Linear Regression Binary Options Strategy

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Strategy of linear regression

In previous articles in the section “Forex Strategy” I discussed the use of simple indicators, which are popular among beginners: stochastic, relative strength index (RSI), moving averages. Today I will give an example of a more professional use of indicators that together indicate good entry points in the market.

Three indicators of strategy for linear regression

The current strategy of the linear regression is based on three indicators, one of which you already know:

  • Linear Regression indicator, which clearly shows a price channel on a given trader timeframe. Visually shows the direction of price chart and on builds a channel on points that allows you to see the moment of position opening. Green – uptrend, red – falling down;
  • Xaser FV – index of market volatility. A zero value indicates flat horizontal price movement. Its growth suggests that the market begins to move, reducing movement in the market coming to an end;
  • RSI – relative strength index trend showing probabilistic reversal points of the price chart.

The values of indicators, which are suitable for the strategy of linear regression:

  1. Linear Regression:
  • TimeFrame = Current Time Frame (4 hours, chosen by us);
  • LrsPeriod = 40 (the period for calculating the indicator values);
  • Price = 0 (after the closure);
  • MultiColor = True (different colors of the indicator).
  1. Xaser FV:
  • Xaser Period = 14 (the indicator calculation period);
  • Flat_Period = 0 (the calculation period of a flat);
  • the other parameters by
  1. RSI:
  • Period 14;
  • Apply to Close;
  • Levels 30, 50, 70.

Trade terms of strategy of classical linear regression: use the MetaTrader 4 trading terminal where you can always easy and fast to download any indicator or to write your own. Currency pair – classic: EUR / USD, the timeframe is 4 hours.

Conditions for opening long positions. The entry point is the next candle to which the following conditions are met:

  • Linear Regression changed color from red to green;
  • Xaser FV last 2-3 candles is at a zero value (therefore, the trend is growing), as well as before this indicator was at level 0 at least 3 bars;
  • RSI is above 50 level.

Stop-loss insured position at the level of 30-60 points. We leave from the position of the already known way: we get a profit of 30 points, close 50% position, the second half of the position insure a trailing stop (a floating order of 50 points.

Opening a short position is similar with mirror image Linear Regression (change color from green to red) and RSI (below 50 level). Trade is not conducted at the end of the week, with value Xaser FV to “0” and at the time of publication of news.

Linear Regression Line

Linear regression, when used in the context of technical analysis, is a method by which to determine the prevailing trend of the past X number of periods.

Unlike a moving average, which is curved and continually molded to conform to a particular transformation of price over the data range specified, a linear regression line is, as the name suggests, linear. It takes a certain number of user-defined periods and plots a linear line that best fits the general trend.

To clarify, it is not simply taking the current price and the price from X number of periods ago and drawing a line between the two. The activity in between the two points is every bit as critical.

For example, in the particular 50-day period in the S&P 500 below, the net gain of the market is positive. Yet the linear regression line is negatively sloped. This has to do with a strong down-move over the course of this period. Most forms of linear regression are based on the mean or average, which makes it sensitive to outliers. Since the mean price over this period was below where it currently stands, the linear regression line is negatively sloped.

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The shape of the linear regression line is simply designed to represent yet another way to track the market’s trend.

Conceptually, linear regression implies that it can predict how an output will change based on an input. In this case, it’s simply using previous price data to predict the general trend of future price data. This is, of course, a naïve assumption, but trends have a way of persisting over time until the information embedded in a market materially changes.

If we set the linear regression line to a 100-day period, we see the line markedly take a different shape:

For trend traders, this might present confusing signals to have the 50-day and 100-day regression lines be so profoundly different. Which one is more “correct”?

First, it is never recommended to use any given indicator in isolation. Being in buy/long trades when a X-period regression line is pointing up and sell/short trades when a X-period regression line is pointing down will not be a profitable trading strategy.

It should ideally be made to fit your trading timeframe. Those who trade with the intention of holding positions over the course of years might apply a 200-day linear regression line to a daily chart. Someone who holds positions minutes or hours might apply a 20-period linear regression line to a 5-minute chart.

If paired with a moving average, it would make sense to have them both be the same period for equal comparison’s sake. For example, here’s the linear regression line paired with a 50-period simple moving average (SMA).

If you’re a trend follower and trust the signals that the linear regression line and SMA give you on these particular periods, you’d probably pass on anything trend-related.

Examples of the Linear Regression Line Within a Broader System

The linear regression line can be relevant when identifying the trend within a larger trading system.

Many trading systems are based on the premise that once all indicators match up, a trade signal is thereby given in a particular direction.

For example, we could invent a trading system that involves trade entries based on trading with the trend according to a 100-period linear regression line and 100-period moving average.

With respect to price reversals, we can use Keltner channels. For Keltner channels, we’ll use 20-period bands and a 3x multiple of the average true range.

  1. Trade only with the trend, meaning both the 100-period linear regression line and 100-period moving average are in agreement.
  2. When the above rule is true, take long trades when price hits the bottom band of the Keltner channel. Likewise, when both the linear regression line and moving average are in agreement in a downtrending market, a touch of the upper band of the Keltner channel would be a signal to go short.
  3. To exit a trade, we can use either a shift in the trend – i.e., the slope of either the linear regression line or moving average changes (opposite the direction of the trade) – or a touch of the linear regression line.

