Solved – What statistical tools does a analyst (financial) require

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I just graduated in engineering where I have a very strong background in pure maths, but unfortunately I didnt study any statistics in my course. I know calculus, probability theory, measure theory, analysis etc. But I have not done any courses on regression etc.

I am planning to apply for several "analyst" positions at various banks/investment firms in the coming months.

Amongst some of them, they specifically require the applicants to have a good knowledge in statistics.

What statistical techniques/concepts do I need and should I learn (self study), that an financial analyst would require? Basically I will be analysing and computing statistical and financial data, what techniques should I learn? Should I start with regression, time
series etc.?

As taken from wikipedia, this is something I would probably be doing:

Financial analysts use spreadsheet and statistical software packages
to analyze financial data, spot trends, and develop forecasts. On the basis of their results, they write reports
and make presentations, usually making recommendations to buy or sell
a particular investment or security. Senior analysts may actually make
the decision to buy or sell for the company or client if they are the
ones responsible for managing the assets. Other analysts use the data
to measure the financial risks associated with making a particular
investment decision.

So what statistical concepts/tools/techniques/methods do I need to study, in order to do the above (in the quotes)?

I just got the book George Snedecor: Statistical Methods, but what main concepts/techniques are most important/most used by analysts? I'd like to quickly start into those topics first.

Best Answer

Maybe you want to take a look in Statistics and Finance: An Introduction by David Ruppert. It covers a wide range of topics but none in detail. The author actually written this book with engineers in mind and it's very application-oriented.

Table of Content:

1 Introduction
2 Probability and Statistical Models
3 Returns
4 Time Series Models
5 Portfolio Theory
6 Regression
7 The Capital Asset Pricing Model
8 Options Pricing
9 Fixed Income Securities
10 Resampling
11 Value-At-Risk
12 GARCH Models
13 Nonparametric Regression and Splines
14 Behavioral Finance
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