Behavioural Biases and Investment Decision-Making: UK Student Retail Investors in the Stock Market

I am seeking a well-structured, academically rigorous draft that covers the Introduction, the research background, and Literature review chapters of my PhD dissertation on behavioural biases among retail stock-market investors. The work needs to begin with a broad, global institutional and retail investors and progressively narrow to the United Kingdom, finishing with a specific focus on UK university students who trade through the main online platforms. What I need from you • Introduction: a clear statement of the research problem, objectives and significance, framed within behavioural finance theory. • Research background: concise overview of global retail participation in the main markets, highlighting changes brought by fintech apps and recent market events (e.g., COVID-19 sell-off, game-stop, meme-stock rallies). • Literature review: a critical synthesis of all investor biases—overconfidence, loss aversion, herd behaviour, anchoring, mental accounting, confirmation bias and any additional biases the literature recognises. Start with international studies, then filter down to UK findings, and finally spotlight research involving UK students. Use recent peer-reviewed journal articles and landmark studies, weaving in illustrative major-event examples to keep the review engaging and relevant. • Clear identification of gaps that justify my proposed empirical work. • Full Harvard-style reference list. Acceptance criteria 1. Logical flow from global context to UK student segment. 2. Balanced coverage of every major bias with proper critical comparison of findings. 3. Recent sources (majority post-2018) plus the foundational classics. 4. Approx. 7,000–8,000 words, excluding references, delivered as an editable Word document. 5. Original text that passes plagiarism checks. If you are comfortable synthesising academic finance literature and can deliver polished, publication-ready prose, I look forward to reading your draft.