k**k
发帖数: 61 | 1 从概念上讲，这个优化问题没什么难的．但我想用matlab中现有的功能去实现，比如说
最常用的constrained optimization中的fmincon函数．难点就是如何设objective
function.要能做到在每一个weight scenario下能自动找出对应的expected shortfall
．之前我提的objective function就是一个workable的例子，只是我没看懂．谁能有具
体的idea? |
|
k**k
发帖数: 61 | 2 You are exactly right. I accidentally dropped the summation term. Could you
please explain why this yields the correct answer? Note that "a", the 95%
VaR varies under each weight scenario. The algorithm I saw starts with a
relatively arbitrage value of "a". Under that objective function, it returns
the same optimal weight each time.
Thoughts? |
|
k**k
发帖数: 61 | 3 How should I interpret this? By setting the objective function that way I
could achieve optimization of both parameters simultaneously? Still kinda
hard to grasp though. Any literature that talks about such idea?
which |
|
m***s
发帖数: 605 | 4 see
Rockafellar, R.T. and Uryasev, S., 2000, Optimization of conditional value-a
t-risk. J. Risk, 2, 21-41.
Rockafellar, R.T. and Uryasev, S., 2002, Conditional value-at-risk for gener
al loss distributions. J. Bank. Finance, 26(7) 1443-1471.
But I thought you were doing parametric CVaR. You have marginal and t-copula
. Everytime, you change the weights, your parametric CVaR should be differen
t from the non-parametric CVaR, no? |
|
l******f
发帖数: 568 | 5 optimization methods in finance
low |
|
n**h
发帖数: 237 | 6 请问有经验的大侠商用Portfolio Optimizer那种比较好。
谢谢 |
|
n**h
发帖数: 237 | 7 顶一下。
是不是大家都自己写optimizer。不用商用的啊？ |
|
i**M
发帖数: 108 | 8 【 以下文字转载自 Mathematics 讨论区 】
发信人: iFEM (莫扎特的音符), 信区: Mathematics
标 题: optimization question
发信站: BBS 未名空间站 (Wed May 25 16:52:30 2011, 美东)
Suppose c(p) is a monotonically dreasing function as shown in the picture. c
is the cost and p is the risk. As p increases, the risk is increasing but
the cost is decreasing. The question is how to minimize the cost and keep
the risk not too high? Thanks! |
|
z****g
发帖数: 1978 | 9 你又没给target function，谈何optimization |
|
C***m
发帖数: 120 | 10 If the underlying pays no dividend, the call option on this underlying is
never optimal to early exercise.
Foreign currency call option takes currency as underlying, while people earn
interest from currency. It is like currency paying dividend, so it may not
satisfy the no dividend assumption.
to |
|
x******a
发帖数: 6336 | 11 1.解一个ode或者pde求出x*,所以你得到了一个极大domain D
2.optimal stopping time就是第一次hit D的边界的时间。u*(x)=E^xu(X_(t_D))
3.有积分多加一个coordinate, 和没积分没有本质区别.
4. RXNT同学注意到这个第一问入手 \rho > \mu 积分难道不是正无穷？
X_0>0的时候，E(|X|)=E(X)=X_0*exp(\mu t)，你可以先看看习题10.17.
和 Ch 10 Oksendal - Stochastic differential equations (book)(6ed., Springer
, 2003)(385s).
)) | X(0)=x]
到达X*，应该stop。
Option Without Maturity的求解，之后怎么做？就不会了 |
|
a*s
发帖数: 425 | 12 做optimization
一般不用matlab吧，特别是matlab提供的优化package,好像比较弱,
不过有些solver的确是用matlab写的，比如一些SDP solver
LP,MIP,这种一般用CPLEX,Gurobi
QP好像mosek比较好，不过CPLEX应该也差不多
NLP有很多solver, 比如 knitro, filter，很多 |
|
c****y
发帖数: 3592 | 13 cplex是个软件，用起来不太方便吧，能不能导出code？除了optimization,其他code还
是要自己写的 |
|
Y******u
发帖数: 1912 | 14 i don't think this is linear optimization |
|
a*s
发帖数: 425 | 15 找个nonlinear的solver 比如knitro或者filter都可以解，就是找到的可能是local
optimal |
|
q**j
发帖数: 10612 | 16 就是普通的quadratic programming optimizer。最好有现成package解常见问题的。另
外r 里面的 Rmetrics有人用过没有？能否handle比较大的数据？（最好5分钟一次那种
，或者daily的也行）。多谢指教。 |
|
q**j
发帖数: 10612 | 17 就是普通的quadratic programming optimizer。最好有现成package解常见问题的。另
外r 里面的 Rmetrics有人用过没有？能否handle比较大的数据？（最好5分钟一次那种
，或者daily的也行）。多谢指教。 |
|
p*****y
发帖数: 529 | 18 一般这种optimizers有trial period没有？ |
|
v******e
发帖数: 6 | 19 多谢前辈指点。我以为optimization方向比较好找工作，原来并非如此啊 |
|
a****n
发帖数: 56 | 20 同求，方向是stochastic optimization,编程还成，如何找工作有人理啊》》》》？？
？？ |
|
L******g
发帖数: 1371 | 21 Other than Mosek,
Is there any free c++ package for optimization?
