# Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

## Cunwei's Blogs

Aim for the moon. If you miss, you may hit a star.

## Cunwei Fan (范存炜)

Ph.D. candidate at University of Illinois Interested in physics, statistics and quantatitive finance

## Everyday Life

Happiness and enjoyment

## Technical

Accmulate in the learning path

## Realized Garch model with dynamical conditional correlation

Study of Garch model with realized variance and study the dynamic conditional correlation model on 6 stock stock data.

## My cute son’s photos before he turns to one month

My son turns to one month and he is so cute. He has a name now : Xuanyi Ben Fan (范本轩逸).

## Travel Experience to Hawaii

Travel Plan I have always been dreaming of traveling to Hawaii and enjoy the beach and sunshine. This spring break we got cheap tickets and make our plan to...

My son is born !

## EM Algorithm for Linear Clusters

Here is an interesting situation occurred to me. In a scatter plot, it is clear that there are two straight lines and each line is contanminated by some nois...

## Some FPGA basic element design and Vivado code

I am doing a service task for CERN on a hardware project. I learned something on FPGA and some basic vivado code and glad to share here.

## Introduction on how to write an Athena(ATLAS) package for release22

I am writing this post is because I recently met some problem of writing an Athena Algorithm for my research. I am using a simple code to get lepton n-tuples...

## Some Properties of Linear Regression

If we regress $X$ on $Y$ and get $\beta$ as the slope and if we regress $Y$ on $X$ and get slope $\beta’$. What is the product of $\beta$ and $\beta’$

## Interesting Statsitcal Problems in Interviews

Problem 1 If we have $n$ dice draws with a dice that has $k$ sides. Let $X_i$ to be the random variables that describes the number of times that the dice fac...

## Lecture 01 (Jan 21, 2022)

First Lecture: Intorduction of autocorrleation for linear time series

## Lecture 02 (Jan 24, 2022)

Calculate the variance and convergence rates for autocorrelation sample estimator by central limit theorem. Introduce statistical tests for ACF.

## Lecture 03 (Jan 26, 2022)

Some introduction of AR model and linear model covariance calculation.

## Lecture 04 (Jan 31, 2022)

Introduce AR(2) model and disucss the condition of weakly stationary for AR(1) and AR(2) models

## Lecture 05 (Feb 02, 2022)

Periodicity of AR models with complex roots; Asymptotic statistics of AR(p) models

## Lecture 06 (Feb 04, 2022)

Introduction to PACF and Information criteria (AIC, BIC)

## Lecture 07 (Feb 07, 2022)

Introduction to MA model and conditional loglikelihood maximization method. Introdcution to ARMA model

## Lecture 08 (Feb 09, 2022)

Introduction to ARMA model and its AR and MA representation

## Lecture 09 (Feb 11, 2022)

Introduction of Karhunen-Leove theorem, the spectral theorem and autocovariance generating function

## Lecture 10 (Feb 14, 2022)

Spectral density as the Fourier transform of autocovariance, the sample version spectral representation theory and sample periodogram

## Lecture 11 (Feb 16, 2022)

Spectral representation sample version proof. Variance decomposition into Fourier components. Estimate spectral density

## Lecture 12 (Feb 18, 2022)

Non parametric estimation of spectral density (Kernel Method)

## Lecture 13 (Feb 21, 2022)

Introduction to Conditional Variance

## Lecture 14 (Feb 23, 2022)

Introduction to ARCH model

## Lecture 15 (Feb 25, 2022)

Estimation of ARCH Model with method of moments

## Lecture 16 (Feb 28, 2022)

Introduction to Generalized ARCH and model estimation and forecast

## Lecture 17 (March 02, 2022)

Introduction to Non-linear Models including TAR ans SETAR

## Lecture 18 (March 04, 2022)

Introduction to unit root models

## Lecture 19 (March 07, 2022)

Construct statistical test for unit root from samples

## Lecture 20 (March 09, 2022)

Random Walk with Drift term and statistical test for non-zero drift

## Lecture 21 (March 11, 2022)

Statistical Test for The Drift Term

## Lecture 22 (March 21, 2022)

Continuous Time Model

## Lecture 23 (March 23, 2022)

Introduction to Ito’s Process and Ito’s Lemma

## Lecture 24 (March 25, 2022)

Introduction to Ito’s Process and Ito’s Lemma

## Lecture 25 (March 28, 2022)

Application of Ito’s Lemma: Derivation of Black-Scholes Formula

## Lecture 26 (March 30, 2022)

Diffusion Processes with Jumps

## Lecture 27 (April 01, 2022)

Continutation of Jump Diffusion Model and Introduction to Multiple Time Series

## Lecture 28 (April 04, 2022)

Introduction to Vector Autoregressive (VAR) model

## Lecture 29 (April 06, 2022)

Introduction to Cointegration and Vector Error Correction Model

## Lecture 30 (April 08, 2022)

Introduction to Vector Error Correction Model

## Lecture 31 (April 11, 2022)

Introduction to state space model, the Kalman Filterl

## Lecture 32 (April 13, 2022)

Continuation of the discussion of Kalman Filter