o**n
发帖数: 2130 | 1 Higgs gamma gamma, cms 6-sigma， atlas 5-sigma higgs 125 ,with large MET |
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T*********r
发帖数: 11175 | 2 Higgs\to \tau\tau以及bbar的新结果
对超越标准模型也不太好
Higgs\to \gamma\gamma压根就没有公布
据说也是往回走了。。。。 |
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s*******i
发帖数: 12823 | 3 原则上波长可以短到planck length， 能量是 10^19 GeV
现在观测到的gamma ray的能量离这个能标应该还差得远吧,通常的超高能gamma ray也
就几个 GeV量级
长波就没谱了，太长的你也没有那么大的天线来接收吧.. |
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r*****t
发帖数: 286 | 4 ☆─────────────────────────────────────☆
theta (delta, gamma and vega) 于 (Tue May 1 22:59:25 2007) 提到:
(x1,x2,x3)--multiNorm(u,sigma), and we know u and sigma.
then condition on x3=x, what is the covariance matrix of muitinorm distr
ibution (x1,x2)?
anyone can shed light on this?
☆─────────────────────────────────────☆
quantler (quant) 于 (Tue May 1 23:03:41 2007) 提到:
熬了一个通宵后 我的神智已经不是很清醒了
不能帮您了：）
☆─────────────────────────────────────☆
theta (delta, gamma and vega) 于 (Tue May 1 2 |
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q********u
发帖数: 53 | 5 trade realized vol against implied vol
Mostly people hedge delta periodically = trading vol
BS expansion shows that Your winning will be your gamma part
your losing will be your theta part because theta is negative for non-div
option
Gamma part contribution > theta part lose it will be a winning trade
Otherwise, it will be a losing trade
sell |
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S*******r
发帖数: 11017 | 6 用SPOT把DELTA成分HEDGE掉 就留下GAMMA部分 然后坐在头寸上 赌GAMMA效应大过TIME
DECAY
在用SPOT来回HEDGE过程中 可能还能来回抽几下油水 大约是这样的 高人请指正 |
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z****u
发帖数: 185 | 7 First, insightful comments!
Can you elaborate on the following statement? why the gamma of a variance
swap is constant? what is this constant btw? any assumptions assumed?
Thanks.
...
换而言之，不管是股价冲天还是股价暴跌，variance的$gamma都是constant |
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i****e
发帖数: 78 | 8 var swap is priced and replicated such that gamma is const,
a simplified example:if you buy 1 contract option for each possible strikes,
then no matter where the underlying is, there always exists
an option ATM in your basket, then your gamma is nearly const
when underlyer moves around.
you can google var swap for more details. |
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m********0
发帖数: 2717 | 9 但是那个paper里面只给了个limit啊。o(1)多没劲
再说1/Gamma(n) - 3/2 不都是负的了？
Gamma(n) 不是(n-1)! 吗？ |
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u********e
发帖数: 263 | 10 算是我转述错了。gamma(n)^-1 只说gamma函数的反函数。 |
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l*****i
发帖数: 3929 | 12 Normally (Note I said normally) for a portfolio, gamma and theta have opposi
te signs.
and
gamma |
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p**********9
发帖数: 101 | 13 1.IBM is 10% of an index, the delta of the index is $100M, the gamma is $10M
, and the vega is $1M. What's the delta, gamma and vega of IBM?
2.100 coins, 1 has 2 heads, the others are fair. If you pick one coin and
flip it 100 times and get 100 heads, what's the probability that it's the 2
headed coin?
3.Assume you have a fair coin. How many flips on average does it take to
get two heads in a row. This I answered without any problem and no help.
anyone know the answers?
I am totally confused |
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t*****e
发帖数: 38 | 14 1) how would you replicate a binary call from vanilla call and put?
I said by using two strike with k and k - delta and then normalize?
2) you have 4 risk reports for 3 portfolios and the cumulative portfolio?
under what condition that the cumulative delta, gamma are not the sum of
individual deltas and gammas?
give me some baozi bah |
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t*****e
发帖数: 38 | 15 you are given n+1 reports for the delta, vega, gamma of n portfolio manager,
why you need the extra one, i.e., under what condition the linear
relationship between aggregate delta(gamma etc...) and individual delta
breaks down? |
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D**u
发帖数: 204 | 16 The law of sin in R^3 is different from the plane case.