Google it found CGAL, OOQP,QuadProg++,
any one have experience to use these?
any comment are more than welcome! |
|
S*********g
发帖数: 5298 | 22 要不就自己写吧。或者做些近视整点close form的解。portfolio optimization的话差
别也不会太大
★ 发自iPhone App: ChineseWeb 8.6 |
|
L*******t
发帖数: 2385 | 23 业界Portfolio Optimization都有什么model啊？ |
|
S*********g
发帖数: 5298 | 24 肯定写不过他们，但也不至于万倍吧
搞明白自己的问题，做些适当的简化。程序就会变的很简单。建的portfolio也不会差
那么多。risk model/market impact上的噪音引起的问题恐怕比optimize本身的误差要
大的多
★ 发自iPhone App: ChineseWeb 8.6
★ 发自iPhone App: ChineseWeb 8.6 |
|
l******9
发帖数: 579 | 25 I need do some SQL server query design.
For doing the same query, there may be many different kinds of query design.
But, I need to learn which kinds of query design/implementation are optimal
for performance.
Could anybody recommend some books/publications to learn how to do that ?
Any help would be appreciated. |
|
L*******t
发帖数: 2385 | 26 portfolio optimization现在业界有啥好办法么？ |
|
Y******u
发帖数: 1912 | 27 是啊，他们的strategy就是不同theme的optimize asset allocation，没有一个个小的
alpha strategy |
|
|
h*******e
发帖数: 68 | 29 【 以下文字转载自 JobHunting 讨论区 】
发信人: idontknow (碧螺春真好喝), 信区: JobHunting
标 题: 面试题 (statistician and optimization) --总结
发信站: BBS 未名空间站 (Tue Aug 14 17:44:37 2007)
9 个不同勒礼物，分给4个小孩，每个小孩至少要分到一个礼物，问有多少种分法？
◎◎
好像很难算，因为每组个数不确定。
======================================
方法一，也是我最喜欢勒解法 (first by nowoman in Quant)
假定"9 个不同勒礼物，分给4个小孩，每个小孩至少要分到一个礼物" 的方法为f(9,4)
,then, we have,
f(9,4)=4^9-c(4,1)*f(9,3)-c(4,2)*f(9,2)-c(4,3)*f(9,1)
Where f(9,1)=1
That's it! |
|
o******6
发帖数: 538 | 30 ☆─────────────────────────────────────☆
orioniori (猎人) 于 (Sun Mar 2 16:20:58 2008) 提到:
发信人: orioniori (猎人), 信区: EE
标 题: Nonlinear Constrained Optimization 问题求教
发信站: BBS 未名空间站 (Sun Mar 2 14:18:31 2008)
在下是新手，不才， 有初级问题请教达人们：
目标函数 F(x1,x2,....xn)可以closeform表示出来，是个非线性函数（很多erfc函数
和指数运算，非Quadratic）。
约束函数T(x1,x2,....xn)也是一个非线性非quadratic的函数，并且可以closeform表
示出来。
现在给定Tmax上限常量，要求：
[x1,x2,....xn] = argmax{F(x1,x2,....xn)}
s.t.
T(x1,x2,....xn) <= Tmax
有什么比较好的方法，除了穷举之外？
有什么比较好 的reference或者tutorial可以参考? |
|
l*******D
发帖数: 282 | 31 Sorry cannot type Chinese here.
Does anyone know how to do multi-dim optimization in R? Basically the
parameter has four dim and I want to find the best estimate for these
parameters using MSE.
