## Testing setup: Risk/Reward

I believe any tradeable edge should find trades that quickly become profitable. However, there are many ways to make money. We should also evaluate a strategy based on its risk/reward profile. A strategy may not be profitable 3 or 5 bars into the future like we have been testing, but may still signify a turning point with low risk. Before evaluating strategies based on risk/reward we have to establish a baseline to eliminate bias in our data set.

In this article, we will once again be running random simulations. We will use a 1:2 risk:reward ratio. Entries will be random based on the target number of trades (500,1500,5000). The strategy will set a profit target 3 *ATR(14) above the closing price and a stop loss 1.5 * ATR(14) below the closing price. The strategy will exit when the first target is hit or end of the day. Whichever comes first. After 100 random simulations we will then average all of the results and produce targets like we did in this article: Testing Setup

**Baseline Results for 5,000 trades (Long):**

Percent Profitable: 34.18%

Expected Return: -$29,377

Target Percent: 36.86%

Target Return: +$38,493

**Baseline Results for 1,500 trades (Long):**

Percent Profitable: 34.37%

Expected Return: -$8,587

Target Percent: 40.79%

Target Return: +$36,331

**Baseline Results for 500 trades (Long):**

Percent Profitable: 34.73%

Expected Return: -$1,886

Target Percent: 45.54%

Target Return: +$26,455

Now we will perform the same simulations to determine the bias for short trades. We are still using a 1:2 risk/reward ratio.

**Baseline Results for 5,000 trades (Short):**

Percent Profitable: 32.23%

Expected Return: -$34,763

Target Percent: 34.8%

Target Return: +$33,439

**Baseline Results for 1,500 trades (Short):**

Percent Profitable: 31.98%

Expected Return: -$11,147

Target Percent: 37.69%

Target Return: +$32,599

**Baseline Results for 500 trades (Short):**

Percent Profitable: 31.58%

Expected Return: -$4,478

Target Percent: 40.94%

Target Return: +$21,362

Based on these results it is very clear that using a 1:2 risk/reward ratio requires a great entry. I believe the random entries fared so poorly due to all of the noise in the markets. This should serve as a good indicator when comparing edges.

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## DOW 30 Baseline (Long Only)

As we continue to explore trading methods, we will need a way to compare our results to other markets. Below are the baseline figures for each of the 30 DOW components.

**NOTE: **I started with just 15,000 trades and 5 bars initially as these are the results relevant to the strategies I am currently testing. The remaining baseline values will be updated as we continue testing and need the results.

