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An example of a bond.

Investment banks

Independent

  • Bloomberg (independent institutional global research firm)
  • Monness & Crespi
  • Morningstar, Inc. (independent institutional global research firm)
  • Standard & Poor's, which provides its reports through some discount brokerages (e.g. TD Ameritrade)
  • The Motley Fool, which provides private financial and investing advice
  • Zacks Investment Research

Securities research is a discipline within the financial services industry. Securities research professionals are known most generally as "analysts", "research analysts", or "securities analysts"; all the foregoing terms are synonymous. Research analysts produce research reports and typically issue a recommendation: buy ("overweight"), hold, or sell ("underweight"); see target price and trade idea.

These reports can be accessed from a number of sources, and brokerages will often offer the reports free to their customers.[1] Research can be categorized by the security type, as well as by whether it is buy-side research or sell-side research; analysts further focus on particular industries. Although usually associated with fundamental analysis, research also focuses on technical analysis, and reports will often include both. See also Financial analyst § Securities firms.

Analyst specialization

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Securities analysts are commonly divided between the two basic kinds of securities: equity analysts (researching stocks and their issuers)[2] and fixed income analysts (researching bond issuers); there are various other financial instruments. There are some analysts who cover all of the securities of a particular issuer, stocks and bonds alike.

Securities analysts are usually further subdivided by industry specialization (or sectors)—among the industries with the most analyst coverage are biotechnology, financial services, energy, and computer hardware, software and services. Analysts will regularly attend quarterly earnings conference calls; see also earnings guidance.

Fixed-income analysts are also often subdivided by asset class—among the fixed income asset classes with the most analyst coverage are convertible bonds, high yield bonds (see high-yield debt), and distressed bonds (see distressed securities). Although technically not securities, syndicated bank loans typically fall within the domain of fixed income analysts, and are covered, as if they were bonds, by reference to the industry of their borrowers or asset class in which their credit quality would place them. See Corporate bond § Risk analysis.

Research can be further categorized as buy-side research or sell-side research. Sell-side research is conducted by sell-side analysts at investment banks and independent equity research boutiques, and is sold to buy-side investors. Buy-side research, however, is usually not published as it is created for internal use at an asset manager or hedge fund. Sell-side research is offered as part of a broad set of financial services including broking and corporate finance.

New regulation in Europe, Markets in Financial Instruments Directive II (MiFID II), is set to change how research is bought.[3] Research must be "unbundled" from execution costs and priced by the research provider. It has typically been accessed by institutional investors through Thomson Reuters subscription services or Bloomberg terminals but marketplaces like Research Exchange Ltd have emerged where individual research reports or subscriptions can be purchased.

Independent equity research has largely sprung into existence as a result of scandals such as Enron, Lernout & Hauspie and Worldcom where investment banks wrote positive research despite deteriorating fundamentals or fraudulent management. Credit rating agencies such as Moody's, Fitch, and S&P provide a similar service for bond securities. There are also a few retail investor firms such as Morningstar, SEENSCO, Valueline, Zacks Investment Research and AC Investment Research.

Regulations

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Qualifications

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Main article: List of securities examinations

Qualifications for investment professionals vary by country, with many countries having specific examination boards which handle certification. A notable certification is the CFA.

In the United States

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In the US, as of 2002, investment professionals seeking to become sell-side equity research analysts must pass the Research Analyst examination administered by FINRA. The exam is divided into two parts: 86 and 87. The Series 86 Research Analyst exam is the Quantitative portion consisting of material from introductory economics and financial accounting. The Series 87 Research Analyst exam is the Regulatory portion consisting of material from the Securities Act of 1933, Securities Exchange Act of 1934, NASD and NYSE Rules. Prior to the update to the FINRA licensing exams in 2018, the Series 7 examination/license was a pre-requisite for the Research Analyst exams. Now, candidates must pass the Securities Industry Essentials exam before taking the Series 86 and 87.[4][5] The Series 7 Top-Off and Series 63 exams are sometimes required at the state-level for research analysts. Successful completion of the CFA level I & II exams provides a waiver for the Series 86 exam, but not the Series 87 examination.[6]

In Hong Kong

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In Hong Kong, investment professionals must pass the Paper 1 administered by the Hong Kong Securities Institute.[7] Passing this exam allows the individual to receive the Type 4 license to be a publishing research analyst in Hong Kong.[8]

Industry rules

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Buy-side and independent research are generally unregulated. Sell-side research is subject to regulation by the securities authorities of the locales where it is performed. The large majority of all sell-side research is performed either in the United Kingdom or the United States. UK sell-side research is regulated by the Financial Services Authority. US sell-side research has a more complex regime of regulation. The U.S. Securities and Exchange Commission has prescribed certain relevant rules (among them Regulation AC and Regulation FD) but has generally delegated research regulation to the self-regulatory organizations. The principal SROs (the National Association of Securities Dealers and the New York Stock Exchange) have issued detailed regulations of equity research, and much more cursory regulation of fixed income research. (With respect to the latter, the NYSE and the NASD have re-delegated the substance of regulation to the broker-dealer trade group Securities Industry and Financial Markets Association as the merger successor of the Bond Market Association, to whom the role was originally assigned.) The impact upon securities research regulation of the pending merger of the NASD with the regulatory arm of the NYSE is currently uncertain.

In the immediate aftermath of the excesses of the 1990s referred to above, Eliot Spitzer, Governor of the State of New York, asserted a significant role in policing securities research performed by New York-based analysts; it is unclear whether oversight by the New York State Attorney General will become a long-term meaningful component of securities research. The going-forward conduct provisions of a master settlement agreement between (on the one hand) most of the aforesaid U.S. regulators and (on the other hand) many of the largest U.S. broker-dealers, is an important source of ongoing regulation, with the force of law for the broker-dealers who are party to it, and a strong, if not formally legally binding effect, on broker-dealers not party to it.

