Data Trends for Investment Professionals


Stock Market Data: The Ultimate Guide [Part 1]

Introduction to Stock Market Data

The volume and variety of data used by stock market investors have exploded in recent years. Gone are the days when stock prices and company fundamentals sufficed to build a robust investment strategy.

Today, analysts and traders use a far wider set of data to inform their investment decisions: market structure data, sentiment and psychology data, consensus and survey data and much more.

Quandl has the richest collection of publicly available equity data on the internet. This is Quandl’s guide to stock market data: What’s available, where to find it and how to use it. This is the first in a two-part series; you can read the second part by following this link.

Reliable stock quotes are the foundation of any trading strategy. Analysts require accurate current stock quotes, to judge prevailing market conditions and bias-free historical stock prices, for backtesting and research.

Stock Quotes

There are a multitude of stock quote providers; however, not all of them are equivalent in quality. At a minimum, a good stock data publisher should have excellent, robust, transparent methodology for data collection, ideally directly from primary sources (exchanges). Historical stock prices need to be correctly adjusted for splits, dividends, spinoffs, mergers and other corporate actions.

Comprehensive documentation is a must: You should ask how the data is sourced, how it is organized, how it is adjusted if necessary, and how it can be accessed by the user. The data itself must be pristine: free of errors, gaps and outliers. Timeliness, reliability and consistency are essential for professional applications. Responsive customer support is another way that providers can add value to their data.

Surprisingly few data publishers satisfy all these criteria; nonetheless, the best stock market analysts insist on all of these. Quandl has aggregated several databases from a variety of publishers that score highly on all these components. These publishers cover both current and historical stock quotes, spanning different exchanges and stock classes. A list of different types of stock quotes follows:

Aggregated Quotes from Multiple Exchanges

The following three end-of-day stock price databases collect selected stock quotes from multiple US exchanges, collate and clean the data, and adjust for splits, dividends and other corporate actions.

  • Wiki Stock Prices – Free historical stock quotes for 3,000 US stock tickers, maintained by the Quandl community.
  • QuoteMedia Stock Prices – Professional-grade historical stock prices for 9,500 active US stock tickers, including dividends, splits and adjustments. Data from QuoteMedia, going back to 1996. Guaranteed daily update time.

Comprehensive Quotes from Single Exchanges

The following five end-of-day stock price databases cover a single exchange each, with comprehensive quotes for that exchange.

  • NYSE Stock Prices – End-of-day and historical quotes for all 11,500 stocks traded on the New York Stock Exchange.
  • NASDAQ Stock Prices – End-of-day and historical prices for all 28,500 NASDAQ stocks.
  • NYSE MKT (AMEX) Prices – Historical and end-of-day quotes for all 12,000 NYSE MKT stocks (formerly American Stock Exchange).
  • OTC Bulletin Board Prices – Prices for 12,000 over-the-counter bulletin board stocks, with history going back to 2007.
  • OTC Markets Group Prices – Current and historical quotes for over 48,000 OTC Markets Group stocks (formerly Pink Sheets).

The above five stock market databases all include daily quotes, historical prices, dividends, splits and other adjustments.

Intra-Day Stock Price Data

Quandl has historical intra-day data for five different market sector indexes. These five databases include trade-based Open, High, Low, Close and Volume for every stock in each index, for every one-minute bar. The databases are updated daily and cover over five years of market history.

Intra-day stock price data on Quandl is provided by AlgoSeek, a pioneering trading infrastructure company.

Global Stock Prices

Quandl has historical stock quotes, both adjusted and un-adjusted, for many international stock exchanges. Each of these databases includes daily OHLCV quotes and multiple years of history.

  • XJPX – Japan Exchange Group
  • XLON – London Stock Exchange
  • XSES – Singapore Exchange
  • XTSE – Toronto Stock Exchange
  • XTSX – Toronto Ventures Exchange
  • XBOM – Bombay Stock Exchange
  • XNSE – National Stock Exchange of India
  • TC1 – Consolidated India Stock Prices
  • XHKG – Hong Kong Stock Exchange
  • XSHE – Shenzhen Stock Exchange
  • XSHG – Shanghai Stock Exchange
  • DY4 – Consolidated Chinese Stock Prices

Most of these global stock databases are sourced from Exchange Data International, the leading institutional-grade provider of stock price history in the world.

