“Lazy Trader” is popilat trading strategy that uses the Monday high and low breakout to define the entry points.
How to trade Lazy Traded?
A Trader should firstly define the highest and the lowest point of first 4 candles of the week. If price breaks the high of 4 candles + 50 pips buffer then a traded should open the buy trade. If price breaks the low of 4 candles – 50 pips buffer then a trader should open the sell trade.
To run a back-test we have coded a complete Lazy Trader trading strategy as a MetaTrader 4 Expert Advisor. During preliminary analysis we have identified that the best time frame for Lazy Trader trading strategy is 1 hour (H1).
We have run a back-test of Lazy Trader strategy. For our test as a trade exit rule we have used a Trailing Stop of 30 pips which is launched after a trade has started and is modified each new 1 pip of profit. From our point of view, such approach allows to maximize profit and minimize drawdown.
We have run the test for 2009.01.01-2020.04.21 using Every Tick modelling on USDJPY-H1, using 1:3 leverage, without reinvestment, assuming spread equals 10 ticks. These are the main parameters of Lazy Trader trading strategy performance at its non-optimized state:
|ROI||# of trades||Winning ratio||Max. drawdown|
Trading data analysis
After running the initial test of a simple non-filtered strategy we perform a trading data analysis that allows to identify possible filters to use to make the strategy more profitable reducing the drawdown simultaneously.
The following charts may give some possible insights on which filters to apply (time sessions, day of week limitation, trend strength threshold, overbought/oversold conditions, volatility range) to turn this strategy profitable should you decide to use this strategy in your investment portfolio:
Lazy Trader trading strategy can be used with other indicators to filter out losing trades and make entry signals more accurate. After analysing trading data we have found the following insights which have helped us to increase the profitability of Lazy Trader trading strategy and reduce it’s drawdown
- The majority of sell trades that were opened at boundary state of RSI were losing trades when trading “Lazy Trader” trading strategy during 2009 – 2020. The market is not stable at overbought and oversold zones.
(ROI increase -6% -> 0.7%, Drawdown reduction 64% -> 15%)
- Trades that were opened at a lower value of ADX brought more losses when trading “Lazy Trader” trading strategy during 2009 – 2020. The lower value of ADX shows that the trend has not yet stabilized.
(ROI increase -6% -> -1.3%, Drawdown reduction 64% -> 24%)
- The most profitable trades were opened at the middle value of DeMarker when trading “Lazy Trader” during 2009 – 2020. DeMarker aims to assess the directional bias of the market.
(ROI increase -6% -> 1.3%, Drawdown reduction 64% -> 16%)
We have analysed data received from a test of Lazy Trader trading strategy during 2009 — 2020 years and applied some filters such as RSI, ADX and Demarker. As a result, the profitability of the strategy has increased from -6.25% up to 3.92% and it’s drawdown has reduced from 64.41% to 5.62% using leverage 1:3.
Reducing the drawdown has allowed us to increase the leverage that can be used while trading this strategy up to 1:40, which in turn, has resulted in annualized ROI increase up to 52.3%!
Reducing the drawdown has also allowed us to use risk based lot calculation. Below you can see the back-test results using $10,000 initial balance and 7% risk per trade:
|ROI||# of trades||Winning ratio||Max. drawdown|
Analyze your trading strategy!
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Disclaimer: Hypothetical or Simulated performance results have certain limitations, unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not 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 profit or losses similar to those shown.
Past performance is not necessarily indicative of future results. The customer is responsible for using the product at his or her own risk and “Nordman Algorithms” is not responsible for any possible losses caused by use of the product, including but not limited to losses.