The latest rule changes are coming into effect in Europe under MiFID II. Research has been deemed an inducement to trade and must be "unbundled" from execution costs.[9] The new rules around Research Unbundling are viewed as a major challenge by asset managers[10] as they materially alter the way in which research has been consumed. Research budgets must be set in advance, payments for research separated from execution, the quality of research regularly assessed, and auditable records of consumption and payments kept.[9] New platforms launched in anticipation of the rules coming into effect. At the same time, accelerator-type initiatives like Boost Research are being created to help independent analysts set up their own businesses for providing independent research and analysis.[11]

See also

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References

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Further reading

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Revisions and contributorsEdit on WikipediaRead on Wikipedia

Securities research

View on Grokipedia
from Grokipedia
Securities research is a specialized within the industry focused on the systematic analysis and evaluation of financial instruments, including , bonds, and other securities, to generate insights and recommendations that inform decisions. Professionals in this field, known as research analysts, examine company financials, market trends, economic indicators, and industry dynamics to assess the value, risks, and potential returns of these assets. This process typically culminates in research reports that provide buy, hold, or sell ratings, enabling investors to allocate capital effectively while mitigating risks. The core activities of securities research encompass both fundamental analysis, which involves dissecting balance sheets, income statements, and reports to determine intrinsic value, and technical analysis, which studies price patterns and trading volumes to predict future movements. Analysts employ valuation models such as (DCF), comparable company analysis, and precedent transactions to quantify opportunities. Research is conducted across various scopes, including company-specific evaluations, sector overviews, and macroeconomic assessments, often integrating data from regulatory filings like those available through the SEC's database. Securities research operates primarily through two analyst categories: sell-side analysts, who work at investment banks and brokerages to produce reports for institutional and retail clients, and buy-side analysts, employed by asset managers, hedge funds, and pension funds to guide internal portfolio strategies. It covers diverse security types, including equity securities (stocks representing ownership) and debt securities (bonds denoting creditor status), with specialized rules governing equity and debt research to ensure independence. Regulatory frameworks, such as those from the (FINRA), mandate conflict-of-interest disclosures, supervisory oversight, and restrictions on analyst trading to promote objectivity and transparency in reports and public communications. In an evolving landscape, securities research increasingly incorporates advanced tools like for and predictive modeling, enhancing efficiency while adapting to global market complexities and regulatory changes. This field plays a pivotal role in capital markets by fostering informed investing, supporting through efficient , and upholding market integrity.

Overview

Definition and Scope

Securities research is the systematic evaluation of financial instruments known as securities, including , bonds, and , to assess their intrinsic value, potential risks, and returns for purposes. This process aims to inform decisions by providing objective analyses and recommendations, such as buy, hold, or sell ratings, based on economic, industry, and company-specific factors. The discipline is integral to the industry, where analysts apply quantitative and qualitative methods to forecast performance and guide portfolio strategies. The scope of securities research primarily encompasses equity securities (like common and preferred stocks), fixed-income securities (such as bonds and treasuries), and (including options and futures), focusing on their tradability and market dynamics. It differs from broader , which may involve internal corporate budgeting, assessment, or macroeconomic modeling without direct ties to marketable investments. While securities research may briefly reference the roles of buy-side and sell-side analysts or methods like fundamental and , its core remains centered on investment valuation rather than operational finance. Key outputs of securities research include detailed research reports that synthesize findings, valuation models (such as or comparable company analysis) to estimate , and forward-looking forecasts for earnings, revenue, and market trends. These deliverables are tailored to securities, enabling investors to compare opportunities across . Analysts commonly rely on specialized data sources like for real-time market intelligence and Morningstar databases for comprehensive stock and fund ratings to support their analyses.

Importance in Financial Markets

Securities research serves as a vital tool for informing decisions among institutional and retail investors, offering in-depth evaluations of securities' value, risks, and potential returns that guide portfolio allocation and trading strategies. By synthesizing complex financial into accessible reports and forecasts, it empowers investors to make evidence-based choices rather than relying solely on incomplete public disclosures. This process substantially reduces in financial markets, where insiders often possess advantages over external participants, as evidenced by studies showing that increased analyst coverage causally lowers equity misvaluation by aligning market prices more closely with intrinsic values. The influence of securities research extends to enhancing overall market efficiency, , and by integrating analyst-generated information into trading dynamics, which helps prices reflect fundamental economic realities more accurately. Greater analyst coverage, for example, mitigates managerial tendencies toward excess cash hoarding—reducing it by up to 24% across coverage deciles—thereby improving corporate liquidity management and market fluidity without compromising operational needs. However, lapses in research quality can undermine these benefits; during the , sell-side analysts' persistent optimism and reluctance to revise downward erroneous forecasts on mortgage-related securities exacerbated mispricing, contributing to the asset bubble's burst and widespread liquidity evaporation. Analysts further bolster corporate governance by scrutinizing executive decisions, financial disclosures, and strategic initiatives, functioning as independent watchdogs that pressure management toward greater accountability and ethical practices. Firms receive superior forecast quality, including higher accuracy in target prices, more optimistic forecasts, and lower dispersion in earnings estimates, creating a feedback loop that incentivizes robust internal controls. On a broader scale, securities drives economic significance by enabling precise capital allocation, directing funds from savers to high-potential enterprises and away from underperformers, which amplifies and sustains GDP growth. In countries with developed financial markets—where plays a key informational role—the elasticity of industry to growth opportunities is markedly higher, with correlations between financial depth and allocation reaching 0.554 across nations, underscoring its contribution to long-term prosperity and crisis resilience.

