DEA-DA的模型我如图所示

DEA-DA的模型用lingo怎么编程啊？有没有哪位大侠知道啊，我真的是没办法了，书上网上我都没找到相关的例子可以参考。

先声明我不会用LINGO,
也没做过DEA-DA
不过顾名思义
应该是分两阶段
Stage-One: Classification and Overlap Identification (COI).
Stage-Two: Handling Overlap (HO).

个人觉得在matlab运行应该不难
底下提供一些信息供参考
matlab 有个function DEA.m可用
是利用 function linprog() 求解

linprog(): solves linear programming problems

x = linprog(f,A,b,Aeq,beq,lb,ub)


%%%%%%底下是DEA简单例子的重点描述

model='BCC';      % model = 'add' for additive, 'BCC' or 'CCR' ;
orientation='io'; % orientation = 'io' or 'oo' (for input or output oriented)  
% Input matrix (one row per DMU);
X = [2 3 4;
     3 2 6;
     6 6 3;
     9 1 2;
     5 9 5;
     4 3 3;
     5 2 6;
     7 6 1;
     9 2 4;
     6 9 9;
     8 3 2;
    10 3 3]
% Output matrix (one row per DMU);
Y = [3 2;
     6 6;
     9 1;
     5 9;
     4 3;
     2 2;
     5 1;
     7 3;
     8 2;
     3 2;
     1 1;
     7 4]
% BCC model;
    case ('BCC')
    switch orientation;
        % Input oriented;
        case ('io')
            Z = zeros(n,n+m+s+1);
            
            % Objective function of the BCC model: min(0*lambda - epsilon*(s+ + s-) + theta);
            f = [zeros(1,n) -epsilon*ones(1,s+m) 1];
            
            lblambda = zeros(n,1);                % Lower bounds for (n) lambdas;
            lboutput = zeros(s,1);                % Lower bounds for (s) outputs;
            lbinput = zeros(m,1);                 % Lower bounds for (m) inputs ;
            lb = [lblambda; lboutput; lbinput];   % Lower bounds for lambdas, outputs (s+) and inputs (s-);
            for j=1:n
                Aeq = [Y', -eye(s,s), zeros(s,m+1);
                      -X', zeros(m,s), -eye(m,m) X(j,:)';
                      ones(1,n), zeros(1,s), zeros(1,m+1)];
                beq = [Y(j,:)';zeros(m,1);1];
                z = linprog(f,[],[],Aeq,beq,lb);
                Z(j,:) = z;
            end
            Z
%%%%%%
DEAresults.table.txt

DEAresults.table.txt
大小:(3.62 KB)

 马上下载

DEA 数据包络分析。
两年前我就很感兴趣了，用来评价投入/产出效率的。是经济学分析里，最好用的一个手段。
可惜当时编程技巧不够，对模型也不理解，没找到好的程序。
哥们儿思路很清晰哦。做得很漂亮。

9# epoh
谢谢啊！真是太佩服您了，我处理的这个问题正是要分您所说的这两个步骤呢，不过在lingo软件的运用上遇到了问题，又找不到好的解决方法。我再去研究研究matlab，不懂的再上来向您和各位大侠请假啊！先谢谢了！

哈哈!看上去就是解数学式子.
其实只要第一步解出来
往下就简单了

楼主上传的模型是non-linear
还须转换成linear model
请参考Extended DEA-DA Approach of Fuzzy Models.pdf
  

Extended Data Envelopment AnalysisDiscriminant Analysis.pdf
大小:(106.42 KB)

 马上下载

page3/13, (3)(4)(5)

个人觉得判别函数
可能根据
Soulef Smaoui, Habib Chabchoub,1 and Belaid Aouni((2009)
Mathematical Programming Approaches to Classification Problems.pdf
2.1.6. The MIP EDEA-DA Model (MIP EDEA-DA)
page 8-9/34
会更好
  http://downloads.hindawi.com/journals/aor/2009/252989.pdf

我找了一组简单数据,
根据公式 stage 1 (2.15),page 8
运用matlab linprog(),结果如下:



数据:

Table 1. The sets of inputs and outputs
Groups       Zj    x    y
Group 1 (G1) P1    1    2
             P2    2    3
             P3    1    4
             P4    2    5
Group 2 (G2) Q1    5    6
             Q2    6    6
             Q3    6    8
             Q4    7    9
             Q5    8    7

