### Forums

### Blogroll

### Search

### Archives

### Categories

- Algo Design Language (3)
- Algo Strategy Engine (2)
- Algorithmic Trading (7)
- Alternative Investment (1)
- ARFIMA (1)
- ARMA (4)
- Asian markets (2)
- Binary Options (1)
- Black Noise (2)
- Cointegration (2)
- Commodity Futures (1)
- Correlation Dimension (1)
- Correlation Integral (1)
- Day Trading (1)
- Derivatives (3)
- Direction Prediction (4)
- Dispersion (1)
- Econometrics (7)
- Economics (1)
- Econophysics (2)
- Education (1)
- Emerging Markets (1)
- Equity Curve (2)
- Equity Futures (1)
- ETFs (3)
- Fat Tails (2)
- FIGARCH (2)
- Financial Engineering (5)
- Fixed Income Futures (1)
- Forecasting (17)
- Fourier Transforms (1)
- Fractional Brownian Motion (2)
- Fractional Cointegration (2)
- Fractional Integration (3)
- Futures (7)
- GARCH (1)
- Genetic Programming (1)
- Graduate Programs (1)
- Granger Causality (1)
- Hedge Funds (2)
- Henon Attractor (1)
- High Frequency Finance (5)
- High Frequency Trading (6)
- Hurst Exponent (2)
- Hybrid Products (1)
- Interest Rate Models (1)
- Jobs (1)
- Kelly Criterion (1)
- Latency (1)
- Logistic Attractor (1)
- Logit Regression (2)
- Long Memory (4)
- Machine Learning (4)
- Market Efficiency (2)
- Market Microstructure (4)
- Market Timing (3)
- Markov Model (1)
- Markov State Models (1)
- Mathematca (1)
- Mathematica (4)
- Matlab (3)
- Mean Reversion (2)
- Metals (1)
- Model Review (1)
- Modeling (4)
- Momentum (1)
- Money Management (3)
- Multifactor Models (2)
- Natural Gas Futures (1)
- Nearest Neighbor (1)
- Neural Networks (1)
- Nonlinear Classification (2)
- Nonlinear Dynamics (2)
- Optimal f (1)
- Options (6)
- Order Flow (2)
- Pairs Trading (2)
- Pink Noise (2)
- Principal Components Analysis (1)
- Purchasing Power Parity (1)
- Quant/Traders (1)
- Random Forrests (1)
- Recruitment (1)
- REGARCH (3)
- Regime Shifts (4)
- Regime Switching (2)
- Regression (1)
- Risk Management (1)
- S&P500 Index (8)
- Scalping (2)
- Signal Processing (1)
- Spline Methods (1)
- Spread Trading (2)
- Statistical Arbitrage (2)
- Stochastic Differential Equations (1)
- Stock Market (1)
- Strange Attractor (1)
- Strategy Development (1)
- Support Vector Machines (1)
- Systematic Strategies (1)
- Time Series Modeling (4)
- Toxic Flow (2)
- TradeStation (2)
- Trading (8)
- Trading Technologies (3)
- Uncategorized (8)
- Unit Roots (1)
- Van Tharp (1)
- VIX Index (6)
- Volatility ETF Strategy (3)
- Volatility Modeling (21)
- volatility sign prediction forecasting Engle (3)
- White Noise (3)
- Yield Curve Modeling (1)

### Tag Cloud

ADL ARFIMA ARMA Models Black Noise Direction Prediction E-min ETFs Financial engineering Forecasting Fractional Brownian Motion Fractional Cointegration Fractional Integration Futures GARCH High Frequency Trading Jump Diffusion Kalman Filter Kurtosis Long Memory Machine Learning Market Microstructure Market Timing Mathematica MultiFactor Models Natural Gas Option Pricing Options Pairs Trading REGARCH Regime Shifts Robustness S&P500 Index Scalping Skewness Smile Statistical Arbitrage Stochastic Volatility Strategy Toxic Flow Tradestation Trading VIX Volatility Volatility Dynamics White Noise

# Tag Archives: Forecasting

## Measuring Toxic Flow for Trading & Risk Management

A common theme of microstructure modeling is that trade flow is often predictive of market direction. One concept in particular that has gained traction is flow toxicity, i.e. flow where resting orders tend to be filled more quickly than expected, while … Continue reading

Posted in Algorithmic Trading, ARMA, Direction Prediction, Econometrics, Econophysics, Forecasting, High Frequency Finance, Market Microstructure, Order Flow, Risk Management, Time Series Modeling, Toxic Flow
Tagged Forecasting, Market Microstructure, Order Flow, Toxic Flow
Comments Off

## Market Microstructure Models for High Frequency Trading Strategies

This note summarizes some of the key research in the field of market microstructure and considers some of the models proposed by the researchers. Many of the ideas presented here have become widely adopted by high frequency trading firms and … Continue reading

Posted in Econophysics, Forecasting, High Frequency Finance, High Frequency Trading, Market Microstructure
Tagged Econophysics, Forecasting, High Frequency Finanance, High Frequency Trading, Market Microstructure
Comments Off

## Forecasting Financial Markets – Part 1: Time Series Analysis

The presentation in this post 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 ARMA Models, Box Jenkins, Direction Prediction, Forecasting, Purchasing Power Parity, Time Series Analysis
Comments Off

## Regime-Switching & Market State Modeling

The Excel workbook referred to in this post can be downloaded here. Market state models are amongst the most useful analytical techniques that can be helpful in developing alpha-signal generators. That term covers a great deal of ground, with ideas … Continue reading

Posted in ARMA, Econometrics, Fat Tails, Forecasting, Markov State Models, Regime Shifts
Tagged ARMA Models, Forecasting, Markov State Models, Regime Shifts
Comments Off

## Resources for Quantitative Analysts

Two of the smartest econometricians I know are Prof. Stephen Taylor of Lancaster University, and Prof. James Davidson of Exeter University. I recall spending many profitable hours in the 1980′s with Stephen’s book Modelling Financial Time Series, which I am … Continue reading

Posted in Econometrics, Forecasting, Time Series Modeling
Tagged Econometrics, Forecasting
Comments Off

## Can Machine Learning Techniques Be Used To Predict Market Direction? The 1,000,000 Model Test.

During the 1990′s the advent of Neural Networks unleashed a torrent of research on their applications in financial markets, accompanied by some rather extravagant claims about their predicative abilities. Sadly, much of the research proved to be sub-standard and the … Continue reading

Posted in Direction Prediction, Forecasting, Logit Regression, Machine Learning, Matlab, Modeling, Nearest Neighbor, Neural Networks, Nonlinear Classification, Nonlinear Dynamics, Random Forrests, S&P500 Index, Support Vector Machines
Tagged Direction Prediction, Forecasting, Machine Learning, Nearest Neighbor, Neural Networks, Nonlinear Classification, Random Forrests, Support Vector Machines
Comments Off

## 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 ARFIMA, Black Noise, Forecasting, Fractional Brownian Motion, Fractional Integration, Henon Attractor, Logistic Attractor, Long Memory, Regime Shifts, Strange Attractor, Volatility, Volatility Dynamics, White Noise
Comments Off