History

Early Development

The emergence of securities research can be traced to the late 18th and 19th centuries, coinciding with the establishment of organized stock exchanges and the growing need for investors to evaluate company financials amid expanding trade in equities. The (NYSE), founded in 1792 through the signed by 24 brokers, marked a pivotal moment by formalizing securities trading in the United States and necessitating basic analytical practices to assess stock values based on available company reports and economic conditions. In , similar developments occurred with the London Stock Exchange's formalization in 1801, where early analysts focused on dividend yields and firm creditworthiness using manual reviews of balance sheets and trade publications, reflecting a shift from speculative trading to more informed evaluation of equity securities. By the early , pre-digital practices dominated securities research, relying on printed financial reports, telegraphs for disseminating , and rudimentary ratio analysis without computational aids. Analysts manually compiled data from sources like the Commercial and Financial Chronicle, using tools such as the (current assets divided by current liabilities), which emerged in the as a key metric for assessment, and later studies by Alexander Wall in 1919 that introduced industry-specific benchmarks. Telegraphs and ticker tapes enabled real-time price transmission across exchanges, allowing clerks to perform and basic , while printed bulletins from firms provided qualitative insights into company prospects. A landmark contribution came in with and David Dodd's (1934), which systematized principles by emphasizing intrinsic value calculation through rigorous examination of , margins of safety, and basic ratios like price-to-earnings. This work, born amid the , influenced the professionalization of research by advocating objective, quantitative approaches over speculation. The further catalyzed institutionalization, prompting investment banks to establish dedicated research departments in to provide clients with independent analysis and restore market confidence; for instance, initiated internal research efforts during this period to evaluate securities more thoroughly.

Key Regulatory Milestones

The Securities Act of 1933 established the foundational requirement for full and fair disclosure of material information by issuers offering securities to the public, creating a transparent environment essential for securities research by ensuring analysts have access to verified data on risks and financials. This act, enforced by the newly formed Securities and Exchange Commission (SEC), prohibited fraudulent practices in securities sales and mandated registration statements detailing business operations, thereby laying the groundwork for research based on standardized disclosures. Complementing this, the Securities Exchange Act of 1934 regulated secondary trading markets and required periodic reporting by listed companies, further promoting ongoing transparency that supports analyst evaluations and investor decision-making. These acts collectively shifted securities research from opaque practices to a disclosure-driven model, mitigating information asymmetries in financial markets. Following high-profile corporate scandals such as Enron and WorldCom, which exposed conflicts of interest in analyst research, the Global Analyst Research Settlement of 2003 represented a pivotal reform in the United States. Ten leading investment banks agreed to a $1.4 billion penalty, with $387.5 million allocated to restitution for affected investors and $432.5 million dedicated to funding independent research providers. The settlement imposed structural separations between research and investment banking divisions, barring analysts from involvement in deal solicitations, roadshows, or compensation tied to banking revenue, and mandating clear disclosures of potential conflicts in research reports. These measures aimed to restore investor trust by curbing biased recommendations, leading to empirical improvements in the objectivity of equity research outputs. In the , the Markets in Financial Instruments Directive II (MiFID II), effective from January 3, 2018, introduced the unbundling of costs from execution commissions to address hidden conflicts and enhance cost transparency for investors. Under this regime, firms must separately account for and pay for , either through direct client billing or segregated payment accounts, preventing the bundling of fees into trading costs. This reform targeted sell-side independence by decoupling production incentives from trading volumes, allowing asset managers greater control over quality and allocation. MiFID II's implementation has prompted a reevaluation of value chains, with studies indicating shifts toward more targeted, high-quality outputs amid reduced overall coverage. The Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010 built on prior reforms by strengthening disclosure frameworks and investor protections in the wake of the , indirectly bolstering securities research through enhanced regulatory scrutiny. Title IX of the act mandated studies on and investment adviser standards, including an assessment of analyst conflict rules, which highlighted oversight gaps for debt research analysts and recommended codifying elements of the 2003 Global Settlement for uniform application. These provisions promoted greater transparency in asset-backed securities and derivatives, providing researchers with more robust data on systemic risks. More recently, the SEC has advanced fair disclosure principles under Regulation FD—originally adopted in 2000 to curb selective dissemination of material nonpublic information—through intensified enforcement actions in 2024, such as charges against companies for social media disclosures that failed to promptly reach the public. This focus reinforces the regulation's role in ensuring equitable access to information critical for unbiased securities analysis.

