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6094

Abstract

nge(len(data)):

        try:
            
            <span class="hljs-class"><span class="hljs-keyword">data</span>[i, where] = (<span class="hljs-title">data</span>[<span class="hljs-title">i</span> - <span class="hljs-title">lookback</span> + 1:<span class="hljs-title">i</span> + 1, <span class="hljs-title">close</span>].<span class="hljs-title">mean</span>())</span>
        
        except <span class="hljs-type">IndexError</span>:
            
            pass
        
<span class="hljs-class"><span class="hljs-keyword">data</span> = jump(<span class="hljs-title">data</span>, <span class="hljs-title">lookback</span>)</span>

return <span class="hljs-class"><span class="hljs-keyword">data</span></span></pre></div><div id="0f03"><pre><span class="hljs-attribute">def</span> demarker(Data, lookback, high, low, where):

<span class="hljs-comment"># Calculating DeMAX</span>
<span class="hljs-attribute">for</span> i in range(len(Data)):
    
    <span class="hljs-attribute">if</span> Data[i, high] &gt; Data[i - <span class="hljs-number">1</span>, high]:
        <span class="hljs-attribute">Data</span>[i, where] = Data[i, high] - Data[i - <span class="hljs-number">1</span>, high]
    <span class="hljs-attribute">else</span>:
        <span class="hljs-attribute">Data</span>[i, where] = <span class="hljs-number">0</span>

<span class="hljs-comment"># Calculating the Moving Average on DeMAX</span>
<span class="hljs-attribute">Data</span> = ma(Data, lookback, where, where + <span class="hljs-number">1</span>)        
        
<span class="hljs-comment"># Calculating DeMIN</span>
<span class="hljs-attribute">for</span> i in range(len(Data)):
    
    <span class="hljs-attribute">if</span> Data[i - <span class="hljs-number">1</span>, low] &gt; Data[i, low]:
        <span class="hljs-attribute">Data</span>[i, where + <span class="hljs-number">2</span>] = Data[i - <span class="hljs-number">1</span>, low] - Data[i, low]
    <span class="hljs-attribute">else</span>:
        <span class="hljs-attribute">Data</span>[i, where + <span class="hljs-number">2</span>] = <span class="hljs-number">0</span>    

<span class="hljs-comment"># Calculating the Moving Average on DeMIN</span>
<span class="hljs-attribute">Data</span> = ma(Data, lookback, where + <span class="hljs-number">2</span>, where + <span class="hljs-number">3</span>)        


<span class="hljs-comment"># Calculating DeMarker</span>
<span class="hljs-attribute">for</span> i in range(len(Data)):
    
    <span class="hljs-attribute">Data</span>[i, where + <span class="hljs-number">4</span>] = Data[i, where + <span class="hljs-number">1</span>] / (Data[i, where + <span class="hljs-number">1</span>] + Data[i, where + <span class="hljs-number">3</span>]) 

<span class="hljs-comment"># Removing Excess Columns</span>
<span class="hljs-attribute">Data</span> = deleter(Data, where, <span class="hljs-number">4</span>)

<span class="hljs-attribute">return</span> Data</pre></div><figure id="a207"><img src="https://cdn-images-1.readmedium.com/v2/resize:fit:800/1*Hzlb4TnTDcvH3sxeXwjTUQ.png"><figcaption><b>EURUSD in the first panel with the 21-period Demarker in the second panel.</b></figcaption></figure><p id="9cfd">Check out my weekly market sentiment report to understand the current positioning and to estimate the future direction of several major markets through complex and simple models working side by side. Find out more about the report through this link:</p><div id="7415" class="link-block">
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    </div><h1 id="8210">Using the Demarker</h1><p id="0df8">I am not a strong believer in the 0.30/0.70 overbought/oversold levels as I prefer to widen them a little bit to at least 0.20/0.80. Therefore, when we see the signals on the chart following the 0.20/0.80 rule, we can get something like the below plot.</p><ul><li><b>A long (Buy) signal is generated whenever the Demarker reaches 0.20 with the previous value above 0.20.</b></li><li><b>A short (Sell) signal is generated whenever the Demarker reaches 0.80 with the previous value below 0.80.</b></li></ul><div id="ff6e"><pre><span class="hljs-keyword">def</span> <span class="hljs-title function_">signal</span>(<span class="hljs-params"><span class="hljs-title class_">Data</span>, what, buy, sell</span>)<span class="hljs-symbol">:</span></pre></div><div id="0e12"><pre><span class="hljs-type">Data</span> = adder(<span class="hljs-type">Data</span>, <span class="hljs-number">10</span>)</pre></div><div id="4a8f"><pre><span class="hljs-symbol">for</span> i in range(len(<span class="hljs-meta">Data</span>)):
        
