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2

This is wrong: effectiveDate / Valuation_date = 10 May 2014 Good that you included the ISIN, which states that the effective date (as contrasted with the issue date) was a few days after 03 May 2013.

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Let's approximate the time to maturity to be 3 years and 10 months. Assume that coupon is paid on March 6 each year. Let face value $F=100$ and coupon $c=0.07375F$. Let the discount factor be $d(0,T)=e^{−r T}$ where $r=0.06535$. The price of the bond is ce^{−10/12 \bullet r}+ce^{−22/12 \bullet r}+ce^{−34/12 \bullet r}+(F+c)e^{−46/12 \bullet r}=103.24 \; ...

2

Assuming you already have a way to obtain hedge ratios and the like, your best available choice is probably blotter (used to be just quantstrat). You will find that it isn't necessarily oriented toward options. Generally for options backtesting, pros end up making their own or buying commercial software. There are tons of commercial providers, but I ...

0

My first thought would be to use quantlib package to get the delta values and comply those to get a position delta. Then use rules based on delta values to hedge. Use discrete time adjustments or use delta bands.

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You want to set the parameter n.roll to the number of n.ahead, n.roll rolling forecasts you want. (The n.ahead parameter controls how many steps ahead you want to forecast for each roll date.) Thus by setting n.roll to a number almost equal to your sample size, and critically setting the out.sample parameter almost equal to your sample size, you're telling ...

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