Research Methods

Fundamental Analysis

Fundamental analysis is a method used in securities research to evaluate the intrinsic value of a by examining the underlying economic, financial, and qualitative factors that influence its performance. This approach combines quantitative assessments, such as reviewing and calculating key ratios, with qualitative evaluations of industry dynamics and management effectiveness to determine whether a is overvalued, undervalued, or fairly priced relative to its fundamentals. Unlike , which relies on price patterns and market trends, focuses on long-term value drivers to support decisions. At its core, fundamental analysis begins with financial statement analysis, which involves scrutinizing a company's , , and to assess its financial health and . The provides a snapshot of assets, liabilities, and shareholders' equity at a specific point in time, revealing the company's and position. The details revenues, expenses, and profitability over a period, highlighting trends in generation. The tracks actual cash inflows and outflows from operating, investing, and financing activities, offering insights into sustainability beyond accrual-based figures. Analysts use these statements to identify strengths, such as robust cash reserves, or weaknesses, like high levels, ensuring a comprehensive view of the company's financial position. Key quantitative tools in this process include financial ratios derived from these statements, which normalize data for comparability across companies or over time. The price-to-earnings (P/E) ratio, calculated as market price per share divided by earnings per share (EPS), measures how much investors pay for each unit of earnings and indicates relative valuation; a lower P/E may suggest undervaluation if growth prospects are similar to peers. Return on equity (ROE), computed as net income divided by average shareholders' equity, evaluates how effectively management generates profits from equity capital; for instance, an ROE above 15% often signals strong performance in mature industries. These ratios, along with others like debt-to-equity (total debt divided by total equity) for leverage assessment, help benchmark a company's efficiency and risk profile against industry norms. Valuation models build on this foundation to estimate intrinsic value. The (DCF) model is a primary absolute valuation technique, expressing value as the of expected future flows discounted at the required : V0=∑t=1∞CFt(1+r)tV_0 = \sum_{t=1}^{\infty} \frac{CF_t}{(1 + r)^t} Here, V0V_0 is the current value, CFtCF_t represents projected flows at time tt, and rr is the discount rate reflecting risk. This model requires forecasting free flows—typically from operating activities minus capital expenditures—and applying a terminal value for , making it sensitive to assumptions about growth and discount rates. Complementary relative valuation methods, such as comparable company analysis, involve applying multiples like P/E from peer firms to the target company's metrics; for example, if similar tech companies trade at an average P/E of 25, a target with projected EPS of $4 would be valued at $100 per share. These models integrate financial data to derive a target price, guiding buy, sell, or hold recommendations. Macroeconomic and microeconomic factors further contextualize the analysis by linking company performance to broader environments. Macro factors include economic indicators like GDP growth, inflation rates, and interest rates, which influence overall demand and borrowing costs; for instance, rising interest rates can compress valuations by increasing discount rates in DCF models. Micro factors encompass industry trends, such as technological disruptions or regulatory changes, and company-specific elements like competitive positioning. Qualitative assessment of quality is crucial here, evaluating aspects like strategic vision, execution track record, and through metrics such as alignment of incentives (e.g., stock ownership) and transparency in disclosures. Strong can enhance by optimizing , while poor may signal risks. The process follows structured steps: data collection from audited financials, regulatory filings (e.g., 10-K reports), and economic databases; ratio computation and over multiple periods; integration of macro/micro factors via scenario modeling; application of valuation models to estimate intrinsic value; and synthesis into a with for key assumptions. For example, valuing a tech stock like a software firm might involve projecting cash flows from subscription revenues, at a 10% rate amid high growth expectations, and comparing P/E to peers like cloud providers, potentially revealing undervaluation if the stock trades below the DCF-derived $150 target. This iterative process, often employed by sector-specialized analysts, ensures recommendations are grounded in verifiable fundamentals.

Technical Analysis

Technical analysis is a methodology in securities research that employs historical , primarily and , to forecast future movements. It operates on the premise that market prices incorporate all available information and that patterns in price action reflect recurring trader behaviors. Unlike approaches focused on intrinsic value, technical analysis prioritizes empirical observations of market dynamics to generate trading signals.

Principles

The foundational principles of technical analysis are rooted in market psychology, which posits that investor emotions such as and drive price trends, leading to repetitive patterns over time. Central to this is the concept of trends, where prices move in identifiable directions—upward (bullish), downward (bearish), or sideways (range-bound)—rather than randomly, allowing analysts to align trades with the prevailing momentum. levels further embody this psychology: support represents a where buying interest is expected to emerge and halt declines, while resistance acts as a ceiling where selling pressure typically prevents further advances; breaches of these levels often signal trend reversals or continuations. These principles trace back to , developed by in the late , which outlines that markets discount all information, trends have three phases (accumulation, public participation, distribution), and volume confirms price moves.

Key Tools

Analysts use a variety of indicators and patterns derived from price and data to quantify these principles. smooth price fluctuations to highlight trends; the simple (SMA), a basic form, calculates the of prices over a specified period nn: SMAn=∑i=1nPin\text{SMA}_n = \frac{\sum_{i=1}^{n} P_i}{n} where PiP_i is the price at time ii. Crossovers between short- and long-term SMAs generate buy or sell signals when the shorter average surpasses or falls below the longer one, respectively. The (RSI), developed by J. Welles Wilder in 1978, measures momentum to identify overbought or oversold conditions on a scale of 0 to 100. It is computed as: RSI=100−1001+RS\text{RSI} = 100 - \frac{100}{1 + \text{RS}} where RS (relative strength) is the ratio of average gains to average losses over a typical 14-period window; RSI values above 70 suggest overbought conditions prone to reversal, while below 30 indicate oversold states. Candlestick patterns, originating from 18th-century Japanese rice traders and popularized in Western markets by Steve Nison, visualize price action in a single period through a "body" (open-to-close range) and "wicks" (high-low extensions). Representative patterns include the , signaling indecision with open and close nearly equal, and the , a bullish reversal indicator with a small body at the high and long lower wick after a downtrend, reflecting rejected lower prices.

Chart Types

Charts transform raw data into visual formats for . Line charts plot closing prices connected sequentially, offering a simple trend overview without intraday details. Bar charts (or OHLC bars) display open, high, low, and close prices for each period as vertical lines with horizontal ticks, revealing volatility and directional bias. Point-and-figure charts, introduced in the 1948 book Technical Analysis of Stock Trends by Robert D. Edwards and John Magee, abstract time by recording only price changes of a predefined box size, using X's for advances and O's for declines to filter noise and emphasize supply-demand shifts. Modern platforms like facilitate these visualizations with customizable tools and across assets.

Application

In practice, technical analysis generates short-term trading signals, such as entry/exit points from indicator crossovers or pattern confirmations, enabling tactical decisions in volatile environments like . For longer horizons, it serves as confirmation of broader trends, with studies showing historical profitability—e.g., strategies yielding up to 17.2% annual returns on the DJIA from 1897–1996—though results vary by market and period. Limitations include the , where widespread adherence to popular signals, such as round-number support levels, influences prices through collective trader actions rather than fundamental shifts, potentially diminishing efficacy in efficient markets. Technical analysis complements fundamental approaches by providing timing insights for established valuations. Adaptations for specific sectors, like commodities, may involve adjusting indicator periods to account for unique volatility patterns.

