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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 ...
pierce's user avatar
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83 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 + \...
Spandaver's user avatar
2 votes
2 answers
174 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 ...
BlueTurtle's user avatar
1 vote
0 answers
132 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 ...
daily's user avatar
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98 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 ...
Vignesh 's user avatar
1 vote
0 answers
169 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. ...
randomWalk's user avatar
1 vote
0 answers
130 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 ...
David Loungani's user avatar
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57 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)...
user53249's user avatar
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3 votes
1 answer
381 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 ...
WolfgangP's user avatar
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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 ...
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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 ...
Dipanshu Gupta's user avatar
2 votes
0 answers
81 views

Robust standard errors OLS for term structure

Suppose i have estimated the following model with OLS: $y_{1,t+1} - y_{1,t} = \alpha + \beta y_{1,t} + \epsilon_{t+1}$. Where $y_{1,t}$ is the 1 month zero-coupon yield at time t. What would be an ...
Lazy019's user avatar
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3 votes
0 answers
469 views

Initial forward variance curve $\xi_0(t)$ in the Rough Bergomi model

The rough Bergomi model is defined as \begin{cases} \frac{dS_t}{S_t} = \sqrt{v_t}dW_t^1 \\ v_t=\xi_0(t)\exp(\eta \tilde{W}_t^H-\frac{1}{2}\eta^2t^{2H}) \\ \tilde{W}_t^H = \int_0^t \sqrt{2H}(t-s)^{H-\...
NN2's user avatar
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1 vote
0 answers
139 views

MatLab code does not work for Heston model calibration

I am trying to calibrate Heston model on some data and I have the following code. Code is supposed, after it reads the data, to give back 5 parameters. However, I get an empty answer from MatLab. Does ...
Francesco Bova's user avatar
1 vote
1 answer
210 views

Long-Term Energy Price Modelling: Log Returns, Distributions, Time-Weighting

I wish to forecast energy prices in the long-term (ca. 20 years) for energy-efficiency investments. While I understand that the energy carriers are particularly sensitive to external (geo-political) ...
Anthony's user avatar
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3 votes
1 answer
179 views

Which references would be useful as an introduction to econometrics as it pertains to CONTINUOUS TIME models?

It seems like the problem of trying to estimate model parameters for continuous time models is not commonly covered in standard econometric textbooks, even those focusing on time series. I certainly ...
Stéphane's user avatar
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4 votes
0 answers
131 views

How often to tune the regularisation parameter in LASSO?

I'm trying to implement the following paper: Avellaneda & Lee (2010), Statistical Arbitrage in the US equities market. To build the strategy, the idea is to trade a stock and hedge using a basket ...
Eaglez's user avatar
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2 votes
0 answers
447 views

James-Stein estimator for superior estimates of returns in m.v. portfolio optimization

I am currently learning about statistical techniques to enhance the estimation of input parameters in a m.v. optimization. Specifically I have some doubts about the James-Stein estimator applied as an ...
Nipper's user avatar
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2 votes
0 answers
57 views

Correcting high AR(1) coefficients in dynamic Gordon model

I have just finished my thesis on a heterogeneous dividend expectations model applied to the COVID-19 crisis. However after receiving some feedback there is one last issue I want to resolve. I'm using ...
Niek de Meijier's user avatar
1 vote
2 answers
993 views

Can someone explain the particle filter algorithm in detail with intuition [closed]

I am trying to understand particle filters and their application but i am not able to understand the underlying methodology. I have read a few sources but either the language is not clear or they dive ...
pppp_prs's user avatar
  • 173
2 votes
1 answer
281 views

Cornish Fisher VaR Parameters Calibration

I am trying to calculate Cornish-Fisher (modified VaR), but I am in a trouble because when I am reading some articles, some authors calculate the Cornish-Fisher expansion taking parameters S and K, as ...
CQuintero's user avatar
2 votes
2 answers
275 views

What to do if certain parameters are not market observable?

