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	<title>Risk Modelling, Risk Analysis, Excel Modelling</title>
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		<title>Excel Best Practices and Influence Diagrams</title>
		<link>http://www.michaelrees.co.uk/excel-best-practices-and-influence-diagrams/</link>
		<comments>http://www.michaelrees.co.uk/excel-best-practices-and-influence-diagrams/#comments</comments>
		<pubDate>Wed, 16 Nov 2011 11:25:26 +0000</pubDate>
		<dc:creator>Michael Rees</dc:creator>
				<category><![CDATA[Excel and Risk Modelling Blog]]></category>

		<guid isPermaLink="false">http://pluto.servers.rbl-mer.misp.co.uk/~michaelr/?p=1016</guid>
		<description><![CDATA[My apologies to readers of this blog for such a long gap in the postings … it’s been a hectic time. This short blog follows on from the topic of Excel best practices from the perspective of improving the visual understanding of models. I think that another good way of placing Excel best practices (such [...]]]></description>
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		<title>Some Best Practices in Excel Modelling – Respecting Excel’s Tabular Structure</title>
		<link>http://www.michaelrees.co.uk/some-best-practices-in-excel-modelling-%e2%80%93-respecting-excel%e2%80%99s-tabular-structure/</link>
		<comments>http://www.michaelrees.co.uk/some-best-practices-in-excel-modelling-%e2%80%93-respecting-excel%e2%80%99s-tabular-structure/#comments</comments>
		<pubDate>Sat, 09 Apr 2011 19:17:53 +0000</pubDate>
		<dc:creator>Michael Rees</dc:creator>
				<category><![CDATA[Excel and Risk Modelling Blog]]></category>

		<guid isPermaLink="false">http://www.michaelrees.co.uk/?p=1008</guid>
		<description><![CDATA[Following on from the last positing about objectives- and sensitivity-driven models, this posing presents some key areas in ensuring that Excel’s tabular structure is well-respected, which is a key best practice. Respecting the tabular structure of Excel is in fact, not always perfectly possible, but includes (as far as possible) items such as: The logic [...]]]></description>
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		<title>Best Practices in Excel Modelling – Objectives Driven Models</title>
		<link>http://www.michaelrees.co.uk/best-practices-in-excel-modelling-%e2%80%93-objectives-driven-models/</link>
		<comments>http://www.michaelrees.co.uk/best-practices-in-excel-modelling-%e2%80%93-objectives-driven-models/#comments</comments>
		<pubDate>Fri, 01 Apr 2011 18:55:33 +0000</pubDate>
		<dc:creator>Michael Rees</dc:creator>
				<category><![CDATA[Excel and Risk Modelling Blog]]></category>

		<guid isPermaLink="false">http://www.michaelrees.co.uk/?p=1005</guid>
		<description><![CDATA[Some key best practices in Excel model formulation and implementation are that models are objectives-driven and sensitivity-driven. Further best practices include that Excel’s tabular structure is well-respected. The posting on these two areas is split into two, with the second to follow shortly. An objectives-driven model (which is implicitly related to the idea of sensitivity-driven [...]]]></description>
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		<title>Correlation versus Dependency in Monte Carlo Simulation Models</title>
		<link>http://www.michaelrees.co.uk/correlation-versus-dependency-in-monte-carlo-simulation-models/</link>
		<comments>http://www.michaelrees.co.uk/correlation-versus-dependency-in-monte-carlo-simulation-models/#comments</comments>
		<pubDate>Fri, 18 Mar 2011 20:45:34 +0000</pubDate>
		<dc:creator>Michael Rees</dc:creator>
				<category><![CDATA[Excel and Risk Modelling Blog]]></category>

		<guid isPermaLink="false">http://www.michaelrees.co.uk/?p=1003</guid>
		<description><![CDATA[Most commercial Monte Carlo simulation packages (@RISK®, ModelRisk® etc.), offer the ability to correlate variables. In addition, the implementation of relationships of correlation in any model in most cases requires simulation techniques (standard portfolio optimisation being the exception, where mathematical formulae can be used). As a consequence, other possible forms of dependency relationship are often [...]]]></description>
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		<title>Flexible Model Input Ranges using INDIRECT and ADDRESS</title>
		<link>http://www.michaelrees.co.uk/flexible-model-input-ranges-using-indirect-and-address/</link>
		<comments>http://www.michaelrees.co.uk/flexible-model-input-ranges-using-indirect-and-address/#comments</comments>
		<pubDate>Sat, 12 Mar 2011 21:33:41 +0000</pubDate>
		<dc:creator>Michael Rees</dc:creator>
				<category><![CDATA[Excel and Risk Modelling Blog]]></category>