Why Use Premium Stock Prices?
Why should an analyst pay for premium stock price data, when stock quotes are available for free from many different sources?
With stock price data, and indeed with all data, you get what you pay for. Free sources are readily accessible, but without exception, they are badly documented, poorly supported and difficult to use in professional applications. This would not matter if the data itself were of high quality but it rarely is; more often, it is rife with errors, gaps, outliers and bad calculations.
This is the reason why professional analysts rarely trust free stock data sources.

Stock Fundamentals

Fundamental analysis is one of the oldest and most effective ways to gauge the value of a company. It has its roots in a simple yet powerful idea: At a fundamental level, all businesses essentially carry out the same activities. Companies spend on salaries, sales and marketing; they invest in research and capital assets; they deliver goods and services; and they receive operating and investment income. It does not matter whether you are a software firm or an auto manufacturer or a bank; you still have to carry out these common activities.

These activities can all be reduced to financial quantities, which means that they can be directly compared across companies. This offers the analyst a way to evaluate the price of a software stock versus an auto stock versus a bank stock. Revenues, COGS, SG&A expenses, R&D spend, gross and net profit margins, P/E and PEG ratios, and free cash flow – these are just a few of the metrics that can be compared across companies, to paint an accurate picture of comparative value.

The advent of common accounting standards (GAAP and others) has made it ever easier to compare companies from different industries. Equally important are central regulatory bodies like the SEC and FSA, which mandate timely, standardized filings by all public companies. Finally, data firms like Reuters, Zacks, Inquiry and Mergent have led the way in aggregating this wealth of data, harmonizing it across reporting companies and packaging it for analysts to use.

Quandl has several stock fundamentals and financial ratio databases from multiple data publishers. Quandl’s stock fundamentals data allows you to instantly compare different companies with each other and over time. With data going back decades, easily accessible via API and integrations, these are some of the most popular databases on Quandl.

US Stock Fundamentals Data

These databases cover the US equity market with varying degrees of depth, granularity and aggregation:

Global Stock Fundamentals Data

Accurate fundamentals data for global stocks is difficult to come by. They are either expensive, unreliable or limited in scope (especially historical coverage and coverage for smaller countries). The following four databases on Quandl are unique in that they each offer high-quality fundamental indicators and financial ratios for select global markets in a trustworthy, accessible package.

These four databases cover stock fundamentals data for India, China, Europe and emerging Asia:

Fundamental Indicators

Here are some indicators that are available in these fundamentals databases.

Balance Sheet Income Statement Cash Flow Statement Financial Ratios
Cash & Equivalents Total Revenue Cash from Operations Earnings per Share
Investments Cost of Goods Sold Cash from Investments Price/Earnings Ratio
Receivables Sales, G and A Cash from Financing EBIT
Property & Equipment Research & Development FX Adjustment EBITDA
Goodwill & Intangibles Depreciation & Amortization Capital Expenditure Gross Margin
Total Assets Operating Expenses Starting Cash Profit Margin
Accounts Payable Operating Income Ending Cash Free Cash Flow
Long-Term Debt Investment Income Asset Turnover
Total Liabilities Non-Operating Income Inventory Turnover
Common Stock Pre-Tax Income Receivable Turnover

Getting Started with Quandl
Quandl is a data platform designed for traders, analysts, developers and quants. We bring together 100s of professional-grade financial and economics databases and make them available on a single website.
Quandl works on an a la carte subscription model. You can subscribe to as many or as few databases as you want. Cancel at any time with no penalty.
We offer free trial access to all our databases. To activate, just sign up for a free Quandl account (no credit card required).


Earnings Estimates and Surprises

After stock prices and stock fundamentals, quarterly earnings are by far the most commonly tracked information for a given company.

In a financial sense, the expected price of any stock is merely the net present value of all the cash flows associated with that stock – that is, the company’s dividends and distributions – all of which need to come out of future earnings. Earnings thus have a direct relationship with share prices.

In a pragmatic sense, earnings estimates are important because they are forward-looking. Stock quotes and company financials are always retrospective; they tell you what the company has done in the past, but they don’t necessarily convey information about the future. Earnings estimates do.

