FOR Prof.Dan only
carmen04
finance_dissertations_induction_.pdf
Leeds University Business School
Mission Statement
The databases available to the Accounting and Finance
Division have been specially selected to provide a
platform to deliver excellence in teaching and to support
world leading research.
We maximise the benefit of our database facility by
providing students and staff with easy access and the
knowledge of how to use databases effectively.
Leeds University Business School
My role: Data Support
• I head a support structure for data provision which is aided by
a number of A&F Research Assistants
• I will also be a dissertation supervisor to a number of you
• I will either provide you with bulk data (not bespoke) in some
cases (where appropriate) or if the data is bespoke or easy to
extract yourself (the vast majority of data) this will be your
responsibility
• You will have one small group meeting with me later in the year
after meeting with your supervisor
• It is also always your responsibility to ‘clean’/transform any raw
data. A&F Research Assistants will be available to offer you
advise and support (within acceptable boundaries)
Leeds University Business School
Dissertation Themes: Example papers
1. Asset Pricing and Investment
2. Auditing
3. Insider Trading
4. Corporate Governance
5. Banking
6. Corporate Finance
7. Financial Accounting
Leeds University Business School
Dissertation Topics
Theme 1: Asset Pricing and Investment
1. Momentum trading Verardo, M., 2009, “Heterogeneous Beliefs and Momentum Profits” Journal
of Financial and Quantitative Analysis, Vol. 44, No. 4, pp795-822.
DATA: CRSP North America, Compustat North America
Thomson I/B/E/S
2. Contrarian Strategies Ball, R., Kothari, S. P. and Shanken, J., 'Problems in measuring portfolio
performance An application to contrarian investment strategies', Journal of
Financial Economics, Vol. 38 no. 1, 1995, pp. 79-107.
DATA: CRSP North America
3. Technical Trading Lo, A. W., Mamaysky, H. and Wang, J., 'Foundations of Technical Analysis:
Computational Algorithms, Statistical Inference, and Empirical
Implementation', The Journal of Finance, Vol. 55 no. 4, 2000, pp. 1705-70.
DATA: CRSP North America
4. Forecasting Pesaran, M. H. and A. Timmermann. Predictability of Stock Returns:
Robustness and Economic Significance. Journal of Finance 50(4), 1995, pp:
1201-1228
DATA: CRSP North America
Leeds University Business School
Theme 2: Auditing
5. Audit Fees Palmrose, Z.-V., 'Audit Fees and Auditor Size: Further Evidence', Journal of Accounting Research, Vol. 24 no. 1, 1986, pp. 97-110.
6. Auditor Switch Chow, C. W. and Rice, S. J., 'Qualified Audit Opinions and Auditor Switching', The Accounting Review, Vol. 57 no. 2, 1982, pp. 326-35.
We have the data available to cover the majority of countries in the
World e.g. China, UK or the USA.
Leeds University Business School
Dissertation Topics
Theme 3: Insider Trading
7. Day/Month/year effects Chang, E. C., Pinegar, J. M. and Ravichandran, R., 'International Evidence
on the Robustness of the Day-of-the-Week Effect', Journal of Financial and Quantitative Analysis, Vol. 28 no. 04, 1993, pp. 497-513.
8. Market Reactions Cornell, B. and Sirri, E. R., 'The Reaction of Investors and Stock Prices to Insider Trading', The Journal of Finance, Vol. 47 no. 3, 1992, pp. 1031-59.
We have daily stock data to cover the majority of countries in the
World.
USA: CRSP
CHINA: CSMAR
WORLDWIDE: Compustat Global
WORLDWIDE: Thomson Eikon Datastream
Leeds University Business School
Dissertation Topics
Theme 4: Corporate Governance
9. Board Structure and
Performance
Boone, A. L., Casares Field, L., Karpoff, J. M. and Raheja, C. G., 'The
determinants of corporate board size and composition: An empirical analysis', Journal of Financial Economics, Vol. 85 no. 1, 2007, pp. 66-101.
10. Ownership Structure Lin, C., Ma, Y., Malatesta, P. and Xuan, Y., 'Ownership structure and the
cost of corporate borrowing', Journal of Financial Economics, Vol. 100 no. 1, 2011, pp. 1-23.
We have a large data offering. For example, institional ownerership
data can be sourced from Thomson 13F (via WRDS) and matched with
other data such as company financials and/or share prices.
