Problem 45860. Algorithmic Trading - 2 (optimize Calmar Ratio)

Created by jmac

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{"parts":[{"partUri":"/matlab/document.xml","contentType":"application/vnd.mathworks.matlab.code.document+xml","content":"<?xml version=\"1.0\" encoding=\"UTF-8\"?><w:document xmlns:w=\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\"><w:body><w:p><w:pPr><w:pStyle w:val=\"text\"/><w:jc w:val=\"left\"/></w:pPr><w:r><w:t>This is the second of a series of problems on quant trading. It builds on earlier problem 45776</w:t></w:r><w:r><w:t> </w:t></w:r><w:hyperlink w:docLocation=\"https://www.mathworks.com/matlabcentral/cody/problems/45776-algorithmic-trading-1-optimize-trading-strategy-simple-case\"><w:r><w:t>&lt;https://www.mathworks.com/matlabcentral/cody/problems/45776-algorithmic-trading-1-optimize-trading-strategy-simple-case</w:t></w:r></w:hyperlink><w:r><w:t>&gt;</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/><w:jc w:val=\"left\"/></w:pPr><w:r><w:rPr><w:b/></w:rPr><w:t>Goal</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"ListParagraph\"/><w:numPr><w:numId w:val=\"1\"/></w:numPr><w:jc w:val=\"left\"/></w:pPr><w:r><w:t>Maximize the Calmar Ratio over the test period, calculated on daily returns, defined as</w:t></w:r><w:r><w:t> </w:t></w:r><w:r><w:rPr><w:b/></w:rPr><w:t>C = CAGR/MDD</w:t></w:r><w:r><w:t>, were MDD is the Maximum Drawdown of the return series, defined as the maximum relative drop from a peak (always positive).</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"ListParagraph\"/><w:numPr><w:numId w:val=\"1\"/></w:numPr><w:jc w:val=\"left\"/></w:pPr><w:r><w:t>Max Drawdown can be calculated by</w:t></w:r><w:r><w:t> </w:t></w:r><w:r><w:rPr><w:rFonts w:cs=\"monospace\"/></w:rPr><w:t>MDD = -min((1+cR)./(1+cummax(cR))-1)</w:t></w:r><w:r><w:t>, where</w:t></w:r><w:r><w:t> </w:t></w:r><w:r><w:rPr><w:rFonts w:cs=\"monospace\"/></w:rPr><w:t>cR=cumprod(R+1)-1</w:t></w:r><w:r><w:t> is the cumulative compound return over time,</w:t></w:r><w:r><w:t> </w:t></w:r><w:r><w:rPr><w:rFonts w:cs=\"monospace\"/></w:rPr><w:t>mR=cummax(cR)</w:t></w:r><w:r><w:t> is the historical maximum cumulative compound return over time, and</w:t></w:r><w:r><w:t> </w:t></w:r><w:r><w:rPr><w:rFonts w:cs=\"monospace\"/></w:rPr><w:t>R = D.*(S(1:n-1)&gt;t)</w:t></w:r><w:r><w:t> is the daily return of the investment strategy</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/><w:jc w:val=\"left\"/></w:pPr><w:r><w:t>See</w:t></w:r><w:r><w:t> </w:t></w:r><w:hyperlink w:docLocation=\"https://en.wikipedia.org/wiki/Drawdown_(economics)\"><w:r><w:t>&lt;https://en.wikipedia.org/wiki/Drawdown_(economics</w:t></w:r></w:hyperlink><w:r><w:t>)&gt;</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/><w:jc w:val=\"left\"/></w:pPr><w:r><w:rPr><w:b/></w:rPr><w:t>You are given</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"ListParagraph\"/><w:numPr><w:numId w:val=\"1\"/></w:numPr><w:jc w:val=\"left\"/></w:pPr><w:r><w:rPr><w:b/></w:rPr><w:t>P</w:t></w:r><w:r><w:t>, a [n x 1] vector of daily prices of the traded security, at market open (always positive)</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"ListParagraph\"/><w:numPr><w:numId w:val=\"1\"/></w:numPr><w:jc w:val=\"left\"/></w:pPr><w:r><w:rPr><w:b/></w:rPr><w:t>S</w:t></w:r><w:r><w:t>, a [n x 1] vector of trading signals, calculated just ahead of market open (can take any real value)</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"ListParagraph\"/><w:numPr><w:numId w:val=\"1\"/></w:numPr><w:jc w:val=\"left\"/></w:pPr><w:r><w:t>These will serve both as training and test set</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/><w:jc w:val=\"left\"/></w:pPr><w:r><w:rPr><w:b/></w:rPr><w:t>Your function should return</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"ListParagraph\"/><w:numPr><w:numId w:val=\"1\"/></w:numPr><w:jc w:val=\"left\"/></w:pPr><w:r><w:rPr><w:b/></w:rPr><w:t>t</w:t></w:r><w:r><w:t>, a scalar threshold that determines this simple trading strategy: invest all the available funds in the security when S&gt;t, stay in cash otherwise</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/><w:jc w:val=\"left\"/></w:pPr><w:r><w:rPr><w:b/></w:rPr><w:t>Hints</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"ListParagraph\"/><w:numPr><w:numId w:val=\"1\"/></w:numPr><w:jc w:val=\"left\"/></w:pPr><w:r><w:t>The Calmar Ratio is a risk-weighted return metric. The optimal t also maximizes</w:t></w:r><w:r><w:t> </w:t></w:r><w:r><w:rPr><w:rFonts w:cs=\"monospace\"/></w:rPr><w:t>log(C)</w:t></w:r><w:r><w:t> or, more simply maximizes</w:t></w:r><w:r><w:t> </w:t></w:r><w:r><w:rPr><w:rFonts w:cs=\"monospace\"/></w:rPr><w:t>sum(log(1+D.*(S(1:n-1)&gt;t)))-cummax(cumsum(log(R+1)))</w:t></w:r></w:p></w:body></w:document>","relationship":null}],"relationships":[{"relationshipType":"http://schemas.mathworks.com/matlab/code/2013/relationships/document","target":"/matlab/document.xml","relationshipId":"rId1"}]}

