The [Kalman filter][1], also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing noise (random variations) and other inaccuracies, and produces estimates of unknown variables that tend to be more precise than those based on a ...

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Example Scalar Model Extended Kalman Filter

I have a simple question. I think not a question is, is a request. This month I have been studying how to understand and implement the Kalman filter algorithm for simple models such as the local level....
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kalman filter update equation

Assume that futures price $F(t,T)$ follows the Ito process as described by the following stochastic process $$ln F(t,T)=lnF(0,T)+(Z_1(t)e^{-k(T-t)}+Z_2(t))-(1/4k)[(1-e^{-2kT})(h_1^2+h_2^2))+4h_1h_0(1-...
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Kalman vs simple OLS

I am studying how some local and global variables (x and alpha) affects a local variable y have the following regression $y_{it} = \sum_{j} \beta_{ij} x_{itj}+\sum_j \delta_{ij}\alpha_{jt}+\epsilon$ ...
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nloptr and portfolio replication using Kalman Filter

Let me first say that I am relatively new to R. For a school project I am trying to create a replicating portfolio using a constrained Kalman Filter. I have tried using nloptr without success - I am ...
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Does Kalman filter always improve over linear regression?

If I have a simple linear regression that has statistical signification but I would like to improve the overall prediction results. Will a Kalman filter be always an improvement or as least achieve ...
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Moving window forecasting in Python

I am looking to create some code that will out-of-sample forecast the HAR-RV model. The model itself is formulated as the following, and the betas are estimated through HAC-OLS or Newey-West. ...
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How to find optimal noise covariance matrices Q & R

I am trying to use the discrete Kalman filter for forecasting and I wonder what is commonly considered as the optimal way of determining the measurement noise covariance constants (Q and R) for a ...
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Correct form for State Space Equation for Kalman Filter for DNS

In this paper: http://www.ssc.upenn.edu/~fdiebold/papers/paper55/DRAfinal.pdf in eqns 3,5 the state eqn has the mean removed. $(z_t-\mu)=A(z_{t-1}-\mu) + \epsilon_t$ $y_t=C z_t + \delta_t$ ...
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Identifiability of a state space model (Dynamic Linear Model)

Take a general linear Gaussian state space model (SSM)(aka Dynamic Linear Model DLM): $X_{t+1}=FX_t + V_t$ $Y=HX_t+W_t$ $V_t \sim N(0,Q)$ $W_t \sim N(0,R)$ I am interested in the ...
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How to tune Kalman filter's parameter?

I plan to use Kalman filter to estimate saving account amount. However, I'm a bit lost at how to tune the filter's parameters. Taking as the example from the Wikipedia page, basically there are ...
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226 views

Kalman filtering

Is it possible to the extract the latent factor f from the following equations using kalman smoothing? f is the unobserved state value while z is observed series. From the literature i could read ...
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Time-Varying Copulas (GAUSS)

Could anyone suggest me how to begin with Time-varying Copulas or Stochastic Copulas? I'm looking for the GAUSS code, however it seems there are only MATLAB code available over the internet. I'm ...
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Kalman Filter Equity Example

I am looking out for some material where I can study about Kalman Filter applied to Equity using Excel or R?
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robust open source Kalman filter library in C++

I would like to know if anyone has experience with a good open source kalman filter implementation in C++ that I could use. I require an implementation that supports computation of likelihood similar ...
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Variable Selection with Kalman Filter

I'm trying to estimate factor loadings on portfolios over time for portfolios that are traded pretty frequently. I have a sense that several portfolios are loading on the Fama-French HML factor ...
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188 views

Simulating state space model with AR(1) dynamics

I asked a question similar to this previously: https://dsp.stackexchange.com/questions/16341/simulating-a-state-space-model However I think I have a better handle on it now and want to re-ask it: I ...
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mean reversion with Kalman Filter - Spread calculation

Ernest Chan in its book "Algorithmic Trading" shows how to use the Kalman Filter for mean reversion pair trading. I have seen that he uses the measurement prediction error for calculating the spread ...
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632 views

Maximum Likelihood using a Kalman filter for two factor model

I'm trying to implement a Kalman Filter for the parameter estimation of a linear gaussian two factor model in Matlab. (Schwartz Smith model for commodity prices) In other words: I try to compute the ...
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Parameter estimation of Ornstein–Uhlenbeck and CIR processes

I would like to estimate Ornstein–Uhlenbeck process' parameters via Kalman filter. My process is the following one: $\text{d}x_{t}=\alpha(\theta-x_{t})\text{d}t+\sigma\text{d}W_{t}$ I'm interested ...
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Good criteria to sort state-space $\beta_{t}$ according to Kalman filter output

Let the usual state-space linear model (without constant term for the sake of simplicity): $y_{t}=\beta_{t} X_{t}+\epsilon_{t}$ If we use Gaussian Kalman filter to estimate $\beta_{t}$ we get $P_{t}$...
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Time-varying correlation via state-space representation and Kalman filter

Let a linear time-varying mode like this one: $y_{t}=\alpha_{t}+\beta_{t}x_{t}+\epsilon_{t}$. You can also suppress the constant term to simplify this example: $y_{t}=\beta_{t}x_{t}+\epsilon_{t}$. ...
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Counterintuitive time varying Beta with Kalman filter

If you're used to play with R, you'll enjoy the following reproducible code: ...