结果如下:

a1+      a1-           a2+           a2-        c
0.00E+00 0.997         0.003         1.01E-16  -8.009
0.00E+00 0.997         3.00E-03      2.56E-22  -7.015
9.03E-06 0.996990973   0.003         1.38E-17  -6.018036108
9.03E-06 0.996990973   3.00E-03     -1.08E-19  -5.024036108
0.49775  0.49925       0.003         0         -5.03
9.97E-01 2.83E-17      3.00E-03      0         -4.036
9.03E-06 0.996990973   3.00E-03      0         -3.039009027
9.03E-06 0.996990973   0.003         7.53E-18  -2.045009027
0.997    0             0.003         0         -2.048

s   zeta1+      zeta1-      zeta2+   zeta2-
-10 7.95E-16    1           1.00E+00 1.01E-16
-10 3.31E-16    1           1.00E+00 2.91E-14
-10 0.003009027 0.996990973 1.00E+00 0
-10 0.003009027 0.996990973 1.00E+00 2.42E-14
-10 5.01E-01    0.49925     1.00E+00 5.02E-15
-10 1.00E+00    5.40E-16    1.00E+00 3.70E-16
-10 0.003009027 0.996990973 1.00E+00 1.17E-14
-10 0.003009027 0.996990973 1.00E+00 2.15E-16
-10 1           6.84E-16    1.00E+00 7.90E-16

这样的结果是否符合预期?

9# epoh

为什么在matlab7上运行提示以下错误？谢谢！

???     case ('BCC')
        |
Error: Illegal use of reserved keyword "case".

DEA.m完整程序如下:
内含数据
预设

model='BCC';     % Choice of model = 'add' for additive, 'BCC' or 'CCR' ;

orientation='io';% orientation = 'io' or 'oo' (for input or output oriented)


上传DEA.rar 必会档名重复,受检拦阻.
我改为123abc.rar

123abc.rar
大小:(1.67 KB)

 马上下载

本附件包括：

• DEA.m

in matlab command window
>> DEA

%%%%%%%%%%
ps:
漏掉了"maximum entropy spectral estimation"
Spectral Analysis

  nonparametric (classic) and parametric (modern)

你说的可能是

  parametric--> AR(p),ARMA based --> maximum entropy
http://home.eng.iastate.edu/~julied/classes/ee524/LectureNotes/l8.pdf

这在R有4种方法来估计参数:

ar.burg Estimate autoregression model by Burg's method
         (maximum entropy method (MEM) or Burg's method)
ar.ols  Estimate autoregression model by ordinary least squares
ar.mle  Estimate autoregression model by maximum likelihood
ar.yw   Estimate autoregression model by solving Yule-Walker equations

%%%%%%%%%%%%%%%%%%%
补充Martingale Difference Sequences
modeling financial time series　with s-plus
page 103/1016
3.2.7 Martingales and Martingale Difference Sequences
Example 8 ARCH process
解释得更清楚

epoh老师，您好！
我看您的程序，估计出的结果应该是BCC,ADD,CCR等几种结果，而且显示结果应该是表格，
为什么在我的matlab7上显示的结果只有一种，而且为如下形式呢？
Optimization terminated.

Z =

  Columns 1 through 8

    1.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000
    0.0000    1.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000
    0.0000    0.0000    1.0000    0.0000    0.0000    0.0000    0.0000    0.0000
    0.0000    0.0000    0.0000    1.0000    0.0000    0.0000    0.0000    0.0000
    0.6923    0.0607    0.0000    0.0850    0.0000    0.0000    0.0000    0.1619
    0.0000    0.0000    0.0000    0.0000    0.0000    1.0000    0.0000    0.0000
    0.0000    0.7647    0.0000    0.2353    0.0000    0.0000    0.0000    0.0000
    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    1.0000
    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000
    0.9048    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0952
    0.0000    0.0000    0.0000    0.5294    0.0000    0.1765    0.0000    0.2941
    0.0000    0.0000    0.0000    0.2500    0.0000    0.0000    0.0000    0.2500

  Columns 9 through 16

    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000
    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000
    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000
    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000
    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    2.9830
    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000
    0.0000    0.0000    0.0000    0.0000    0.7647    5.7059    0.0000    0.0000
    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000
    1.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000
    0.0000    0.0000    0.0000    0.0000    0.3810    0.0952    0.0000    0.4286
    0.0000    0.0000    0.0000    0.0000    4.0588    5.0000    0.0000    0.0000
    0.5000    0.0000    0.0000    0.0000    0.0000    0.0000    0.6667    0.0000

  Columns 17 through 18

    0.0000    1.0000
    0.0000    1.0000
    0.0000    1.0000
    0.0000    1.0000
    0.0000    0.6931
    0.0000    1.0000
    0.2353    0.8824
    0.0000    1.0000
    0.0000    1.0000
    0.0000    0.4127
    0.0000    0.9412
    0.0000    0.9167

maximum entropy spectral estimation"
Spectral Analysis  
这在R有4种方法来估计参数，这些估计方法在R中的那个包中呢？我看18PDF中没有说？
Martingale Difference Sequences
modeling financial time series　with s-plus
page 103/1016
3.2.7 Martingales and Martingale Difference Sequences
Example 8 ARCH process
您提供的这个材料太好了，我看的书太少了，多向老师学习！
非常感谢！