Also note that backtesting this strategy is particular difficult given that the linear regression line changes shape continually. How and where it’s displayed on the chart currently is purely dependent on the market at the current moment, not where it was at some point in the past. The best you can do is infer on the basis of knowing how linear regression lines are made to fit a particular data set.

Example #1

Let’s see how this would have worked out on a daily chart of WTI crude oil:

Here we have one or two trade signals (shown through the two green arrows), depending on whether you’re willing to take the same setup more than once. We see both trend confirmation tools pointing up.

We ignore price’s touch of the top band on the way up as those trades would have gone opposite the trend. But we do get a touch of the bottom band twice. This presented a solid setup to take a long trade in the direction of the up-trend of the market.

Some trader’s might take just the initial touch and ignore the subsequent touch since it’s fundamentally the same trade idea. Moreover, it might constitute “doubling down” on a position and could make one’s book (i.e., current set of live/open trades) more concentrated and dependent on a certain outcome to profit.

The trade was exited upon a touch of the linear regression line (white line).

Example #2

Let’s apply it to a daily chart of the USD/SEK (US dollar versus the Swedish krona).

With this currency pair in a downtrend, we see confluence with a down-sloping 100-period linear regression line, down-sloping SMA, and touch of the upper band on the Keltner channel.

Based on the chart and our rules stipulated above, this trade would still be open if our close signal is a touch of the linear regression line. However, it would be closed if we were more flexible and extended it to a touch of the SMA or if we added a center line in the Keltner channel.

Conclusion

A linear regression line is an easy-to-read way of obtaining the general direction of price over a past specified period. Unlike a moving average, which bends to conform to its weighting input, a linear regression line works to best fit data into a straight line.

Linear regression lines will be more dependent on the period of the timeframe considered relative to moving averages. It’s rare that there will be wide dispersions in the general gradation of a moving average between, for example, 50 and 100 periods. There can, however, be a big difference between a 50-period linear regression line and a 100-period regression line.

Note the difference below.

50-period linear regression line + 50-period SMA

100-period linear regression line + 100-period SMA

A linear regression line should not be used a system itself. Rather it should be used in the context of a larger trading system – mechanical or otherwise – that uses other technical indicators, price, candlestick patterns, support and resistance levels, and/or fundamental analysis to improve the accuracy of trading decisions.

RSI and Regression Line Strategy – From Forex to Binary Options

Full Review of the RSI & Regression Line Binary Options Strategy

This strategy was created by a Forex trader, can it work for binary options trading? The strategy was originally posted on Forex-strategies-revealed.com by the author Mennzz. He uses RSI and regression lines to pick profitable entry points. The regression Line is also known as the Regression Curve indicator described in the article Linear Regression Curve Indicator. You can read it if you want but fortunately, this is a simple strategy so you are not required to understand how regressions are calculated. Just remember that the Regression Line is not the same as an EMA, even though they look very similar!

What is the RSI & Regression Line Strategy?

This strategy uses two indicators; the RSI, which is the common and well-known Relative Strength Index and the Regression Line Indicator. The latter can’t be found on MetaTrader 4 and has to be downloaded and installed manually, you will find the download file at the end of this review. Set RSI to period 7 and keep the 30 & 70 levels for oversold and overbought areas. For Linear Regression, the author recommends period 14. He also mentions that he achieved the best results trading the pairs USD/JPY and AUD/USD using daily charts. We look for call signals when RSI crosses from oversold level (30) up. The signal is confirmed if the current candlestick crosses above the regression line and closes above it. The opposite is true for put options. Look for RSI crosses from overbought level (70) coming down and confirm if a bearish candlestick has crossed below the Regression Line and closes below it. Mennzz claims that it is not always necessary to wait for RSI to completely cross 70/30 but it is safest to trade the crosses only.

Mennzz has marked with vertical lines 4 opportunities on this daily chart of USD/JPY. Green: Call and Red: Put.

The Signals:

Call Option: When RSI crosses level 30 from below and a bullish candlestick closes above the Regression Line.

Put Option: When RSI crosses level 70 from above and a bearish candlestick closes below the Regression Line.

Why does the RSI & Regression Line Strategy Suck?

The author warns us that occasionally the RSI will fake signals. It happens when RSI bounces either between 30-50 or 50-70. This could be during consolidations, a period of indecision during which this strategy might result in losing trades. RSI 7 rarely reaches oversold or overbought areas on higher time frames which is another issue the author alludes to. A downside that was not brought up by the Mennzz is that waiting for a candlestick to close in the desired direction could mean a retracement on the following candle. Leaving you out of the money right at the start.

Why doesn’t the RSI & Regression Line Strategy Suck?

This strategy uses two very strong indicators that are known to be accurate. It doesn’t overcrowd the charts and doesn’t confuse the trader with too many things to look for. It is newbie-friendly and can be traded in the direction of the trend. Thus, with simple trend analysis you can avoid most of the fake signals and if you apply the right money management can use this strategy on an on-going basis.

Conclusion – Yes to Higher Time frames

I like this strategy because the author states that it was tested live and points us in the right direction by letting us know which pairs that perform best. The charts are not overcrowded with arrows and indicators and relies only on the strong RSI and Regression Line. However, the Daily chart might not be the dream time frame for a binary options trader. It is no secret that we like shorter time frames for day trading therefore you have to test it on your own, on lower time frames. I can say from first glance that it looks like it will work fine. Later in the comments it was suggested to not go below H2 due to the increment of false signals but so long as you follow underlying trends and use good judgment you should be OK.

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