Stock market performance by president chart Guide

Stock market performance by president chart Guide

<p><strong>What you will learn:</strong> what a stock market performance by president chart is, why analysts produce it, the data and methodological choices that change results, common chart types, empirical summaries from public studies, and step‑by‑step reproducible workflows (including a simple Python example). If you want accurate comparisons across administrations, this guide explains the required data choices and the caveats every reader must see.</p> <h2 id="overview-and-purpose">Overview and purpose</h2> <p>A stock market performance by president chart is a visualization and analysis that tracks how major U.S. equity indices perform across presidential terms or from election/inauguration dates. Researchers, journalists, investors and educators create these charts to provide a comparative historical perspective, to highlight election‑period market behavior, and to explore whether market returns cluster by presidency, party or business cycle. Common indices used are the S&amp;P 500, the Dow Jones Industrial Average (DJIA) and the NASDAQ Composite. Because the exact measurement choices matter, any published stock market performance by president chart should state its data source, start/end conventions and whether dividends are included.</p> <h2 id="data-sources-and-coverage">Data sources and coverage</h2> <p>Typical primary data sources for building a stock market performance by president chart include official index vendors and major data aggregators. Examples of public and academic sources often used are S&amp;P historical series (via vendors), major financial terminals and databases, Federal Reserve Economic Data (FRED), CRSP for academic total‑return series, and long‑running public pages like Macrotrends and StockCharts. Data vintage and availability differ by index: the DJIA has century‑plus daily price records, while reliable total‑return series for the S&amp;P 500 are commonly available back to the mid‑20th century via CRSP and index providers.</p> <p>When referencing market conditions or earnings that can influence presidential‑era returns, timely reports matter. For example, as of Jan 16, 2026, according to FactSet, about 7% of S&amp;P 500 companies had reported fourth‑quarter results and analysts estimated an 8.2% year‑over‑year increase in EPS for the quarter — the tenth consecutive quarter of annual EPS growth if realized. Also, institutional topical reports (such as Q4 2025 market reviews) can shape short‑term patterns that appear inside a presidential term.</p> <h2 id="methodology">Methodology</h2> <h3 id="start-and-end-points">Start and end points (inauguration vs election date)</h3> <p>One of the largest choices when making a stock market performance by president chart is the date convention: start at the election date, the inauguration date, or another fixed calendar boundary. Two common conventions are:</p> <ul> <li>Election‑date convention: measure returns from the date of the election (usually early November) to the next election or to the end of the administration. This captures market reactions to the election outcome immediately.</li> <li>Inauguration‑date convention: measure returns from the inauguration (usually Jan 20) to the next inauguration. This aligns performance strictly with the period the president holds office.</li> </ul> <p>Implication: short‑window events around November–January (e.g., large policy announcements, surprise economic news, or major earnings seasons) can cause materially different rankings depending on the chosen convention. Any stock market performance by president chart must state which convention it uses.</p> <h3 id="index-choice-and-total-return-vs-price-return">Index choice and total return vs price return</h3> <p>Charts may use price‑only indices or total‑return indices (which assume dividends are reinvested). Price‑only series understate equity returns over long horizons because dividends contribute a significant share of long‑term equity returns. For example, a stock market performance by president chart built on S&amp;P 500 price levels will typically show lower cumulative returns than one using the S&amp;P 500 total‑return index. Academic and professional analyses frequently favor total‑return data to present an investor‑centric view.</p> <h3 id="time-resolution-and-normalization">Time resolution and normalization</h3> <p>Charts use daily, monthly or quarterly resolution. Common normalizations include percent‑change, indexing each series to 100 at the start of the term, or growth‑of‑$1 (how $1 invested at term start would evolve). Monthly‑end aggregation reduces noise from intra‑month trading and is popular for presidential comparisons. Percent returns and indexed series are easier to compare visually across terms of different lengths.</p> <h3 id="treatment-of-partial-acting-presidencies">Treatment of partial/acting presidencies and term overlaps</h3> <p>When vice presidents assume office mid‑term or a president dies or resigns, analysts differ on representation. Options include:</p> <ul> <li>Attribution to the individual who held office for each calendar day (most granular).</li> <li>Attribute result to the elected president but footnote the mid‑term change.</li> <li>Combine multi‑term consecutive presidencies into a single aggregated bar or line for readability.</li> </ul> <p>Clarity on the chosen approach is required for any credible stock market performance by president chart.</p> <h3 id="inflation-adjustment-and-other-adjustments">Inflation adjustment and other adjustments</h3> <p>Analysts sometimes show real (inflation‑adjusted) returns to compare purchasing‑power outcomes. Others may present nominal returns but annotate important macro factors: unemployment, GDP growth, inflation, or large monetary policy shifts. Because monetary policy and business cycles are major drivers of equity returns, many authors include side‑by‑side macro panels or scatterplots to show correlation (not causation).</p> <h2 id="common-chart-types-and-visualizations">Common chart types and visualizations</h2> <p>Popular visual formats in a stock market performance by president chart include:</p> <ul> <li>Running cumulative return lines: separate line for each president, indexed to the same start.</li> <li>Bar charts of term total returns: one bar per president showing cumulative return over the term.</li> <li>Growth‑of‑$1 stacks: visualizing how $1 would grow under each presidency.</li> <li>Heatmaps by month‑in‑term: showing typical monthly returns across terms to reveal seasonal or cycle patterns.</li> <li>Presidential‑cycle averaged curves: averaging returns across terms by year‑into‑term to show common early‑term or late‑term effects.