另外，我在学习茆师松教授《高等数理统计》书中，
有一个概念始终无法理解：就是Fisher信息阵，
我想问一下：这个信息阵是怎么来的？尤其是主要思想是什么？
非常感谢！
在学习金融计量和资产定价这么多年的过程中，
我深刻感受到，理论学好非常重要，要是理论不弄懂，
计量出的结果就看不懂，在经济管理中，我最喜欢金融和管理，
非常感谢epoh老师！

现在是设置model='BCC';   
如果你要做其他model
请修改为
model='add';  
or
model='CCR';  

当然连 file name "DEAresults.table"也一齐修改最好
避免覆盖混淆.

%%%%%%%%%%
ar.burg, ar.mle, ar.ols, ar.yw
基本安装就有了,不用另外装package.   

%%%%%%%%%%
信息阵是怎么来的？
都是数学式子
请看Chapter 10 The Method of Maximum Likelihood
10.4 The Covariance Matrix of the ML Estimator

Econometric Theory and Methods

Russell Davidson and James G. MacKinnon ，Oxford University Press

  https://bbs.pinggu.org/b5i45851.html

  

epoh老师，您好！
这两天我要用到Eviews的BV_GARCH.PRG和TV_GARCH.PRG两个程序，
我在EVIEWS6中没有找到，您有吗？
非常感谢！

Eviews6.0\Example Files\Sample Programs\logl

logl.rar

20# epoh
非常感谢！
我想问下：R中有没有对高频数据和超高频数据进行分析的包？
                   另外，对金融数据进行小波分析的包是那一个？

Package ‘wavelets’
  A package of funtions for computing wavelet filters,
  wavelet transforms and multiresolution analyses


High-Frequency Financial Data
我没见过有 R package ,但s-plus有.
Analysis of High-Frequency Financial Data with S-PLUS
  http://faculty.washington.edu/ezivot/ezresearch.htm
  paper.pdf
  HFAnalysis.ssc
  HFLibrary.SSC.
  Data

%%%%%%%%%%%%%
刚下载高等数理统计
原来你说的Fisher information matrix是用在点估计
请看MS_NotesWeek9,MS_Tutorial8
  

Barbara Bogacka.rar
大小:(235.85 KB)

 马上下载

2.2 Point Estimation
2.2.2 Comparing estimators
Estimators can be compared through their mean square errors. If they are unbiased,
this is equivalent to comparing their variances. In many applications, we
try to find an unbiased estimator which has minimum variance, or at least low
variance. We can compare the variances of several unbiased estimators, but how
do we know if we have found an estimator with the lowest variance among all
unbiased estimators?

The answer is given by Cram´er-Rao lower bound (CRLB).
and denominator is Fisher information matrix

22# epoh
尊敬的epoh老师，您好！
    我在splus8中先装入finmetrics后，然后再运行HFlibrary.SSC和HFanalysis.ssc，均无法运行。我想问您一下：附件中的这些splus文件如何在splus中运行？

