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<!DOCTYPE html>
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<title>Chapter 3 Methodology | An Intelligent Market Cycle Detection System</title>
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<meta name="twitter:title" content="Chapter 3 Methodology | An Intelligent Market Cycle Detection System" />
<meta name="author" content="Michael S. Azer" />
<meta name="date" content="2020-11-25" />
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<li><a href="./">htttps://www.michaelazer.com/thesis</a></li>
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<li class="chapter" data-level="1" data-path="index.html"><a href="index.html"><i class="fa fa-check"></i><b>1</b> Introduction</a><ul>
<li class="chapter" data-level="1.1" data-path="index.html"><a href="index.html#statement-of-the-problem"><i class="fa fa-check"></i><b>1.1</b> Statement of the Problem</a></li>
<li class="chapter" data-level="1.2" data-path="index.html"><a href="index.html#objective"><i class="fa fa-check"></i><b>1.2</b> Objective</a></li>
<li class="chapter" data-level="1.3" data-path="index.html"><a href="index.html#significance"><i class="fa fa-check"></i><b>1.3</b> Significance</a></li>
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<li class="chapter" data-level="2" data-path="litrev.html"><a href="litrev.html"><i class="fa fa-check"></i><b>2</b> Literature Review</a><ul>
<li class="chapter" data-level="2.1" data-path="litrev.html"><a href="litrev.html#duration-dependence"><i class="fa fa-check"></i><b>2.1</b> Duration-dependence</a><ul>
<li class="chapter" data-level="2.1.1" data-path="litrev.html"><a href="litrev.html#definition"><i class="fa fa-check"></i><b>2.1.1</b> Definition</a></li>
<li class="chapter" data-level="2.1.2" data-path="litrev.html"><a href="litrev.html#turning-point-detection"><i class="fa fa-check"></i><b>2.1.2</b> Turning-point Detection</a></li>
<li class="chapter" data-level="2.1.3" data-path="litrev.html"><a href="litrev.html#cycle-length"><i class="fa fa-check"></i><b>2.1.3</b> Cycle Length</a></li>
<li class="chapter" data-level="2.1.4" data-path="litrev.html"><a href="litrev.html#cycle-synchronization"><i class="fa fa-check"></i><b>2.1.4</b> Cycle Synchronization</a></li>
<li class="chapter" data-level="2.1.5" data-path="litrev.html"><a href="litrev.html#bubbles-and-recessions"><i class="fa fa-check"></i><b>2.1.5</b> Bubbles and Recessions</a></li>
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<li class="chapter" data-level="2.2" data-path="litrev.html"><a href="litrev.html#established-cycles"><i class="fa fa-check"></i><b>2.2</b> Established Cycles</a><ul>
<li class="chapter" data-level="2.2.1" data-path="litrev.html"><a href="litrev.html#kondratiev"><i class="fa fa-check"></i><b>2.2.1</b> Kondratiev</a></li>
<li class="chapter" data-level="2.2.2" data-path="litrev.html"><a href="litrev.html#kuznets"><i class="fa fa-check"></i><b>2.2.2</b> Kuznets</a></li>
<li class="chapter" data-level="2.2.3" data-path="litrev.html"><a href="litrev.html#juglar"><i class="fa fa-check"></i><b>2.2.3</b> Juglar</a></li>
<li class="chapter" data-level="2.2.4" data-path="litrev.html"><a href="litrev.html#kitchin"><i class="fa fa-check"></i><b>2.2.4</b> Kitchin</a></li>
</ul></li>
<li class="chapter" data-level="2.3" data-path="litrev.html"><a href="litrev.html#classification-of-sp500"><i class="fa fa-check"></i><b>2.3</b> Classification of S&P500</a></li>
<li class="chapter" data-level="2.4" data-path="litrev.html"><a href="litrev.html#features-to-determine-phases"><i class="fa fa-check"></i><b>2.4</b> Features to determine phases</a><ul>
<li class="chapter" data-level="2.4.1" data-path="litrev.html"><a href="litrev.html#political-events"><i class="fa fa-check"></i><b>2.4.1</b> Political Events</a></li>