Leeds University Business School
Dissertation Topics
Theme 5: Banking
11. M&As in the Banking
Industry
Hagendorff, J., Hernando, I., Nieto, M. J. and Wall, L. D., 'What do premiums
paid for bank M&As reflect? The case of the European Union', Journal of Banking & Finance, Vol. 36 no. 3, 2011, pp. 749-59.
12. Financial Crisis and
Banking Performance
Simon H, K., 'Operating performance of banks among Asian economies: An
international and time series comparison', Journal of Banking & Finance, Vol. 27 no. 3, 2003, pp. 471-89.
13. Risk Management in
Credit Institutions
Alfred, L., 'Measuring systemic risk: A risk management approach', Journal of
Banking & Finance, Vol. 29 no. 10, 2005, pp. 2577-603.
Theme 6: Corporate Finance
14. Initial Public Offerings
(IPOs)
Loughran, T. and Ritter, J. R., 'Why Don't Issuers Get Upset About Leaving
Money on the Table in IPOs?', Review of Financial Studies, Vol. 15 no. 2, January 2, 2002, 2002, pp. 413-44.
15. Mergers and
Acquisitions (M&A)
Faccio M., McConnell J. and Stolin D. ‘Returns to Acquirers of Listed and
Unlisted Targets.’ Journal of Financial and Quantitative Analysis, vol. 41 ,
2006, pp 197-220
16. Dividend policy Fuller, K. P. and Goldstein, M. A., 'Do dividends matter more in declining markets?' Journal of Corporate Finance, Vol. 17 no. 3, 2011, pp. 457-73.
Leeds University Business School
Dissertation Topics
Theme 7: Financial Accounting
18. Value Relevance Banker, R. D., Huang, R. and Natarajan, R., 'Incentive Contracting and Value
Relevance of Earnings and Cash Flows', Journal of Accounting Research, Vol. 47 no. 3, 2009, pp. 647-78.
19. Pre-post IFRS effects Landsman, W. R., Maydew, E. L. and Thornock, J. R., 'The information
content of annual earnings announcements and mandatory adoption of IFRS', Journal of Accounting and Economics, Vol. 53 no. 1–2, 2012, pp. 34-54.
20. Capital Markets DeFond, M., Hu, X., Hung, M. and Li, S., 'The impact of mandatory IFRS
adoption on foreign mutual fund ownership: The role of comparability', Journal of Accounting and Economics, Vol. 51 no. 3, 2011, pp. 240-58.
Theme 6: Corporate Finance (cont)
17. Capital Structure Gungoraydinoglu, A. and Oztekin, O., 'Firm- and country-level determinants of
corporate leverage: Some new international evidence', Journal of Corporate Finance, Vol. 17 no. 5, 2011, pp. 1457-74.
Leeds University Business School
General introduction to databases available
The following slides present some of our most popular databases
which you will use for your research
Leeds University Business School
Wharton Data Research Services Platform
(WRDS)
Many of the databases you will use during the course of your
dissertation will be those available via the Wharton Research
Database Platform.
https://wrds-web.wharton.upenn.edu/wrds/
Leeds University Business School
Centre for Research in Security Prices (CRSP)
CRSP provides the most comprehensive collection of security
price, return, and volume data for the NYSE, AMEX, and Nasdaq
stock markets. Data is available at various frequencies, including
daily.
Leeds University Business School
Compustat North America
• US and Canadian fundamental and market data for
more than 30,000 active and inactive publicly held
companies.
• The databases offered, provide thousands of Income
Statement, Balance Sheet, Statement of Cash Flows,
and supplemental data items.
• For most companies data goes back 20+ years (annual
and quarterly. Also available are indices, industry
segments, bank data, market prices, dividends, and
earnings data.
Leeds University Business School
Compustat Global
Comprehensive database of non-U.S. and non-Canadian fundamental and market
information on more than 33,900 active and inactive publicly held companies with
annual data history from 1987 (or longer for some countries). Includes daily share
prices from 1985-c
Leeds University Business School
Thomson Reuters Eikon (including
Datastream)
Thomson Eikon:
This is the new version of Datastream Professional and provides a wealth of historical data useful for research and in many respects is similar to Bloomberg but with slightly different strengths. One of the key benefits for researchers is the easier access to historical company financials (an alternative is accessing Thomson One via the library databases website).