</li> <li>Scatterplots vs macro variables: plotting term returns against GDP growth, inflation, or rate changes to inspect relationships.</li> </ul> <h2 id="empirical-findings-and-summary-statistics">Empirical findings and summary statistics</h2> <p>Published summaries of stock market performance by president charts often report the following types of finding: average term returns, best and worst presidency returns, distribution of election‑year returns, and party‑level averages. Results vary with methodology. Some widely cited public pages and institutional reports provide examples and figures:</p> <ul> <li>Macrotrends publishes long series comparing index returns by president, often using price and sometimes total returns.</li> <li>Dimensional publishes discussion pieces that emphasize statistical caveats and the relative contribution of macro factors.</li> <li>MFS and similar asset managers have produced PDF analyses that average presidential cycles over long samples and adjust for macro conditions.</li> <li>Popular business outlets and wealth managers sometimes create ranked lists (best/worst presidents by market return), with the ranking sensitive to start/end conventions and dividend inclusion.</li> </ul> <p>Because different authors use different index definitions and start dates, the same president can appear as a top performer in one chart and a middling performer in another. That variability is why methodology disclosure is essential.</p> <h2 id="party-comparisons-and-academic-findings">Party comparisons and academic findings</h2> <p>Analyses that compare returns across presidents by party (Democrat vs Republican) produce contested results. Some simple averages suggest one party may have delivered higher average returns over the sample period, but academic studies highlight confounding factors: business‑cycle timing, monetary policy regimes, global shocks, and starting valuations. The Wikipedia entry summarizing U.S. economic performance by presidential party collates many such results and shows how sensitive outcomes are to sample selection and controls. Robust academic work typically uses regression analysis controlling for common drivers and finds limited evidence that party alone explains much of stock market variance.</p> <h2 id="notable-presidential-case-studies">Notable presidential case studies</h2> <p>Short capsule summaries (contextual, not causal):</p> <ul> <li>Franklin D. Roosevelt — markets moved from the Depression trough into long‑term recovery and wartime economy; long horizon context matters for returns.</li> <li>Herbert Hoover — sharp market decline in 1929–1932 around the Great Depression; short‑term crisis dynamics dominated.</li> <li>Ronald Reagan — strong market performance in the 1980s amid disinflation, monetary policy changes and structural shifts in the economy.</li> <li>Barack Obama — recovery and an extended bull market after the 2008–2009 financial crisis; fiscal and monetary stimulus and the corporate profit cycle were important contributors.</li> <li>Donald Trump — notable volatility inside the term, with episodes driven by trade and tariff news, earnings trends and macro conditions.</li> <li>Joe Biden — recent performance is intertwined with post‑pandemic recovery dynamics, inflation and central bank policy adjustments.</li> </ul> <p>Each capsule connects to broader macro, policy and earnings cycles; readers should avoid assuming a direct causal link between the name on the presidency and daily market moves.</p> <h2 id="interpretation-causation-vs-correlation-and-limitations">Interpretation, causation vs correlation, and limitations</h2> <p>The key caveats for any stock market performance by president chart are:</p> <ul> <li>Presidential policies are one of many drivers: monetary policy, global macro shocks, corporate earnings, and technological change often matter more for markets than executive actions alone.</li> <li>Method choices are decisive: index used, dividend treatment, start/end convention, and inflation adjustment all change outcomes.</li> <li>Charts show correlation not causation: a president’s name coinciding with a bull or bear market does not prove the president caused the movement.</li> <li>Short samples are noisy: single‑term analysis is unreliable for inference; multi‑term aggregation helps but still faces structural regime shifts.</li> </ul> <p>For example, earnings season and corporate fundamentals frequently shape short‑run index returns. As of Jan 16, 2026, FactSet’s coverage of fourth‑quarter earnings pointed to an estimated 8.2% EPS increase for the S&amp;P 500 — a continuation of earnings trends that can influence market direction inside an administration. Analysts and chart authors commonly annotate presidential‑period charts with earnings and macro overlays to show these interacting drivers.</p> <h2 id="use-by-investors-media-and-policymakers">Use by investors, media, and policymakers</h2> <p>Market participants use the charts for different purposes:</p> <ul> <li>Media: to tell a simple story during election cycles (rankings and best/worst lists).</li> <li>Investors: to provide long‑run context for asset allocation or to explore seasonality.</li> <li>Policymakers and academics: to test hypotheses about policy effects or business‑cycle timing.</li> </ul> <p>Recommended practice: treat these charts as descriptive history and avoid timing or allocation decisions based solely on a president’s name. Combine presidential charts with earnings, valuation and interest‑rate information before making comparisons.</p> <h2 id="reproducibility-and-how-to-create-the-charts">Reproducibility and how to create the charts</h2> <p>Reproducibility is straightforward when data and code are shared. Basic steps to create a stock market performance by president chart:</p> <ol> <li>Choose index and data source (S&amp;P 500 total‑return if you want investor‑level returns; specify price vs total‑return).</li> <li>Select start/end convention (inauguration vs election date) and collect exact dates for each president.</li> <li>Aggregate to the desired frequency (daily, monthly) and compute percent returns or indexed series (set index = 100 at term start).</li> <li>Visualize: lines for cumulative return, bars for total return, heatmaps for monthly seasonality.</li> <li>Document everything: data vendor, download date (data vintage), and code used to reproduce results.</li> </ol> <p>Common tools: Python (pandas, matplotlib, seaborn), R (tidyverse, ggplot2), and spreadsheets for smaller samples. Below is a compact Python example that reads monthly S&amp;P 500 total‑return data and constructs presidential term series. The code is intended as reproducible starting code; adapt it to your vendor's file formats and your chosen conventions.</p> <h3 id="sample-python-code">Sample Python/pandas example</h3> <pre><code>import pandas as pd