Any suggestion for related documents would be greatly appreciated. |
|
|
B******5
发帖数: 4676 | 33 算是吧，不过主要用于discrete的optimization |
|
N******n
发帖数: 3003 | 34
algorithm
好像不算numerical solution, but it can be an approximation to numerical
optimization. |
|
y***n
发帖数: 51 | 35 我觉得Genetic algorithm 是算numerical optimization的。很多书本都只介绍比较传
统的方法，就想你前面列出的newton raphson. |
|
l*******3
发帖数: 186 | 36 做maximum likelihood estimation，用optimization怎么都的不出正确的数值。现在
是做simulation阶段，总共10个parameters，如果固定其他parameters，只让一个
parameter变，那么likelihood function确实总在true parameter valuealuede地方是
最大的，但是所有parameters放在一起optiomize likelihood function，就怎么都的
不到真实parameter value。到底是怎么回事呢？大侠帮帮忙啊，谢谢！ |
|
k*******a
发帖数: 772 | 37 也许是R的问题，试试MATLAB或者SAS的optimization function |
|
d******1
发帖数: 1389 | 38 维数太高了，很难converge到你的global maximum。如果你的目的只是求，mle，试一
试grid search。每个参数optimize的时候不要用gradient descent的方法，在一个范
围内取一个grid，取能maximize你的mle的grid上的值。
如果coding不是那么麻烦，你可以试一试。 |
|
l*******s
发帖数: 1258 | 39 能否确定这个一定有global optimization，而不是只有local的
另外，iteration次数够不够大？ |
|
p****e
发帖数: 165 | 40 在MySQL中如何做query tuning? 就是优化query plan. Document里说是用EXPLAIN来
optimize query. 但如何看query plan的结果呢？比如我有几百行的sql queries, 运
行需要花10分钟得到结果，那么用EXPLAIN看query plan之后，有看哪些方面去优化呢？
谢谢！ |
|
|
w****e
发帖数: 2210 | 42 看到有人说只有3部分 其中不包括optimized这部分
谢谢 |
|
m******t
发帖数: 273 | 43 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 |
|
H****E
发帖数: 254 | 44 大师们，
请教一个问题关于优化。如果我有多于一个variable来进行优化，什么method比较好呢
？可能有一个primary metric to optimize on, and two more secondary metrics.
目的是primary是最优的，然后secondary也不要下降。
如果现成的工具比如说R里面有包就好了。多谢！ |
|
d*****r
发帖数: 39446 | 45 【此篇文章是由自动发信系统所张贴】
optimal 已经退出本俱乐部, 特此通知. |
|
w*******y
发帖数: 60932 | 46 Link here- Link:
http://freebiest.com/software/giveaway-jv16power-tools-2011-htm
quote
jv16 PowerTools 2011 is the ultimate Windows optimization and tuneup utility
suite. The bottom line is that it keeps your computer running smooth, fast
and greatly improves its overall stability. It is one of the leading
registry cleaners in the world which contain 27 different main tools, and
dozens of smaller tools help you speed up your computer. |
|
l****o
发帖数: 2909 | 47 1. Mishra SK, Wang SY, Lai KK, Explicitly B-preinvex fuzzy mappings,
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS , 83 (1): 39-47 JAN 2006.
2. Lean Yu, Shouyang Wang, K.K. Lai, An Integrated Data Preparation Scheme
for Neural Network Data Analysis, IEEE Transactions on Knowledge and Data
Engineering, 18, pp.1-13, 2006.
3. Kin Keung Lai, Lean Yu, Shouyang Wang, Multi-agent Web Text Mining on the
Grid for Enterprise Decision Support, Lecture Notes in Computer Science,
3842, pp. 540 - 544, 2006.
4... 阅读全帖 |
|
l******h
发帖数: 2 | 48 Highly reputational company with very competitive compensation for all
positions.
Please send in your resume and position/positions you like to apply to my
email address below.
h*******[email protected]
All resumes will be deliver to hiring manager directly. Act fast!
Thanks!
Silicon Engineering Group
Sr. Physical Design Timing Engineer
Timing (STA) Manager
Senior Physical Design Engineer
CAD Manager - Front-End Design and Verification
Sr. CAD Engineer - Place & Route / Physical Design Engineer
Sr. CA... 阅读全帖 |
|
l******h
发帖数: 2 | 49 Highly reputational company with very competitive compensation for all
positions.
Please send in your resume and position/positions you like to apply to my
email address below.
h*******[email protected]
All resumes will be deliver to hiring manager directly. Act fast!
Thanks!
Silicon Engineering Group
Sr. Physical Design Timing Engineer
Timing (STA) Manager
Senior Physical Design Engineer
CAD Manager - Front-End Design and Verification
Sr. CAD Engineer - Place & Route / Physical Design Engineer
Sr. CA... 阅读全帖 |
|
f**d
发帖数: 768 | 50 这是一本计算神经科学的优秀著作，全文拷贝这里（图和公式缺），有兴趣的同学可以
阅读
如需要，我可以分享PDF文件（－－仅供个人学习，无商业用途）
From Computer to Brain
William W. Lytton
From Computer to Brain
Foundations of Computational Neuroscience
Springer
William W. Lytton, M.D.
Associate Professor, State University of New York, Downstato, Brooklyn, NY
Visiting Associate Professor, University of Wisconsin, Madison
Visiting Associate Professor, Polytechnic University, Brooklyn, NY
Staff Neurologist., Kings County Hospital, Brooklyn, NY
In From Computer to Brain: ... 阅读全帖 |
|