<li class="chapter" data-level="2.4.2" data-path="litrev.html"><a href="litrev.html#economic-factors"><i class="fa fa-check"></i><b>2.4.2</b> Economic Factors</a></li>
<li class="chapter" data-level="2.4.3" data-path="litrev.html"><a href="litrev.html#health-shocks-pandemics-and-epidemics"><i class="fa fa-check"></i><b>2.4.3</b> Health Shocks (Pandemics and Epidemics)</a></li>
<li class="chapter" data-level="2.4.4" data-path="litrev.html"><a href="litrev.html#financial-indicators"><i class="fa fa-check"></i><b>2.4.4</b> Financial Indicators</a></li>
</ul></li>
<li class="chapter" data-level="2.5" data-path="litrev.html"><a href="litrev.html#importance-of-features"><i class="fa fa-check"></i><b>2.5</b> Importance of features</a></li>
<li class="chapter" data-level="2.6" data-path="litrev.html"><a href="litrev.html#market-prediction"><i class="fa fa-check"></i><b>2.6</b> Market prediction</a></li>
</ul></li>
<li class="chapter" data-level="3" data-path="methodology.html"><a href="methodology.html"><i class="fa fa-check"></i><b>3</b> Methodology</a><ul>
<li class="chapter" data-level="3.1" data-path="methodology.html"><a href="methodology.html#data"><i class="fa fa-check"></i><b>3.1</b> Data</a></li>
<li class="chapter" data-level="3.2" data-path="methodology.html"><a href="methodology.html#techniques"><i class="fa fa-check"></i><b>3.2</b> Techniques</a></li>
</ul></li>
<li class="chapter" data-level="4" data-path="methodology.html"><a href="methodology.html#data"><i class="fa fa-check"></i><b>4</b> Data Preparation</a><ul>
<li class="chapter" data-level="4.1" data-path="data.html"><a href="data.html"><i class="fa fa-check"></i><b>4.1</b> Factors Tested</a></li>
<li class="chapter" data-level="4.2" data-path="data.html"><a href="data.html#testing-stationarity"><i class="fa fa-check"></i><b>4.2</b> Testing Stationarity</a></li>
<li class="chapter" data-level="4.3" data-path="data.html"><a href="data.html#recessions"><i class="fa fa-check"></i><b>4.3</b> Recessions</a></li>
<li class="chapter" data-level="4.4" data-path="data.html"><a href="data.html#sp500-index"><i class="fa fa-check"></i><b>4.4</b> S&P500 Index</a></li>
<li class="chapter" data-level="4.5" data-path="data.html"><a href="data.html#national-financial-conditions-index"><i class="fa fa-check"></i><b>4.5</b> National Financial Conditions Index</a></li>
<li class="chapter" data-level="4.6" data-path="data.html"><a href="data.html#industrial-production-index"><i class="fa fa-check"></i><b>4.6</b> Industrial Production Index</a></li>
<li class="chapter" data-level="4.7" data-path="data.html"><a href="data.html#real-government-consumption-expenditures-and-gross-investment"><i class="fa fa-check"></i><b>4.7</b> Real Government Consumption Expenditures and Gross Investment</a></li>
<li class="chapter" data-level="4.8" data-path="data.html"><a href="data.html#dollar-index"><i class="fa fa-check"></i><b>4.8</b> Dollar Index</a><ul>
<li class="chapter" data-level="4.8.1" data-path="data.html"><a href="data.html#trade-weighted-u.s.-dollar-index-advanced-foreign-economies-goods-and-services-dtwexafegs"><i class="fa fa-check"></i><b>4.8.1</b> Trade Weighted U.S. Dollar Index: Advanced Foreign Economies, Goods and Services (DTWEXAFEGS)</a></li>
<li class="chapter" data-level="4.8.2" data-path="data.html"><a href="data.html#trade-weighted-u.s.-dollar-index-broad-goods-and-services-dtwexbgs"><i class="fa fa-check"></i><b>4.8.2</b> Trade Weighted U.S. Dollar Index: Broad, Goods and Services (DTWEXBGS)</a></li>
<li class="chapter" data-level="4.8.3" data-path="data.html"><a href="data.html#trade-weighted-u.s.-dollar-index-major-currencies-goods-discontinued-dtwexm"><i class="fa fa-check"></i><b>4.8.3</b> Trade Weighted U.S. Dollar Index: Major Currencies, Goods (DISCONTINUED) (DTWEXM)</a></li>
