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      <title><![CDATA[Research - quantminer.webnode.page]]></title>
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      <pubDate>Sat, 23 May 2009 16:44:00 +0200</pubDate>
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         <title><![CDATA[Collateral Management and Appraisal]]></title>
         <link>https://quantminer.webnode.page/news/collateral-management-and-appraisal/</link>
         <description><![CDATA[Collateral management is the key in a bank's credit risk management. Collateral valuation is also very important to loss given default modeling and risk recovery prediction. This slide presents the steps that need to be taken in collateral management.
Download Link<br />
QuantMinds.NET]]></description>
         <pubDate>Sat, 23 May 2009 16:44:00 +0200</pubDate>
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         <title><![CDATA[Predictive Modeling on Probability of Default – Logit Model Using Microsoft Excel and VBA]]></title>
         <link>https://quantminer.webnode.page/news/predictive-modeling-on-probability-of-default-logit-model-using-microsoft-excel-and-vba/</link>
         <description><![CDATA[
Logistic regression is often used to estimate the probability of default in commercial loans against different types of borrowers (obligor’s PD model). Microsoft Excel is probably the most popular used software in daily banking business work. However, the logistic regression model function is not captured by Excel. In this case study, I developed a Visual Basic Application (VBA) add-in in Excel macro environment to regress the linear logistic function with algorithms that capture the maximum...<br />
QuantMinds.NET]]></description>
         <pubDate>Sat, 23 May 2009 14:20:00 +0200</pubDate>
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         <category><![CDATA[Research]]></category>
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         <title><![CDATA[Predicting Default Risk Using Merton’s Model – a Case Study in Chinese Stock ]]></title>
         <link>https://quantminer.webnode.page/news/predicting-default-risk-using-mertons-model-a-case-study-in-chinese-stock-/</link>
         <description><![CDATA[&#160;
This case study presents a simple spreadsheet-based version of Merton’s credit risk model (i.e., normally as KMV model) to predict default risk using a Chinese utility stock data (Quote: 600021 Shanghai Electric Power Limited) from 2008 to 2009. Due to the limitation of data availability in developing country such as China, the option-based modeling approach is to be the most straightforward approach to evaluate the default risk of public company.&#160;&#160;&#160; 
Key Word: Merton’s...<br />
QuantMinds.NET]]></description>
         <pubDate>Thu, 21 May 2009 20:17:00 +0200</pubDate>
         <guid isPermaLink="true">https://quantminer.webnode.page/news/predicting-default-risk-using-mertons-model-a-case-study-in-chinese-stock-/</guid>
         <category><![CDATA[Research]]></category>
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         <title><![CDATA[Calculation of Capital Cost of Equity (Godon Model & Capital Asset Pricing Model):]]></title>
         <link>https://quantminer.webnode.page/news/calculation-of-capital-cost-of-equity-godon-model-capital-asset-pricing-model-/</link>
         <description><![CDATA[&#160;
&#160;

    
    Calculation of Capital Cost of Equity (Godon Model &amp; Capital Asset Pricing Model): 
    

&#160;&#160;&#160;&#160; Download: Speadsheet
&#160;<br />
QuantMinds.NET]]></description>
         <pubDate>Wed, 29 Apr 2009 09:53:00 +0200</pubDate>
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         <category><![CDATA[Research]]></category>
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         <title><![CDATA[Credit Approval Process]]></title>
         <link>https://quantminer.webnode.page/news/credit-approval-process/</link>
         <description><![CDATA[&#160;
&#160;Abstract
This article briefly introduces the general process of credit approval in a commercial bank. As the key&#160;of the loan structuring process, the contents of a loan agreement and its secured assets and&#160;grantee&#160;were thoroughly introduced.&#160;
Key Words: Credit, Loan, Commercial Bank, Collateral, Covenant
&#160;
Credit Approval Process&#160;&#160;
&#160;<br />
QuantMinds.NET]]></description>
         <pubDate>Mon, 27 Apr 2009 22:15:00 +0200</pubDate>
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         <category><![CDATA[Research]]></category>
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         <title><![CDATA[How to Measure Natural Gas Price Elasticity ]]></title>
         <link>https://quantminer.webnode.page/news/case-study-how-to-measure-natural-gas-price-elasticity/</link>
         <description><![CDATA[In this&#160;case study,&#160;I’ll show you how to measure demand elasticities in the real world. We’ll develop a simple theory, write it down mathematically, find some data and crunch the numbers in Excel. At the end, I’ll hand over a spreadsheet with our own elasticity estimates for retail gasoline that replicate the numbers from a well-known recent econometric study.
