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FIND AMAZING TRADING STRATEGIES, OR TEST YOUR OWN WITH SIGNALSOLVER

When you are looking for trading strategies for stocks, ETFs and mutual funds, a logical place to start is to know what worked in the past. SignalSolver helps you with that. Type in a stock, ETF or mutual fund symbol and SignalSolver downloads historic price data then backtests it to find buy-sell signals and trading strategies that gave good results. It is quite simple to use and can load monthly, weekly or daily stock price data. The trading strategies it finds are often simple price action based techniques that you won't find elsewhere. But while it is very good at finding exploits based on historic data, profitability moving forward is never guaranteed. Backtesting cannot predict future prices. SignalSolver is an unlocked, digitally signed VBA application wrapped in an unprotected Excel workbook, so you can easily add functionality for your own needs.

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SIGNALS POSTED RECENTLY

The MASC BAO Trading Strategy

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 […]

AMZN top 4 algorithms day by day

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 […]

AAPL $31,000,000 trading strategy, equity curve

AAPL $31,000,000 Algorithm

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 which  amounts to over six times better reward/risk than buy-hold. This is a variation […]

Multi-algorithm test results for NUGT (4 algorithms)

Multi-algorithm study results for NUGT DUST and X

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. […]

Multi-algorithm results for UWTI

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 […]

Multi-algorithm analysis for FB (Facebook)

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 […]

Multi-algorithm tests for AMZN

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 […]

Preliminary results of multi-algorithm testing

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 […]