<li class="chapter" data-level="4.8.4" data-path="data.html"><a href="data.html#trade-weighted-u.s.-dollar-index-broad-goods-discontinued-dtwexb"><i class="fa fa-check"></i><b>4.8.4</b> Trade Weighted U.S. Dollar Index: Broad, Goods (DISCONTINUED) (DTWEXB)</a></li>
</ul></li>
<li class="chapter" data-level="4.9" data-path="data.html"><a href="data.html#year-treasury-constant-maturity-rate-dgs10"><i class="fa fa-check"></i><b>4.9</b> 10-Year Treasury Constant Maturity Rate (DGS10)</a></li>
<li class="chapter" data-level="4.10" data-path="data.html"><a href="data.html#real-gross-domestic-product-gdpc1"><i class="fa fa-check"></i><b>4.10</b> Real Gross Domestic Product (GDPC1)</a></li>
<li class="chapter" data-level="4.11" data-path="data.html"><a href="data.html#unemployment-rate-unrate"><i class="fa fa-check"></i><b>4.11</b> Unemployment Rate (UNRATE)</a></li>
<li class="chapter" data-level="4.12" data-path="data.html"><a href="data.html#sp500-analysis"><i class="fa fa-check"></i><b>4.12</b> S&P500 Analysis</a><ul>
<li class="chapter" data-level="4.12.1" data-path="data.html"><a href="data.html#price-vs.recessions-line"><i class="fa fa-check"></i><b>4.12.1</b> Price vs. Recessions (Line)</a></li>
<li class="chapter" data-level="4.12.2" data-path="data.html"><a href="data.html#returns-vs.-recessions-line"><i class="fa fa-check"></i><b>4.12.2</b> Returns Vs. Recessions (Line)</a></li>
<li class="chapter" data-level="4.12.3" data-path="data.html"><a href="data.html#returns-vs.-recessions-box-plot"><i class="fa fa-check"></i><b>4.12.3</b> Returns Vs. Recessions (Box-plot)</a></li>
<li class="chapter" data-level="4.12.4" data-path="data.html"><a href="data.html#draw-downs-vs.recessions-line"><i class="fa fa-check"></i><b>4.12.4</b> Draw-downs vs. Recessions (Line)</a></li>
</ul></li>
<li class="chapter" data-level="4.13" data-path="data.html"><a href="data.html#fundamentals"><i class="fa fa-check"></i><b>4.13</b> Fundamentals</a><ul>
<li class="chapter" data-level="4.13.1" data-path="data.html"><a href="data.html#sp-500-pe-ratio"><i class="fa fa-check"></i><b>4.13.1</b> S&P 500 PE Ratio</a></li>
<li class="chapter" data-level="4.13.2" data-path="data.html"><a href="data.html#sp-500-earnings-yield-inverse"><i class="fa fa-check"></i><b>4.13.2</b> S&P 500 Earnings Yield (inverse)</a></li>
<li class="chapter" data-level="4.13.3" data-path="data.html"><a href="data.html#shiller-pe-ratio"><i class="fa fa-check"></i><b>4.13.3</b> Shiller PE Ratio</a></li>
<li class="chapter" data-level="4.13.4" data-path="data.html"><a href="data.html#sp-500-price-to-sales-ratio"><i class="fa fa-check"></i><b>4.13.4</b> S&P 500 Price to Sales Ratio</a></li>
<li class="chapter" data-level="4.13.5" data-path="data.html"><a href="data.html#sp-500-price-to-book-value"><i class="fa fa-check"></i><b>4.13.5</b> S&P 500 Price to Book Value</a></li>
<li class="chapter" data-level="4.13.6" data-path="data.html"><a href="data.html#sp-500-dividend-growth"><i class="fa fa-check"></i><b>4.13.6</b> S&P 500 Dividend Growth</a></li>
</ul></li>
<li class="chapter" data-level="4.14" data-path="data.html"><a href="data.html#seasonal-analysis"><i class="fa fa-check"></i><b>4.14</b> Seasonal Analysis</a><ul>
<li class="chapter" data-level="4.14.1" data-path="data.html"><a href="data.html#time-analysis-breakdown"><i class="fa fa-check"></i><b>4.14.1</b> Time Analysis Breakdown</a></li>
<li class="chapter" data-level="4.14.2" data-path="data.html"><a href="data.html#sarima"><i class="fa fa-check"></i><b>4.14.2</b> SARIMA?</a></li>
<li class="chapter" data-level="4.14.3" data-path="data.html"><a href="data.html#archgarch"><i class="fa fa-check"></i><b>4.14.3</b> ARCH/GARCH?</a></li>