> # Created on 02/20/2003
# By Bingcheng Yan
# Last updated on 11/06/2003
## Moved utility functions to the HF Library
## The library has to be attached to run this script file
## Functions used in the script file:
## TAQLoad()
## OlsenLoad()
## reorderTS()
## plotByDays()
## ExchangeHoursOnly()
## FxBizWeekOnly()
## align.withinDay()
## align.withinWeek()
## diff.withinDay()
## diff.withinWeek()
## is.tsBW()
## tsBW()
## DurationInInterv()
## PriceChgInInterv()
## getSpread()
## SmoothAcrossIntervs()
## tableSmoother()
## rbindtimeSeries()
## aggregateSeriesHF()
## tradeDirec()
## Genr.RealVol()
## Attach the FxLibrary
attach("D:\\Consulting\\FxLibrary", pos = 2, name = "FxLibrary")
> ## Load the FinMetrics module
module("finmetrics", first = F)
> #################### Section 2 Data Proceesing ####################################
### loading MSFT Trade data ####
msftt.ts = TAQLoad(file = "D:\\CompFinProg\\HFAnalysis\\trade_msft.txt", type = "trade")
> msftt.ts[1:5,  ]
        Positions Cond Ex Symbol Corr G127    Price Size Seq
5/1/1997 8:01:02 T    T  MSFT   0    0    121.1250 1500 0  
5/1/1997 8:02:24 T    T  MSFT   0    0    121.5625  500 0  
5/1/1997 8:03:20 T    T  MSFT   0    0    121.5625 1000 0  
5/1/1997 8:03:22 T    T  MSFT   0    0    121.5625 1200 0  
        Positions Cond Ex Symbol Corr G127    Price Size Seq
5/1/1997 8:38:15 T    T  MSFT   0    0    121.6250 1000 0  
> slotNames(msftt.ts)
[1] "data"              "positions"         "start.position"    "end.position"      "future.positions"
[6] "units"             "title"             "documentation"     "attributes"        "fiscal.year.start"
[11] "type"            
> msftt.ts@data[1:5,  ]
  Cond Ex Symbol Corr G127    Price Size Seq
1    T  T   MSFT    0    0 121.1250 1500   0
2    T  T   MSFT    0    0 121.5625  500   0
3    T  T   MSFT    0    0 121.5625 1000   0
4    T  T   MSFT    0    0 121.5625 1200   0
  Cond Ex Symbol Corr G127    Price Size Seq
5    T  T   MSFT    0    0 121.6250 1000   0
> msftt.ts@positions[1:5]
[1] 5/1/1997 8:01:02 5/1/1997 8:02:24 5/1/1997 8:03:20 5/1/1997 8:03:22 5/1/1997 8:38:15
> ### loading MSFT Quote data ###
msftq.ts = TAQLoad("D:\\CompFinProg\\HFAnalysis\\quote_msft.txt", type = "quote")
> msftq.ts[1:5,  ]
        Positions Ex MMID Symbol     Bid BidSize Mode     Ask AskSize Seq
5/1/1997 8:17:24 T       MSFT   121.500 11      12   121.625 11      0  
5/1/1997 9:00:44 T       MSFT   121.750 10      12   121.625 11      0  
5/1/1997 9:07:27 T       MSFT   121.750 10      12   121.625 10      0  
5/1/1997 9:16:30 T       MSFT   121.875 10      12   121.625 10      0  
        Positions Ex MMID Symbol     Bid BidSize Mode     Ask AskSize Seq
5/1/1997 9:20:29 T       MSFT   121.875 10      12   121.625  3      0  
> ### loading GE Trade data ####
get.ts = TAQLoad("D:\\CompFinProg\\HFAnalysis\\trade_ge.txt", type = "trade")
> get.ts[1:5,  ]
        Positions Cond Ex Symbol Corr G127   Price  Size     Seq
5/1/1997 9:30:17      N  GE     0    0    110.625 78700 3689550
5/1/1997 9:30:20      M  GE     0    0    110.625   100       0
5/1/1997 9:30:20      M  GE     0    0    110.625   100       0
5/1/1997 9:30:20      M  GE     0    0    110.625   300       0
        Positions Cond Ex Symbol Corr G127   Price  Size     Seq
5/1/1997 9:30:20      M  GE     0    0    110.625   100       0
> ### loading GE Quote data ###
geq.ts = TAQLoad("D:\\CompFinProg\\HFAnalysis\\quote_ge.txt", type = "quote")
> geq.ts[1:5,  ]
        Positions Ex MMID Symbol     Bid BidSize Mode    Ask AskSize     Seq
5/1/1997 9:00:44 T  TRIM GE       0.000 0       12     0.00  0            0
5/1/1997 9:00:44 T  MADF GE       0.000 0       12     0.00  0            0
5/1/1997 9:30:20 C       GE     106.125 5       12     0.00  0            0
5/1/1997 9:30:27 N       GE     110.625 5       10   110.75 10      3689560
        Positions Ex MMID Symbol     Bid BidSize Mode    Ask AskSize     Seq
5/1/1997 9:30:30 M       GE     109.125 5       12   111.00  1            0
> ### loading USD/EUR data ###
eurusd.ts = OlsenLoad("D:\\CompFinProg\\HFAnalysis\\eur_usd.txt")
> eurusd.ts[1:5,  ]
         Positions    Bid    Ask Institution
3/11/2001 1:07:46 0.9337 0.9342 AREX      
3/11/2001 1:07:52 0.9336 0.9341 AREX      
3/11/2001 1:07:57 0.9334 0.9339 AREX      
3/11/2001 1:08:04 0.9337 0.9342 AREX      
         Positions    Bid    Ask Institution
3/11/2001 5:42:35 0.9330 0.9340 CMBK      
> eurusd.ts[1:5, "Bid"]
         Positions    Bid
3/11/2001 1:07:46 0.9337
3/11/2001 1:07:52 0.9336
3/11/2001 1:07:57 0.9334
3/11/2001 1:08:04 0.9337
         Positions    Bid
3/11/2001 5:42:35 0.9330
> #### Data examination and cleaning ###
# Re-order data series
msftt.ts = reorderTS(msftt.ts)
Problem in sub(x.data, pos.order,  ): argument "x" is missing with no default
Use traceback() to see the call stack

