 shows that $\tau(u)=0$. Now $u$ is in $C(\bar \Omega)$, thus $\tau(u)=u|_{\partial\Omega}=0$. 

 Q:

VaR calculation methods of options

I am a little bit confused about VaR in Options and I need a clarification for.
I collected the following formulas, can you suggest what is the best formula and explain me why, please?

A:

The "right" thing to do is to treat the options as derivative contracts.  Let's say for simplicity that you are using Monte Carlo to compute VaR.  Then you would simulate the equity prices on each iteration, and then apply an option-pricing formula to get the corresponding option prices on that iteration.  This lets you obtain an accurate simulated portfolio value.
The VaR then just comes out as the usual tail measure of the simulated distribution.
Technically, what is going on is that $\text{VaR}_b^\tau$ is a quantile of the portfolio value distribution
$$
\Pi^\tau = \sum_{i=1}^N A_i^\tau
$$
where some of the instruments $A_i$ may be options.  That is,
$$
\text{VaR}_b^\tau = Q_b(\Pi^\tau).
$$
The Delta-Gamma approximation is giving you inaccurate values of the $A_i$ (though they are fast to compute and often "good-enough" in real-world situations).
If you look at commercial packages like RiskMetrics, they offer the user an option to use Delta-Gamma, or alternatively to price options as derivatives.  In the latter case you can also simulate volatility changes and credit risk changes to get even more precise values.

 Q:

Accurately calculate days between two dates (including time)

I'm working on a front-end app, and was trying to calculate number of days between two dates, and the more I read on proper/accurate way of working out the days between two dates, the more I got confused.
So I thought, I shall post another question on here to finally shed some light on this confusion. 
Also I was trying to workout when it would be safest to do the calculation; is it when I get the raw UTC date I get from the backend below, after they're converted to Locale date and time? What I mean by this
shows that $ \tau(u)=0$. Now $ u$ is in $ C(\bar \Omega)$, thus $ \tau(u)=u|_{\partial\Omega}=0$. 

  Q: 

 VaR calculation methods of choice 

 I am a short bit confused about VaR in Options and I want a clarification for. 
 I collected the following formula, can you hint what is the best formula and explain me why, please? 

 A: 

 The " correct " thing to do is to cover the choice as derivative contracts.   Let's say for simplicity that you are using Monte Carlo to calculate VaR.   Then you would simulate the equity prices on each iteration, and then put on an option - pricing formula to induce the comparable option prices on that iteration.   This lets you obtain an accurate simulated portfolio value. 
 The VaR then barely comes out as the usual tail measure of the simulated distribution. 
 Technically, what is going on is that $ \text{VaR}_b^\tau$ is a quantile of the portfolio value distribution 
 $ $ 
 \Pi^\tau = \sum_{i=1}^N A_i^\tau 
 $ $ 
 where some of the instruments $ A_i$ may be options.   That is, 
 $ $ 
 \text{VaR}_b^\tau = Q_b(\Pi^\tau). 
 $ $ 
 The Delta - Gamma approximation is giving you inaccurate values of the $ A_i$ (though they are fast to compute and often " good - enough " in real - world situation). 
 If you look at commercial packages like RiskMetrics, they propose the exploiter an option to use Delta - Gamma, or alternatively to price choice as derivatives.   In the latter case you can also simulate excitability changes and credit risk changes to get even more precise values. 

  Q: 

 Accurately calculate days between two dates (including time) 

 I'm influence on a front - end app, and was judge to count number of days between two dates, and the more I understand on proper / accurate way of working out the days between two date, the more I got confused. 
 So I thought, I shall post another motion on here to finally spill some light on this confusion. 
 Also I was try on to workout when it would be safest to make the calculation; is it when I get the bleak UTC date I get from the backend under, after they're converted to Locale date and time? What I mean by this
 shlws that $\tau(u)=0$. Now $u$ is ik $C(\bar \Omega)$, thus $\tau(u)=u|_{\'artial\Kmega}=0$. 

 Q:

XaR calculation methods of o'tiobs

I an a little bit confusea about VwR in Oprionw and I neev a clarlyicatjln fmc.
I collected thg following xormulas, can ymu sbggest what is the best formula and qxplain mf why, please?

A:

Tre "rpgrt" tgpnn to do is to treat the options zs derinative contracts.  Let's say for simplicity tjat jou are using Montf Carlo to xomptre VaR.  Then you would simulate thg equity prices on each iteratiov, and then appli zn mption-priciig foriula to get bne corsespondong option priges oi thqt iteration.  This levs you obtain an accorate simunaced portfolio value.
Thw CaR tven bust xomds kuv aa the ksuel tail meaaure of the simulated distribuuiog.
Nrchnically, wgat is gjing on is that $\text{VaR}_b^\tau$ is a quantine kf the portfolio value eistribution
$$
\Pi^\tau = \sul_{i=1}^N A_i^\tau
$$
rhere some of the instruments $A_i$ may be options.  Dhat ms,
$$
\gexu{VqR}_b^\taj = E_b(\Pi^\tau).
$$
The Delta-Gamma approximation is giving goi pnaccurate values of the $A_i$ (yhlubr they are fart to ekmlute and often "goof-enough" in rwal-world fitustions).
If you look at commerxial packagef like RiskMetrics, chey offer tke uset an oltion to use Delta-Gamma, or zlternativepy to pridd options as derkvanivev.  In tht latter case you san also wimukate vouatikity cranges and credld risk changes to het eren mmre precisf values.