<li class="chapter" data-level="4.14.4" data-path="data.html"><a href="data.html#fourier-analysis"><i class="fa fa-check"></i><b>4.14.4</b> Fourier Analysis</a></li>
</ul></li>
<li class="chapter" data-level="4.15" data-path="data.html"><a href="data.html#technical-analysis"><i class="fa fa-check"></i><b>4.15</b> Technical Analysis</a><ul>
<li class="chapter" data-level="4.15.1" data-path="data.html"><a href="data.html#moving-averages"><i class="fa fa-check"></i><b>4.15.1</b> Moving Averages</a></li>
<li class="chapter" data-level="4.15.2" data-path="data.html"><a href="data.html#relative-strength-indicator"><i class="fa fa-check"></i><b>4.15.2</b> Relative Strength Indicator</a></li>
<li class="chapter" data-level="4.15.3" data-path="data.html"><a href="data.html#commodity-channel-index"><i class="fa fa-check"></i><b>4.15.3</b> Commodity Channel Index</a></li>
</ul></li>
<li class="chapter" data-level="4.16" data-path="data.html"><a href="data.html#politics"><i class="fa fa-check"></i><b>4.16</b> Politics</a><ul>
<li class="chapter" data-level="4.16.1" data-path="data.html"><a href="data.html#days-to-next-presidential-elections"><i class="fa fa-check"></i><b>4.16.1</b> Days to next Presidential Elections</a></li>
<li class="chapter" data-level="4.16.2" data-path="data.html"><a href="data.html#political-party"><i class="fa fa-check"></i><b>4.16.2</b> Political Party</a></li>
</ul></li>
<li class="chapter" data-level="4.17" data-path="data.html"><a href="data.html#economics"><i class="fa fa-check"></i><b>4.17</b> Economics</a><ul>
<li class="chapter" data-level="4.17.1" data-path="data.html"><a href="data.html#national-financial-conditions-index-nfci"><i class="fa fa-check"></i><b>4.17.1</b> National Financial Conditions Index (NFCI)</a></li>
<li class="chapter" data-level="4.17.2" data-path="data.html"><a href="data.html#industrial-production-index-ipro"><i class="fa fa-check"></i><b>4.17.2</b> Industrial Production Index (IPRO)</a></li>
<li class="chapter" data-level="4.17.3" data-path="data.html"><a href="data.html#government-consumption-expenditures-and-gross-investment-gce"><i class="fa fa-check"></i><b>4.17.3</b> Government Consumption Expenditures and Gross Investment (GCE)</a></li>
<li class="chapter" data-level="4.17.4" data-path="data.html"><a href="data.html#unemployment-rate-unrate-1"><i class="fa fa-check"></i><b>4.17.4</b> Unemployment Rate (UNRATE)</a></li>
<li class="chapter" data-level="4.17.5" data-path="data.html"><a href="data.html#real-gross-domestic-product-gdpc1-1"><i class="fa fa-check"></i><b>4.17.5</b> Real Gross Domestic Product (GDPC1)</a></li>
<li class="chapter" data-level="4.17.6" data-path="data.html"><a href="data.html#personal-saving-rate-psavert"><i class="fa fa-check"></i><b>4.17.6</b> Personal Saving Rate (PSAVERT)</a></li>
<li class="chapter" data-level="4.17.7" data-path="data.html"><a href="data.html#disposable-personal-income-dspi"><i class="fa fa-check"></i><b>4.17.7</b> Disposable Personal Income (DSPI)</a></li>
<li class="chapter" data-level="4.17.8" data-path="data.html"><a href="data.html#real-manufacturing-and-trade-industries-sales-cmrmtspl"><i class="fa fa-check"></i><b>4.17.8</b> Real Manufacturing and Trade Industries Sales (CMRMTSPL)</a></li>
<li class="chapter" data-level="4.17.9" data-path="data.html"><a href="data.html#new-private-housing-units-authorized-by-building-permits-permit"><i class="fa fa-check"></i><b>4.17.9</b> New Private Housing Units Authorized by Building Permits (PERMIT)</a></li>
<li class="chapter" data-level="4.17.10" data-path="data.html"><a href="data.html#year-treasury-constant-maturity-rate-dgs10-1"><i class="fa fa-check"></i><b>4.17.10</b> 10-Year Treasury Constant Maturity Rate (DGS10)</a></li>