Lets say I have no clue on correlation between 2 equities in the market (i.e. i don't have an observable market price). What is the best way to go about marking this correlation for lets say the best ...
Arshdeep's user avatar
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2 votes
0 answers
81 views

Beta estimates of Regressions on AR(1) Process

I am currently working through the paper The Myth of Long-Horizon Predictability [1] and I got stuck in reproducing the empirical results in Section 1.4. It is my understanding that time series of ...
Hans-Peter Schrei's user avatar
3 votes
0 answers
95 views

Are the increments of a stochastic process driven by fractional Brownian motion independent?

I'm studying the following equation $$\tag1 dX_t = \mu X_t dt + \sigma X_t dB^H_t $$ where $B^H$ is the fractional Brownian motion (fBm) of Hurst parameter $H\in(0,1)$, that is a continuous ...
sound wave's user avatar
0 votes
3 answers
446 views

maximum likelihood pdf

I am looking at the topic maximum likelihood, and I cannot understand why we set the pdf of $y_{t}$ equal to 1. It is with regards to a OLS example. The information i got is this: Model: $y_{t}=\...
mbih's user avatar
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1 vote
0 answers
47 views

Likelihood increases on increasing variance of measurement error in kalman filter

I tried to fit a local trend model to daily data of a currency. I used the "dlm" package and tried to estimate the parameters V (measurement noise) and W (the process noise) via maximum likelihood. ...
pppp_prs's user avatar
  • 173
3 votes
0 answers
346 views

Estimating Market Price of Risk

I need help with estimating market price of risk. Assume money market account and two risky assets which exposed to same two sources of risks follow process: $dM(t)=rM(t)dt$ $dS_1(t)=S_1(t)(\mu_1dt+\...
TryingtobeQuant's user avatar
1 vote
1 answer
100 views

Calibrate a model parameter with an error function

Suppose I want to find the implied volatility using an option model from market prices. Surely I can find the implied volatility for each strike price ($k$ different strike prices) for a given ...
alexbougias's user avatar
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1 vote
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104 views

Brownian motion from price-series, what is the time step?

If I assume a given empirical price-series is a brownian motion, I can estimate the drift and standard deviation as long as I know what the time step was when the process was 'generated'. But since ...
wildbunny's user avatar
  • 629
3 votes
0 answers
128 views

Inverse Problems in Finance

Are there any canonical references for inverse problems in finance? For example, if I have a measure that evolves with Fokker-Planck dynamics, are there standard approaches used by the community to ...
vrume21's user avatar
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1 vote
0 answers
103 views

Parameter Estimation of any model

I am new to time series modelling.I cant get my head around parameter estimation and its methods. My question consists of 3 parts : 1st : Lets say i have a model like Garch or Heston model or a SVJD ...
pppp_prs's user avatar
  • 173
0 votes
2 answers
2k views

GARCH fit: "failure to achieve convergence"... a problem?

Sometimes when one is trying to fit a GARCH model may happen that in the estimation summary (whatever software is) there is written "failure to achieve convergence after n iteration" or similar things....
LeoAn's user avatar
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0 answers
68 views

Good introduction to estimating stochastic diffusion processes?

So, in an advanced Econometrics course, the current topic relates to estimating transition densities and diffusion processes by MLE, such as this R package doc describes, for ex., and I have to admit ...
Coolio2654's user avatar
2 votes
1 answer
277 views

Practical way to estimate price sensitivity to unexpected earnings (i.e., post-earnings drift)?

Post-earnings announcement drift is a well documented anomaly in financial research. In 2017 May NBER paper, Replicating Anomalies, the authors found that anomalies related to standardized unexpected ...
David Addison's user avatar
0 votes
1 answer
334 views

How to estimate historical implied volatility?

I want to estimate the historical price of out of the money puts on equities. I do have about 10 years history of implied volatility (IV) but I would like more. I had the naïve idea modeling the IV ...
Jean-Christophe Curtillet's user avatar
8 votes
2 answers
1k views

Estimation of the drift of a non-stationary process

I'd like to estimate the drift of a continuous-paths, non-stationary, stochastic process $X_t$ from a time series of values $\{X_{i\Delta t}\}_{i=1,\dots,N}$ sampled from a single realisation of that ...
user26877's user avatar
2 votes
1 answer
51 views

What are some reasonable parameters with three Wiener processes?

