Questions tagged [parameter-estimation]
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61 questions
2 votes
0 answers
82 views
Replicating Parameter Estimates from Fergusson’s 2020 Inflation Forecasting Models
I’m working on replicating the parameter estimates for the four models in Table 1 of the paper “Forecasting Inflation Using Univariate Continuous-Time Stochastic Models” by Kevin Fergusson (2020), ...
- 21
0 votes
0 answers
145 views
Why does calibrating a Vasicek model to bond prices yield risk-neutral (Q-measure) parameters?
while reading Options, Futures and Other Derivatives (Hull, 8th ed.), Chapter 30 (p. 688) I came across the sentences “There is an important difference between the two approaches. The first approach (...
0 votes
0 answers
42 views
How to prove regime switching is not happening in parameters from data
Generally in economics/finance autoregressive models features regime switching in both parameters and volatility. In my case my data is giving a rough indication that regime switching in parameter is ...
2 votes
0 answers
103 views
What are common parametric forms for VIX smiles?
It is common in SPX markets to fit smiles using Stochastic volatility-inspired and Surface stochastic volatility-inspired parametric forms introduced by Gatheral and Jacquier (2014). In VIX markets ...
- 297
1 vote
0 answers
65 views
Comparing standard error asymptotics of standard deviation and mean absolute deviation estimators
I was reading Chapter 4 of Jean-Philippe Bouchaud's book "Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk Management" and in section 4.2.2 author was ...
- 11
0 votes
0 answers
139 views
Maximum likelihood estimation of system of correlated SDEs
I have the following system of SDEs (which you can think of as 3 different stocks) $$dX_t^1 = \mu_t X_t^1 dt + \sigma_t X_t^1 dW_t^1$$ $$dX_t^2 = \mu_2 dt + \sigma_2 dW_t^2$$ $$dX_t^3 = \mu_3 dt + \...
2 votes
2 answers
291 views
What is the process for using OLS on time series models (HAR like)
I am reading about HAR models for realised variance and they all seem to use WLS or OLS to calculate the parameters. Now I understand how that works if you just use say the 10 years of AAPL intraday ...
- 123
1 vote
0 answers
229 views
ESSVI calibration problem in translating parameter bounds
I am trying to implement the calibration algorithm presented in the "ESSVI Implied Volatility Surface" white paper from Factset by Akhundzadeh et al. The eSSVI model includes 2 variables ...
- 11
0 votes
0 answers
224 views
Calibration for CIR Model Discretization for Predictor Corrector and Milstein method
I'm new to Quantitative Finance. I've data which I need to fit a CIR model and estimate its parameters. $ dX_{t+1} = a(b-X_{t})dt + \sigma \sqrt{X_t}dW_{t} $ While I can fit and obtain ...
- 1
1 vote
0 answers
252 views
how to estimate Geometric Brownian Motion parameters on long timeseries [closed]
I'm working on a 50-years financial timeseries and I would like to simulate GBM paths from it. The first thing I'm supposed to do is to estimate the drift $\mu$ and the volatility $\sigma$ parameters. ...
- 11
1 vote
0 answers
158 views
How can I estimate value-at-risk of a long/short portfolio without making simplifying assumptions?
I have had a couple of long-standing questions about the mathematics behind a simple "vanilla" parametric VaR calculation and I'm hoping someone could clear up my confusion. Most likely I am ...
0 votes
0 answers
95 views
Nonlinear Constrained optimization for a CIR model
I want to calibrate a CIR model which is commonly used to model the evolution of interest rates. Briefly speaking, we know that its dynamics is of the form \begin{equation} dr_t = \kappa (\theta - r_t)...
- 419
3 votes
1 answer
562 views
Estimating volatility of a geometric Brownian motion at different sample rates
I have troubles estimating volatility (= standard deviation of log returns) when the data is re-sampled at different sample frequencies. Problem I have generated a time series data using a geometric ...
- 295
0 votes
0 answers
93 views
Option pricing when stock price follows binomial tree
Assume that the stock price is currently trading at $S_0$. It is known that the stock price follows a binomial tree, such that its price will be either $S_0e^{\theta_u}$ or $S_0e^{−\theta_d}$ over the ...
- 123
3 votes
1 answer
325 views
How to parameterising Greek Surfaces?
I'm currently working on my master thesis, where I have data on option trading volume and flow (number of shares bought minus sold; i.e., net position), divided among three kinds of market ...