Thomson Datastream
Offers current and historical time series data on stocks, stock indices, bonds, futures, options, interest rates, commodities, derivatives, currencies, and economic data. The data coverage is global. Data frequency various with respect to the specific data with most market data available on a daily basis; and most economic data is available monthly or quarterly.
Leeds University Business School
Thomson Reuters Eikon: Access
• Both Eikon and Datastream are often best accessed through
Microsoft Excel when bulk data is required
• Datastream is an Excel tab alongside the Eikon tab in Excel.
Please use one of the three designated computers (labelled) in
the Bloomberg trading room
Leeds University Business School
Thomson Eikon and Datastream user guides
including training videos
• Thomson Reuters provide excellent training videos on how to
use Eikon and Datastream (training tab is available at:
training.thomsonreuters.com ). These videos will help to get
you started and teach you how to use the Thomson databases.
The two most important direct links are available via the
following links (when you follow the link you will need to
register with your student email first):
• Eikon:
https://training.thomsonreuters.com/eikon4/?mkt=149
• Datastream:
https://training.thomsonreuters.com/cert/datastream/#flr379
Leeds University Business School
Bankscope
• Global banking information on over 28,000 banks worldwide.
• Detailed consolidated and/or unconsolidated balance sheet
and income statement. Data comes from Fitch Ratings and six
other sources. Also provides company and country risk ratings
and reports, ownership, and security and price information.
• Detailed financials - statements are in multiple formats
including a new universal format to compare banks globally.
• Ratings, and rating reports, from FitchRatings, Moody's,
Standard & Poor's and Capital Intelligence.
• Country risk and country finance reports.
• Stock data for listed banks.
Leeds University Business School
• Directors and contacts.
• Original filings/images.
• Detailed bank structures.
• Economic country profiles and outlooks.
• Business and related news.
• M&A deals and rumours.
• Fitch Bank Credit Model for 11,000 banks
Bankscope (2)
Leeds University Business School
Bankscope (3)
• Data can be exported as either Microsoft Word or Excel files.
• The search and download procedures in Bankscope is similar to
Fame, as both databases are from BvD. However, you will see
different data items recorded in Bankscope than Fame as each
database has its own focus.
• Accessible from the University library website. Remember, Fame
only keeps the most recent 10 years data, and Bankscope may only
hold the most recent 7 years data for certain data items.
Leeds University Business School
Bloomberg
Bloomberg provides real-time and historical financial
information on individual equities, stock market indices,
fixed-income securities currencies, commodities and
futures for both international and domestic markets.
The database also provides company profiles and
financial statements, analysts’ forecasts, news on
worldwide financial markets and audio and video
presentations by key players in business and finance.
Leeds University Business School
BvD: Fame
Fame contains comprehensive information on companies in the UK and
Ireland. You can use it to research individual companies, search for
companies with specific profiles and for analysis.
• Company financials, in detailed format, with up to 10 years of history
• Financial strength indicators
• Directors and contacts
• Original filings/images as filed at Companies House and the
Companies Registration Office in Ireland
• Stock data for listed companies
• Detailed corporate structures and the corporate family
• Shareholders and subsidiaries
• Industry research, Adverse filings, Business and company-related news
• M&As
Leeds University Business School
China Stock Market and Accounting Research
(CSMAR)
CSMAR provides a wealth of data on Chinese companies and
Chinese financial markets.
A number of different databases are available within CSMAR;
databases that provide:
• Analyst forecasts,
• M&As,
• Equity prices,
• Information on company directors
• Share dealings by insiders (directors)
Leeds University Business School
Institutional Brokerage Estimates System
(I/B/E/S)
• Historical earnings estimates for 30,000 firms worldwide.
• Used in top journals- earning expectations research
• A number of different data items are available including long-term
growth forecasts, earnings per share, stock recommendations,
revenue and cash flow.
• Historical and global earning information
– US data from 1976 - International from 1987
– 45 countries and more than 12,000 firms
• Current data
– available at company summary, company detail, and global
aggregate levels.
