ldhmm.simulate_abs_acf

This utility simulates the auto-correlation. The first few lag of ACF should match 
the ACF from the market data fairly well. This is a major validation of a successful HMM.
Be aware this is a CPU intensive calculation. It uses the multi-core functionality.

Hidden Markov Model (HMM) based on symmetric lambda distribution
framework is implemented for the study of return time-series in the financial
market. Major features in the S&P500 index, such as regime identification,
volatility clustering, and anti-correlation between return and volatility,
can be extracted from HMM cleanly. Univariate symmetric lambda distribution
is essentially a location-scale family of exponential power distribution.
Such distribution is suitable for describing highly leptokurtic time series
obtained from the financial market. It provides a theoretically solid foundation
to explore such data where the normal distribution is not adequate. The HMM
implementation follows closely the book: "Hidden Markov Models for Time Series",
by Zucchini, MacDonald, Langrock (2016).

Stephen Lihn

ldhmm

Hidden Markov Model for Financial Time-Series Based on Lambda
Distribution

ldhmm.simulate_abs_acf function

<dl><dt>object</dt>
<dd>an ldhmm object that can supply m, param.nbr and stationary.</dd>
<dt>n</dt>
<dd>a positive integer specifying number of observations to simulate.</dd>
<dt>lag.max</dt>
<dd>a positive integer, specifying number of lags to be computed.</dd>
<dt>debug</dt>
<dd>logical, specifying to print progress message or not. Default is <code>FALSE</code>.</dd></dl>

Arguments

Author

Simulating auto-correlation (ACF) — ldhmm.simulate_abs_acf

<dl>

<dt>object</dt>
<dd>an ldhmm object that can supply m, param.nbr and stationary.</dd>


<dt>n</dt>
<dd>a positive integer specifying number of observations to simulate.</dd>


<dt>lag.max</dt>
<dd>a positive integer, specifying number of lags to be computed.</dd>


<dt>debug</dt>
<dd>logical, specifying to print progress message or not. Default is <code>FALSE</code>.</dd>

</dl>

ldhmm.simulate_abs_acf: Simulating auto-correlation (ACF)

Description

Usage

Value

Arguments

Author