In R^3, the law of sin is instead to be:
sin(a)/sin(alpha) = sin(b)/sin(beta) = sin(c)/sin(gamma),
where alpha, beta and gamma are the dihedral angles
between the vectors. |
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g******n
发帖数: 7 | 17 Gamma is the second order derivative of call option price w.r.t the
underlying price.
Second order derivative describs convexity.
Simple call option is always convex, so gamma is positive. |
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w*****m
发帖数: 414 | 18 Thanks, moonsspring and gbmorgan,
I was wrong. I mean it but wrote something wrong.
Yes, you are right. Simple call option is always convex. It's very clear why
gamma is always positive.
But could you tell me a little bit more about how to short gamma? |
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l*******l
发帖数: 248 | 19 why do we make gamma neutral first, then delta neutral? I don't think small
positive gamma matters. |
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t**********a
发帖数: 166 | 20 small gamma does not matter, even you can't make strictly delta neutral in
reality (trade size need to larger than some size).
At the end, it all depends on the views, if you want to express view on
realized price move vs implied vol, you might want to long or short gamma... |
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l*******1
发帖数: 113 | 21 vega1 = gamma1 * s^2 * vol * T1
vega2= gamma2 *s^2 * vol * T2
sum(vega) = 0 = s^2*vol*sum(gamma*T）
if T is the same, then vega neutral = gamma neutral.
If T is different, then its not equivalent. |
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t**********a
发帖数: 166 | 22 vol can be different for different strike, plus with vol smile, calculated
gamma is no longer black-scholes gamma even using BS pricer ... |
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m*********g
发帖数: 646 | 23 看你HEDGE到什么程度了。如果你GAMMA NEUTRAL 了那GAMMA没影响。但你需要DYNAMIC
HEDGE。 |
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l*******l
发帖数: 248 | 24 不可以吧，long call gamma为正，股票gamma是0 |
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x******a
发帖数: 6336 | 25 Receiver: thank you very much.
From what I know, after delt hedge, theta is approxiamte -1/2*dollar gamma*
vol^2. And in the static replication, the weight of the options is chosen so
that dollar gamma is a constant. I think theta is therefore a constant. I
am not quite familiar with this area. Can you let me know some reference
besides the two papers from JPM and GS? Thank you again.
be |
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l*******1
发帖数: 113 | 26
你确定？
jump是有利对冲的，因为你short一个option。无论是jump up 还是down，你的PnL on
the option是
-delta*(change price)，
如果是正常的call, 你的损失是 -[delta*(change in price) + 0.5*gamma*(change
in price)^2]
比起正常的hedge，如果有jump，你的hedge cost 变低了。
seller 在卖option的时候，因为option with jump 让seller delta-hedge时候在
gamma上的损失比较小，所以必须价格比普通call要高。 |
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r**a
发帖数: 536 | 27 Actually, this is a really good question. First, we need to know the
definition of risk free portfolio or how to capture the risk in terms of
math. In my opinion, you have to go to the VaR. The risk free portfolio
should be defined by VaR_1(L)=0, which means that we have 100% confidence
that the probability that the loss L exceeds 0 is no larger than 0. Here the
loss L is defined by $L=V(t, ...)-V(t+\delta t,...)$. Note there are
several different kinds of definations of L, e.g. discounted loss ... 阅读全帖 |
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l*******1
发帖数: 113 | 28 Infinity.
overall gain = premium + hedging error
hedging error = -1/2*gamma*(realized variance - implied variance)
if realized variance is infinite, then hedging error is infinity...
lose insanely on the gamma. |
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k****z
发帖数: 550 | 29 你也说到了，本质上的方法都是gamma hedge。
问题是要分析你的市场的Gamma来源是什么，是模型，是供求曲线，还是别的来源。至
于怎么hedge的方法有时候是需要想象力的。 |
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m******t
发帖数: 273 | 30 【 以下文字转载自 Statistics 讨论区 】
发信人: myregmit (myregmit), 信区: Statistics
标 题: find distribution paramters only by data mean and std. dev.
发信站: BBS 未名空间站 (Mon Mar 17 17:14:15 2014, 美东)
I need to estimate a truncated gamma distribution paramters (shape , scale).
But, I only know the data mean and std. dev. I do not know the dat set.
