With the advancement in science and technology, learning has become more flexible with online processes. For in-depth knowledge in any domain, one needs to go through a lot of books which is not possible to have physically. Hence, accessing the free sites where the data and sources are available from where you can get the idea and requisite learning did have become more important. A domain like quantitative finance needs a lot of researching and reading which can be better facilitated with the free sources available online these days for procuring relevant knowledge. Here, is a brief list of what you can get and from where.
Free financial data
As far as grasping of quantitative finance is concerned, it requires a lot of analysis entailed with the relevant sets of data. If you are wondering as to form where you can get the sets of data to run the analysis, there are multiple avenues available these days that offer the same. Dukascopy is surely one of the primary sources from where you can collect your data sets related to forex tick data. Google Finance is another source that offers authentic data sets related to the end of day equity data that will keep you updated about the financial moves of the market. The Quandl is another platform that provides substantial catalog data of the market. The easy to use API helps the users to operate smoothly on this platform. You can also opt for yahoo finance to have a clear insight into the market mechanisms.
Financial Engineering
Financial engineering is an integral part of the quantitative finance domain and can now be learned online through the course. The multilayered syllabus of the domain integrated with course provides the learner with in-depth knowledge and makes him/her a pro in financial engineering and the risk management aspects of it. Indulge in the studies of time series methods to master the strategic part of the quant finance with the introductory books from Eric Zivot. While developing your skills in quantitative analysis, it is important that you brush your mathematical skills as well. Mathematical Methods for Quantitative Finance is another source from where you can get your concepts refreshed once more. QuantNet and Wilmott are two more options to augment your learning and comprehension process in becoming a quant trader.
Algorithmic Trading
A quant trader also needs to understand the dynamics of the market with every change in the parameters related to it. Being an inseparable part of the quantitative finance, this domain also has a lot to research on but at no cost. You can refer to an elite trader to get an update on almost every aspect of trading with special emphasis on algorithmic trading. Referring to QuantConnect will empower a quant with cluster computing, capital data, and other free data. A lot more can be enjoyed if you indulge in a monthly subscription package. Access to minute-resolution US equities data and in-browser Python IDE can be had with Quantopian. You can also share and comment on strategies through Quantopian.
Programming
To master the scopes associated with quantitative finance, it is a mandate to become an expert at programming. The Bayesian Methods of Hackers, Building Skill in Object-Oriented Design, Data Structures And Algorithms With Object-Oriented Design Patterns in Python, High-Performance Python, Learn Python the Hard Way, Think Python, Think Stats, and Natural Language Processing With Python are some of the rich sources from where you can learn to be a smart programmer minus any hassle. Your knowledge of quantitative finance can get augmented at any point of time for free by accessing all of the above-mentioned avenues.
