Our Comprehensive Learning Approach
Here understanding becomes 10 times faster,
taking about 6 minutes compared to an hour required when they were done traditionally.
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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.
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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.
Digital finance knowledge and skills are essential components of the technology transformation. And having the skills to understand how these technologies are deployed and integrated into a business strategy is essential.
Step 3
Implementation & Automation using Python in Real-Time
Market Risk ⇌ Value-at-Risk Methodology ⇌ Backtesting HistoVaR Model
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About Instructor
Meet Pankaj Maheshwari!
He is a seasoned market risk professional with over 9 years of experience in finance, investment, and risk management. His specialized focus is on market risk, and he has a track record of success handling a wide range of responsibilities, including quantitative assessment of internal and regulatory submissions, banks' internal portfolios and regulatory stress-testing, such as CCAR & EBA, with a focus on the interest rate risk asset class of banks' portfolios, validation of risk measurement models, such as VaR, SVaR, and SPS models, through backtesting & stress testing, full revaluation & scenario-generating systems for VaR & SVaR, generation & validation of market risk reports across a variety of regulatory and internal event-specific scenarios, valuation of linear and non-linear fixed-income products, including derivative instruments and risk attribution.
In addition to his professional experience, Pankaj is also a content creator. He built an ed-tech platform, "The FinAnalytics", that offers online learning programs to help candidates upskill and enable them to achieve their dream job. He has delivered 1000+ training sessions to post-grad students and corporate professionals with the most successful training programs being "Ultimate Python for Finance" and "Master Market Risk" and has mentored 600+ candidates and transformed careers in India and other countries around the world. He has a strong belief in the transformative power of automation, machine learning, and artificial intelligence in the investment and risk management domains and is committed to helping others pursue these areas of study.
In addition, he is proficient in programming languages such as Python, R, VBA, SQL, and JavaScript, as well as web design and development. His diversified portfolio of learning, including his proven track record of consistency, hard work, and a commitment to continuous learning, distinguishes him from others. He is a strategic thinker with a results-oriented approach, strong analytical and problem-solving skills, and a passion for investing.