# Tag Info

### Wrt speed, how optimised is QuantLib's Heston pricing class?

QuantLib does a lot of things behind the scenes that provide convenient functionality but get in the way of pure speed. For instance, in your example code, when you write ...
• 7,808
Accepted

### Implicit function theorem and sensitivities to market risk for Nelson-Siegel-Svensson model

To my understanding, there exist two ways to invoke the IFT in quantitative finance applications in a calibration / bootstrapping context. When minimizing some error function during bootstrapping. ...
• 6,977
Accepted

• 11.1k
1 vote

### A quant job interview question about (toy) futures

First, the majority of this answer is due to Rylan whose answer gave me the idea of reducing the number of states to 5. This then allowed me to avoid the use of Bellman's equation which is probably ...
• 1,160
1 vote

### Optimization of Take-Profit and Stop-Loss

It's really important to optimize this step. Returns are not a random walk. If they were, then you could set your stop loss to .25 of a step and take profit to .75 of a step with an expectancy ratio ...
1 vote

### Reverse Optimization: finding the returns that satisfy specific weights given one known return

OP takes Black-Litterman reverse optimization expected returns, overrides one of the values with a different expected return, and finds that the resulting portfolio didn't match the original one. This ...
• 5,421
1 vote
Accepted

### Why not inequality constraint in mean-variance portfolio optimization?

I'm not sure if I understand your question correctly. I'll try to answer, but you ay want to clarify what you're asking. I'll review portfolio optimization and constraints. Typically, you have a ...
• 12.6k
1 vote

### Calibrating the Heston with the Levenberg-Marquardt algorithm

The situation is a little more complicated than expected. We use this notation for the damped least squares equation $$[J^{T}J + \lambda I_{d}] \Delta \theta = -\nabla f(\theta)$$ where $\theta$ is ...
• 66

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