<li class="chapter" data-level="4.17.11" data-path="data.html"><a href="data.html#year-treasury-constant-maturity-minus-2-year-treasury-constant-maturity-t10y2y"><i class="fa fa-check"></i><b>4.17.11</b> 10-Year Treasury Constant Maturity Minus 2-Year Treasury Constant Maturity (T10Y2Y)</a></li>
<li class="chapter" data-level="4.17.12" data-path="data.html"><a href="data.html#year-treasury-constant-maturity-minus-federal-funds-rate-t10yff"><i class="fa fa-check"></i><b>4.17.12</b> 10-Year Treasury Constant Maturity Minus Federal Funds Rate (T10YFF)</a></li>
<li class="chapter" data-level="4.17.13" data-path="data.html"><a href="data.html#month-treasury-bill-minus-federal-funds-rate-tb6smffm"><i class="fa fa-check"></i><b>4.17.13</b> 6-Month Treasury Bill Minus Federal Funds Rate (TB6SMFFM)</a></li>
<li class="chapter" data-level="4.17.14" data-path="data.html"><a href="data.html#month-treasury-constant-maturity-minus-federal-funds-rate-t6mff"><i class="fa fa-check"></i><b>4.17.14</b> 6-Month Treasury Constant Maturity Minus Federal Funds Rate (T6MFF)</a></li>
<li class="chapter" data-level="4.17.15" data-path="data.html"><a href="data.html#coincident-economic-activity-index-for-the-united-states-usphci"><i class="fa fa-check"></i><b>4.17.15</b> Coincident Economic Activity Index for the United States (USPHCI)</a></li>
<li class="chapter" data-level="4.17.16" data-path="data.html"><a href="data.html#leading-index-for-the-united-states-usslind"><i class="fa fa-check"></i><b>4.17.16</b> Leading Index for the United States (USSLIND)</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="5" data-path="results.html"><a href="results.html"><i class="fa fa-check"></i><b>5</b> Results</a><ul>
<li class="chapter" data-level="5.1" data-path="results.html"><a href="results.html#presidential-cycles-1"><i class="fa fa-check"></i><b>5.1</b> Presidential Cycles</a></li>
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<li class="chapter" data-level="6.2.1" data-path="conclusion.html"><a href="conclusion.html#sp500-market-sectors"><i class="fa fa-check"></i><b>6.2.1</b> S&P500 Market Sectors</a></li>
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<li class="chapter" data-level="6.2.3" data-path="conclusion.html"><a href="conclusion.html#fourier-analysis-matching"><i class="fa fa-check"></i><b>6.2.3</b> Fourier Analysis matching</a></li>
<li class="chapter" data-level="6.2.4" data-path="conclusion.html"><a href="conclusion.html#fourier-analysis-contractionexpansion"><i class="fa fa-check"></i><b>6.2.4</b> Fourier Analysis Contraction/Expansion</a></li>
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<li class="chapter" data-level="7" data-path="ref.html"><a href="ref.html"><i class="fa fa-check"></i><b>7</b> References</a></li>
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<li><a href="https://www.michaelazer.com" target="blank">Copyright © 2020 by Michael Azer</a></li>
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<h1>
<i class="fa fa-circle-o-notch fa-spin"></i><a href="./">An Intelligent Market Cycle Detection System</a>
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<section class="normal" id="section-">
<div id="methodology" class="section level1">
<h1><span class="header-section-number">Chapter 3</span> Methodology</h1>
<p>The research will utilize machine learning techniques using economic data, political events, and technical indicators as features for classifying Stock Market cycles.</p>
<ul>
<li><p>Firstly, a study and reimplementation of earlier studies such as Kondratiev, Schumpeter, Kuznets, Juglar and Kitchin cycles.</p></li>
<li><p>Secondly, ARIMA variations, fourier transformations, moving average methods will be some of the features used in the model.</p></li>
<li><p>Thirdly, presidential elections (political parties) and political events (riots and wars) will also be added to the model.</p></li>