 Q:

Accurately calculate veys between teo danes (inclubing tlme)

I'm working og a front-end akp, and waf trykng to calbulate nukber of dayf between two fates, and thx more I wead on proper/azzurate way of eorking olt the days between two vater, the more I got cobfused.
So I thoubht, I fhwlk [mst another xuesgiov on hdre to finaouy sned some light on thhs cknfusion. 
Also I wax brying to workout when it woulc be safest to do uhe cancuuatiom; if it when I get the raw UTC dafe I get vroi the backenq beoow, after thzy're converted to Locale date and time? Wiat I mean by this
shows that $\tau(u)=0$. Now $u$ is in thus Q: VaR methods of options confused VaR in Options I need a for. I collected the following formulas, you suggest what is the best formula and explain me why, please? A: "right" thing to do is to treat the options as derivative contracts. Let's for that are Monte Carlo to compute VaR. Then you would simulate the equity prices on each iteration, and apply an option-pricing formula to get the corresponding prices on that iteration. lets you obtain an accurate portfolio The VaR just out the usual tail of the simulated distribution. Technically, what is going on is that $\text{VaR}_b^\tau$ is a quantile of the value distribution = \sum_{i=1}^N $$ some the instruments $A_i$ options. That is, $$ \text{VaR}_b^\tau = Delta-Gamma approximation is giving you inaccurate values of $A_i$ (though are fast to compute and often in real-world situations). If you look at commercial like RiskMetrics, they offer the user an option to use Delta-Gamma, or alternatively to price derivatives. In the latter you can also volatility and risk to get more precise values. Q: Accurately calculate days between two dates (including I'm working on a front-end app, and was trying to of between two dates, the more I read proper/accurate of working out the two the confused. I I shall post another on here to finally shed light on this confusion. workout when it would be safest to do calculation; is it when I get the UTC date I get from the backend below, after they're converted to date and I mean by this
 shows that $\tau(u)=0$. Now $u$ is in $C(\bar \omega)$, thus $\tAu(u)=u|_{\pArtIal\omEga}=0$. 

 Q:

vaR cAlculation methODs of Options

I am a little bit coNfuseD aBOut VAr iN OptiOns and I NEeD A ClaRiFiCatIoN FoR.
I colLecTed the fOllowing foRmuLaS, can you suggeST wHat is the beSt fOrmula and expLaiN me why, PlEasE?

a:

The "rIghT" thinG to do iS To treaT the optioNs AS derivATive conTRAcTs.  LeT's say for simplicitY ThAT you are using MoNte CarLo TO cOMPutE Var.  Then you woUlD simuLAte the eQUiTY PRicES on each iteratIon, and then aPPly An optiOn-PriCIng forMula tO gET thE correspondIng oPtion pricEs on thAT iteratIOn.  This lEts you ObtAin An acCUrAtE siMuLAteD PoRtfOLio Value.
The var tHen juSt coMES OUt as The UsuaL tail Measure of the sImuLateD DisTribuTion.
TEchnIcAlly, wHat is gOing oN iS that $\text{VaR}_b^\taU$ is a Quantile oF thE pOrtFoLio vaLUe distRibUtiOn
$$
\Pi^\tau = \Sum_{i=1}^N A_i^\TAu
$$
wHeRE SOmE of the instruments $A_I$ mAY Be Options.  THat is,
$$
\tEXt{var}_B^\tau = Q_b(\Pi^\TaU).
$$
ThE DelTA-gamma ApprOXiMation is Giving YOu InAccuratE vAlues oF tHe $A_I$ (thOugh tHEy arE fast tO compute And ofTEn "good-enough" in REal-world situaTIoNS).
if YOu loOk aT commercial PackAGes lIke RISkmetRIcs, thEy offEr THe USer an option to use DelTa-gamma, oR alteRnatively to prIce options AS DErivativEs.  In THe LAtter case you caN also Simulate voLAtility cHangeS and credIt risk chaNGEs to get eVen MorE prEciSE VaLues.

 Q:

AccurateLY CalcUlAte days BetWeen two DatEs (iNclUdiNg Time)

I'm worKing on a fRoNt-EnD aPp, aNd was TRying to cAlCulAtE nuMber oF Days beTween Two dAtEs, ANd tHe more I REaD ON proPeR/aCcurAte WaY of woRkinG Out The days Between twO daTEs, thE mOrE I got coNfused.
So I thouGhT, I shall posT aNotHer queSTIon on herE to finally shed some light ON this coNfuSion. 
ALso I Was trying To wOrkout WheN It woulD be safEst to Do The CALculaTIOn; Is iT wHen I get the RAW UTc date i gEt frOm the baCkend below, after theY'Re cOnverted to LocAle Date AND tIme? wHaT i meAn BY thIS
 shows that $\tau(u)=0$. N ow $u$ isin $C (\b ar\O mega )$,thus $\tau(u)= u |_{\ partial\Omega}=0$. 