load monthly total-return index (date as index, column 'TR')

data must contain a complete span covering all terms of interest

sp500 = pd.read_csv('sp500_total_return_monthly.csv', parse_dates=['date'], index_col='date')

define presidents with term start and end (example entries)

presidents = [ {'name':'Frank Roosevelt','start':'1933-03-04','end':'1945-04-12'}, {'name':'Harry Truman','start':'1945-04-12','end':'1953-01-20'}, # ... add each president with ISO dates matching your convention ]

prepare results container

terms = [] for p in presidents: start = pd.to_datetime(p['start']) end = pd.to_datetime(p['end']) series = sp500.loc[start:end]['TR'] # index to 100 at term start indexed = (series / series.iloc[0]) * 100 indexed.name = p['name'] terms.append(indexed)

combine and plot

df = pd.concat(terms, axis=1)

export df to csv for reproducibility

df.to_csv('presidential_sp500_indexed.csv')

simple plot

import matplotlib.pyplot as plt plt.figure(figsize=(10,6)) df.plot(legend=False) plt.title('S&P 500 Total Return Indexed to 100 by Presidential Term') plt.xlabel('Date') plt.ylabel('Indexed value (start=100)') plt.show()

Notes on the code: replace the CSV filename with your data source. Ensure your total‑return file includes dividend reinvestment. Record the download date and data vendor in a README so others can reproduce the chart.