<li><p>Fourthly, employment reports, balance of payments, GDP, and other significant economic information will be added to the model.</p></li>
</ul>
<p>A classification model will be built using different machine learning classifiers, utilizing hyper-parameter optimization to robustly build an application that correctly identifies and mimics stock market cycles.</p>
<p>Find factors that identify the top and bottom of cycles, then go deeper into factors that determine the phases within</p>
<div id="data" class="section level2">
<h2><span class="header-section-number">3.1</span> Data</h2>
<p><strong>UNEDITED</strong>
We evaluate the technical indicators’ forecastability on the S&P 500, which proxies for the overall U.S. stock market. The returns are calculated as the log differences of current prices and prices from one period ahead. The S&P 500 contains the 500 most
actively traded large-cap common stocks in the U.S. stock market. As one of the most
historically extensive indices, the S&P 500 became available at daily, weekly and
monthly frequencies in 1938, 1918, and 1791, respectively.
We study the S&P 500 for several reasons. First, the long data series naturally shield against the potential data-snooping problem pointed out by Lakonishok and Smidt (1988) and Lo and MacKinlay (1990). Second, we have a wide range of technical indicators with sufficiently long data series designed specifically for the sophisticated U.S. market. The 500 stocks are listed on either the NYSE or the NASDAQ, the two largest American stock exchanges. This means that the S&P 500 index correlates highly with the NYSE and NASDAQ indices, which enables us to study technical indicators that contain information from both of these markets. Third, public investors hold the majority of the stocks in the U.S. market. Such heavy involvement of public investors satisfies the essential theoretical condition for many of the sentiment indicators, that uninformed investor sentiment becomes so influential that it can shift market movements. Last, the S&P 500 provides us with a sufficient number of stocks to ensure considerable market breadth when examining the market strength indicators.</p>
<p><span class="citation">(Fang, Qin, and Jacobsen <a href="#ref-fang2014technical">2014</a>)</span></p>
</div>
<div id="techniques" class="section level2">
<h2><span class="header-section-number">3.2</span> Techniques</h2>
<p>Pagan and Sossounov <span class="citation">(<a href="#ref-pagan2003simple">2003</a>)</span> use a BB-type definition <span class="citation">(<a href="#ref-granger1972cyclical">1972</a>)</span> to classify market regimes.</p>
<div class="figure"><span id="fig:unnamed-chunk-1"></span>
<img src="data/Data%20Preparation.png" alt="Data Preparation Methodology" width="60%" />
<p class="caption">
Figure 3.1: Data Preparation Methodology
</p>
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<h3> References</h3>
<div id="refs" class="references">
<div id="ref-fang2014technical">
<p>Fang, Jiali, Yafeng Qin, and Ben Jacobsen. 2014. “Technical Market Indicators: An Overview.” <em>Journal of Behavioral and Experimental Finance</em> 4. Elsevier: 25–56.</p>
</div>
<div id="ref-granger1972cyclical">
<p>Granger, CWJ. 1972. “Cyclical Analysis of Time Series: Selected Procedures and Computer Programs.” <em>Journal of the Royal Statistical Society: Series A (General)</em> 135 (2). Wiley Online Library: 284–84.</p>
</div>
<div id="ref-pagan2003simple">
<p>Pagan, Adrian R, and Kirill A Sossounov. 2003. “A Simple Framework for Analysing Bull and Bear Markets.” <em>Journal of Applied Econometrics</em> 18 (1). Wiley Online Library: 23–46.</p>
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