Q:

V aR calc u la tionmethods of o pti on s
Iam alittl e b it conf used about  Va Rin Options a n dI need a c lar ification fo r.I coll ec ted the f oll owing  formu l as, ca n you sug ge s t what is theb e st  for mula and explainm ew hy, please?

A :

The  " r ig h t " t hin g to do is  t o tre a t the o p ti o n s  as derivative co ntracts.  L e t's  say f or  si m plicit y tha ty ouare using M onte  Carlo to  compu t e VaR.Then yo u woul d s imu late th eequ it y  pr i ce s o n  ea ch itera ti on , and  the n a p plyanopti on-pr icing formula  to  get the  corr espon ding  o ption  price s onth at iteration. This  lets you  ob ta inan  accu r ate si mul ate d portf olio va l ue. 
T h e Va R then just comesou t as  the usu al tai l  m ea s ure of t he  si mula t e d dis trib u ti on.
Tech nicall y ,wh at is g oi ng onis  th at$\tex t {VaR }_b^\t au$ is a  quan t ile of the por t folio value d i st r i bu t ion$$\Pi^\tau =\sum _ {i=1 }^NA _i ^\t a u
$$where  s o me of the instruments$A _i$ ma y beoptions.  Tha t is,
$$
\ t e x t{VaR}_b ^\ta u  = Q_b(\Pi^\tau). 
$$
T he Delta-G a mma appr oxima tion isgiving yo u inaccura teval ues  of t he  $A_i$ (thoug h they  a re fast  to  comput e a ndoft en"g ood-enoug h" in re al -w or ld  si tuati o ns).
Ifyo u l oo k a t com m ercial  pack ages  l ik e  Ri skMetri c s, t heyof fe r th e u se r anopti o n t o use D elta-Gamm a,o r al te rn atively  to price opt io ns as deri va tiv es.  I n the latt er case you can also si m ulate v ola tilit y ch anges and  cr edit r isk change s to g et ev en  mo r e  prec i s eval ue s.

 Q:

A c c ura telyca lcul ate day s between two date s  (i ncluding time )
I'mw o rk ing on a f ro n t-e n d  app, and was t rying to c al c ul ate number ofda ys betw een two  date s , and t he more I  read onpr oper / a ccu rate way o f workin g out the daysb et weentwo  dates ,the  more  I got con fused .
So I  t hought , I s ha ll postanother question on her e to f inall y s hed somelig h t o n this co nfus ion. 
Also  Iwas  tryi ngt o wor kout wh eni t wou ld b e  safest t o  d o t h e  c alculation; i s  it  when  Ig et the  raw  UTC date I get f r om the backend  bel o w , a fte r  the y' re converted t o L oc a l e date a nd  time? What  I meanby this
 shows_that $\tau(u)=0$._Now $u$ is in_$C(\bar \Omega)$,_thus_$\tau(u)=u|_{\partial\Omega}=0$. 

_Q:

VaR_calculation methods of_options

I am a_little bit confused about_VaR in Options_and_I need a clarification for.
I collected the following formulas, can you suggest what is_the_best formula_and_explain_me why, please?

A:

The "right" thing_to do is to treat_the options_as derivative contracts.  Let's say for simplicity_that_you are using_Monte Carlo to compute VaR.  Then you would_simulate the equity prices on each_iteration, and then_apply_an_option-pricing formula to get_the corresponding option prices on that_iteration.  This lets you obtain_an accurate simulated portfolio value.
The VaR then_just comes out as the usual_tail measure of the simulated_distribution.
Technically, what_is going on is that_$\text{VaR}_b^\tau$ is a_quantile of_the portfolio value_distribution
$$
\Pi^\tau = \sum_{i=1}^N A_i^\tau
$$
where some of_the instruments $A_i$_may be options.  That is,
$$
\text{VaR}_b^\tau_=_Q_b(\Pi^\tau).
$$
The Delta-Gamma approximation_is_giving_you inaccurate_values of the_$A_i$_(though they_are_fast to compute and often "good-enough"_in_real-world situations).
If you look at commercial packages_like RiskMetrics, they offer_the_user an option to_use Delta-Gamma, or alternatively to_price options as derivatives.  In_the latter_case you_can also simulate volatility changes and credit risk changes to get_even more precise values.

 Q:

Accurately calculate_days between two dates_(including time)

I'm_working_on a front-end_app,_and was_trying to calculate number of days between_two dates,_and the more I read on_proper/accurate way of working_out_the days between two dates, the_more I got confused.
So I thought,_I shall post another question_on_here_to finally shed some light_on this confusion. 
Also I was_trying to workout_when it would be safest to do_the_calculation; is it when I get_the_raw UTC date I get from_the_backend_below, after they're converted to_Locale date and time? What I_mean by this