    <span class="hljs-meta">if</span> <span class="hljs-meta">Data</span>[i, what] &lt; lower_barrier <span class="hljs-keyword">and</span> <span class="hljs-meta">Data</span>[i - <span class="hljs-number">1</span>, what] &gt; lower_barrier:
        <span class="hljs-meta">Data</span>[i + <span class="hljs-number">1</span>, buy] = <span class="hljs-number">1</span>
        
    <span class="hljs-meta">if</span> <span class="hljs-meta">Data</span>[i, what] &gt; upper_barrier <span class="hljs-keyword">and</span> <span class="hljs-meta">Data</span>[i - <span class="hljs-number">1</span>, what] &lt; upper_barrier:
        <span class="hljs-meta">Data</span>[i + <

Options

span class="hljs-number">1, sell] = -1

return <span class="hljs-meta">Data</span></pre></div><figure id="7ee7"><img src="https://cdn-images-1.readmedium.com/v2/resize:fit:800/1*Vwt17ycpypw7FqWrOQ2urQ.png"><figcaption><b>Signal chart.</b></figcaption></figure><p id="251c">Another strategy can be created which states that only the exit of the extreme zones will yield a trade:</p><ul><li><b>A long (Buy) signal is generated whenever the Demarker exits 0.20 with the previous value below 0.20.</b></li><li><b>A short (Sell) signal is generated whenever the Demarker exits 0.80 with the previous value above 0.80.</b></li></ul><div id="47c0"><pre><span class="hljs-keyword">def</span> <span class="hljs-title function_">signal</span>(<span class="hljs-params"><span class="hljs-title class_">Data</span>, what, buy, sell</span>)<span class="hljs-symbol">:</span></pre></div><div id="2fa6"><pre><span class="hljs-type">Data</span> = adder(<span class="hljs-type">Data</span>, <span class="hljs-number">10</span>)</pre></div><div id="f24b"><pre><span class="hljs-symbol">for</span> i in range(len(<span class="hljs-meta">Data</span>)):
        
    <span class="hljs-meta">if</span> <span class="hljs-meta">Data</span>[i, what] &gt; lower_barrier <span class="hljs-keyword">and</span> <span class="hljs-meta">Data</span>[i - <span class="hljs-number">1</span>, what] &lt; lower_barrier:
        <span class="hljs-meta">Data</span>[i + <span class="hljs-number">1</span>, buy] = <span class="hljs-number">1</span>
        
    <span class="hljs-meta">if</span> <span class="hljs-meta">Data</span>[i, what] &lt; upper_barrier <span class="hljs-keyword">and</span> <span class="hljs-meta">Data</span>[i - <span class="hljs-number">1</span>, what] &gt; upper_barrier:
        <span class="hljs-meta">Data</span>[i + <span class="hljs-number">1</span>, sell] = -<span class="hljs-number">1</span>
        
return <span class="hljs-meta">Data</span></pre></div><figure id="2c88"><img src="https://cdn-images-1.readmedium.com/v2/resize:fit:800/1*_4OQFQtIqhz1AfcsJcXosg.png"><figcaption><b>Signal chart.</b></figcaption></figure><p id="d761">The second technique of waiting before initiating the position showed slightly better results but not statistically different. In anyways, both are losing strategies with the second one losing less (0.94 profit factor compared to 0.96).</p><p id="3618">I have recently partnered with Lumiwealth, and if you want to see how to create all sorts of algorithms yourself, feel free to check out the below link. From algorithmic trading to blockchain and machine learning, they have hands-on detailed courses that I highly recommend.</p><div id="fead" class="link-block">
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    </div><h1 id="e420">Summary</h1><p id="05a4">To sum up, what I am trying to do is to simply contribute to the world of objective technical analysis which is promoting more transparent techniques and strategies that need to be back-tested before being implemented. This way, technical analysis will get rid of the bad reputation of being subjective and scientifically unfounded.</p><p id="570c">Medium is a hub to interesting reads. I read a lot of articles before I decided to start writing. Consider joining Medium using my referral link (at <b>NO </b>additional cost to you).</p><div id="de8c" class="link-block">
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            <h2>Join Medium with my referral link — Sofien Kaabar</h2>
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    </div><p id="5d41">I recommend you always follow the the below steps whenever you come across a trading technique or strategy:</p><ul><li>Have a critical mindset and get rid of any emotions.</li><li>Back-test it using real life simulation and conditions.</li><li>If you find potential, try optimizing it and running a forward test.</li><li>Always include transaction costs and any slippage simulation in your tests.</li><li>Always include risk management and position sizing in your tests.</li></ul><p id="beb3">Finally, even after making sure of the above, stay careful and monitor the strategy because market dynamics may shift and make the strategy unprofitable.</p><p id="4f75">For the paperback link of the book, you may use the following link:</p><div id="355f" class="link-block">
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            <h2>Contrarian Trading Strategies in Python</h2>
            <div><h3>Amazon.com: Contrarian Trading Strategies in Python: 9798434008075: Kaabar, Sofien: Books</h3></div>
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