S-PLUS : Copyright (c) 1988, 2007 Insightful Cor
p.
S : Copyright Insightful Corp.
Enterprise Developer Version 8.0.4  for Microsof
t Windows : 2007
Working data will be in F:\0计量经济学前沿\Analy
sis of High-Frequency Financial Data with S-PLUS

> # Created on 02/20/2003
> # By Bingcheng Yan
> # Last updated on 11/06/2003
>
>
> ## Moved utility functions to the HF Library
> ## The library has to be attached to run this script file
> ## Functions used in the script file:
> ##        TAQLoad()
> ## OlsenLoad()
> ## reorderTS()
> ## plotByDays()
> ## ExchangeHoursOnly()
> ## FxBizWeekOnly()
> ## align.withinDay()
> ## align.withinWeek()
> ## diff.withinDay()
> ## diff.withinWeek()
> ## is.tsBW()
> ## tsBW()
> ## DurationInInterv()
> ## PriceChgInInterv()
> ## getSpread()
> ## SmoothAcrossIntervs()
> ## tableSmoother()
> ## rbindtimeSeries()
> ## aggregateSeriesHF()
> ## tradeDirec()
> ## Genr.RealVol()
>
>
> ## Attach the FxLibrary
> attach("D:\\Consulting\\FxLibrary", pos = 2, name = "FxLibrary")
>
> ## Load the FinMetrics module
> module("finmetrics", first=F)
>
>
> #################### Section 2 Data Proceesing ####################################
> ### loading MSFT Trade data ####
> msftt.ts = TAQLoad(file = "D:\\CompFinProg\\HFAnalysis\\trade_msft.txt",
+                                                 type = "trade")
> msftt.ts[1:5,]
        Positions Cond Ex Symbol Corr G127    Price Size Seq
5/1/1997 8:01:02 T    T  MSFT   0    0    121.1250 1500 0  
5/1/1997 8:02:24 T    T  MSFT   0    0    121.5625  500 0  
5/1/1997 8:03:20 T    T  MSFT   0    0    121.5625 1000 0  
5/1/1997 8:03:22 T    T  MSFT   0    0    121.5625 1200 0  
5/1/1997 8:38:15 T    T  MSFT   0    0    121.6250 1000 0  
> slotNames(msftt.ts)
[1] "data"              "positions"         "start.position"    "end.position"      "future.positions"
[6] "units"             "title"             "documentation"     "attributes"        "fiscal.year.start"
[11] "type"            
> msftt.ts@data[1:5, ]
  Cond Ex Symbol Corr G127    Price Size Seq
1    T  T   MSFT    0    0 121.1250 1500   0
2    T  T   MSFT    0    0 121.5625  500   0
3    T  T   MSFT    0    0 121.5625 1000   0
4    T  T   MSFT    0    0 121.5625 1200   0
5    T  T   MSFT    0    0 121.6250 1000   0
> msftt.ts@positions[1:5]
[1] 5/1/1997 8:01:02 5/1/1997 8:02:24 5/1/1997 8:03:20 5/1/1997 8:03:22 5/1/1997 8:38:15
>
> ### loading MSFT Quote data ###
> msftq.ts = TAQLoad("D:\\CompFinProg\\HFAnalysis\\quote_msft.txt",
+                                                 type = "quote")
> msftq.ts[1:5,]
        Positions Ex MMID Symbol     Bid BidSize Mode     Ask AskSize Seq
5/1/1997 8:17:24 T       MSFT   121.500 11      12   121.625 11      0  
5/1/1997 9:00:44 T       MSFT   121.750 10      12   121.625 11      0  
5/1/1997 9:07:27 T       MSFT   121.750 10      12   121.625 10      0  
5/1/1997 9:16:30 T       MSFT   121.875 10      12   121.625 10      0  
5/1/1997 9:20:29 T       MSFT   121.875 10      12   121.625  3      0  
>
> ### loading GE Trade data ####
> get.ts = TAQLoad("D:\\CompFinProg\\HFAnalysis\\trade_ge.txt",