Given the mean and std. dev. of a data set from a trucnated gamma
distribution, how to find shape and scale of the distribution parameters ?
I know MLE may be sueful for ... 阅读全帖 |
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m******t
发帖数: 273 | 31 【 以下文字转载自 Statistics 讨论区 】
发信人: myregmit (myregmit), 信区: Statistics
标 题: solve an optimization model with integral as constraints
发信站: BBS 未名空间站 (Wed Mar 19 22:21:44 2014, 美东)
I need to solve a mathematical optimization model with integral as
constraints.
Min. | s1 - k1 | + | s2- k2 |
s.t.
integral_from_0_to_M of f(x) = 1
s1 = integral_from_0_to_M of x * f(x)
s2 = integral_from_0_to_M of x^2 * f(x)
M, k1 and k2 are positive numbers
f(x) is a proba... 阅读全帖 |
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S*******s
发帖数: 13043 | 32
当然不是。波动率只是期权价格的一个参数。
这不是套利是投机vega (gamma)。hedge delta赌gamma每天都有很多人做。 |
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W**********r
发帖数: 68 | 33 5. Suppose you have bought a July ITM call and sold an August ATM put.
What would be your delta in this position? Once you hedged out your delta
what are the following greeks:
-Gamma
-Vega
-Rho
-Theta
这个我觉得是long Gamma，short Vega， long Rho， paying Theta
6. Suppose you know the following information about a market:
- Future is at 66
- 70 strike straddle is trading at 27
- 50-60 put spread is at 2.5
- 50-60-70 put fly is at .2
- Assume volatility is constant across strikes
Using the prices given an... 阅读全帖 |
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s******k
发帖数: 6659 | 34 Negative gamma position? Hedge by long gamma? |
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s**e
发帖数: 103 | 35
for adiabetical expansion, P*V^{\gamma}=constant. \gamma=c_p/c_v
another useful equation is the ideal gas state equation, PV/T=constant. |
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z****e
发帖数: 2024 | 37 "the interval estimation" or say the "inference", based on the law of large
numbers, ie, asymptotic normality.
However, since GAMMA has none zero mean, i'm not sure, how to fit b1 and b3
using OLS because GAMMA has two parameters \theta and \k as well.
no
be |
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w**********y
发帖数: 1691 | 38 Gamma啊.两个parameter非常flexible,你要decreasing的或者近似symmetrical的都行.
在insurance中,有loss ratio model.而常用来描述每次claim的loss(简单理解成赔偿
金额)的distribution就是Gamma.
如果要fat tail的,那就需要更复杂的.
看这里面的图:
http://en.wikipedia.org/wiki/Gamma_distribution |
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a*********r
发帖数: 108 | 39 先把b取个倒数，仍然记作b，然后求b的UMVUE。
这时E(X)=a/b,Var(X)=a/b^2
记y＝sum(x1,...,xn)
则y~Gamma(na,b),a已知
1/y~Inverse Gamma(na,b)
E(1/y)=b/(na-1),Var(1/y)=b^2/((na-1)^2*(na-2))
于是就令估计量bb=(na-1)/Y, Y是y代入x的那些样本值。
Var(bb)=b^2/(na-2)
而算一下可以知道C-R下限是b^2/(na)，就差一点
另一方面算算便可知a已知的情况下，minimal sufficient and complete statistics
就是y＝sum(x)了
bb已经是y的函数，condition on y无法进一步缩小方差，CRLB不可达到。
Rao-Blackwell + Lehmann-Scheffe定理，bb是UMVUE
仅供参考，不知道搞错了没有。 |
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m**c
发帖数: 88 | 40 楼上的解释是对的.
但是如果我同时生成几种分布的随机数,比如:
set.seed(1)
x1=rnorm(10) #生成10个正态分布的随机数
y1=rgamma(10) # 生成10个Gamma分布的随机数
............
set.seed(1)
x2=rnorm(10) #生成10个正态分布的随机数
y2=rgamma(10) # 生成10个Gamma分布的随机数
我想 x1 = x 2 应该是没有什么疑问吧.
但是y1 不一定等于y2吧?
