Bitcoin trader thenn, A Guide to Trading Cryptocurrency Part 7: Linear Regression | BTCMANAGER

In this trading guide, we will introduce you to a useful concept that can be used for trading, amongst other things.

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Linear regression is a simple, easy-to-use strategy that can be utilized to identify entry and exit points based on the price action of the cryptocurrency.

What is a Linear Regression?

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A linear regression is a mathematical method used to capture the determination of a specific variable. We want to know what factors determine the price of bitcoin.

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A linear regression can be modeled. The parameter b basically tell us the relationship between the past and current price of bitcoin.

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The parameter e captures all other variables effect on price and is known as the residual. Of course, this model can be extended to bitcoin trader thenn as many time periods as you like.

We could go even further and add other variables if we wanted to.

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Using various diagnostics, we can assess the fit of the model to the data and forecast based on this model. For each time period, we would simply update the data, run the model again and produce a new forecast. HOwever, this is no crystal ball, and the purpose is not to obtain a point forecast. Instead, we obtain an estimate such that we can map out the possible underlying values based on the estimate we have made and accounting for standard errors, known as a confidence interval.

As for the confidence interval, we can think of it visually as a normal distribution. The middle of the shape above would be our estimate and provided we have good enough estimators, the true value of the relationship we are estimating bitcoin trader thenn lie somewhere in the bell-shaped curve. Return to the mean Another interesting thing to note is that most financial time series data have a property known as a unit root.

It basically means the variable exhibits a behavior known as mean reversion.

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We will see in the next section how mean bitcoin trader thenn is relevant to the linear regression trading indicator. We can visually represent a linear regression similar to the example outlined above on charts such as TradingView. See below for the linear regression for bitcoin on the daily timeframe.

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The author prefers to use Fibonacci numbers and usually the 89 and for long-term view on the weekly outlook, bitcoin trader thenn you can also use lower numbers on lower timeframes for smaller trends. The higher, the better, since you capture more of the data available, but requires more patience to act upon.

In the chart above, we have used bitcoin trader thenn, so 89 periods are included in the regression sample to provide an estimate. The mean — or expected value — is bitcoin trader thenn by the line in the middle.

In 89 periods, the price has bobbed toward and away from the mean exchange pm la btc times. Once a support or resistance breaks, we should not fight against the market, but flow with it. As shown above, we can see clear sell signals in mid-February and early March, but a word of caution is here. For instance, we see that the price on March 4 closed above the zone highlighted by the indicator and was also a hanging man candlestick patternso indicating to sell.

However, the downtrend in bitcoin has been going on since Decembermore than three months and the period regression shows a downward trend. It could be that the price of bitcoin breaks out of the channel illustrated above, in which case we should revert to a different period for the regression or a different timeframe and best capture the shorter-term trend.

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For instance, bitcoin trader thenn we believe the downward channel will be broken. We can draw a new linear regression on the chart by changing the timeframe in one of two ways; change the period or change the timeframe. The chart below changes from daily to 4-hour price action and where the channel indicates to sell is much higher as with the places to buy. Of course, this is assuming the current trend holds.

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In essence, we have to find the current structure of the market, monitor and eye our buy and sell zones. Linear regression is based on extrapolation — meaning it is based on the historical price action. It should be obvious that past patterns are not necessarily repeated in the future.

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As with all trading indicators, using them on their own may give you some insight into the true behavior of markets, but you are more likely to succeed when combining synergistic indicators; for example, one based on price action, one based on momentum, one based sistemul de tranzacționare bitcoin pe rezervorul de rechin volume, etc.

In the next section, we will show you what indicators work best with Linear Regression. Therefore, we would like such additional indicators to enhance and confirm our signals.

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It does nothing more than providing a signal saying — you need to buy or sell in this session! The Parabolic SAR is represented by a dot. Say it is above the price action, and then you bitcoin trader thenn it moves now to below the price action, we have a buy signal, and vice versa for a sell signal. When combined with the Linear Regression indicator, both signals can help reinforce each other.

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While both can be used to provide an entry, Linear regression will be more useful in planning an exit. Volume Finally, volume is an important indicator that should be included in any trading strategy.

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Volume precedes price action, meaning changes in volume are key in determining future trends of the price of a cryptocurrency. The chart below shows how these pieces come together. The price has been around the mean for some time, suggesting bitcoin could be propelled further upward.

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On April 5, the market for AEON-BTC is illustrated below, and you see the price had already touched the -2 standard deviation, motivating an entry into a long position. In part, it depends on the date.

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In the chart above, we see that 0. Finally, another exit point could be near the high 0. Of course, the trend could be broken and force the linear regression to have a smaller gradient or an even higher one so that the channel changes its direction, so these charts need to be monitored every week to adjust your exit positions or find new entries.

For instance, a move above the -1 standard deviation line would prompt another long entry, as would a move above the mean. Summary In summary, the linear regression is a trading indicator allowing you to time entries and exit on cryptocurrencies.

It does not tell you anything about momentum or volume, so ensure you use it with indicators measuring these aspects of the market.

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