		<guid isPermaLink="false">http://www.michaelrees.co.uk/?p=1001</guid>
		<description><![CDATA[A frequent issue that arises in Excel modelling is how to change the input values to a model whilst retaining the integrity of the model’s calculations. Sensitivity analysis is the simplest case of that, and often such analysis and related calculations can be implemented by the use of standard lookup functions, such as CHOOSE, INDEX [...]]]></description>
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		<title>The Multinomial Distribution</title>
		<link>http://www.michaelrees.co.uk/the-multinomial-distribution/</link>
		<comments>http://www.michaelrees.co.uk/the-multinomial-distribution/#comments</comments>
		<pubDate>Thu, 10 Mar 2011 21:49:04 +0000</pubDate>
		<dc:creator>Michael Rees</dc:creator>
				<category><![CDATA[Excel and Risk Modelling Blog]]></category>

		<guid isPermaLink="false">http://www.michaelrees.co.uk/?p=999</guid>
		<description><![CDATA[The multinomial distribution is a generalisation of the binomial distribution; whereas the binomial describes how many of n independent trials occur (and hence also implicitly do not occur) i.e. it divides the trials into two categories, the multinomial allows for more than two categories. It has a number of important applications and uses. The binomial [...]]]></description>
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		<slash:comments>0</slash:comments>
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		<title>Choosing the Right Distribution in a Monte Carlo Simulation Model</title>
		<link>http://www.michaelrees.co.uk/choosing-the-right-distribution-in-a-monte-carlo-simulation-model/</link>
		<comments>http://www.michaelrees.co.uk/choosing-the-right-distribution-in-a-monte-carlo-simulation-model/#comments</comments>
		<pubDate>Wed, 09 Mar 2011 16:55:03 +0000</pubDate>
		<dc:creator>Michael Rees</dc:creator>
				<category><![CDATA[Excel and Risk Modelling Blog]]></category>

		<guid isPermaLink="false">http://www.michaelrees.co.uk/?p=996</guid>
		<description><![CDATA[Many people may be familiar with a framework for choosing a distribution to use in a Monte Carlo simulation model (i.e. “data-driven”, “scientific”, or “pragmatic”), that I also discuss in my book. In addition to this framwork &#8211; and arguably more fundamental in formulating a model correctl &#8211;  is the issue of the tendency to [...]]]></description>
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		<slash:comments>0</slash:comments>
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		<title>Using the RiskTheo Functions in @RISK®</title>
		<link>http://www.michaelrees.co.uk/using-the-risktheo-functions-in-risk%c2%ae/</link>
		<comments>http://www.michaelrees.co.uk/using-the-risktheo-functions-in-risk%c2%ae/#comments</comments>
		<pubDate>Mon, 07 Mar 2011 20:03:00 +0000</pubDate>
		<dc:creator>Michael Rees</dc:creator>
				<category><![CDATA[Excel and Risk Modelling Blog]]></category>

		<guid isPermaLink="false">http://www.michaelrees.co.uk/?p=993</guid>
		<description><![CDATA[The RiskTheo functions in @RISK® (version 5 upwards) provide a useful way to calculate the exact values associated with a distribution. These functions are arguably underutilised and not so well known by those who learnt version 4 without learning all the new features of version 5. One powerful use is to combine them with the [...]]]></description>
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		<slash:comments>0</slash:comments>
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		<title>Interpreting the Role of Distributions in Risk and Simulation Models</title>
		<link>http://www.michaelrees.co.uk/interpreting-the-role-of-distributions-in-risk-and-simulation-models/</link>
		<comments>http://www.michaelrees.co.uk/interpreting-the-role-of-distributions-in-risk-and-simulation-models/#comments</comments>
		<pubDate>Sat, 05 Mar 2011 21:14:09 +0000</pubDate>
		<dc:creator>Michael Rees</dc:creator>
				<category><![CDATA[Excel and Risk Modelling Blog]]></category>

		<guid isPermaLink="false">http://www.michaelrees.co.uk/?p=989</guid>
		<description><![CDATA[The use of probability distributions in risk modelling (when using Monte Carlo simulation techniques) is often only partially understood. I am not talking here about the selection of the appropriate distribution (continuous, discrete, compound, Poisson, Normal?, etc), but rather the implication of what it means to assume that a model parameter or variable follows a [...]]]></description>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Lessons from Risk Management Failures</title>
		<link>http://www.michaelrees.co.uk/lessons-from-risk-management-failures/</link>
		<comments>http://www.michaelrees.co.uk/lessons-from-risk-management-failures/#comments</comments>
		<pubDate>Sun, 27 Feb 2011 10:32:50 +0000</pubDate>
		<dc:creator>Michael Rees</dc:creator>
				<category><![CDATA[Excel and Risk Modelling Blog]]></category>

		<guid isPermaLink="false">http://www.michaelrees.co.uk/?p=986</guid>
		<description><![CDATA[A recent piece of work ahs involved studying some failures in risk management and trying to draw conclusions and learn lessons from them. Many major situations, such as the recent financial crisis, the BP Deepwater catastrophe, failures of insurers in the EU have been studied through formal enquiries, each with their own conclusions. My own [...]]]></description>
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