RSI Stochastic with Bollinger Bands - forex market hours gmt.mq4

RSI Stochastic with Bollinger Bands ~ forex market hours gmt.mq4

The two indicators I will be using are Bollinger Bands and stochastic relative strength index (StochR SI ). StochRSI , which combines the features of stochastics and RSI , was

detailed in Tushar S. Chande and Stanley Kroll’s book, The New Technical Trader. I selected this combination because it is a useful way to determine when prices will stop tagging a Bollinger Band and are likely to move all the way from one band to the next. Of course, those prices may not move all the way, so you will need to use stops for protection. You will also want to use a simple money management strategy of allocating only a portion of your capital to any one position.

First, let’s take a look at R SI and StochRSI . Stochastics, you will recall, is simply a way of measuring, for a given period of time, where today’s close is relative to the lowest low, and where within the range of the highest high and lowest low the price falls over the same time period. The formula for stochastics for a 14-day period is:

Todaysclose– Lowestlowofthelast14 days/

Highesthighofthelast14 days– Lowestlowofthelast14 days

Note the use of range — high minus low — in the denominator of the calculation.

Many trading techniques and strategies are built around range in some form, and if you use several indicators, you want independent sources, so that the indicators independently confirm one another.

Independent confirmation is one part of Dow theory you should consider embracing. For example, Larry Williams’ %R is the reverse of stochastics, substituting the difference of highest high

over a given period minus today’s close for the numerator. So if you want to use this indicator together with stochastics, you are not using independent indicators.

Instead, you should consider using an indicator that does not involve a range, such as volume, or one that is statistical in nature, such as Bollinger Bands.

The next step is to identify the type of stock that will work best. If you are going to use an indicator that relies on price volatility such as StochR SI , then you should examine your charts to see the

nature of the current volatility. For example, I have used AOL Time Warner (AOL ) in Figure 1. What differentiates the four areas (A, B, C, and D) is the combination of price and volume

volatility. Area A has low price and high volume volatility. Area B has both high price and volume volatility. Area C has high price volatility, and low volume volatility for the stock.

Finally, area D has moderate volume and price volatility. A useful rule to remember is that a price is “in gear” — that is, in sync — if price goes up on high volume or down on lowered volume. Prices that reflect such moves are prices that the market is comfortable with. If you were long in area A or

short in area D, you would have done well. A trading system designed for areas A and D — “ingear” moves — is likely to have a terrible time in areas B and C. As you will discover shortly, AOL represents the good, the bad, the ugly, and the really ugly when it comes to using a trading system that only takes long positions.

IGURE 1: DAILY AO L PRICE AND VO LUME. Price volatility is less before June 1998. For indicators that use price volatility such as StochRSI, you want to use fewer periods in the calculation to generate trading signals than you would prior to June 1998.

Stochastic RSI VS RSI

RSI VS . STOCH RSI If you compare RSI and StochRSI measurements over a few months, you

will notice a difference: One of them will hit the extreme faster and tend to stay near the extreme better than the other. The formula for StochRSI for a 14-day period is:

RSI– LowestRSIoverthelast14 days/

HighestRSIoverthelast14 days– LowestRSIoverthelast14 days

If you build this indicator, of course, you can make the RSI use a 14-day period or you can, for example, make the RSI based on a nine day period and retain the 14 days for the stochastics portion. As you can see from Figure 2, StochRSI does a better job of hitting its extreme and staying there than R SI does. StochR SI allows you to draw a line that acts as a threshold line better than RSI (black lines drawn within green boxes). While bothRSI and StochRSI range between zero and one — although cosmetic adjustments are made to RSI so it appears to range between zero and 100 — StochRSI hits its extreme faster because you are only looking at the RSI over a recent lookback period. Still, there are times, as in April, when StochRSI gives you a mixed message.

This is where Bollinger Bands can help. If you overlay price with Bollinger Bands, as in Figure 3, you begin to get an idea of the setup for a long position:

Act when prices are tagging the lower band (point A) with a move up (point B), while StochRSI shows a significant gain in value (point C). However, this setup has potential problems for long trades; look at the red box in the chart. In April and May 2000, you have examples of prices tagging the lower band and then closing above. In one instance (event D), StochR SI would potentially give a confirming signal that you should go long, but then prices go back down to the lower band. This is an example of the problem I referred to earlier, that low volume is often

FIGURE 2: DAILY AO L PRICE AND VO LUME 2000 WITH RSI (TOP CHART) AND STOCHRSI (SECOND FROM TOP CHART). StochRSI not only responds quickly to price changes, but also hits its extreme and stays there better than RSI (see green boxes); 14-day periods are used for both RSI and StochRSI.

accompanied by randomness. Note that volume in late April and May is significantly lower than in the preceding time frame. I will try to incorporate some rules into the trading system to account for this, but in such a situation it is often best to exit and find another stock.

