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SuperCharge Your Career

Quantitative and Computational Finance; Investment and Risk Management Programs

The FinAnalytics is an industry-centric project-based online learning platform that up-skills aspiring students and professionals, facilitating the hands-on experience for them to attain their desired employment opportunities by offering courses around financial products and derivative instruments, quantitative and computational finance, financial market and credit risk, excel and python for finance, and a lot more.











Our Comprehensive Learning Approach

Here understanding becomes 10 times faster,

taking about 6 minutes compared to an hour required when they were done traditionally.


Our methodology encourages experimentation and focuses not only mere acquisition of information and facts but also on encouraging an attitude of critical engagement and analysis of the things we learn. Most of the content has use or application to a context and is extremely connected to their immediate curriculum which makes it easy for the trainees to relate to it before getting into modeling.

Step 1

Gain Conceptual Understanding

Market Risk ⇌ Value-at-Risk Methodology ⇌ A Practical Guide for Risk Professionals

Value-at-Risk measure targets to calculate the maximum possible loss that can occur on investment under normal circumstances at a certain confidence level in a given time frame. Most interestingly, this measure can be applied to a single position, on a portfolio of securities, or on an entire trading desk.

"under normal circumstances" - value-at-risk to be calculated under normal market conditions and for that, the calculated returns using the historical time-series data assumed to be normally distributed. "at a certain confidence level" -  value-at-risk can be calculated at a 95%, or 97.5%, or 99% confidence level. The confidence level determines at what level the firm is willing to assess the risk. "in a given time frame" - the risk can be assessed at different time frames, also called value-at-risk horizon. This horizon refers to the time period between two data points and that time period could be 1 day, 10 days, 1 month, 3 months, or a year to calculate 1-Day VaR, 10-Days VaR, 1-Month VaR, 3-Months VaR or 1-Year VaR respectively.

Step 2

Application with Financial & Statistical Modeling in Excel

Market Risk ⇌ Value-at-Risk Methodology ⇌ Parametric Model

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Our programs are intensive where trainees learn financial & statistical modeling in Excel using an intuitive, step-by-step approach. Trainees will use real market data to build the models from scratch, the way it should be done and being done in the finance industry. These programs are a synthesis of Excel modeling, navigating through various financial data available, and the application of conceptual understanding.


Our programs are focused on delivering practical Python skills for finance professionals looking to maximize their use of these time-saving tools within their organizations. Our programs will provide a view of what lies under the surface of model output, and help to better interrogate a model, along with algorithms, simulators, and predictive engines using statistical and automation tools, opening the paths to get into investment banking, hedge funds, trading desks, and similar roles in other global financial organizations where you partner with data scientists and others to drive the adoption and use of python.