This strategy is equal to the very popular "ANN Strategy" coded by sirolf2009(1) which calculates the percentage difference of the daily close price, but this bar-bone version works completely without his Artificial Neural Network (ANN) part.
Main difference besides stripping out the ANN is that my version uses close prices instead of OHLC4 prices, because they perform better in backtesting. And the default threshold is set to 0 to keep it simple instead of 0.0014 with a larger step value of 0.001 instead of 0.0001. Just like the ANN strategy this strategy goes long if the close of the current day is larger than the close price of the last day. If the inverse logic is true, the strategy goes short (last close larger current close). (2)
This basic strategy does not have any stop loss or take profit money management logic. And I repeat, the credit for the fundamental code idea goes to sirolf2009.
(2) Because the multi-time-frame close of the current day is future data, meaning not available in live-trading (also described as repainting), is the reason why this strategy and the original "ANN Strategy" coded by sirolf2009 perform so excellent in backtesting.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact , if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
(1) You can get the original code by sirolf2009 including the ANN as indicator here:
(1) and this is sirolf2009's very popular strategy version of his ANN:
//@version=2 strategy("Daily Close Comparison Strategy (by ChartArt)", shorttitle="CA_-_Daily_Close_Strat", overlay=false) // ChartArt's Daily Close Comparison Strategy // // Version 1.0 // Idea by ChartArt on February 28, 2016. // // This strategy is equal to the very // popular "ANN Strategy" coded by sirolf2009, // but without the Artificial Neural Network (ANN). // // Main difference besides stripping out the ANN // is that I use close prices instead of OHLC4 prices. // And the default threshold is set to 0 instead of 0.0014 // with a step of 0.001 instead of 0.0001. // // This strategy goes long if the close of the current day // is larger than the close price of the last day. // If the inverse logic is true, the strategy // goes short (last close larger current close). // // This simple strategy does not have any // stop loss or take profit money management logic. // // List of my work: // https://www.tradingview.com/u/ChartArt/ // // __ __ ___ __ ___ // / ` |__| /\ |__) | /\ |__) | // \__, | | /~~\ | \ | /~~\ | \ | // // threshold = input(title="Price Difference Threshold", type=float, defval=0, step=0.001) getDiff() => yesterday=security(tickerid, 'D', close) today=security(tickerid, 'D', close) delta=today-yesterday percentage=delta/yesterday closeDiff = getDiff() buying = closeDiff > threshold ? true : closeDiff < -threshold ? false : buying hline(0, title="zero line") bgcolor(buying ? green : red, transp=25) plot(closeDiff, color=silver, style=area, transp=75) plot(closeDiff, color=aqua, title="prediction") longCondition = buying if (longCondition) strategy.entry("Long", strategy.long) shortCondition = buying != true if (shortCondition) strategy.entry("Short", strategy.short)
This is the only strategy I shared on Tradingview which repaints and which is why I warned so many times about this problem.
You can read more about the repainting issue of certain strategies when you go to this other strategy linked below:
(This other strategy below does not repaint by the way. It wins all the time by only closing trades when the targeted profit has been achieved. I just deemed it a good place to discuss this related issue of strategies which seem to work so great in backtesting)