• Historical data
– available at company summary and global aggregate levels
Leeds University Business School
Lexis-Nexis
• Lexis-Nexis, is an useful source of news information,
including international newspapers, trade publications and
company information. All articles are available in full text and
material is updated daily
• Easy to use but remember to narrow down any search by
limiting dates or by choosing a specific set of newspapers
– For example, you can choose to search across all English
language newspapers, or just UK national newspapers
• A disadvantage of Lexis-Nexis is the requirement to manually
collect information (no export function)
• The database is accessible from the library website
Leeds University Business School
SNL Financial
• The SNL Financial database covers Banks and Thrifts, Financial
Services, Insurance, Real Estate, Energy and Media &
Communications.
• Coverage includes more than 3,300 public companies and over
50,000 private companies in North America, with international
coverage expanding every year.
• SNL Financial offers greater detail and depth compared to other
comparable databases. A host of customisable analytical tools are
available including valuation, peer and M&A models are offered.
• LUBS users can use either the web based interface or an Excel
Add-In. SNL also provides powerful mapping tools which allow
users to look at the spread of bank deposits and market share for
example.
Leeds University Business School
Thomson One
Thomson One provides access to global financial data including:
• Company accounts, scanned filings and annual reports,
shareholder data, M&As, IPOs, equities, bonds, syndicated
loans and earnings estimates.
• In addition, some basic country level economic data is also
available.
• Data, in most cases, goes back over 20 years.
Leeds University Business School
Thomson-Reuters Institutional Holdings (13F)
database
Provides institutional ownership data (13F filings) for institutional
managers with > $100m in assets under management
– Originally the CDA/Spectrum 34 database
Leeds University Business School
WRDS: Available datasets
• Blockholders Dataset: contains standardized data for blockholders
for 1,913 companies.
• FamaFrench (“Research”) Portfolios and Factors The Fama-French
Three Factor Model provides a useful tool for understanding portfolio
performance, measuring the impact of active management, portfolio
construction and estimating future returns.
• Federal Deposit Insurance Corporation (FDIC) FDIC Data
• Federal Reserve Bank Reports Three databases are available:
Foreign Exchange Rates, Interest Rates and State Indexes.
• Penn World Tables Penn World Tables from the Univ. of
Pennsylvania provide national income accounts-type variables
converted to international prices.
• SEC Disclosure of Order Execution SEC-mandated Disclosure of
Order Execution Statistics
Leeds University Business School
WRDS: Available datasets (2)
• Bank Regulatory
– Data on Bank holding companies, commercial banks, savings
banks, and savings and loans institutions
– Quarterly data from 1976 for commercial banks
– Quarterly data from 1986 for commercial banks
– Financial institution merger data from 1986
• Direct Marketing Educational Foundation (DMEF)
– Buying history for over 100,000 customers taken from
catalogue and non-profit marketing businesses
• Chicago Board Options Exchange Volatility Index (VIX)
– measure of market expectations of near-term (30 days)
volatility conveyed by S&P 500 stock index option prices
– From 1993
Leeds University Business School
Additional library business databases
• ABI Complete (ABI Global)
– Business and economic conditions, management techniques,
theory and practice of business, advertising, marketing,
economics, human resources, finance, taxation, computers.
Around 3,000 worldwide periodicals
• Business Source Premier
– Search journal articles trade publications, country reports,
industry information, company news and conference
proceedings
Leeds University Business School
Add. Library business databases (2)
• ICC
– Financial information on all live companies registered at the
UK’s Companies House
– Over 2m unincorporated firms
– Search function: by company name, director or basic
financials
• Passport
– Data and market research reports on consumer markets
worldwide
Leeds University Business School
Add. Library business databases (3)
• UK Data Service
– Place to access many datasets available including those from
the OECD, United Nations, World Bank and the IMF
Leeds University Business School
LUBS5059M Finance Dissertation
Dr Konstantinos Bozos
Associate Professor in Accounting & Finance
Director of PG Accounting & Finance Programmes [email protected]
Leeds University Business School
The Dissertation
• The culmination of the Masters programme.
• It provides you with opportunities to:
– apply aspects learned in other parts of the
programme
– develop these in greater detail and,
– develop a complete piece of work from the initial idea
through to a final written report.