Roles and Types of Analysts

Buy-Side vs. Sell-Side Analysts

Buy-side analysts are professionals employed by institutional investors, such as firms, funds, funds, and mutual funds, where they conduct internal to inform proprietary strategies and decisions aimed at maximizing portfolio returns for their . Their work emphasizes in-depth analysis tailored to the specific needs of their firm's , with results often kept confidential to maintain a competitive edge in the market. Unlike their counterparts, buy-side analysts prioritize long-term value creation, focusing on risk-adjusted performance rather than short-term market reactions. Since the implementation of the EU's Markets in Financial Instruments Directive II (MiFID II) in 2018, which required unbundling costs from trading commissions, sell-side budgets have declined significantly, leading to reduced analyst coverage and more focused, higher-quality reports. In response, buy-side firms have expanded in-house capabilities, increasing the number of buy-side analysts and shifting more analysis internally, particularly in and globally influencing practices. In contrast, sell-side analysts work for brokerage firms, investment banks, and other financial institutions that provide services to external clients, producing publicly distributed reports, recommendations, and forecasts to facilitate trading activity and generate commissions for their employer. Their primary function is to offer objective insights on companies, sectors, and market trends, often including buy, sell, or hold ratings that influence investor behavior and trading volumes. Sell-side is broadly disseminated to attract clients and support the firm's revenue from , trading, and advisory services. The core differences between buy-side and sell-side analysts lie in their functions, incentives, and workflows. Functionally, buy-side analysts integrate directly into decisions, such as building and adjusting portfolios, while sell-side analysts focus on generating detailed reports and facilitating client interactions like roadshows with company management to uncover insights. Incentives also diverge: buy-side compensation is heavily tied to the overall performance of the firm's , often through bonuses linked to portfolio returns, whereas sell-side analysts are rewarded based on the accuracy of their forecasts, the volume of trading their drives, and contributions to deal flow. Workflows reflect these priorities—buy-side processes are more collaborative and internal, involving close coordination with portfolio managers for strategy development, while sell-side workflows are client-oriented, involving frequent publication deadlines and broader market outreach to maximize distribution and impact. Access to information further distinguishes the two: buy-side analysts often participate in exclusive roadshows and direct engagements with company executives, leveraging their firm's investment scale for deeper insights, but they operate with less emphasis on public disclosure to protect trade secrets. Sell-side analysts, conversely, rely on a mix of public data and arranged meetings to produce accessible reports, sometimes using "soft dollars" from buy-side clients to fund their indirectly. Performance metrics align with these roles—buy-side success is measured by sustained portfolio outperformance and alpha generation, whereas sell-side evaluation centers on forecast precision, report readership, and the market-moving influence of their recommendations. For instance, buy-side research teams at firms like Vanguard, a major asset manager overseeing trillions in assets, focus on internal equity and fixed-income strategies to optimize long-term client returns without public fanfare. In comparison, sell-side analysts at Goldman Sachs produce global investment research reports on equities, fixed income, and commodities, distributed to institutional clients to support trading and advisory activities. Both sides may apply fundamental and technical analysis methods, but buy-side adapts them for proprietary portfolio construction, while sell-side emphasizes standardized, client-shareable outputs.

Specializations by Sector and Asset Class

Securities research analysts often specialize in particular sectors or to develop deep expertise, enabling them to provide nuanced insights into market dynamics and opportunities within those domains. This specialization allows analysts to tailor their evaluations to industry-specific factors, such as regulatory environments, technological disruptions, or macroeconomic influences, enhancing the accuracy of their recommendations for investors. In sector specializations, analysts in the sector focus on models, assessing rapid product cycles, valuations, and the impact of emerging technologies like on company growth. For instance, technology analysts evaluate software-as-a-service metrics and hardware risks to forecast revenue streams in volatile markets. Energy sector specialists emphasize price forecasting, analyzing and gas supply-demand balances, geopolitical events, and the shift toward renewables, often using econometric models to predict price fluctuations. Healthcare analysts, particularly in and pharmaceuticals, scrutinize FDA approval processes, outcomes, and drug pipeline potentials, which can dramatically affect stock valuations based on regulatory milestones. Asset class specializations further delineate analyst roles, with equity-focused researchers prioritizing earnings growth projections, models, and comparable company analyses to determine intrinsic values. Fixed-income analysts concentrate on analysis, evaluating sensitivities, credit spreads, and default risks for bonds and securities to guide portfolio allocation. In derivatives research, specialists apply options pricing basics, such as the Black-Scholes model, which calculates fair values based on underlying asset prices, volatility, time to expiration, and strike prices, aiding in hedging and strategies without delving into complex derivations. Specialized roles demand domain-specific skills beyond general financial acumen, such as scientific backgrounds for biotech healthcare analysts, who often hold PhDs or MDs to interpret clinical data and therapeutic mechanisms. Technology analysts require proficiency in industry trends and software metrics, while energy specialists need expertise in commodity markets and econometric forecasting. These skills ensure analysts can integrate technical knowledge with for robust evaluations. The evolution of specializations has seen the continued rise of ESG and sustainable investing, which has become mainstream by 2025, with dedicated analysts incorporating AI for enhanced data processing and adhering to regulations such as the EU's Sustainable Finance Disclosure Regulation (SFDR) and proposed SEC climate disclosure rules. As of 2025, ESG assets under management globally exceed $40 trillion, influencing valuations across sectors and asset classes through frameworks like those from . Emerging specializations as of 2025 include , where analysts leverage and AI for predictive modeling and algorithmic trading signals, and /cryptocurrency analysis, evaluating digital assets' volatility, regulatory risks (e.g., SEC classifications), and technology integrations in securities markets.