Finally, earnings estimates are important because they reflect investor consensus. To the extent that an analyst’s estimate for earnings differs from the market consensus, there is an opportunity for the analyst to profit from corrections or convergence.

Conventional Earnings Estimates – US and Canada

A wealth of indicators has arisen around basic earnings estimates: earnings announcement schedules, company “guidance” to analysts, earnings “surprises” where actuals deviate from estimates, trends in earnings and so on. The following databases are available on Quandl:

  • Earnings Estimates – Current consensus earnings estimates for 5,000 companies based on surveying 2600 analysts from 185 firms.
  • Earnings Trends – Current earnings estimates measured 7, 30, 60 and 90 days ago, reflecting upward or downward trends in analyst expectations.
  • Earnings Surprises – Historical and actual earnings and surprise calculations, for 16,000 companies to 1994.
  • Earnings Estimate History – Past consensus estimates for earnings for 5,000 public firms going back to 1979.
  • Earnings Announcements – Expected earnings announcements, EPS forecasts and dates, both confirmed and estimated, for 7,000 firms.
  • Pre-Announcement History – Historical company guidance data for 5,000 companies going back to 2002; useful for backtesting.

Other Measures of Earnings and Sales – US and Canada

Earnings can be measured in several ways. Some analysts argue that EBITDA, or Sales, or “Street” Earnings, are more predictive of stock price movements than “conventional” earnings. These alternative measures are available in the below Quandl databases:

  • Street Earnings Estimates – Consensus earnings estimates for 5,000 companies using “Street” accounting method, based on surveying 2,600 analysts from 185 research firms.
  • Street Earnings History – Historical earnings estimates calculated using “Street” accounting method.
  • EBITDA Estimates – Consensus estimates for EBITDA, calculated to be comparable to Income Statement releases.
  • Sales Estimates – Consensus sales estimates for 4,000 US and Canadian companies for the forthcoming quarters and years.
  • Sales Estimate History – Historical sales estimates from analysts, useful for backtesting past consensus versus past performance.
  • Sales Surprises – Sales estimates versus actual sales numbers, adjusted to match accounting methodology.
  • Growth History – History of long-term growth estimates for over 5,000 publicly traded companies.

The field of earnings estimation was pioneered by Len Zacks in the 1970s, and Zacks Research remains one of the leading authorities in this area. The above US and Canada earnings databases on Quandl are all published by Zacks Research. Each database benefits from decades of expert knowledge and process refinement.

Earnings Estimates and Surprises

Corporate actions like dividends, splits, mergers, spinoffs and buybacks are important leading indicators of company performance, signaling what management thinks of the prospects of the company, and the best use of cash. Research suggests that stock splits often follow a sustained period of stock price outperformance. Large cash reserves can be a signal of excellent current business profitability/cash flow but they can also signal a lack of investable growth opportunities.

Sophisticated analysts incorporate corporate actions into their models, looking for predictive patterns in these actions. While not all actions translate directly into buy/sell signals, the combination of actions and other fundamentals can often hold useful information. There may also be arbitrages available temporarily, during the exercise of an action.

Quandl has several databases covering corporate actions for the US and global equity markets. Some of these are listed below:

Note that corporate actions also affect nominal stock prices; however, sophisticated investors know to use adjusted stock prices in their analysis, and not nominal prices. The historical stock price databases listed in section 2 above include both adjusted and un-adjusted stock prices.

Adjusting Stock Prices for Corporate Actions
Corporate actions, such as cash and stock dividends, splits, spinoffs, reverse splits, mergers, acquisitions and rights offerings, all have the potential to affect nominal stock prices. However, many of these actions have no real economic impact; hence this effect on nominal prices is misleading. To calculate true portfolio returns, analysts must use adjusted stock prices.
The adjustments required to capture the actual economics of a corporate action can be quite complicated, depending on the nature of the action.
Quandl’s comprehensive guide to the mathematics of stock price adjustments can be found here. This guide is an essential resource for analysts looking to understand the impact of corporate actions on nominal stock prices.

Continue reading Part Two of our Ultimate Stock Market Data Guide.

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