+                                                 type = "trade")
> get.ts[1:5,]
        Positions Cond Ex Symbol Corr G127   Price  Size     Seq
5/1/1997 9:30:17      N  GE     0    0    110.625 78700 3689550
5/1/1997 9:30:20      M  GE     0    0    110.625   100       0
5/1/1997 9:30:20      M  GE     0    0    110.625   100       0
5/1/1997 9:30:20      M  GE     0    0    110.625   300       0
5/1/1997 9:30:20      M  GE     0    0    110.625   100       0
>                                                
> ### loading GE Quote data ###
> geq.ts = TAQLoad("D:\\CompFinProg\\HFAnalysis\\quote_ge.txt",
+                                                 type = "quote")
> geq.ts[1:5,]
        Positions Ex MMID Symbol     Bid BidSize Mode    Ask AskSize     Seq
5/1/1997 9:00:44 T  TRIM GE       0.000 0       12     0.00  0            0
5/1/1997 9:00:44 T  MADF GE       0.000 0       12     0.00  0            0
5/1/1997 9:30:20 C       GE     106.125 5       12     0.00  0            0
5/1/1997 9:30:27 N       GE     110.625 5       10   110.75 10      3689560
5/1/1997 9:30:30 M       GE     109.125 5       12   111.00  1            0
>
>
> ### loading USD/EUR data ###
> eurusd.ts = OlsenLoad("D:\\CompFinProg\\HFAnalysis\\eur_usd.txt")
> eurusd.ts[1:5,]
         Positions    Bid    Ask Institution
3/11/2001 1:07:46 0.9337 0.9342 AREX      
3/11/2001 1:07:52 0.9336 0.9341 AREX      
3/11/2001 1:07:57 0.9334 0.9339 AREX      
3/11/2001 1:08:04 0.9337 0.9342 AREX      
3/11/2001 5:42:35 0.9330 0.9340 CMBK      
> eurusd.ts[1:5, "Bid"]
         Positions    Bid
3/11/2001 1:07:46 0.9337
3/11/2001 1:07:52 0.9336
3/11/2001 1:07:57 0.9334
3/11/2001 1:08:04 0.9337
3/11/2001 5:42:35 0.9330
>
>
>
> #### Data examination and cleaning ###
> # Re-order data series
> msftt.ts = reorderTS(msftt.ts)
Problem in sub(x.data, pos.order,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> msftq.ts = reorderTS(msftq.ts)
Problem in sub(x.data, pos.order,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> get.ts = reorderTS(get.ts)
Problem in sub(x.data, pos.order,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> geq.ts = reorderTS(geq.ts)
Problem in sub(x.data, pos.order,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> eurusd.ts = reorderTS(eurusd.ts)
Problem in sub(x.data, pos.order,  ): argument "x" is missing with no default
Use traceback() to see the call stack
>
> ## Plot data by days
> par(mfrow = c(3,3))
> plotByDays(ts = msftt.ts, coltoplot = "Price", days.max = 7)
Problem in substituteString(pattern ..: pattern
should be a single character string, length is 8

Use traceback() to see the call stack
Problem in substituteString(pattern ..: pattern should be a single character string, length is 8
Use traceback() to see the call stack
>
> par(mfrow = c(3,3))
> plotByDays(ts = eurusd.ts, coltoplot = 1, days.max = 7)
Problem in substituteString(pattern = pattern, replacement = replac..: pattern should be a single character str
ing, length is 3
Use traceback() to see the call stack
>
> ## Time interval restrictions
>
> msftt.ts = ExchangeHoursOnly(ts = msftt.ts,
+                   exch.hours = c("9:30", "16:00"), start.include = T, close.include = T)
Problem in sub(ts@data, idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> msftq.ts = ExchangeHoursOnly(ts = msftq.ts,
+                   exch.hours = c("9:30", "16:00"), start.include = T, close.include = T)
Problem in sub(ts@data, idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> get.ts = ExchangeHoursOnly(ts = get.ts,
+                   exch.hours = c("9:30", "16:00"), start.include = T, close.include = T)
Problem in sub(ts@data, idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> geq.ts = ExchangeHoursOnly(ts = geq.ts,
+                   exch.hours = c("9:30", "16:00"), start.include = T, close.include = T)
Problem in sub(ts@data, idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
>