Regulations and Compliance

Qualifications and Certifications

Securities researchers, also known as equity research analysts or investment analysts, typically require a strong educational foundation in , , or related fields to enter the profession. A in , , , or is the most common entry-level qualification, providing essential knowledge in financial markets, valuation techniques, and economic principles. Many professionals pursue advanced degrees, such as a (MBA) with a finance concentration, to enhance analytical skills and prospects, particularly for senior roles. Key professional certifications establish credibility and demonstrate expertise in securities analysis. The (CFA) designation, administered by the , is widely regarded as the global gold standard for investment professionals. It involves passing three rigorous levels of exams covering , quantitative methods, , financial reporting, and portfolio management, along with relevant work experience. In the United States, research analysts must pass the (FINRA) Series 86 (Research Analyst Analysis) and Series 87 (Research Analyst Regulatory) exams, which were updated in 2018 to align with modern regulatory standards and focus on analytical and compliance knowledge. Regional requirements vary to ensure local compliance and competency. In the U.S., analysts employed by SEC-registered broker-dealers must register with the SEC and FINRA, often requiring sponsorship and adherence to qualification standards beyond exams. Hong Kong's (SFC) mandates a Type 4 license for advising on securities, which necessitates passing the Licensing Examination Paper 1 (Fundamentals of Securities and Futures Regulation) as a core requirement. In the , the (ESMA) under MiFID II guidelines requires investment firms to ensure analysts possess appropriate qualifications, typically including a relevant degree or certification, with an emphasis on ongoing competence assessments. Continuing education is essential to maintain certifications and stay abreast of evolving markets and regulations. CFA charterholders, for instance, must complete 20 hours of (CPD) every two years, including at least two hours on , while under FINRA Rule 1240 (as amended effective January 1, 2023), registered persons, including analysts, must complete the Regulatory Element of annually by December 31 for each registration held. This consists of a computer-based session on significant rule changes, regulatory developments, and ethical standards relevant to their roles. Firms must also annually evaluate needs and deliver Firm Element sessions covering regulatory updates and tailored to their operations. Certifications like the CFA also incorporate ethical , which underpins professional conduct in . Certain sector specializations, such as or sustainable investing, may require additional targeted qualifications.

Industry Rules and Ethical Standards

In the United States, the Securities and Exchange Commission (SEC) introduced Regulation Analyst Certification (Regulation AC) in 2003 to enhance research independence by requiring analysts to certify the factual accuracy and completeness of their research reports and the basis for their recommendations, thereby mitigating conflicts of interest between research and investment banking activities. Complementing this, the 2003 Global Analyst Research Settlement, involving ten major investment firms and totaling $1.4 billion in penalties and investor restitution, imposed structural reforms including a complete ban on "spinning," the practice of allocating hot initial public offering (IPO) shares to corporate executives in exchange for investment banking business, to prevent undue influence on analyst output. Ethical standards in securities research emphasize objectivity, competence, and transparency, as outlined in the CFA Institute's Code of and Standards of Professional Conduct, which mandates that members and candidates act with integrity, maintain independence and objectivity in investment analysis, and exercise and competence in applying to services. A core requirement across jurisdictions is the disclosure of conflicts of interest in research reports, such as personal financial interests, ownership positions, or compensation tied to revenue, ensuring investors receive unbiased information. Enforcement of these rules in the U.S. falls primarily under the Rule 2241, which consolidates requirements for managing conflicts in equity research reports, including restrictions on analyst interactions with personnel and prohibitions on tying analyst compensation to specific deal outcomes; violations can result in fines, suspensions, or permanent bars from the industry, as guided by FINRA's Sanction Guidelines. In the , the enforces similar standards through the Conduct of Business Sourcebook (COBS) Chapter 12, which regulates the production and dissemination of investment research to ensure independence and clear conflict disclosures, with penalties including fines up to millions of pounds or authorization revocation for non-compliance. Globally, variations reflect regional priorities on integrity. In the , the Markets in Financial Instruments Directive II (MiFID II), effective from 2018, introduced research unbundling rules requiring investment firms to separately charge clients for rather than bundling it with execution services, aiming to reduce hidden conflicts and improve transparency in payments. In , the Australian Securities and Investments Commission (ASIC) oversees sell-side via Regulatory Guide 264, which mandates robust conflict management policies, safeguards, and disclosures to protect market integrity, with actions including civil penalties or licensing conditions for breaches.

Conflicts of Interest and Independence

Conflicts of interest in securities research primarily arise from the structural ties between analysts and their employers' activities, where firms initial public offerings (IPOs) or providing other services may pressure analysts to issue favorable ratings to secure or maintain business. For instance, during IPO processes, analysts affiliated with banks often produce optimistic reports that support higher valuations, as their compensation or can depend on generating deal flow for the division. Personal trading by analysts in the securities they cover represents another significant conflict, as it incentivizes biased recommendations to profit from price movements influenced by their own reports or market reactions. The of the late 1990s exemplified these issues, with sell-side analysts at major firms issuing predominantly "buy" ratings—with some firms providing no sell recommendations—for stocks, despite evident overvaluation, to bolster revenues from IPOs and mergers. This optimism contributed to inflated market prices and subsequent crashes, leading to investor losses estimated in trillions. Reforms following the , including enhancements to the 2003 Global Analyst Research Settlement via Dodd-Frank provisions, aimed to strengthen independence but have shown limitations; for example, ongoing oversight gaps allow subtle influences like performance-based compensation to persist, as noted in evaluations of SEC enforcement. To mitigate these conflicts, firms implement firewalls—physical and procedural barriers between research and investment banking departments—to prevent the flow of non-public information and , a requirement formalized in the 2003 Global Settlement involving $1.4 billion in penalties across ten major firms. Additionally, third-party verification of reports by independent reviewers helps ensure objectivity, though implementation varies and relies on checks. Current debates center on the unbundling of research payments from trading commissions under the European Union's MiFID II directive, effective , which sought to reduce conflicts by making clients directly pay for but raised concerns about diminished coverage for small- and mid-cap firms in the due to cost burdens on asset managers. This has prompted discussions on whether further subsidies or regulatory adjustments are needed to balance independence with coverage adequacy, particularly for smaller issuers.