I will now execute a trading system, without stops and money management, to see what it can do. The trading system is going to have the following trading rules for a long position:

FIGURE 3: DAILY AOL AND VOLUME AND STOCHRSI (UPPER CHART): FEBRUARY/JUNE 2000. A 20-day, two standard deviation Bollinger Band is overlaid on the price chart. On the left hand side is a setup that promises to enter a long position. It starts with prices tagging the lower band, event A. Prices close above the lower band, event B, and at the same time StochRSI has moved up to a value of 0.4, event C. What is distressing is the action in the red box, especially in view of event D, a spike in StochRSI and a close above the lower band followed by a retreat of prices. But if you look at volume below, the problem mentioned earlier is obviously apparent: low volume giving you a random price movement.

Entry:

1 Look for prices tagging the lower Bollinger Band

2 Look for a closing price of an up day, that is (close>open), that is above the lower band after having prices follow (1)

3 Volume of this up day should be greater than the volume of the previous up day

4 StochR SI should be above a threshold to ensure some momentum is associated with the push up

5 The (close-open)/(high-low)>0.2, to avoid days that have short candlestick bodies.

Exit:

1 StochR SI should be less than a threshold to assure loss of momentum

2 Look for prices to reach the upper band

3 Closing price should be near the top Bollinger Band.

You are looking for the stock to continue up if it has been tagging a lower Bollinger Band and then made a convincing move up, so that it conforms to entry rules 2 through 5 above. I used weighted closes in calculating the Bollinger Bands:

(2*close+high+low)/4.

From Figure 4 you can see that investing $1,000 in 1997 and using this trading system without stops resulted in $58,000 (second chart from top), which beat buy/ hold by more than $47,000. However, there are serious drawdowns in each of the areas B, C, and D. The only factor that varied in this trading system was the number of periods for StochRSI and Bollinger Bands. When using the initial version of this system I optimized the StochR SI thresholds as well. The equity looked better in terms of drawdowns and ended up with $300,000+, which led me to believe that there might be something to this approach.

Optimizing on everything — from periods to thresholds — results in spectacular equity performance (Figure 5), and although it is curve-fitting, it shows the potential you are trying to

achieve. It also shows the trading system is biased to take advantage of strong

uptrends: During uptrends, prices that tag the bottom Bollinger Band will

FIGURE 4: DAILY AOL AND VOLUME WITH EQUITY PERFORMANCE. Starting with $1,000, a trading system that goes long using Bollinger Bands and StochRSI is seen to have four trading behaviors, as indicated by areas A, B, C, and D. Note the equity scales are X10. The second chart from the top is the equity performance without stops. In area

A, the system makes little money despite rising prices, breaks even in B, has a better performance in C, and then performs poorly during D. Even area C is not especially appealing because you are faced with serious drawdowns, unless you use stops (as seen in top chart). The top chart, using maximum stop-losses of 5%, provides better performance.

move to the upper band, resulting in a trading system that can do much better than buy and hold. But letting thresholds optimize curve-fits the performance too much, so I set the thresholds visually. To get rid of the serious drawdowns, I used maximum loss stops of 5%, which improved the equity performance (Figure 4: top chart). Still, area B just eats away at your equity, although it does appear I took care of the low volume problem in area C.

FIGURE 5: DAILY AOL AND VOLUME WITH EQUITY PERFO RMANCE FOR AREA A. A $1,000 equity investment reaches $45,000+, while buy and hold reaches $20,000+. While this kind of equity performance (top chart) is spectacular, it comes from letting all the variables in the trading system be optimized — curve-fitting. What this shows, however, is the potential of the system if the periods and thresholds are chosen correctly, along with the right (strong uptrend) price movement. It also reflects the bias of the trading system, which takes advantage of the fact that in a strong uptrend, prices that tag the lower Bollinger Band do so only briefly.

Reference :

Stocks and Commodities Developping a Trading System by Dennis Peterson.

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