Category Archives: Fractional Brownian Motion

Forecasting Financial Markets – Part 1: Time Series Analysis

The presentation in this┬ápost covers a number of important topics in forecasting, including: Stationary processes and random walks Unit roots and autocorrelation ARMA models Seasonality Model testing Forecasting Dickey-Fuller and Phillips-Perron tests for unit roots Also included are a number … Continue reading

Posted in ARMA, Econometrics, Forecasting, Purchasing Power Parity, Time Series Modeling, Unit Roots, White Noise | Tagged , , , , , | 1 Comment

Long Memory and Regime Shifts in Asset Volatility

This post covers quite a wide range of concepts in volatility modeling relating to long memory and regime shifts. The post discusses autocorrelation, long memory, fractional integration, black noise, white noise, Hurst Exponents, regime shift detections, Asian markets and various topics froms nonlinear dynamics. Continue reading

Posted in ARFIMA, Asian markets, Black Noise, Correlation Dimension, Correlation Integral, FIGARCH, Forecasting, Fractional Brownian Motion, Fractional Integration, Henon Attractor, Hurst Exponent, Logistic Attractor, Long Memory, Modeling, Nonlinear Dynamics, Pink Noise, Regime Shifts, Strange Attractor, Uncategorized, Volatility Modeling, White Noise | Tagged , , , , , , , , , , , , | 3 Comments

Modeling Asset Volatility

I am planning a series of posts on the subject of asset volatility and option pricing and thought I would begin with a survey of some of the central ideas. The attached presentation on┬áModeling Asset Volatility sets out the foundation … Continue reading

Posted in Black Noise, Cointegration, Derivatives, Direction Prediction, Dispersion, Forecasting, Fractional Brownian Motion, Fractional Cointegration, Fractional Integration, Long Memory, Mean Reversion, Momentum, Multifactor Models, Options, Pink Noise, REGARCH, Regime Shifts, Volatility Modeling, White Noise | Tagged , , , , , , , , , , , , , , , , | 5 Comments