I recently came across the Kaeppel’s Sector Seasonality Strategy which is described in Kaeppel’s Corner: Sector Seasonality and updated in Kaeppel’s Corner: Get Me Back, Clarence. Today I want to show how to back-test the Kaeppel’s Sector Seasonality Strategy using the Systematic Investor Toolbox. Following are ... [Read more...]

Today I want to share and present an example of the flexible Stop Loss functionality that I added to the Systematic Investor Toolbox. Let’s examine a simple Moving Average Crossover strategy: Buy is triggered once fast moving average crosses above the slow moving average Sell is triggered once fast ... [Read more...]

I came across the link to the John Ehlers paper: Predictive Indicators for Effective Trading Strategies, while reading the Dekalog Blog. John Ehlers offers a different way to smooth prices and incorporate the new filter into the oscillator construction. Fortunately, the EasyLanguage code was also provided and i was able ... [Read more...]

One of the important steps of evaluating new trading idea or strategy is to see how it behaved historically (i.e. create back-test and examine the equity curve in different economic and market conditions) However, creating a long back-test is usually problematic because most ETFs do not have a long ... [Read more...]

I showed an example of Extending Commodity time series back in 2012. Since then, the web site that I used to get the Thomson Reuters/Jefferies CRB Index data is no longer working. But there are a few alternatives: Thomson Reuters / Jefferies CRB Index. To get data, first select “TRJ/CRB ... [Read more...]

Historical Stock Data is critical for testing your investment strategies. I illustrated all my back-test examples with getSymbols function from quantmod package. For example, following is a back-test comparison for a few portfolio allocation methods: The getSymbols function, from quantmod package, downloads historical stock prices from Yahoo Fiance. I often ... [Read more...]

I have just returned from the R/Finance conference and want to share with you my slides and examples. The Cluster Risk Parity portfolio allocation method is an example of Cluster Portfolio Allocation methods that focuses on diversification or more specifically diversification of your risk bets. (i.e. portfolio that ... [Read more...]

Today, I want to share the Retirement : simulating wealth with random returns, inflation and withdrawals – Shiny web application (code at GitHub). This application was developed and contributed by Pierre Chretien, I only made minor updates. This is application is a great example of how easy it is to convert your ... [Read more...]

Maximum Sharpe Portfolio or Tangency Portfolio is a portfolio on the efficient frontier at the point where line drawn from the point (0, risk-free rate) is tangent to the efficient frontier. There is a great discussion about Maximum Sharpe Portfolio or Tangency Portfolio at quadprog optimization question. In general case, finding ... [Read more...]

In the Cluster Portfolio Allocation post, I have outlined the 3 steps to construct Cluster Risk Parity portfolio. At each rebalancing period: Create Clusters Allocate funds within each Cluster using Risk Parity Allocate funds across all Clusters using Risk Parity I created a helper function distribute.weights() function in strategy.r ... [Read more...]

Today, I want to share the Sector Rotation Back Test application (code at GitHub). This is the last application in the series of examples (I have shared 5 examples) that will demonstrate the amazing Shiny framework and Systematic Investor Toolbox to analyze stocks, make back-tests, and create summary reports. The motivation ... [Read more...]

Today, I want to share the Market Filter Back Test application (code at GitHub). This is the forth application in the series of examples (I plan to share 5 examples) that will demonstrate the amazing Shiny framework and Systematic Investor Toolbox to analyze stocks, make back-tests, and create summary reports. The ... [Read more...]

Today, I want to share the January Seasonality application (code at GitHub). This example is based on the An Example of Seasonality Analysis post. This is the third application in the series of examples (I plan to share 5 examples) that will demonstrate the amazing Shiny framework and Systematic Investor Toolbox ... [Read more...]

Today, I want to share the Multiple Stocks Plot application (code at GitHub). This is the second application in the series of examples (I plan to share 5 examples) that will demonstrate the amazing Shiny framework and Systematic Investor Toolbox to analyze stocks, make back-tests, and create summary reports. The motivation ... [Read more...]

Today, I want to share the Single Stock Plot application (code at GitHub). This is the first application in the series of examples (I plan to share 5 examples) that will demonstrate the amazing Shiny framework and Systematic Investor Toolbox to analyze stocks, make back-tests, and create summary reports. The motivation ... [Read more...]

Today, I want to continue with clustering theme and show how the portfolio weights are determined in the Cluster Portfolio Allocation method. One example of the Cluster Portfolio Allocation method is Cluster Risk Parity (Varadi, Kapler, 2012). The Cluster Portfolio Allocation method has 3 steps: Create Clusters Allocate funds within each Cluster ... [Read more...]

In the Tracking Number of Historical Clusters post, I looked at how 3 different methods were able to identify clusters across the 10 major asset universe. Today, I want to share the impact of clustering on the larger universe. Below I examined the historical time series of number of clusters in the ... [Read more...]

Today, I want to demonstrate how easy it is to create a seasonality analysis study and produce a sample summary report. As an example study, I will use S&P Annual Performance After a Big January post by Avondale Asset Management. The first step is to load historical prices and ... [Read more...]

In the prior post, Optimal number of clusters, we looked at methods of selecting number of clusters. Today, I want to continue with clustering theme and show historical Number of Clusters time series using these methods. In particular, I will look at the following methods of selecting optimal number of ... [Read more...]

Michael Johnston at the ETF Database shared a very interesting post with me over the holidays. The S&P 500 Visual History – is an interactive post that shows the top 10 components in the S&P 500 each year, going back to 1980. On a different note, Judson Bishop contributed a plota.recession() function ... [Read more...]