# Tag Info

0

Hmm... a not fully checked potential solution based on the comment by will, which initially (before I changed the np.random.randn to (underlyings, sims)) all the "random" numbers were identical across the simulations. Anyhow this "appears" to work very fast, although the matrices of random numbers (after fixing the seed) are not the same ...

0

I also have not looked at vba. But the assumption that the leveraged portfolio sharpe ratio is the same as unleveraged book is INCORRECT and a flawed assumption. let the flames start. please google before flaming. but its complicated beyond your code to simulate this feedback loop

5

This was too long for a comment, so I'm writing it as an answer. I have provided some interesting literature that will give you insight into the common pitfalls of backtesting algorithmic trading strategies. Marcos Lopéz de Prado on backtesting: Marcos Lopéz de Prado provides some very good slides giving you a quick introduction to the goal of backtesting, ...

1

In general, the model validation consists of several steps: Checking the model design, i.e. model theory, model assumptions, model limitations, etc.; Checking the model inputs, i.e. market data sources, market data quality, model parameters quality, calibration process, etc.; Checking the model implementation, i.e. checking if the model is implemented in ...

2

This recent paper https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3891120 (highly recommended in its entirety) has its entire section 5 devoted to XVA model validation. You may also find these ORE slides insightful https://www.opensourcerisk.org/wp-content/uploads/2018/12/ore_user_meeting_2018_patrick_buechel.pdf

0

For two GMBs $$S_i(t)=S_i(0)e^{(r-\delta_i)t+\sigma_i W_i(t)-\sigma_i^2 t/2}\,,\quad i=1,2$$ with ${\rm Corr}[W_1(t),W_2(t)]=\rho\,t$ we have \begin{align} \mathbb E\left[S_i(t)\right]&=S_i(0)e^{(r-\delta_i)t}\,,\\[2mm] \mathbb E\left[S_i^2(t)\right]&=S_i^2(0)e^{2(r-\delta_i)t+\sigma_i^2t}\,,\\[2mm] {\rm Var}\left[S_i(t)\right]&=S_i^2(0)e^{2(r-\...

3

Adding to Dimitris' answer (this is a too long for a comment) Proceed as follows: Identify risk factors $r^{(i)}$, $i=1\ldots n$. Say the absolute returns of the pillars 1Y,2Y,...30Y of the discounting and forwarding zero rate term structures. Make sure that you have no gaps in your observations. Based on the time series of each risk factor, run a GARCH ...

3

Let us suppose for concreteness that the 10y swap rate is 0.5% today and was 7% a year and and 6.5% a "year minus a day" ago... reprice the swaps for each historical scenario and calculate returns as the difference between the swaps PV from each scenario and the today's PV This won't help you at all, really. Take a step back and consider your ...

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