How I would start learning Quantitative Trading again

摘要： Advent of financial markets has been one of the biggest enablers of innovation as well as prosperity in the modern era making it possible for corporations to raise....

▲圖片來源：medium.com

Advent of financial markets has been one of the biggest enablers of innovation as well as prosperity in the modern era making it possible for corporations to raise capital in public markets at a point where private markets become insufficient. Public markets have become the ultimate judge of these corporations, rewarding as well as punishing them in a just manner. Markets have no mercy but no malice as well.

Along with markets, market participants i.e. Traders have changed a lot too. Trading pits are a thing of past and Quantitative/Algorithmic Trading where bots take care of trade execution, getting fills in order of milliseconds is not unheard of. I personally find my work days as a Quant to be extremely challenging as well as mentally stimulating.

If you’re getting started, this article is for you. If you’re a veteran, you can offer your advice or critique my ideas. Most of my journey up till here has been a lot of exploring on online forums to develop my understanding of the secretive world of Quants as well as working with them closely through internships. I am writing this article for my 2 years younger self who is just beginning his journey towards Quantitative Finance.

Let’s get into it, shall we?

Domain Knowledge

Quantitative Finance:

• Options, Futures, and Other Derivatives (John C. Hull): Literal bible. Pick this up to develop a good intuition on all concepts pertaining to quantitative finance

• Akuna Capital Option 101 Course: Gives a really good overview of Market Making from an industrial standpoint in the beginning. Next, dives deep into Futures, Option Strategies, Payoffs, Time Premium / Put-Call Parity, Theos, Covered Trades, Greeks, and Volatility Calculations

Time Series Analysis

• Analysis of Financial Time Series (Ruey S. Tsay): Almost every dataset that you deal with as a Quant would be a time series. Understanding various types of models and prediction methods as well as refining financial time series’ and removing unnecessary components is an important part of building a strategy

Machine Learning

• Stanford (CS 239 and CS 231) / DeepLearning.AI: Crunching through numbers and huge datasets is an integral part of Signal Construction. A background in ML really assists in that and would make you competent enough to understand the mathematics in research papers which is super beneficial for someone aiming to become a Quantitative Researcher

Hands-on Experience

• Kaggle for Quants (QuantConnect, Numerai, Alphien): Get your hands dirty with these platforms, they consist of tournaments/competitions as well as backtesting environment. Here is a good introduction to understanding backtesting on such platforms

Discussion Forums

• WSO: The community of finance bros on WSO is simply priceless. To get the realest views about various sectors of finance and know first person views on working environment as well as interview process, this is the go-to place

Interview Preparation

Probability

• First Course in Probability (Sheldon Ross): Probability questions are generally discrete probability problems or ones based on Expected Value / Variance concepts. Make sure to practice all questions from Fifty Challenging Problems in Probability and Heard on the Street (Chapter 1, 4)

Statistics

• Basics of Statistics are very important and always asked in the interview. eg. Assumptions of Linear Regression. One discrete random walk question can be expected. Lots of basic discrete/continuous R.V. probability questions. These are good notes to quickly grasp the concepts.

Puzzles

• Brainstellar: Complete all problems (Easy, Medium, Hard). There would be a lot of repeated questions in interviews and would immensely help in responding quickly if you have seen the problems beforehand

Speed Mental Math

• A lot of trading firms test the quickness and accuracy of responses to simple math questions eg. 2 digit multiplication, square root etc. Start practicing daily from the following platforms about 3 months before the interview to leave no chances of failure in such a simple round (typically the first one).

Guesstimates

• Estimation questions (you might be asked for confidence interval too) to be answered within 10-20 seconds. eg. What’s the percentage of the world population under the age of 15? Approach the problems from either top-to-bottom or bottom-to-top approach, estimating the size of components at each level (here)

Data Structures and Algorithm, Programming Skills

• Competitive Programming: Completing either of InterviewBit / LeetCode should be enough for Quant Trader roles but things get very subjective here. Indian firms focus much more on CP than their foreign counterparts in my experience.

轉貼自Source： medium.com

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