Finance assignment help for UK students.

Rarely in the arithmetic. Most finance briefs award the majority of marks for the reasoning around the number: the assumptions you state, the workings you show, the interpretation you give and the limitations you acknowledge. A correct net present value with no discussion of the discount rate, the forecast assumptions or the sensitivity of the result will usually sit in the middle band. The support concentrates on that layer: presenting the model clearly, justifying each input, and writing the interpretation that converts a figure into a recommendation.

Introduction with scope and the company or asset in question, a short methodology note stating your data source and period, the analysis itself grouped by theme rather than by ratio, interpretation, limitations, conclusion and recommendation, then references and appendices holding the full calculations. Group profitability, liquidity, efficiency, gearing and investor ratios into themes and comment on the trend and the peer comparison, because a table of twelve ratios with one line each reads as data entry. Keep the spreadsheet in an appendix and keep the argument in the body.

Start with the company's annual report and audited financial statements, which are free on the investor relations pages and filed at Companies House. For market and comparator data, use the databases your university subscribes to: Bloomberg, Refinitiv Eikon or Datastream, FAME, Orbis, Capital IQ or MarketLine. Open sources include the Office for National Statistics, the Bank of England statistical database, the World Bank and Yahoo Finance for price series. In Harvard, cite the company as a corporate author for annual reports, and cite the database rather than the chart image for market data, giving the provider, the dataset name, the period covered and the date you accessed it. State your data period and any currency or inflation adjustment in the methodology, because unexplained data choices invite questions in marking.

Yes. For econometrics coursework that means model specification, regression output interpretation, hypothesis testing, diagnostics such as heteroskedasticity and autocorrelation, and writing results in the form journals and markers expect. For dissertations, the practical constraint is nearly always data: choose a question answerable with a series you can actually access for the full period, and confirm that before you commit. Support then covers the literature review, methodology justification, results chapter and discussion.