• An important part of the Masters programme
• Contributes 45 credits (25% of 180 credits)
• Based on self-directed study
• Supervised by an academic member of staff
Leeds University Business School
Your Dissertation Support Structure
You
Research
Methods
Critical Skills
Module
SAS STATA
Training Data
Support
Your Supervisor
Research
Support
Leeds University Business School
The Dissertation Team:
Konstantinos
Bozos
Jessica
Johnson
Ali Altanlar Timothy King
Module Leader LUBS5019
Module Leader LUBS5099
Module Leader LUBS5018
Data Support
Officer
Malek El Diri Hossein
Jahanshahloo
Peng Li Laima
Spokeviciute
Doctoral Research
Assistant
Doctoral Research
Assistant
Doctoral Research
Assistant
Doctoral Research
Assistant
Leeds University Business School
Dissertation Supervisors (Tentative List)
• Altanlar Ali Lecturer in Credit and Risk
• Amini Shima Lecturer in Accounting & Finance
• Bordianu Andreea Teaching Fellow
• Bozos Konstantinos Associate Professor in Accounting & Finance,
• Cai Charlie Chair in Finance
• Clacher Iain Associate Professor in Accounting and Finance
• Duboisee De Ricquebourg Alan Teaching Fellow in Accounting & Finance
• King Timothy Research Officer, Accounting and Finance
• Myles Cathy Senior Teaching Fellow in Accounting and Finance
• Robinson Andrew Professor in Accounting and Finance
• Short Helen Senior Lecturer in Accounting and Finance
• Uddin Moshfique Lecturer in Accounting and Finance
• Veronesi Gianluca Associate Professor in Accounting & Finance
• Vallascas Franscesco Chair in Banking
• Ye Ying (Joanna) Senior Teaching Fellow in Accounting and Finance
• Wilson Nicholas Professor of Credit Management
Leeds University Business School
The Dissertation process
(Stage 1- Pre-Dissertation procedures)
1. Introduction to the Dissertation to the entire class.
– Presentation of the Module Procedures,
– Description of eligible topics and thematic units,
– Presentation of databases - data availability
2. Submission of 1-page Research proposal to module
leader
3. Evaluation of feasibility and feedback on 1-page
Research proposal
4. Allocation of supervisors
Leeds University Business School
The Dissertation process
(Stage 2 – Main Dissertation)
5. Initial Meeting with allocated supervisor
6. Meeting with research data officer
7. Subsequent meetings with supervisor
8. Ad hoc consultation meetings with doctoral research
assistants
9. Submission of 1 chapter to the supervisor for
feedback
10. Dissertation Submission
Leeds University Business School
Timeline
Term Week Week commencing Activity - Event
16 08/02/16 2-hour Induction
18 22/02/16 1-Page Proposal
20 07/03/16 Feedback on 1-Page Proposal
23 25/04/16 Supervisor Allocation
25 09/05/16 LUBS5018M Deadline
26 16/05/16
S2 Exams27 23/05/16
28 30/05/16
29 06/06/16 Meeting 1 with Supervisor
30 13/06/16 Meeting with Data Officer
S1 20/06/16
S2-S11 27/06/16
29/08/16
Meetings 2-4 with Supervisor
Ad hoc Meetings with Doctoral Research
Assistants
S12 05/09/16 Submission Deadline
Leeds University Business School
The 1- Page Research Proposal
Student Name Student ID Programme of Study
Konstantinos Bozos 2005XXXXX MSc Accounting & Finance
How has the International Harmonization of Financial Reporting Standards Affected Merger Premiums within the European Union?
Abstract
This study will examine the impact of IFRS adoption on merger premiums. While empirical studies have investigated the effect of IFRS adoption on
a number of reporting indicators and the consequences of divergence from country-specific standards to IFRS within the EU (Ding et al., 2007), there
has been no examination of the direct link between IFRS adoption and M&A premiums. Using M&A deals within the EU during 2000-2011 I aim to
examine the role of overall IFRS adoption, the differences between voluntary and mandatory adopters and the role of the target country’s pre-IFRS
accounting infrastructure and framework (absence of IFRS and IAS). Within the M&A context, a harmonized reporting framework is expected to
reduce the costs of information asymmetry for acquiring firms via the improved transparency in the targets’ reports, and the reduced uncertainty for
the acquirers in takeover decisions. On the other hand, under IFRS goodwill is subject to annual impairment testing (IAS 36), potentially
incentivising overpayment, since acquirers could count on goodwill write-offs against reserves. It is also expected that the impact of IFRS adoption
will differ between voluntary and mandatory adopters, while the differences between domestic GAAP and IFRS will also have an effect on merger
premiums.