<div style = "text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; "><div style="block-size: 531px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 265.5px; transform-origin: 407px 265.5px; vertical-align: baseline; "><div style="block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; "><span style="block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; ">This is the second of a series of problems on quant trading. It builds on earlier problem 45776<span style="block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; "> <a target='_blank' href = "https://www.mathworks.com/matlabcentral/cody/problems/45776-algorithmic-trading-1-optimize-trading-strategy-simple-case">&lt;https://www.mathworks.com/matlabcentral/cody/problems/45776-algorithmic-trading-1-optimize-trading-strategy-simple-case</a><span style="block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; ">&gt;</div><div style="block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; "><span style="block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; ">Goal</div><ul style="block-size: 103px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 51.5px; transform-origin: 391px 51.5px; margin-top: 10px; margin-bottom: 20px; "><li style="block-size: 40px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 20px; text-align: left; transform-origin: 363px 20px; white-space: pre-wrap; margin-left: 56px; ">Maximize the Calmar Ratio over the test period, calculated on daily returns, defined as C = CAGR/MDD, were MDD is the Maximum Drawdown of the return series, defined as the maximum relative drop from a peak (always positive).</li><li style="block-size: 63px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 31.5px; text-align: left; transform-origin: 363px 31.5px; white-space: pre-wrap; margin-left: 56px; ">Max Drawdown can be calculated by MDD = -min((1+cR)./(1+cummax(cR))-1), where cR=cumprod(R+1)-1 is the cumulative compound return over time, mR=cummax(cR) is the historical maximum cumulative compound return over time, and R = D.*(S(1:n-1)&gt;t) is the daily return of the investment strategy</li></ul><div style="block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; "><span style="block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; ">See<span style="block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; "> <a target='_blank' href = "https://en.wikipedia.org/wiki/Drawdown_(economics)">&lt;https://en.wikipedia.org/wiki/Drawdown_(economics</a><span style="block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; ">)&gt;</div><div style="block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; "><span style="block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; ">You are given</div><ul style="block-size: 60px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 30px; transform-origin: 391px 30px; margin-top: 10px; margin-bottom: 20px; "><li style="block-size: 20px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10px; text-align: left; transform-origin: 363px 10px; white-space: pre-wrap; margin-left: 56px; ">P, a [n x 1] vector of daily prices of the traded security, at market open (always positive)</li><li style="block-size: 20px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10px; text-align: left; transform-origin: 363px 10px; white-space: pre-wrap; margin-left: 56px; ">S, a [n x 1] vector of trading signals, calculated just ahead of market open (can take any real value)</li><li style="block-size: 20px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10px; text-align: left; transform-origin: 363px 10px; white-space: pre-wrap; margin-left: 56px; ">These will serve both as training and test set</li></ul><div style="block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; "><span style="block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; ">Your function should return</div><ul style="block-size: 40px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 20px; transform-origin: 391px 20px; margin-top: 10px; margin-bottom: 20px; "><li style="display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 20px; text-align: left; transform-origin: 363px 20px; white-space: pre-wrap; margin-left: 56px; ">t, a scalar threshold that determines this simple trading strategy: invest all the available funds in the security when S&gt;t, stay in cash otherwise</li></ul><div style="block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; "><span style="block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; ">Hints</div><ul style="block-size: 42px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 21px; transform-origin: 391px 21px; margin-top: 10px; margin-bottom: 20px; "><li style="display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 21px; text-align: left; transform-origin: 363px 21px; white-space: pre-wrap; margin-left: 56px; ">The Calmar Ratio is a risk-weighted return metric. The optimal t also maximizes log(C) or, more simply maximizes sum(log(1+D.*(S(1:n-1)&gt;t)))-cummax(cumsum(log(R+1)))</li></ul></div></div>

This is the second of a series of problems on quant trading. It builds on earlier problem 45776 <https://www.mathworks.com/matlabcentral/cody/problems/45776-algorithmic-trading-1-optimize-trading-strategy-simple-case>

*Goal*

* Maximize the Calmar Ratio over the test period, calculated on daily returns, defined as *C = CAGR/MDD*, were MDD is the Maximum Drawdown of the return series, defined as the maximum relative drop from a peak (always positive).
* Max Drawdown can be calculated by |MDD = -min((1+cR)./(1+cummax(cR))-1)|, where |cR=cumprod(R+1)-1| is the cumulative compound return over time, |mR=cummax(cR)| is the historical maximum cumulative compound return over time, and |R = D.*(S(1:n-1)>t)| is the daily return of the investment strategy

See <https://en.wikipedia.org/wiki/Drawdown_(economics)>

*You are given*

* *P*, a [n x 1] vector of daily prices of the traded security, at market open (always positive)
* *S*, a [n x 1] vector of trading signals, calculated just ahead of market open (can take any real value)
* These will serve both as training and test set

*Your function should return*

* *t*, a scalar threshold that determines this simple trading strategy: invest all the available funds in the security when S>t, stay in cash otherwise

*Hints*

* The Calmar Ratio is a risk-weighted return metric. The optimal t also maximizes |log(C)| or, more simply maximizes |sum(log(1+D.*(S(1:n-1)>t)))-cummax(cumsum(log(R+1)))|

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jmac on 22 Nov 2020

Test suite fixed.

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Problem 45860. Algorithmic Trading - 2 (optimize Calmar Ratio)

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