Derivatives
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🎯 GARCH is not just a descriptive model — its purpose is to forecast the volatility of future returns on invested capital. In previous posts, we: Now we answer the key question: How do we use the model once we are confident it works properly? 🔧 Forecasting Mechanism The original model is defined as:σt+12=ω+αut2+βσt2sigma_{t+1}^2 =…
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Models of return volatility such as EWMA and GARCH aim to explain volatility clustering. In real markets, calm periods tend to be followed by calm periods, while turbulent periods are followed by turbulent periods. The better a model explains this clustering, the higher its quality. For example, the quality of a GARCH model can be…
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In previous posts, I covered the calculation of portfolio Value at Risk (VaR) and Expected Shortfall using the historical simulation and linear modeling methods. Now, in order to close the topic, I will briefly touch on several additional interesting aspects. Bond Portfolio – Interest Rate Risk In the previous notes, VaR calculations referred to an…
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In the previous note about VaR, I discussed and showed how it is calculated using simulation of historical data. Now I will demonstrate how it is calculated using linear modeling. First, we again construct the statistics of historical data; Then we calculate returns obtained from price changes — LN (t1/t0); After that, we build the…