**15,000 Trades – 5 Bars (Long Only)**

**AA**

Percent Profitable: 52.35%

Expected Return: -$25.92

Target Percent: 54.14%

Target Return: +$34.17

**AXP**

Percent Profitable: 51.59%

Expected Return: -$5.02

Target Percent: 53.41%

Target Return: +$77

**BA**

Percent Profitable: 52.19%

Expected Return: -$4.89

Target Percent: 53.8%

Target Return: +$93.36

**BAC**

Percent Profitable: 52.45%

Expected Return: +$12.12

Target Percent: 54.29%

Target Return: +$99.14

**CAT**

Percent Profitable: 52.12%

Expected Return: +$16.57

Target Percent: 53.9%

Target Return: +$129.27

**CSCO**

Percent Profitable: 53.07%

Expected Return: -$13.07

Target Percent: 54.84%

Target Return: +$33.04

**CVX**

Percent Profitable: 51.97%

Expected Return: +$9.15

Target Percent: 53.82%

Target Return: +$116

**DD**

Percent Profitable: 52.29%

Expected Return: -$4.24

Target Percent: 54.11%

Target Return: +$67.23

**DIS**

Percent Profitable: 53.84%

Expected Return: +$9.88

Target Percent: 55.8%

Target Return: +$61.68

**GE**

Percent Profitable: 52.14%

Expected Return: -$18.58

Target Percent: 54.12%

Target Return: +$31.94

**HD**

Percent Profitable: 52.12%

Expected Return: -$10.14

Target Percent: 53.75%

Target Return: +$57.14

**HPQ**

Percent Profitable: 53.73%

Expected Return: +$25.61

Target Percent: 55.68%

Target Return: +$94.37

**IBM**

Percent Profitable: 51.34%

Expected Return: +$28.61

Target Percent: 53.23%

Target Return: +$185.3

**INTC**

Percent Profitable: 52.83%

Expected Return: -$6.83

Target Percent: 54.96%

Target Return: +$50.88

**JNJ**

Percent Profitable: 51.73%

Expected Return: +$4.5

Target Percent: 53.47%

Target Return: +$77.85

**JPM**

Percent Profitable: 52.26%

Expected Return: -$.16

Target Percent: 54.11%

Target Return: +$88.05

**KFT**

Percent Profitable: 54.4%

Expected Return: +$11.26

Target Percent: 56.22%

Target Return: +$52.33

**KO**

Percent Profitable: 53.4%

Expected Return: +$19.82

Target Percent: 55.28%

Target Return: +$96.66

**MCD**

Percent Profitable: 52.23%

Expected Return: +$15.27

Target Percent: 55%

Target Return: +$74.2

**MMM**

Percent Profitable: 51.14%

Expected Return: +$1.98

Target Percent: 52.86%

Target Return: +$127.42

**MRK**

Percent Profitable: 52.07%

Expected Return: -$9.47

Target Percent: 54.05%

Target Return: +$75.55

**MSFT**

Percent Profitable: 53.02%

Expected Return: -$3.09

Target Percent: 54.96%

Target Return: +$77.03

**PFE**

Percent Profitable: 52.87%

Expected Return: -$16.74

Target Percent: 54.74%

Target Return: +$26.48

**PG**

Percent Profitable: 52.77%

Expected Return: +$32.26

Target Percent: 54.41%

Target Return: +$112.04

**T**

Percent Profitable: 53.01%

Expected Return: -$6.74

Target Percent: 54.8%

Target Return: +$56.14

**TRV**

Percent Profitable: 51.4%

Expected Return: -$2.12

Target Percent: 54.74%

Target Return: +$65.6

**UTX**

Percent Profitable: 51.39%

Expected Return: -$3.14

Target Percent: 53.18%

Target Return: +$93.14

**VZ**

Percent Profitable: 52.63%

Expected Return: -$4.41

Target Percent: 54.3%

Target Return: +$59.05

**WMT**

Percent Profitable: 52.01%

Expected Return: -$13.17

Target Percent: 53.16%

Target Return: +$58.17

**XOM**

Percent Profitable: 52.36%

Expected Return: +$10.13

Target Percent: 54.22%

Target Return: +$108.32

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## How reliable are the targets?

Before going much further, we need to determine if our targets are sufficient at removing random chance from the equation. I will run 10,000 simulations targeting 500 trades and 10,000 simulations targeting 15,000 trades. If any random simulation is able to exceed our target percent or target profit, then the values are not reliable enough. However, if 10,000 simulations are not enough to produce a value exceeding our targets, then I am satisfied. With enough simulations any target could be achieved, but we have to have realistic goals.

**Results for 10,000 Simulations targeting 500 trades (3 bars into future):**

No simulations were able to exceed either target profit nor target percent. 51 simulations were able to exceed 60%, but the closest any came was 62%. This is well below the 64.04% that we target. Five simulations were able to surpass +$7,000 but none came close to the +$10,000 target.

**Results for 10,000 Simulations targeting 15000 trades (3 bars into future):**

No simulations were able to exceed either target profit nor target percent. Several simulations got close but were unable to exceed targets. Because the target percentage is a lot smaller for 15,000 trades than 500 trades the safety margin appears small. However, I feel confident enough in these targets to consider anything that exceeds them to not be due to random chance.

**Concerns:**

My Primary concern while evaluating both the long and short baselines stem from the fact that both long and short trades have > 50% winning percentages. I was unable to reconcile how this could be possible. However, after evaluating trade by trade, I finally realized that NinjaTrader counts profit zero as a win. What happens is both the long and short simulations contain several trades that end flat. This inflates the winning % of both directions.

While evaluating these indicators we are not including commission or slippage. If we had, those flat trades would actually be losses and the winning % of both directions would go down. Since neither the evaluation of the strategies or the original baselines contained slippage/commissions all results obtained should still be valid. Once we attempt to create an actual strategy using what we learn we will include commission/slippage and will need to recalculate baselines accordingly.

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## 5 Minute Testing Procedure (Short Only)

We have already established a baseline for Long trades. Now we need to do the same thing on the short side. When comparing methods, some may behave differently when shorting than when going long. The target will be any method that can predict market direction (5) standard deviations above the baseline average. We will establish baselines for both percent profitable and expected return per contract.

To establish a baseline we will run 100 random entry simulations against the target market. Because we do not know ahead of time the target trading frequency, we have to perform this test several times using various random rules. We will target 15,000 trades, 5,000 trades, 1,500 trades, and 500 trades over the sample period. The simulations aim to predict the market direction 3, and 5 bars into the future. We will be using a target market of ES Futures.

The strategies will not enter trades after 2:05 PM or before 8:30 AM. This ensures all exits are at the appropriate number of bars.