Impact of Technology and AI

Technological advancements have profoundly transformed securities research through the integration of big data analytics, enabling analysts to process vast datasets for deeper insights into market dynamics and investment opportunities. Big data techniques allow for the analysis of unstructured information from sources like social media, news feeds, and transaction records, improving the accuracy of risk assessments and trend identification in financial markets. Algorithmic screening, particularly using natural language processing (NLP), has become a cornerstone for extracting sentiment and key themes from corporate earnings calls, which often signal future performance more effectively than traditional metrics alone. For instance, NLP models applied to earnings transcripts can predict stock price movements by quantifying managerial tone and investor reactions, enhancing the efficiency of fundamental analysis. Artificial intelligence applications further automate and refine securities research, with models excelling in predictive modeling for stock forecasts. These models, including networks and random forests, analyze historical price data alongside to generate probabilistic forecasts, often outperforming conventional statistical methods in volatile markets. Robo-advisors represent another key AI-driven innovation, automating tasks such as portfolio screening and based on user risk profiles, thereby democratizing access to sophisticated analysis previously reserved for institutional investors. By leveraging algorithms to continuously monitor market conditions and rebalance holdings, robo-advisors reduce human bias and operational costs in routine advisory functions. Looking ahead, technology promises to enhance data transparency in securities research by creating immutable ledgers for transaction records and ownership verification, mitigating issues like data manipulation in global markets. This approach facilitates real-time auditing and secure sharing of financial datasets among researchers and firms, fostering greater trust in cross-border investment analysis. holds high-level potential for tackling complex valuations, such as optimizing large-scale portfolios under multiple constraints, where classical computers falter due to exponential computational demands. Early quantum algorithms, like variational quantum eigensolvers, could simulate intricate risk scenarios and pricing more rapidly, though practical implementation remains nascent. Despite these benefits, technology and AI introduce significant challenges, including data privacy concerns amplified by regulations like the General Data Protection Regulation (GDPR). Financial firms conducting securities research must ensure compliance with GDPR when processing in , implementing measures like anonymization to avoid fines exceeding 4% of global revenue. Additionally, AI-driven poses risks of job displacement for junior analysts, with projections indicating that up to 30% of work hours in the sector could be automated by 2030, shifting roles toward oversight and strategic interpretation. These trends integrate with traditional fundamental and technical methods by augmenting data inputs, but they necessitate regulatory adaptations to address algorithmic biases and ensure ethical AI deployment in research practices.