<h2 id="interactive-resources-and-prominent-public-charts">Interactive resources and prominent public charts</h2> <p>Several public interactive exhibits demonstrate the concepts described above. Examples include long‑running vendor pages that show indexed performance by president, chart galleries that separate series by party, and asset manager PDFs that average presidential cycles with macro overlays. When using or citing these resources, confirm the data vintage and the price vs total‑return choice. For users who want to publish or share interactive charts, consider hosting the reproducible data and code and use charting libraries to allow readers to toggle conventions.</p> <h2 id="scholarly-debate-and-further-reading">Scholarly debate and further reading</h2> <p>Key topics in academic debate include whether party affiliation or the identity of a president has a statistically significant effect on long‑run stock returns after controlling for macro variables, and whether predictable presidential‑cycle patterns exist once macro timing is accounted for. Institutional reports from asset managers and databases (Dimensional, MFS, Schroders and others) provide accessible summaries and often include regression‑style tests. For deeper work, consult academic journals on political economy and finance where authors present controlled tests using CRSP or similar datasets.</p> <h2 id="see-also">See also</h2> <ul> <li>Presidential cycle (finance)</li> <li>S&amp;P 500 historical performance</li> <li>U.S. economic performance by presidential party</li> <li>Earnings season and index earnings trends</li> </ul> <h2 id="references">References</h2> <p>Primary sources and illustrative public analyses often cited when constructing or explaining a stock market performance by president chart include: Macrotrends pages on Stock Market Performance by President; Dimensional articles on the limits of presidential attribution; Kiplinger summaries; stock chart galleries such as StockCharts' Presidential Cycles; asset manager PDFs or briefs from MFS and Schroders; Darrow Wealth Management illustrative charts; and public data from FRED and CRSP. For earnings and short‑term drivers inside presidential terms, FactSet earnings coverage (as of Jan 16, 2026) and market news summaries provide contemporaneous context.</p> <h2 id="external-resources">External resources and data notes</h2> <p>To reproduce charts, use vendor total‑return series (CRSP or index provider), FRED for macro overlays, and institutionally sourced datasets for robustness checks. Where available, publish the CSV used and the exact download date. For timely context: as of Jan 16, 2026, FactSet reported S&amp;P 500 estimated Q4 EPS growth of 8.2% year‑over‑year, and institutional commentaries (e.g., Q4 2025 crypto market reviews) noted mixed signals across markets and on‑chain adoption metrics. These short‑term developments can create intra‑term market moves that appear in presidential summaries; annotate charts accordingly.</p> <h2 id="editorial-guidance-and-best-practices">Editorial guidance and best practices</h2> <p>When publishing any stock market performance by president chart:</p> <ul> <li>Always state methodology: index, total vs price, start/end convention, frequency and date vintage.</li> <li>Avoid causal claims without econometric controls; present correlations and alternative explanations.</li> <li>Publish downloadable data and code for reproducibility.</li> <li>Annotate charts with major macro events and earnings seasons to show interacting drivers.</li> </ul> <h2 id="bitget-note">Bitget note</h2> <p>If you publish charts or trade based on historical analysis, preserve your datasets and code in a secure repository and use exchange and wallet tools that prioritize provenance and safety. For traders who also manage crypto or tokenized data alongside traditional markets, Bitget provides exchange services and custody products designed to support secure asset management. For on‑device or self‑custody wallets, consider Bitget Wallet for integration with Bitget services.</p> <h2 id="final-remarks">Further exploration and next steps</h2> <p>Stock market performance by president chart comparisons are useful historical tools when produced and read carefully. They are best used alongside earnings data, macro indicators and valuation metrics. If you want a hands‑on start, download a monthly total‑return series for the S&amp;P 500, pick a clear start/end convention, run the sample Python script above, and publish the CSV and code. Readers who want to publish interactive exhibits can extend the script to add macro overlays (GDP, inflation, Fed funds rate) and an earnings‑season annotation layer.</p> <p>To explore more, test different conventions (election vs inauguration, price vs total return) and compare how the rankings and visual patterns change. Document each experiment — reproducibility is the best way to make presidential comparisons credible and useful.</p> <footer> <p><small>Reporting dates and timely items cited in this guide: As of Jan 16, 2026, FactSet data reported an 8.2% estimated year‑over‑year EPS increase for the S&amp;P 500 fourth quarter; as of Dec 31, 2025, institutional quarterly reviews noted mixed price signals in crypto markets despite rising on‑chain activity. Market news items cited for context were reported in mid‑January 2026 by major financial news aggregators. Always check original data vendors for the latest figures and the exact download date before reproducing any chart.</small></p> <p><small>This page is informational and educational. It does not provide investment advice.</small></p> </footer>