**Baseline Results for 3 Bars into the future targeting 15,000 trades:**

Percent Profitable: 53.96%

Expected Return: +$5,345

Target Percent: 55.88%

Target Return: +$68,377

**Baseline Results for 5 Bars into the future targeting 15,000 trades:**

Percent Profitable: 52.54%

Expected Return: +$8,939

Target Percent: 54.12%

Target Return: +$70,660

**Baseline Results for 3 Bars into the future targeting 5,000 trades:**

Percent Profitable: 53.85%

Expected Return: +$380

Target Percent: 57.07%

Target Return: +$32,217

**Baseline Results for 5 Bars into the future targeting 5,000 trades:**

Percent Profitable: 52.67%

Expected Return: +$2,403

Target Percent: 55.97%

Target Return: +$44,050

**Baseline Results for 3 Bars into the future targeting 1,500 trades:**

Percent Profitable: 54.01%

Expected Return: +3,32

Target Percent: 60.17%

Target Return: +$19,144

**Baseline Results for 5 Bars into the future targeting 1,500 trades:**

Percent Profitable: 52.65%

Expected Return: +1,380

Target Percent: 58.98%

Target Return: +$25,199

**Baseline Results for 3 Bars into the future targeting 500 trades:**

Percent Profitable: 53.93%

Expected Return: +$179

Target Percent: 64.24%

Target Return: +$9,766

**Baseline Results for 5 Bars into the future targeting 500 trades:**

Percent Profitable: 52.73%

Expected Return: +$573

Target Percent: 63.92%

Target Return: +$16,306

These results show a different pattern than the long trades showed. When going long the expected return in most simulations were negative. The expected return on the short side is positive. Since all trades are for a pre-set number of bars, you could conclude from these results that the market moves down faster than it moves up.

**Source Code:**

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## 5-Minute Testing Procedures (Long Only)

Our initial focus is not to discover a profitable strategy. Instead, we aim to discover methods that can reliability tilt the odds in our favor. The target will be any method that can predict market direction (5) standard deviations above the baseline average. We will establish baselines for both percent profitable and expected return per contract.

To establish a baseline we will run 100 random entry simulations against the target market. Because we do not know ahead of time the target trading frequency, we have to perform this test several times using various random rules. We will target 15,000 trades, 5,000 trades, 1,500 trades, and 500 trades over the sample period. The simulations aim to predict the market direction 3, and 5 bars into the future. We will be using a target market of ES Futures.

The strategies will not enter trades after 2:05 PM or before 8:30 AM. This ensures all exits are at the appropriate number of bars.

**Baseline Results for 3 Bars into the future targeting 15,000 trades:**

Percent Profitable: 54.21%

Expected Return: -$4,048

Target Percent: 56.1%

Target Return: +$47,248

**Baseline Results for 5 Bars into the future targeting 15,000 trades:**

Percent Profitable: 53.27%

Expected Return: -$6,435

Target Percent: 55.17%

Target Return: +$56,325

**Baseline Results for 3 Bars into the future targeting 5,000 trades:**

Percent Profitable: 54.18%

Expected Return: -$2,009

Target Percent: 56.52%

Target Return: +$23,900

**Baseline Results for 5 Bars into the future targeting 5,000 trades:**

Percent Profitable: 53.31%

Expected Return: -$2,900

Target Percent: 56.24%

Target Return: +$37,468

**Baseline Results for 3 Bars into the future targeting 1,500 trades:**

Percent Profitable: 54.32%

Expected Return: -$455

Target Percent: 59.2%

Target Return: +$17,490

**Baseline Results for 5 Bars into the future targeting 1,500 trades:**

Percent Profitable: 53.35%

Expected Return: -$1,080

Target Percent: 59.14%

Target Return: +$22,699

**Baseline Results for 3 Bars into the future targeting 500 trades:**

Percent Profitable: 53.91%

Expected Return: -$367

Target Percent: 64.04%

Target Return: +$10,081

**Baseline Results for 5 Bars into the future targeting 500 trades:**

Percent Profitable: 53.30%

Expected Return: -$173

Target Percent: 64.86%

Target Return: +$16,000

Based on these results, its evident that the sample period has a slight positive bias. Averaging around 54% profitable trades. However, the sample period has a negative profit expectancy of around -$.30 per trade. As you can see, the more trades we do the less variation and the lower threshold we need to cross to be considered “not random”. However, when targeting only 500 trades in the sample period a method will need to be nearly 65% profitable to rule out randomness.

**Source Code:
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## The Testing Environment

Our research can only be as accurate as the data used. To help ensure accuracy, all testing will be performed on data provided by e-signal. We are looking to thoroughly test indicators and strategies, not re-invent the wheel. Therefore, we will be using NinjaTrader 7 for all backtesting.

Most published results will be based on ES futures. However, to increase sample size we will also utilize a basket of DOW stocks for optimization and to also test how robust a method actually is. A method that works great on the ES, but fails miserably when tried on other stocks is generally the product of curve fitting.

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