This is now fixed.

The check_list test function always returns True if one of the arrays is empty.

Description for VAR is extremely dense; it definitely requires much more description on what should be used for the calculation of predicted gain/loss. Even the description in Investopedia provides a formula and denotes each term, which is infinitely easier to understand than the current kata description (which is hopeless to grasp).

The method should be named "get_shift", and should take 1 argument: Name of the Equity/Currency Using our previously imported data

The argument name in the code is misleading:

def get_shift(self, asset):

It is not an asset, it's asset | currency.

Similarly, typo:

def get_var(self, asset, risk_class, convidence):

convidence -> confidence. Tests also uses conv when conf should be the correct term.

Test messages are kind of unacceptable:

MartyCorp un-ordered relative shift should be [0.044444, -0.010638, -0.021505, -0.010989, 0.111111, 0.04, -0.009615, -0.019417, -0.019802, 0.010101]: False should equal True

it only shows the expected value, but not the actual value.

permutation tests is passing in a tuple instead of a list.

Thanks for your kind words.

i happy the the sheer length of the kata-description-text did not scare you away from this kata ( since i think the that the underlying topic is pretty interesting ).

Have a nice day :-)

I would say this kata is pretty tough to solve, but I'm glad I finally completed it after 3 days of thoughts.

I liked this kata, but some parts of kata were pretty unclear to deal with. Still, I managed to resolve them and, with some accuracy tricks, I passed this problem.

Thanks for the kata! :)

No lists were harmed in this solution!

i think that carloscerro is right.

The valuation-test seems to rely on an unchanged input variable.

please check the following code. It will fail for the first basic test (One toggle), but will succeed if you out-commend the lines 2 and 3:

def solve(puzzle):
  if 0 < len(puzzle):
    puzzle[0][0] = (puzzle[0][0] + 1) % 2
  return [(1, 1)]

Hi Reswin,

thanks for the feedback.
In fact, uttumuttu did a good job and seems to be very clever in general.

PS:
This kind of approach ( using past or self-defined relative shifts for the risk-factors ) is not only used to calculate Vaule-at-Risk, but also other by risk-measures like "expected shortfall", or scenarios ( e.g. black friday ) or sensitivities ( checking how much win/loss e.g. a yield shift of 1% would induce ).

@uttumuttu's second suggestion to describe VAR was helfpul for me: "The simplest explanation (of VAR) is that each equity's total shifts are obtained as the relative shifts of its currency-converted price series." I enjoyed the kata because it not only allowed me to practice Python but also to learn about VAR.

Sorry have written, before thinking:

VAR is not sub-additive in both dimensions ( over Risk-Classes and over sub-Positions ).

Will modify th desciption accordingly.

Hi uttumttu,

thanks a lot for your input.
Since i am very new to writing kata, i do need some help indeed.
It's in fact a thin line between spoiling too much of the algorythm/implementation or potentially frustrate someone trying to solve it.

i don't know, if that is common practise, but feel free to apply some your suggestions to the description, as well.

I added the following section ( it's near the end ), but i do get the feeling, that the whole kata description may be too long now ( distracting interested people ) for such a relative simple calculation :

We had no Forex risk involved in this example, since the equity was listed in your base-currency.
Please ensure that the shifts of the foreign currency are taken into account, as well, when calculating the 'Total'-VAR for a foreign-currency-equity-positions.

You then might notice some kind of strange behaviour of your VAR-results:
VAR is not additive !

So neither

total VAR = equity VAR + currency VAR

nor

VAR(EQ_all) = VAR(EQ1) + VAR(EQ2)
for an Equity position EQ_all that consists fo Equity position 1 ( EQ1 ) + Equity position 2 ( EQ2 )

In fact, the VAR for a given position might be lower or equal than the sum of the VAR of it's parts.

When looking at the different Riskclasses, it's even 'worse': The total-VAR can be lower, equal or bigger than the sum of equity-VAR and currency-VAR.

Keep in mind, that the Value-at-Risk measurement is based on the potential top losses (relative shifts) only. And these top losses ( for individual equities or riskclasses ) may have occurred on different historical days ( for the equities/riskclasses ) involved.