London School of Economics and Political Science｜MSc Financial Statistics (Research)。项目库类目：数据科学 · 理科。
下面的学制、学费、入学时间、语言要求与课程设置均来自该校该项目本身，不与其他学校同一名称的项目共用。
QS 2027 · 第 62 位
学位 硕士 · 学制 1年 · 学费 41900英镑/年 · 入学 9月 · 34 门课程
📖 项目简介
The MSc Financial Statistics programme is mainly intended for students wishing to pursue careers in the finance industry or as a stepping stone towards PhD study in statistics for finance.
It provides high-level training in statistics with applications in finance. You'll learn to analyse and critically interpret data, build statistical models of real situations, and use statistical software packages.
The compulsory courses consolidate your understanding of fundamental ideas in probability and statistics and introduce advanced topics. You can choose options to focus on various topics, including those in statistics (with applications in finance or social science), data science, or approved courses from other departments.
The research stream is similar to the MSc Financial Statistics nine-month programme but involves a compulsory dissertation which replaces one unit's worth of optional courses and extends the length of the programme to 12 months.
R J Larsen and M L Marx, Introduction to Mathematical Statistics and its Applications (5th edition, Pearson 2012)
W N Venables, D M Smith, and the R Core Team, An Introduction to R. Notes on R: A Programming Environment for Data Analysis and Graphics (2016)
以上为伦敦政治经济学院该项目官网项目页原文（英文），本站未做改写或补写。
📋 项目参数
金融统计学（研究）理学硕士
MSc Financial Statistics (Research)
硕士理科
学制1年
学费41900英镑/年
入学时间9月
语言要求雅思 7（W 6.5 / S 6.5 / L 6.5 / R 6.5） · 托福 100（W 24 / S 22 / L 22 / R 23） · 托福（新版） 5.5（W 5 / S 4.5 / L 5 / R 5） · PTE 70（W 62 / S 62 / L 62 / R 62）
就业方向金融机构、科技公司、研究机构、政府部门、咨询公司
岗位分布数据分析师、统计学家、精算师、量化分析师、风险分析师
📚 课程设置（34 门，必修课程 3 / 选修课程 30 / 论文课程 1）
必修课程3 门
ST425统计推断：原理、方法与计算Statistical Inference: Principles, Methods and Computation
ST436金融统计学Financial Statistics
ST458金融统计学 IIFinancial Statistics II
选修课程30 门
MA417金融领域的计算方法Computational Methods in Finance
ST405无监督机器学习与多元数据分析Unsupervised Machine Learning and Multivariate Data Analysis
ST409随机过程Stochastic Processes
ST411广义线性建模与生存分析Generalised Linear Modelling and Survival Analysis
ST416多级建模Multilevel Modelling
ST418高级时间序列分析Advanced Time Series Analysis
ST429风险管理的统计方法Statistical Methods for Risk Management
ST443机器学习与数据挖掘Machine Learning and Data Mining
ST445管理与可视化数据Managing and Visualising Data
ST446大数据分布式计算Distributed Computing for Big Data
ST449人工智能Artificial Intelligence
ST451贝叶斯机器学习Bayesian Machine Learning
ST455强化学习Reinforcement Learning
ST456深度学习Deep Learning
ST457图形数据分析与表示学习Graph Data Analytics and Representation Learning
ST459量子计算与信息Quantum Computation and Information
ST463随机模拟、训练与校准Stochastic Simulation, Training, and Calibration
FM402金融风险分析Financial Risk Analysis
FM413固定收益市场Fixed Income Markets
FM429资产市场 AAsset Markets A
FM441衍生产品Derivatives
FM442金融与风险分析定量方法Quantitative Methods for Finance and Risk Analysis
MA415布莱克与斯科尔斯理论的数学The Mathematics of the Black and Scholes Theory
MA416利率与信用风险理论基础The Foundations of Interest Rate and Credit Risk Theory
MA427非线性优化及其应用Nonlinear Optimisation and Applications
MA435金融数学中的机器学习Machine Learning in Financial Mathematics
MY456调查方法学Survey Methodology
MY457观察与实验研究的因果推断Causal Inference for Observational and Experimental Studies
MY459计算文本分析与大型语言模型Computational Text Analysis and Large Language Models
MY461社会网络分析Social Network Analysis
论文课程1 门
ST499论文Dissertation
✨ 项目特色
该项目官网「Unique Program Features」原文，说的是这个项目自身的特点（学制长短、资助、实践安排、认证等），不是学校层面的通用介绍。
Discover more about our students and department.
Meet the department
Why LSE
The Department of Statistics at LSE is one of the oldest and most distinguished in the UK.
The department has an international reputation for the development of statistical methodology and a long history of pioneering contributions to research and teaching. Many of the world’s most famous and innovative statisticians have been associated with LSE.
Our research spans four main areas – data science , probability in finance and insurance , social statistics , and time series and statistical learning . The department has close links with the Data Science Institute at LSE – an interdisciplinary institute that fosters the study of data science, with a particular emphasis on the social, economic and political contexts.
All aspects of our research were ranked world-leading or internationally excellent in the most recent Research Excellence Framework (2021) , submitted jointly with the Department of Mathematics .
The department’s research strengths are reflected in our teaching curriculum. We have a comprehensive range of undergraduate and postgraduate degrees and doctoral research opportunities – hosted in a vibrant department with a supportive and friendly community of staff and students.
Our alumni enjoy successful careers in diverse areas, such as banking, accounting, finance, statistics, government and business consulting while others pursue postgraduate study or research. Our alumni frequently return to LSE to share their career experiences with current students.
🎯 入学要求
官网给出的录取条件原文，含学校统一要求与该项目的附加要求；语言成绩的具体分数线请到项目官网核对。
Upper second class honours (2:1) degree or equivalent with substantial amount of statistics and mathematics.
Please select your country from the dropdown list below to find out the entry requirements that apply to you.
Overseas
Search for a country English language requirements
The English language requirement for this programme is Standard . Read more about our English language requirements .
Competition for places at LSE is strong. So, even if you meet the minimum entry requirements, this doesn't guarantee you an offer of a place.
However, please don’t feel deterred from applying – we want to hear from all suitably qualified students. Think carefully about how you can put together the strongest possible application to help you stand out.
雅思 7（W 6.5 / S 6.5 / L 6.5 / R 6.5） · 托福 100（W 24 / S 22 / L 22 / R 23） · 托福（新版） 5.5（W 5 / S 4.5 / L 5 / R 5） · PTE 70（W 62 / S 62 / L 62 / R 62）。
伦敦政治经济学院金融统计学（研究）理学硕士的入学要求是什么？
Upper second class honours (2:1) degree or equivalent with substantial amount of statistics and mathematics. Please select your country from the dropdown list below to find out the entry requirements that apply to you.