[PDF] Top 20 Estimation of Hidden Markov Models and Their Applications in Finance
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Estimation of Hidden Markov Models and Their Applications in Finance
... Brokers who have long-term positions in different securities hedge their portfolios dif- ferently depending whether to expect a future crash or rally. In the trading world the value of the financial contract can only go ... See full document
192
Semiparametric estimation of diffusion models with applications in finance
... single-factor models of th e short-term interest ...structure models assumes th a t th e short-term interest rate is a Markov process solving a SDE, in which case this state variable drives the whole ... See full document
189
Estimating empirical codon hidden Markov models
... estimated models to one of the most important applications of codon models: the detec- tion of positive ...ECM estimation might be inaccurate and its performance might be ...codon ... See full document
12
Further applications of higher-order Markov chains and developments in regime-switching models
... existing models in time series that take into account the data memory property have stationary param- eters, which seem inadequate in real-world ...underlying Markov process for these models o ff ers ... See full document
235
Spectral Estimation of Hidden Markov Models
... Hidden Markov Models (HMMs) Baum and Eagon (1967) are widely used in model- ing time series data from text, speech, video and genomic ...In applications where the dimension of the observations ... See full document
91
Bayesian Hidden Topic Markov Models
... topic models offer a statistical model of textual ...of hidden Markov models is proposed using a fully Bayesian ...a Markov process over the topics is expected to better model the ... See full document
120
Using Excel to Simulate and Visualize Conditional Heteroskedastic Models
... Many applications of Hidden Markov Models are possible whenever we have data collected over ...series models (AR, MA, ARMA ...the Hidden Markov Model the observations ... See full document
5
Perfect sampling for nonhomogeneous Markov chains and hidden Markov models
... ergodic Markov chain in ...the Markov chain in ...nonhomogeneous Markov chains, a setting which to date has received little attention, perhaps due to a lack of appropriate formulation or ... See full document
35
An Infinite Hidden Markov Model for Short term Interest Rates
... Models of the term structure of interest rates are important in finance. They are used to price contingent claims, manage financial risk and assess the cost of capital. In most models the short-rate ... See full document
34
Bayesian Nonparametric Hidden Semi-Markov Models
... One approach to avoiding the rapid-switching problem is the Sticky HDP-HMM (Fox et al., 2008), which introduces a learned global self-transition bias to discourage rapid switching. Indeed, the Sticky model has ... See full document
29
Hidden Markov model signal processing and control
... processing applications to communication systems are considered for mixed state hidden Markov ...processing applications, control problems are also considered in this ... See full document
189
Unsupervised Neural Hidden Markov Models
... Part-of-speech tags encode morphosyntactic informa- tion about a language and are a fundamental tool in downstream NLP applications. In English, the Penn Treebank (Marcus et al., 1994) distinguishes 36 cate- ... See full document
9
Online learning in discrete hidden Markov models
... Hidden Markov Models (HMMs) [1, 2] are extensively studied machine learning models for time series with several applications in fields like speech recognition [2], bioinfor- matics [3, ... See full document
8
PERFORMANCE COMPARISION OF ENVIRONMENTAL NOISE MODELLING USING HIDDEN MARKOV MODEL AND FUZZY HIDDEN MARKOV MODEL
... Hidden Markov models are widely used in science, engineering and many other areas (speech recognition, optical character recognition, machine translation, bioinformatics, computer vision, ... See full document
10
Clustering Hidden Markov Models with Variational HEM
... In this paper, we presented a variational HEM (VHEM) algorithm for clustering HMMs with respect to their probability distributions, while generating a novel HMM center to represent each cluster. Experimental results ... See full document
51
Frequency tracking and hidden Markov models
... The hidden Markov model-maximum likelihood (HMM-ML) frequency tracker given in [3] and [4] is a good example how HMMs can be useful in frequency ...practical applications can be improved, including ... See full document
267
State-by-state Minimax Adaptive Estimation for Nonparametric Hidden Markov Models
... Note that finding the right penalty term σ is essential in order to obtain minimax rates of convergence. This requires a fine theoretical control of the variance of the auxiliary estimators, in the form of assumption ... See full document
46
Adaptive Estimation Techniques for Hidden Markov Models
... Once the hidden semi-Markov model has been formulated as an augmented homogeneous HMM, known HMM techniques such as the vector versions of the forward-backward algorithm along with the B[r] ... See full document
97
Minimax Adaptive Estimation of Nonparametric Hidden Markov Models
... the hidden chain is full ...regression models with hidden regressor variables that can be Markovian on a continuous state ...estimate hidden parameters in latent-structure ... See full document
43
Applying Hidden Markov Models to Voting Advice Applications
... Advice Applications (VAAs) are used to inform citizens about the political stances of the parties that involved in the upcoming elections, in an effort to facilitate their decision making process and increase their ... See full document
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