References

  1. https://www.finra.org/rules-guidance/rulebooks/finra-rules/2241
  2. https://corporatefinanceinstitute.com/resources/capital_markets/comprehensive-guide-to-investment-research/
  3. https://www.finra.org/rules-guidance/key-topics/research-analyst-rules
  4. https://www.sec.gov/search-filings/edgar-search-assistance/using-edgar-research-investments
  5. https://corporatefinanceinstitute.com/resources/career/buy-side-vs-sell-side/
  6. https://www.finra.org/rules-guidance/rulebooks/finra-rules/2242
  7. https://www.investopedia.com/terms/r/research-report.asp
  8. https://corporatefinanceinstitute.com/resources/valuation/equity-research-report/
  9. https://www.cfainstitute.org/sites/default/files/-/media/documents/support/research-challenge/challenge/rc-equity-research-report-essentials.pdf
  10. https://www.morganstanley.com/what-we-do/research/management-policies
  11. https://www.investopedia.com/articles/professionals/092415/career-advice-financial-analyst-vsresearch-analyst.asp
  12. https://www.ebsco.com/research-starters/business-and-management/financial-security-analysis
  13. https://www.bloomberg.com/professional/products/bloomberg-terminal/research/
  14. https://www.morningstar.com/business/insights/research
  15. https://doi.org/10.1016/j.jbankfin.2020.105856
  16. https://www.gsb.stanford.edu/insights/when-they-are-wrong-analysts-may-dig-their-heels
  17. https://doi.org/10.1007/s00181-022-02297-3
  18. https://pages.stern.nyu.edu/~jwurgler/papers/capallocation.pdf
  19. https://www.sec.gov/newsroom/speeches-statements/gensler-remarks-bloomberg-global-regulatory-forum-102224
  20. https://www.nyse.com/history-of-nyse
  21. http://www.sfu.ca/~poitras/VES_ch2.pdf
  22. https://www.cambridge.org/core/journals/enterprise-and-society/article/material-politics-of-finance-the-ticker-tape-and-the-london-stock-exchange-1860s1890s/7BA79594BE371FBD270D7C0D701F2B33
  23. https://www.ivey.uwo.ca/media/3065497/ben-graham-father-financial-analysis.pdf
  24. https://www.goldmansachs.com/what-we-do/research/the-history-of-goldman-sachs-research.pdf
  25. https://www.investor.gov/introduction-investing/investing-basics/role-sec/laws-govern-securities-industry
  26. https://www.congress.gov/crs-product/IF11256
  27. https://www.sec.gov/enforcement-litigation/litigation-releases/lr-18438
  28. https://www.finra.org/rules-guidance/guidance/reports/2003-global-settlement
  29. https://www.sec.gov/news/speech/factsheet.htm
  30. https://www.sciencedirect.com/science/article/abs/pii/S0304405X21002300
  31. https://onlinelibrary.wiley.com/doi/10.1111/1911-3846.12865
  32. https://www.sifma.org/explore-issues/mifid-ii/
  33. https://www.gao.gov/products/gao-12-209
  34. https://corpgov.law.harvard.edu/2010/07/07/summary-of-dodd-frank-financial-regulation-legislation/
  35. https://www.sec.gov/newsroom/press-releases/2024-149
  36. https://www.winston.com/en/blogs-and-podcasts/capital-markets-and-securities-law-watch/sec-charges-public-company-with-regulation-fd-violation-over-ceos-social-media-posts
  37. https://www.cfainstitute.org/insights/professional-learning/refresher-readings/2025/introduction-financial-statement-analysis
  38. https://www.cfainstitute.org/insights/professional-learning/refresher-readings/2025/market-based-valuation-price-enterprise-value-multiples
  39. https://www.cfainstitute.org/sites/default/files/-/media/documents/support/programs/cfa/cfa_program_level_ii_financial_ratio_list.pdf
  40. https://www.cfainstitute.org/insights/professional-learning/refresher-readings/2025/discounted-dividend-valuation
  41. https://www.cfainstitute.org/insights/professional-learning/refresher-readings/2025/evaluating-quality-financial-reports
  42. https://farmdoc.illinois.edu/assets/marketing/agmas/AgMAS04_04.pdf
  43. https://www.ifcmarkets.com/pdf_files/tradingbooks/en/the-dow-theory-in-technical-analysis.pdf
  44. https://www.amazon.com/Japanese-Candlestick-Charting-Techniques-Second/dp/0735201811
  45. https://www.tradingview.com/
  46. https://digitalcommons.macalester.edu/cgi/viewcontent.cgi?article=1041&context=economics_honors_projects
  47. https://www.ifo.de/DocDL/cesifo1_wp10213.pdf
  48. https://www.investopedia.com/articles/financialcareers/11/sell-side-buy-side-analysts.asp
  49. https://www.schweser.com/cfa/blog/career-information/buy-side-vs-sell-side-comparing-research-analyst-career-paths
  50. https://www.esma.europa.eu/sites/default/files/trv_2020_2-mifid_ii_research_unbundling_first_evidence.pdf
  51. https://link.springer.com/article/10.1007/s11142-020-09545-w
  52. https://www.investopedia.com/terms/b/buyside.asp
  53. https://www.goldmansachs.com/what-we-do/research
  54. https://corporatefinanceinstitute.com/resources/career/equity-research-overview/
  55. https://quintedge.com/what-is-equity-research/
  56. https://www.guggenheimsecurities.com/capabilities/research
  57. https://mergersandinquisitions.com/biotech-equity-research/
  58. https://mergersandinquisitions.com/fixed-income-research/
  59. https://www.investopedia.com/terms/b/blackscholes.asp
  60. https://www.chardan.com/job-posting/YdxF-BMAACcAjaw5
  61. https://www.expertia.ai/career-tips/essential-professional-skills-every-energy-analyst-should-master-62447v
  62. https://www.mdpi.com/2673-8392/4/4/112
  63. https://corpgov.law.harvard.edu/2020/03/02/top-10-esg-trends-for-the-new-decade/
  64. https://www.gs.com/insights/articles/esg-investing-the-next-frontier
  65. https://magistralconsulting.com/equity-research-data-backed-insights-for-smarter-investments/
  66. https://www.finra.org/rules-guidance/rule-filings/sr-finra-2018-005
  67. https://www.finra.org/rules-guidance/rulebooks/finra-rules/1240
  68. https://www.finra.org/rules-guidance/notices/21-41
  69. https://www.sec.gov/divisions/marketreg/mregacfaq0803.htm
  70. https://www.sec.gov/news/press/2002-179.htm
  71. https://www.cfainstitute.org/sites/default/files/-/media/documents/code/code-ethics-standards/code-of-ethics-standards-professional-conduct.pdf
  72. https://www.finra.org/sites/default/files/Sanctions_Guidelines.pdf
  73. https://www.handbook.fca.org.uk/handbook/COBS/12/2.html
  74. https://download.asic.gov.au/media/4739759/rg264-published-21-december-2017_revised.pdf
  75. https://www.sec.gov/news/testimony/073101tslu.htm
  76. https://www.sec.gov/news/press/2002-63.htm
  77. https://web.williams.edu/Economics/Honors/2004/MSirignanoThesis
  78. https://www.gao.gov/assets/gao-12-209.pdf
  79. https://www.sec.gov/files/litigation/litreleases/finaljudgadda.pdf
  80. https://www.esma.europa.eu/sites/default/files/library/esma_50-165-1287_report_on_trends_risks_and_vulnerabilities_no.2_2020.pdf
  81. https://scholarworks.utrgv.edu/cgi/viewcontent.cgi?article=1027&context=account_fac
  82. https://finance.wharton.upenn.edu/~itayg/Files/bigdata-published.pdf
  83. https://www.sciencedirect.com/science/article/pii/S0165176525002411
  84. https://www.mdpi.com/2673-9909/5/3/76
  85. https://www.chicagofed.org/publications/economic-perspectives/2017/7
  86. https://www.frontiersin.org/journals/blockchain/articles/10.3389/fbloc.2025.1491609/full
  87. https://udspace.udel.edu/bitstreams/1e691d77-181e-4301-9cf6-02a402390950/download
  88. https://pmc.ncbi.nlm.nih.gov/articles/PMC10632408/
  89. https://www.sciencedirect.com/science/article/pii/S1877050923003599
  90. https://www.mckinsey.com/mgi/our-research/generative-ai-and-the-future-of-work-in-america
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