par(mfrow = c(3,3))
> plotByDays(ts = msftt.ts, coltoplot = "Price", days.max = 7)
Problem in substituteString(pattern = pattern, replacement = replac..: pattern should be a single character str
ing, length is 8
Use traceback() to see the call stack
>
>
>
> eurusd.ts = FxBizWeekOnly(eurusd.ts, bizweek.hours = c("22:00", "22:00"),
+                                                                  start.include = T, close.include = T)
Problem in sub(ts@data, idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> par(mfrow = c(2,3))
> plotByDays(ts = eurusd.ts, coltoplot = 1)
Problem in substituteString(pattern = pattern, replacement = replac..: pattern should be a single character str
ing, length is 3
Use traceback() to see the call stack
>
>
> ####################### Section 3 Data Manipulation and Characterization ###################
>
> ##### 3.1 Construction of Market Variables ########
> ## 3.1.1 Computing price changes of MSFT prices and USD/EUR bid quotes
> args(PriceChgInInterv)
function(x, ticksize = NULL, interv.type = "daily", bound.hours = c("9:30", "16:00"))
NULL
> pcTicks.msft = PriceChgInInterv(msftt.ts[, "Price"], ticksize = 1/8,
+                                                  interv.type = "daily", bound.hours = c("9:30", "16:00"))
Problem in sub(ts@data, idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
>
> pcTicks.eurusd = PriceChgInInterv(eurusd.ts[, "Bid"], ticksize = 0.0001,
+                                                  interv.type = "weekly", bound.hours = c("22:00", "22:00"))
Problem in sub(ts@data, idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
>
>
>
> ## 3.1.2 Computing durations of MSFT trades and USD/EUR quotes
> args(DurationInInterv)
function(x, units = "seconds", interv.type = "daily", bound.hours = c("9:30", "16:00"))
NULL
> duration.msftt = DurationInInterv(x = msftt.ts, units = "seconds", interv.type = "daily",
+                                                                                 bound.hours = c("9:30", "16:00"))
Problem in sub(ts@data, idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> duration.msftt[1:5,]
Problem: Object "duration.msftt" not found
Use traceback() to see the call stack
>
> duration.eurusd = DurationInInterv(x = eurusd.ts, units = "seconds", interv.type = "weekly",
+                                                                                 bound.hours = c("22:00", "22:00"))
Problem in sub(ts@data, idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> duration.eurusd[1:5,]
Problem: Object "duration.eurusd" not found
Use traceback() to see the call stack
>
> ## 3.1.3 Computing spreads of MSFT quotes and USD/EUR quotes
> args(getSpread)
function(ask, bid, ticksize = NULL)
NULL
> spread.msft = getSpread(ask = msftq.ts[, "Ask"], bid = msftq.ts[, "Bid"], ticksize = 1/8)
> # removing some bad rows with 0 bid or ask or 0 spread
> error.idx = seriesData(msftq.ts)[, "Ask"]==0 |
+                          seriesData(msftq.ts)[, "Bid"]==0 | seriesData(spread.msft)<1
> spread.msft = spread.msft[!error.idx,]

spread.msft[1:5,]
        Positions Spread
5/1/1997 8:17:24 1     
5/1/1997 9:29:41 1     
5/1/1997 9:30:14 1     
5/1/1997 9:30:17 2     
5/1/1997 9:30:17 1     
>
> spread.eurusd = getSpread(ask = eurusd.ts[, "Ask"], bid = eurusd.ts[, "Bid"], ticksize = 0.0001)
> spread.eurusd[1:5,]
         Positions Spread
3/11/2001 1:07:46  5   
3/11/2001 1:07:52  5   
3/11/2001 1:07:57  5   
3/11/2001 1:08:04  5   
3/11/2001 5:42:35 10   
>
> ## 3.1.4 Computing trade direction of MSFT trades
> args(tradeDirec)
function(trade, mq, timeLag = "5s")
NULL
> mq.msft = getMidQuote(ask = msftq.ts[,"Ask"],
+              bid = msftq.ts[, "Bid"])
> trade.direc.msft = tradeDirec(trade = msftt.ts[, "Price"],
+                mq = mq.msft)
Problem in sub(trade@data, idx.trade,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> trade.direc.msft[1:5,]
Problem: Object "trade.direc.msft" not found
Use traceback() to see the call stack
>
> ## 3.1.5 Computing daily realized volatility for MSFT prices
> ## and USD/EUR mid quotes
> args(Genr.RealVol)
function(ts, interv.type = "daily", bound.hours = c("9:30", "16:00"), rv.span, rt.span, how.align = "before")
NULL
> rvDaily.msft = Genr.RealVol(ts = log(msftt.ts[, "Price"])*100, interv.type = "daily", bound.hours = c("9:30", "16:00"),
+                                                                 rv.span = timeSpan("6h30m"), rt.span = timeSpan("5m"))
Problem in sub(ts@data, !na.idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> rvDaily.msft[1:5,]
Problem: Object "rvDaily.msft" not found
Use traceback() to see the call stack
>
> ## get the mid quote of USD/EUR bid - ask quotes
> mq.eurusd = getMidQuote(ask = eurusd.ts[, "Ask"], bid = eurusd.ts[, "Bid"])
>
> rvDaily.eurusd = Genr.RealVol(ts = log(mq.eurusd)*100, interv.type = "weekly", bound.hours = c("22:00", "22:00"),
+                                                                 rv.span = timeSpan("24h"), rt.span = timeSpan("5m"))
Problem in sub(ts@data, !na.idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> rvDaily.eurusd[1:5,]
Problem: Object "rvDaily.eurusd" not found
Use traceback() to see the call stack
>
> ###### 3.2 Statistical Properties of Market Variables ######
> ## Summary stats of price changes
> summaryStats(pcTicks.msft)
Problem: Object "pcTicks.msft" not found
Use traceback() to see the call stack
> summaryStats(pcTicks.eurusd)
Problem: Object "pcTicks.eurusd" not found
Use traceback() to see the call stack
>
> ## Histograms of price changes
> pcFactor.msft = cut(seriesData(pcTicks.msft), breaks=c(min(pcTicks.msft), -3:2, max(pcTicks.msft)), include.lowest =T,
+                         labels = c("<= -3", paste(-2:2), ">= 3"), factor.result=T)
Problem: Object "pcTicks.msft" not found
Use traceback() to see the call stack
> pcFactor.eurusd = cut(seriesData(pcTicks.eurusd), breaks=c(min(pcTicks.eurusd), -6:5, max(pcTicks.eurusd)), include.lowest =T,
+                         labels = c("<= -6", paste(-5:5), ">= 6"), factor.result=T)
Problem: Object "pcTicks.eurusd" not found
Use traceback() to see the call stack
>
> par(mfrow = c(1,2))
> hist.factor(pcFactor.msft, prob = T, xlab = "Price Changes.MSFT",
+                                 main = "Histogram of MSFT\nTrading Price Changes in Ticks")
Problem: Object "pcFactor.msft" not found
Use traceback() to see the call stack
>
> hist.factor(pcFactor.eurusd, prob = T, xlab = "Price Changes.USD/EUR",
+                                 main = "Histogram of USD/EUR\nBid Quote Changes in Ticks")
Problem: Object "pcFactor.eurusd" not found
Use traceback() to see the call stack
>
>
> ## Summary stats of spreads
> summaryStats(spread.msft)

