Exploring the future of financial data architecture: AI-native financial data foundation, large-scale financial data processing, and financial AI safety & governance
Tag: Risk Management
In the previous blog post, we explored the historical approach for estimating the Equity Risk Premium (ERP). The historical approach is a widely used method that is simple to implement. However, it relies on the assumption that the future will resemble the past, which often does not hold true in financial markets. In this blog post, we will … Continue reading Equity Risk Premium Estimates using Forward-Looking Approach
In this blog post, I will begin exploring the topic of equity valuation, one of the most emphasised areas in the CFA Level 2 curriculum. Before delving into the various equity valuation models, I intend to use this and the next few blog posts to discuss how to estimate the equity risk premium (ERP) and … Continue reading Equity Risk Premium Estimates using Historical Approach
In the previous blog post, we explored the Parametric Method for estimating Value at Risk (VaR). While the parametric method offers the advantage of optimal computational efficiency, it relies on strict assumptions, particularly that returns follow a specific distribution (e.g., normal distribution). For complex portfolios, nonlinear instruments, and scenarios where flexibility and precision are critical, the parametric method may not be suitable. In such … Continue reading The Monte Carlo Method of VaR Estimation
In the previous blog post, we explored the Historical Method of VaR Estimation. The historical method is simple and intuitive; however, it relies on the assumption that financial markets will repeat historical patterns, disregarding structural changes in market conditions. This limitation makes the historical method less practical in real-world scenarios. In this blog post, I will … Continue reading The Parametric Method of VaR Estimation
Value at Risk (VaR) is arguably the most widely used metric for risk management. It quantifies the potential loss in the value of a portfolio over a certain period. In this blog post, I will first provide an overview of VaR, clarifying its definition and discussing its advantages and disadvantages. Then, I will implement Python code … Continue reading VaR Overview and the Historical Method
The concept of Key Rate Duration is discussed in the CFA, Fixed Income, module 1, section 8, "The Maturity Structure of Yield Curve Volatilities" and module 3, section 7, "One-Sided and Key Duration". In the real world, the yield curve does not always shift in parallel. Instead, different maturities may experience varying changes in interest … Continue reading Calculate Key Rate Duration
Delta hedging is an options trading strategy used to maintain a delta neutral position by ensuring that the overall delta of a portfolio is zero, so that the price fluctuations of the underlying asset do not significantly impact the position’s value. Dynamic delta hedging involves continuously adjusting the hedging position to account for changes in … Continue reading Dynamic Delta Hedging with DolphinDB
Options Greeks are key metrics used in options trading and risk management to measure how sensitive an option's price is a series of factors, including: Delta - measures the sensitivity of an option's price to the changes in the underlying asset's price. Gamma - measures the change rate of an option's Delta in respect to … Continue reading Options Greeks
Data Ninjago (Financial Data Architecture) 
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