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Create MarketBackFinal 2.0 #2467
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #2467 +/- ##
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Coverage 85.23% 85.24%
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Files 329 329
Lines 30143 30143
Branches 5173 5173
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+ Hits 25693 25694 +1
+ Misses 3021 3020 -1
Partials 1429 1429 |
Hi @OrsonTyphanel93 Do you have a reviewed and published paper that describes your attack? |
Hi guys!!! @beat-buesser , sorry for the delay, for a peer-reviewed paper describing this attack see this one IEEE Access , Q1 Journal which describes the basis of the attack in the sense of adversarial machine learning :) |
Hi @OrsonTyphanel93 Thank you for the link, let me take a closer look to better understand your work. |
@OrsonTyphanel93 Could you please take a look at integrating your attack into the folder structure and architecture of ART? |
Hi guys @beat-buesser ! , I’ll do it as soon as I can , Thanks again! |
Hi guys @beat-buesser !, I'm on the road right now, maybe an expert on the team (who is interested) can help me integrate the attack into the ART corpus... with pleasure, if not I'll see how I integrate it soon !!!!, :) Thanks to you guys, you're the best :) |
Backdoor attack via jumps-Diffusion and stock market and Bayesian Optimization : MarketBackFinal 2.0
Description
Hi guys @beat-buesser !, I am attaching the latest backdoor attack method based on Dynamic Hedging and rough volatility paths, the attack method is called MarketBackFinal 2.0 and it focuses explicitly on Bayesian optimization (BO) of trading processes. jump via a stochastic diffusion method.
Testing
MarketBackFinal 2.0 : For Bayesian optimization, an advanced black-box objective function is used in order to be able to use quadratic terms introducing non-linearity, sinusoidal components which add periodic fluctuations, making the oscillatory function more complex, thus introducing multiple local minima and maxima:
Update September 12rd, 2024 , last notebook,link
This is the last notebook, the next step will be to incorporate methods into the ART.1.19 framework.
Last update September 20, 2024 , last notebook,link
Reference, Figure
[update notebook MarketBackFinal 2.0 ( best version for fluid comprehension ) link..., notebook link(This notebook corresponds to the two figures you are observing )](https://github.com/OrsonTyphanel93/adversarial-robustness-toolbox/blob/dev_1.14.0/Udpdate_ART_1_18_MarketBackFinal_2_0_adversarial_machine_learning.ipynb
notebook link(This notebook corresponds to all the other figures you'll see, the one where I didn't include the vega and the rho on the studs.)
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END.
The pathwise estimator of the option delta is$$\frac{dY}{dS(0)} = e^{-rT} 1_{\bar{S} > K} \frac{\bar{S}}{S(0)}.$$
with$Z_1,\ldots,Z_m$ independent standard normal random variables. The parameter $\sigma$ affects $S(t_i)$ explicitly through this functional relation but also implicitly through the dependence of $S(t_{i-1})$ on $\sigma$ . By differentiating both sides, we get a recursion for the derivatives along the path:
With initial condition$\frac{dS(0)}{d\sigma}=0$ , this recursion is solved by
The pathwise estimator of the Asian option vega is
Let$V_t^C$ be the value of a Call option at time $t$ whose payoff is $\Lambda^C$ on the underlying $S(t)$
where$\Phi$ is the cumulative distribution function of a standard normal random variable, and $d_{1, t}$ and $d_{2, t}$ are given as follows:
and
Then the unique rational price at time 0 of the Call option can be found betting$t=0$ in the equations of $V_t^C, d_{1, t}$ and $d_{2, t}$ to get the famous Black-Scholes pricing formula:
Fourier transform method for price calculation,sources
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FAQ
to quantify the measure of financial risk, you can apply in the code of this notebook dating from August 2024, this code attached in this notebook.
We quantify the simulations by determining the potential financial risks that may arise over a given time horizon.
A zero coupon bond price subject to default risk (at time$t$ ) with a tenor of $T$ years can be defined as follows ,
where$R$ denotes the recovery rate and $r(t)$ is the instantaneous short-rate process. There is a single unit cash-flow at time $T$ , the pay-off is $R \in[0,1]$ .
where$\delta(t, T)$ and $\tilde{\delta}(t, T)$ represent risk-free and default-risky $T$ period zero-coupon bonds, respectively. The terms $\mathbb{Q}(\tau>T)$ and $\mathbb{Q}(\tau \leq T)$ .
Usage/Examples mathematics concept see
Usage/Examples McKean-Vlasov process