The Minimum Correlation Algorithm is a heuristic method discovered by David Varadi. Below I will benchmark the execution speed of 2 versions of the Minimum Correlation Algorithm versus the traditional minimum variance optimization that relies on solving a quadratic programming problem. I have run the code above for n=10 (10 assets), n=100 (100 ... [Read more...]

Today I want to follow up with the Minimum Correlation Algorithm Paper post and show how to incorporate the Minimum Correlation Algorithm into your portfolio construction work flow and also explain why I like the Minimum Correlation Algorithm. First, let’s load the ETF’s data set used in the ... [Read more...]

Over summer I was busy collaborating with David Varadi on the Minimum Correlation Algorithm paper. Today I want to share the results of our collaboration: Minimum Correlation Algorithm Paper Back Test reports Supporting R code The Minimum Correlation Algorithm is fast, robust, and easy to implement. Please add it to ... [Read more...]

First, just a quick update: I’m moving the release date of the SIT package a few months down the road, probably in November. Now back to the post. Recently I came across a series of interesting posts about the Permanent Portfolio at the GestaltU blog. Today I want to ... [Read more...]

While back-testing trading strategies I want all assets to have long history. Unfortunately, sometimes there is no tradeable stock or ETF with sufficient history. For example, I might use GLD as a proxy for Gold allocation, but GLD is only began trading in November of 2004. We can extend the GLD’... [Read more...]

I got a question last week about going from the backtest to the trading. For example, if our system is based on today’s close, we can approximate the close value by the price at say 3:30pm, determine the signal and still have time enter the trade. It is not ... [Read more...]

Today I want to continue with Adaptive Asset Allocation theme and examine how the strategy results are sensitive to look-back parameters used for momentum and volatility computations. I will follow the sample steps that were outlined by David Varadi on the robustness of parameters of the Adaptive Asset Allocation algorithm ... [Read more...]

Today I want to highlight a whitepaper about Adaptive Asset Allocation by Butler, Philbrick and Gordillo and the discussion by David Varadi on the robustness of parameters of the Adaptive Asset Allocation algorithm. In this post I will follow the steps of the Adaptive Asset Allocation paper, and in the ... [Read more...]

I want to share a brilliant idea and a great example from the You’re Looking at the Wrong Number post at the GestaltU blog. Today, I will focus on the section of this post that outlines simple steps to improve a typical 60/40 stock/bond portfolio by using risk allocation ... [Read more...]

Recently, I came across quite a few examples of time series forecasting using R. Here are some examples: Time series cross-validation 4: forecasting the S&P 500 Holt-Winters forecast using ggplot2 Autoplot: Graphical Methods with ggplot2 Large-Scale Parallel Statistical Forecasting Computations in R (2011) by M. Stokely, F. Rohani, E. Tassone Forecasting time ... [Read more...]

In my last post, Factor Attribution to improve performance of the 1-Month Reversal Strategy, I discussed how Factor Attribution can be used to boost performance of the 1-Month Reversal Strategy. Today I want to dig a little dipper and examine this strategy for each sector and also run a sector-neutral ... [Read more...]

Today I want to show how to use Factor Attribution to boost performance of the 1-Month Reversal Strategy. The Short-Term Residual Reversal by D. Blitz, J. Huij, S. Lansdorp, M. Verbeek (2011) paper presents the idea and discusses the results as applied to US stock market since 1929. To improve 1-Month Reversal ... [Read more...]

Today I want to show a simple example of the 1-Month Reversal Strategy. Each month we will buy 20% of loosers and short sell 20% of winners from the S&P 500 index. The loosers and winners are measured by prior 1-Month returns. I will use this post to set the stage for ... [Read more...]

In the prior post, Factor Attribution 2, I have shown how Factor Attribution can be applied to decompose fund’s returns in to Market, Capitalization, and Value factors, the “three-factor model” of Fama and French. Today, I want to show you a different application of Factor Attribution. First, let’s run ... [Read more...]

I want to continue with Factor Attribution theme that I presented in the Factor Attribution post. I have re-organized the code logic into the following 4 functions: factor.rolling.regression – Factor Attribution over given rolling window factor.rolling.regression.detail.plot – detail time-series plot and histogram for each factor factor.rolling.... [Read more...]

I came across a very descriptive visualization of the Factor Attribution that I will replicate today. There is the Three Factor Rolling Regression Viewer at the mas financial tools web site that performs rolling window Factor Analysis of the “three-factor model” of Fama and French. The factor returns are available ... [Read more...]

I have discussed Volatility Position Sizing in the Volatility Position Sizing to improve Risk Adjusted Performance post using the Average True Range (ATR) as a measure of Volatility. Today I want show how to use historical volatility to adjust portfolio leverage. Let’s start with Buy and Hold strategy using ... [Read more...]

Today I want to examine the performance of stocks in the S&P 500 grouped into Quantiles based on one year historical Volatility. The idea is very simple: each week we will form Volatility Quantiles portfolios by grouping stocks in the S&P 500 into Quantiles using one year historical Volatility. Next ... [Read more...]

In the last post, Classical Technical Patterns, I discussed the algorithm and pattern definitions presented in the Foundations of Technical Analysis by A. Lo, H. Mamaysky, J. Wang (2000) paper. Today, I want to check how different patterns performed historically using SPY. I will follow the rolling window procedure discussed on ... [Read more...]

In my presentation about Seasonality Analysis and Pattern Matching at the R/Finance conference, I used examples that I have previously covered in my blog: Month of the Year Seasonality – I introduced the Seasonality charts in the Historical Seasonality Analysis: What company in DOW 30 is likely to do well in ... [Read more...]