也就是说R里面set.seed()函数仅对其后的第一类随机数生成器(本例子中rnorm())起作
用,对其他的随机数生成函数没有作用(rgamma)? |
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s****e
发帖数: 1180 | 41 R 2.12.0的help不好用。将自己电脑上的R升级至2.12.0版本，发现丫的help不好用。
我打了help(gamma)，结果如下：
> help(gamma)
starting httpd help server ... done
Error in shell.exec(url) :
file association for 'http://127.0.0.1:13108/library/base/html/Special.html' not available or invalid
Anyone， any idea? |
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e****i
发帖数: 104 | 42 你可以用mathematica算算，我试了一下答案是2^(-1 - n) exp(-c^2) Gamma[1 + n]
HypergeometricU[(1 + n)/2, 1/2, c^2]，如果n是正整数，gamma(1+n)=n!，
Hypergeometric 可能也有比较简单的解析形式，你查查看吧 |
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c**i
发帖数: 234 | 43 感谢楼上的，看来我没说清楚。我的问题是现在已经有log（pi/1-pi），并且是一个连
续分布的变量，看图形比较像gamma distribution的样子，我想问我有了log（pi/1-pi
），并且知道x1和x2，现在想要估计参数b0,b1,b2,该如何估计？是直接用linear
regression么？如果是的话glm（）里面那个family是不是要设置成gamma？谢谢 |
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r****t
发帖数: 10904 | 44 let A = (Z - X_\gamma \beta_\gamma)' (中间那个差）
用 n = 1'1 => nA = 1'1A, 上面 taylor expand 对应下面项，
然后应该有别的 (是 regression 吧) 假设让 1'1A == A11', |
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K****a
发帖数: 67 | 45 请版上好心人帮帮我一下，感激不尽
需要用SAS Monte Carlo simulation，模拟一组实验数据 group randomization trial：
要求outcomes within a group are correlated and binary(0/1)，given
correlation coefficient as rho=0.01.
predictor variables 有categorical (e.g. treatment, gender ....)和continous
类型。
我搜了许多文献，许多写道要用beta-binomial distribution 来生成数据，可是依然
没有弄明白怎么写code,把这个outcome的相关系数rho插进去，或者我怎么确定相关度
是我想要的呢？
谢谢各位
这是网上一个例子：
data test;
>> b0 = -1.3;
>> b1 = 2.2;
>> b2 = 0;
>> s = 0.6;
>> do group=1 to 30;
>> gamma = s*rannor(123... 阅读全帖 |
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s*********e
发帖数: 1051 | 46 if the positive part is indeed gamma, then full distribution shouldn't be a
mixture.
however, it could be a two-part model, one for point mass at zero and the
other gamma. |
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m****l
发帖数: 528 | 47 请问，有哪个现成的R package或者function能产生Multivariate Exponential/Gamma
的随机数？
我知道MASS里的mvrnorm可以产生多元正态随机数，但是google了半天也没找到产生多
元指数或者多元gamma的package。。
求大牛指点！ |
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m******t
发帖数: 273 | 48 I need to estimate a truncated gamma distribution paramters (shape , scale).
But, I only know the data mean and std. dev. I do not know the dat set.
Given the mean and std. dev. of a data set from a trucnated gamma
distribution, how to find shape and scale of the distribution parameters ?
I know MLE may be sueful for solving this problem. But, they depend on
knowing the whole data set.
Any help would be appreciated. |
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m******t
发帖数: 273 | 49 Yes, I have only mean and std. dev.
I only need to find shape, scale. If we can also find location, it will be
better.
I have a group of data mean and std. dev. It means that each data point in
the given set is a mean and std. dev., which are calculated from a truncated
gamma distribution.
Each point may have a different truncated gamma distribution, which has the
same truncated values.
They may have some relationship between any two data point (mean, std.dev.),
but, we do not know.
So, it makes... 阅读全帖 |
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m******t
发帖数: 273 | 50 I need to solve a mathematical optimization model with integral as
constraints.
Min. | s1 - k1 | + | s2- k2 |
s.t.
integral_from_0_to_M of f(x) = 1
s1 = integral_from_0_to_M of x * f(x)
s2 = integral_from_0_to_M of x^2 * f(x)
M, k1 and k2 are positive numbers
f(x) is a probability density function of x with arguments of
(alpha, beta, 0, M)
f(x) = G * (x * beta)^(alpha -1) * e^(-x * beta)
G = alpha * beta / [( gamma(al... 阅读全帖 |
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