In a foreign currency model, domestic and foreign stocks + exchange rate is modelled via 3 Wiener processes. I am trying to price options in this model, however, I am unsure what some realistic ...
Wegottamove's user avatar
2 votes
0 answers
54 views

LSE GARCH Modells

currently I am working with GARCH Modells. And it came to my attention that for the parameter estimation Maximum Likelihood approaches are commonly used. However I was wondering why Least Squared ...
clee1994's user avatar
0 votes
1 answer
196 views

EM for conditional Gaussian model

Let $$X_1\sim N(\mu_{X_1},\sigma_{X_2}^2)$$ $$X_2\sim N(\mu_{X_2}, \sigma_{X_2}^2)$$ where $\mu_{X_2}=c+aX_1$. Also, I have data $D$ (with missing values on $X_1,X_2$). How can I update/estimate the ...
snowave's user avatar
  • 191
2 votes
3 answers
3k views

Robust standard errors in GARCH modelling (rugarch)

I am currently conducting some GARCH modelling and I am wondering about the robust standard errors, which I can obtain from ugarchfit() in ...
Masher's user avatar
  • 491
4 votes
0 answers
162 views

Volatility Parametrization Libor Market Model - Underspecified Model?

Does the volatility parametrization that I have chosen give an underspecified model? Which volatility parametrization in the Libor Market Model would suit the best for the particular case described ...
Tinkerbell's user avatar
2 votes
2 answers
368 views

How to transform Ornstein-Uhlenbeck parameters from hourly to daily?

I get the parameters (long-term mean, volatility, mean-reversion speed, correlation) of two correlated Ornstein-Uhlenbeck processes via a likelihood estimation from hourly data. If I want to transform ...
LenaH's user avatar
  • 123
2 votes
0 answers
213 views

Simulating t-distributed returns by calibrating degrees of freedom $\nu$ from variance or kurtosis

A slight twist (I hope) on the familiar problem of simulating log returns from a t-distribution. My two questions concern calibration to sample data. First, one can infer the degrees of freedom, $\nu$...
LukeG's user avatar
  • 21
4 votes
1 answer
1k views

How to estimate parameters for 2 correlated Ornstein-Uhlenbeck processes with maximum likelihood?

I would like to use maximum likelihood to estimate the parameters of two correlated Ornstein-Uhlenbeck processes from empirical data. Do you have any good references for this? If you have any hints ...
LenaH's user avatar
  • 123
0 votes
1 answer
877 views

Kalman Filter in Interest Rate Models

A couple questions regarding the use of Kalman filtering in estimating parameters of short rate models: 1) In Duan & Simonato (1995), which seems to be one of the earliest applications of the ...
bcf's user avatar
  • 2,828
3 votes
2 answers
2k views

Degrees of freedom in calculating significance of GARCH coefficients

I am trying to determine the significance of coefficients of a GARCH model by calculate the p-values using the following Matlab formula: pvalues = 2*(1-tcdf(abs(t),n-v)), where $t$ is the t-stat, $...
Masher's user avatar
  • 491
2 votes
1 answer
837 views

GJR-GARCH with $\alpha = 0$ as parameter estimate

I am estimating a GJR-GARCH(1,1) model with variance targeting in R. As data I am using returns on some stock indices. While calculating the GARCH models I obtain $\alpha=0$ for some indices. From ...
Masher's user avatar
  • 491
0 votes
1 answer
66 views

Imposing MLE restrictions by logistic mapping

I am doing some Maximum Likelihood Estimation with a density that has time-varying parameters. I am using the fmincon function in Matlab, but I do not know how to ...
Masher's user avatar
  • 491
2 votes
0 answers
54 views

Texts on the Generalized Method of Moments

I was looking for a book that could explain me well the Generalized Method of Moments, its mathematical nuances, and even have a look to the empirical side, maybe with some guided exercises with Stata ...
james42's user avatar
  • 676
1 vote
2 answers
2k views

Calibration of non-mean-reverting OU process

I'm looking for some reference on how to calibrate a non-mean-reverting Ornstein-Uhlenbeck process to historical data using MLE or OLS. The model has the following SDE: $d\lambda(t)=a\lambda(t)dt+\...
Egodym's user avatar
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