Gas Linear Regression<br />
QuantMinds.NET]]></description>
         <pubDate>Thu, 16 Apr 2009 22:56:00 +0200</pubDate>
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         <category><![CDATA[Research]]></category>
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         <title><![CDATA[Load Forecasting - a Simple EXCEL Spreadsheet]]></title>
         <link>https://quantminer.webnode.page/news/load-forecasting-a-simple-excel-spreadsheet/</link>
         <description><![CDATA[The attached spreadsheet shows a simple load forecasting model that includes only one weather &amp; temperature related variables.
Load Forecasting Case Study
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&#160;<br />
QuantMinds.NET]]></description>
         <pubDate>Thu, 16 Apr 2009 22:45:00 +0200</pubDate>
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         <category><![CDATA[Research]]></category>
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         <title><![CDATA[Credit Scoring Using Logistic Regression - An Auto Loan Case]]></title>
         <link>https://quantminer.webnode.page/news/credit-scoring-using-logistic-regression-an-auto-loan-case/</link>
         <description><![CDATA[This project involves the analysis of a dataset of auto-finance consumer data, including credit–bureau information, loan-application data, and company data regarding consumers’ performance since acquisition. The goal of this project was to analyze the dataset and create a prediction model to evaluate the credit-worthiness of new loan applicants. A logistic regression model was applied and the scorecard cut-off was set up. 
&#160;
Project Site (including report, powerpoint slides, data, sas code...<br />
QuantMinds.NET]]></description>
         <pubDate>Fri, 05 Dec 2008 14:07:00 +0200</pubDate>
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         <category><![CDATA[Research]]></category>
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         <title><![CDATA[Asian Option Pricing Model Using Monte Carlo Simulation: Electricity Pricing Hedging Case Study]]></title>
         <link>https://quantminer.webnode.page/news/asian-option-pricing-model-using-monte-carlo-simulation-a-case-study-in-electricity-markets/</link>
         <description><![CDATA[In competitive electricity markets, The volatility is rooted in the risks associated with holding assets when there is an uncertain risk associated with the future value of the assets. Industrial the price behavior of power is extremely volatile. consumers are highly exposed to volatility in the cost of electricity. This case study focuses on how a business hedges the electricity price volatility by using the average-price options (e.g., Asian option).&#160;Using Monte Carlo Simulation, we...<br />
QuantMinds.NET]]></description>
         <pubDate>Thu, 27 Nov 2008 00:32:00 +0200</pubDate>
         <guid isPermaLink="true">https://quantminer.webnode.page/news/asian-option-pricing-model-using-monte-carlo-simulation-a-case-study-in-electricity-markets/</guid>
         <category><![CDATA[Research]]></category>
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      <item>
         <title><![CDATA[Fitting a Capital Assets Pricing Model - A Case Study in Chinese Stock Market ]]></title>
         <link>https://quantminer.webnode.page/news/fitting-a-capital-assets-pricing-model-a-case-study-in-chinese-stock-market/</link>
         <description><![CDATA[Using weekly market return data of different industrial segments from 2005 to 2007 in China’s stock market, the objective of this study is not focused on validating the Capital Asset Pricing Model (CAPM)’s assumptions in China’s stock market; instead due to the nature of highly volatile and policy-driven market in China, this paper applied different econometric techniques to fit the CAPM within a time series analysis framework. We found that the policy changes did not result in structural...<br />
QuantMinds.NET]]></description>
         <pubDate>Fri, 12 Sep 2008 21:20:00 +0200</pubDate>
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         <category><![CDATA[Research]]></category>
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