Key data requirements
European M&As from the Thomson One Banker (T1B) M&A database. Key Deal characteristics. Target and Acquirer accounting information. Years
of coverage: 2000-2011. Countries: EU 15
Empirical models to be used
100 ntannounceme to prior weeks4 Price Target
ntannounceme to prior weeks4 Price Target - Price Offer Premium
Premium = α1+β1 . Ifrs +γ1
. Cross-Border +γ2
. Toehold +γ3
. Cash +γ4
. Multiple +γ5
. Friendly +δ1
. Logacmcap +δ2
. Acqdte +δ3
. Logtmcap +δ4
. Covroe10
+δ5 . Stdevtroe3 +δ6
. Avtroe +φ0
. Crisis +Σφi
. Yeari +Σφj
. Countryj + ε
Key references
Daske, H., Hail, L., Luez, C., and Verdi, R., (2008). Mandatory IFRS reporting around the world: early evidence on the economic consequences,
Journal of Accounting Research, 46 (5), 1085-1142.
Ding, Y., Hope, O., Jeanjean, T., and Stolowy, H., (2007). Differences between domestic accounting standards and IAS: measurement, determinants
and implications, Journal of Accounting and Public Policy, 26(1), 1-38.
Yip, R. W. Y., and Young, D. (2012). Does Mandatory IFRS Adoption Improve Information Comparability? The Accounting Review, 87(5): 1767-
1789.
Leeds University Business School
Critical Skills Module:
Jessica Johnson
• Preparing for the Dissertation
• The Literature Review
– introduction and reading skills
– description vs. critical evaluation
– referencing and avoiding plagiarism
• Writing – vocabulary and writing style
• Abstract and Introduction
• Conclusions
Leeds University Business School
Data Support:
Dr Timothy King
• We’ll provide you the data to undertake the BEST
POSSIBLE dissertation
Good Coverage
Sample size
Allowing for a robust and meaningful analysis
• Data Support Clinics
Leeds University Business School
Doctoral Research Assistants
• The dissertation is part of a student’s formal assessment.
• There can be absolutely no input from anyone else, other than the
student.
Doctoral Research Assistants responsible for:
• Demonstrating the use of the Bloomberg Terminal and other databases
• Maintaining user manuals and data descriptors for all available
databases.
• Demonstrating basic data retrieval techniques for all databases.
• Demonstrating basic econometric analysis techniques in Stata, SPSS,
SAS with SAMPLE DATA. (data cleaning, simple tabulations, univariate
and multivariate tests, regression analysis, simple time-series analysis,
standard panel data estimations)
• Keeping a shared record of student inquiries and monitor regularly, to
ensure that the service is not being abused by any single student.
Leeds University Business School
Doctoral Research Assistants
Doctoral Research Assistants will not:
• Provide feedback or mentoring to students in any way
• Review econometric specifications, tables, programming code and
results
• Retrieve data on behalf of the student.
• Distribute data via email or cloud computing
• Give any demonstration with real data retrieved or provided by the
student.
• Interfere in the working relationship between student -supervisor
• Take email requests
• Be available to students outside the Bloomberg Financial Markets room
Leeds University Business School
Supervisors
The supervisor is responsible for:
• Keeping an attendance record for each student
• Informing the relevant office (UG or PG) about student invisibility
• Informing students about out-of-office periods
• Agreeing the dissertation topic. Agreeing to a change of topic
• Directing students towards relevant literature and other sources of
information, and discussing the appropriateness of theory and methodology
• Providing feedback on a single draft chapter.
• Responding to student emails within a reasonable time frame (3-4 days)
The supervisor will not:
• Retrieve data or edit text on behalf of the student.
• Provide feedback on more (or less) than the approved material
• Offer a student more (or less) than the allowed number of meetings. (3-4)
Leeds University Business School
The Savoir Vivre of MSc Dissertations…
• Act professionally and take it seriously
– Be punctual and well-prepared for your appointments
– Be clear and well-read during your meetings
– Be polite to your supervisor in any correspondence
– Manage time well & deliver (or at least give an original excuse…)
• Act responsibly and you will graduate
– Do not plagiarize your work (Turnitin is bigger than Wikipedia…)
– Up to 15% overlap collectively (not with individual papers) is OK
– Reference everything you use and use “” for exact phrasing…
– If you are not sure, ask, consult academic handbook
– Do not even consider ‘outsourcing’ your work
Leeds University Business School
Questions
