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I agree with Student T regarding a lack of texts that will teach C++ specifically geared towards finance, and I would also say that isn't the best way to learn the language anyway. I taught a C++ course for graduate students for several years when I was doing a post-doc. The intent of the course was to quickly get engineering graduate students with some ...


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There are two main roots to risk analysis (as I see it): Statistics Modelling where the first is more real-world and requires data analytics, whereas the second is more academic/theoretical. Personally I am more of a theorist and will advocate the second approach, but to have the maths for the second is a bit of a step up, and is built around stochastic ...


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I would tend to do the following: If, under your working modelling assumptions, there exist closed form formulas, then compare your results to them. "The Complete Guide to Option Pricing Formulas" in @Student T is indeed a nice reference for that. Beware of true formulas vs. approximations though. Now if it's not the case: Compare different pricers' ...


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1: Follow the calculations in The Complete Guide to Option Pricing Formulas. The book has many formulas, sample values and outputs. Highly recommended for validating your results. Apparently, this is one of most popular books used by real-world quants (simple and fast). 2: You can still use QuantLib to price with year fractions. I have an example: ...


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two things I would try...and this is really off the top of my head... is 1). to use put-call parity to check that your work makes financial sense. Call = Spot + Put - (strike price)/(1+risk_free_rate)^Time 2). see if you can recreate anything close to present/past market (Yahoo finance?) data prices, i.e. testing your model against reality. good luck


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you can write the pay-off as $$(S_T-K)_+ I_{\min S_t > L} + RI_{\min S_t < L}$$ for down and out call. The first term is the standard call. The second is the rebate. Its value is $$ Re^{-rT} P( \min S_t < L). $$ There is a standard formula for this probability. See eg my book Concepts.



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