentioned in the paper "An overview of probabilistic and time series models in finance" ?

2. What future works have the authors mentioned in the paper "An overview of probabilistic and time series models in finance" ?

3. What are the key when designing these pricing models?

4. What is the GMM procedure used in Hansen and Singleton (1982)?

5. What are some of the popular models used to represent financial series of returns?

6. Why is the SV model considered in the literature?

7. Why is the constant correlation model widely used in the empirical analysis of financial data?

8. what is the role of probabilistic and time series approaches in finance?

9. How can the authors obtain the likelihood function for a continuous record?

10. What is the meaning of the characterization of the absence of FL in market models?

11. What are the main reasons why Jouini and Napp (2002) generalize existing results?

12. Why do the authors use time series models to analyze financial data?

Citations

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References

The Pricing of Options and Corporate Liabilities

Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation

Generalized autoregressive conditional heteroskedasticity

Capital asset prices: a theory of market equilibrium under conditions of risk*

Conditional heteroskedasticity in asset returns: a new approach

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