Excel Based Tools and Services
At Algorithm Science we offer a variety of tools for gathering data from the internet and analyzing it. Here, you can find tools for extracting data from JSON (Java Script Object Notation) streams which is rapidly evolving as the new data standard on the web. We have JSON extractors for all kinds of financial information including historical stock price data, balance sheets, option chains, portfolio information. We also have a tool for searching news. These tools use a framework called JeX which greatly simplifies the process for JSON extraction and we are pleased to offer the JeX framework as a technological innovation which our customers can use to do their own JSON extraction.
Here, you can also find SignalSolver, our flagship product, which back-tests price history and exposes buy and sell signals which would have exploited these price movements. From time to time, we publish the signals we have found, and a few are presented in the sections below.
In support of legacy financial spreadsheets, we also offer EmulateURL, a product which emulates the now defunct Yahoo! Finance URLs which provided historical price, dividend and split data, consequently we are able to give such spreadsheets new life.
SIGNALS POSTED RECENTLY
The MASC BAO trading strategy frequently shows up in the top ten backtests. It has the distinction of being the strategy used in the most profitable backtest SignalSolver has ever found–AAPL Monthly MASC BAO which would have generated over $400 Billion from $10,000 invested. Here we look for MASC BAO strategies which beat Buy/Hold for […]
The out of sample multi-algorithm approach was quite successful for AMZN (see results) so lets do it live and see how it ends up. On Dec 21st, I did the optimization using the EMA band and Figure of merit optimization I have been talking about in the last few posts. For the next 25 trading […]
This AAPL trading strategy would have given a return of $31,712,009 for every dollar invested in December 1980. That’s 123,000 times better than buy-hold, with nearly four times the annualized return (61.4% vs 16.7% for buy-hold) and roughly half the drawdown whichÂ amounts to over six times better reward/risk than buy-hold. This is a variation […]
In the interests of scientific method, I’d like to continue the multi-algorithm study by discussing the worst results, those for X (United States Steel Corp. ), NUGT(Direxion Daily Gold Miners Bull 3X ETF) and DUST(Direxion Daily Gold Miners Bear 3X ETF). There was plenty of potential for disaster in these stocks, very large swings indeed. […]
Oil had a rocky year, lets look at how our multi-algorithm approach worked on an oil related stock, UWTI (VelocityShares 3x Long Crude Oil ETN). In this post, I’m just going to summarize the results:Briefly, the method used is to run SignalSolver to find trading systems which worked for a 250 day period, then run […]
Today, I’ll just throw out some more results from the multi-algorithmic testing I’ve been doing with SignalSolver. This time for Facebook (symbol FB). This is a stock which moved a lot in the time-frames used in the study. Could SignalSolver correctly predict and capitalize on these price movements? Let’s see… As described in the methodology […]
Today I will be looking at some very interesting results of multi-algorithm testing on the stock AMZN (Amazon). The idea here is to use SignalSolver to find multiple trading systems which performed well in the past, then run those systems simultaneously on out-of-sample forward data to see what would have happened had you followed them […]
The portfolio and methodology for this multi algorithm study are described in my previous post. Here are links to the results spreadsheets:EMA/Figure of merit optimization periods: Sept 2014-15 Jan 2014-15 June 2015-16PB/Return optimization period: Jun 2015-16On these spreadsheets you can use the autofilter to include and exclude stocks of interest. For any stock you can […]