Category Archives: S&P500 Index

How to Bulletproof Your Portfolio

Summary How to stay in the market and navigate the rocky terrain ahead, without risking hard won gains. A hedging program to get you out of trouble at the right time and step back in when skies are clear. Even … Continue reading

Posted in ETFs, Modeling, S&P500 Index, Volatility Modeling | Tagged , , , , | Leave a comment

How Not to Develop Trading Strategies – A Cautionary Tale

In his post on Multi-Market Techniques for Robust Trading Strategies (http://www.adaptrade.com/Newsletter/NL-MultiMarket.htm) Michael Bryant of Adaptrade discusses some interesting approaches to improving model robustness. One is to use data from several correlated assets to build the model, on the basis that … Continue reading

Posted in Algorithmic Trading, Futures, Machine Learning, S&P500 Index, Trading | Tagged , , , , , | 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 , , , , , , , | Comments Off

Range-Based EGARCH Option Pricing Models (REGARCH)

The research in this post and the related paper on Range Based EGARCH Option pricing Models is focused on the innovative range-based volatility models introduced in Alizadeh, Brandt, and Diebold (2002) (hereafter ABD).  We develop new option pricing models using … Continue reading

Posted in Financial Engineering, Forecasting, Long Memory, Multifactor Models, Options, REGARCH, S&P500 Index, Volatility Modeling | Tagged , , , | Comments Off

On Testing Direction Prediction Accuracy

As regards the question of forecasting accuracy discussed in the paper on Forecasting Volatility in the S&P 500 Index, there are two possible misunderstandings here that need to be cleared up.  These arise from remarks by one commentator  as follows: … Continue reading

Posted in Direction Prediction, Forecasting, Modeling, Options, S&P500 Index, Volatility Modeling, volatility sign prediction forecasting Engle | Tagged , , , , , , , | Comments Off

Market Timing in the S&P 500 Index Using Volatility Forecasts

To illustrate some of the possibilities of this approach, we constructed a simple market timing strategy in which a position was taken in the S&P 500 index or in 90-Day T-Bills, depending on an ex-ante forecast of positive returns from the logit regression model (and using an expanding window to estimate the drift coefficient). We assume that the position is held for 30 days and rebalanced at the end of each period. In this test we make no allowance for market impact, or transaction costs.
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Posted in Binary Options, Forecasting, Logit Regression, Market Timing, S&P500 Index, Volatility Modeling, volatility sign prediction forecasting Engle | Tagged , , , , , , , , | Comments Off