Sample Quantiles:
min 1Q median 3Q max
   1  1      1  1   3

Sample Moments:
  mean    std skewness kurtosis
1.198 0.4022    1.591    3.766

Number of Observations:  20234
> summaryStats(spread.eurusd)

Sample Quantiles:
min 1Q median 3Q max
   1  3      4  5  10

Sample Moments:
  mean   std skewness kurtosis
3.999 1.614   0.2786    3.057

Number of Observations:  127351
>
> ## Histograms of spreads
> par(mfrow = c(1,2))
> hist.factor(seriesData(spread.msft), prob = T, xlab = "Spread.MSFT",
+                                 main = "Histogram of MSFT\nSpread in Ticks")
>
> hist.factor(seriesData(spread.eurusd), prob = T, xlab = "Spread.USD/EUR",
+                                 main = "Histogram of USD/EUR\nSpread in Ticks")
>
> ## Summary Stats of durations
> summaryStats(duration.msftt)
Problem: Object "duration.msftt" not found
Use traceback() to see the call stack
Problem: Object "duration.msftt" not found
Use traceback() to see the call stack
> summaryStats(duration.eurusd)
Problem: Object "duration.eurusd" not found
Use traceback() to see the call stack
>
> ## Histograms of durations
> durFactor.msftt = cut(seriesData(duration.msftt), left.include=T,
+                                                 breaks=c(0:10, max(duration.msftt)), include.lowest =T,
+                                                 labels = c(paste(0:9), ">= 10"), factor.result=T)
Problem: Object "duration.msftt" not found
Use traceback() to see the call stack
> durFactor.eurusd = cut(seriesData(duration.eurusd), left.include=T,
+                                                 breaks=c(0:10, max(duration.eurusd)), include.lowest =T,
+                                                 labels = c(paste(0:9), ">= 10"), factor.result=T)
Problem: Object "duration.eurusd" not found
Use traceback() to see the call stack

> par(mfrow = c(1,2))
> hist.factor(durFactor.msftt, prob = T, xlab = "Duration.MSFT",
+                                 main = "Histogram of MSFT\nTransaction Durations in Seconds")
Problem: Object "durFactor.msftt" not found
Use traceback() to see the call stack
>
> hist.factor(durFactor.eurusd, prob = T, xlab = "Duration.USD/EUR",
+                                 main = "Histogram of USD/EUR\nQuote Durations in Seconds")
Problem: Object "durFactor.eurusd" not found
Use traceback() to see the call stack
>
> ### Temporal dependence in price changes and bid-ask bounce
> ## Two-way classification table of lead-lag price changes
> pcLag.msft = pcTicks.msft[1:(nrow(pcTicks.msft)-1),]
Problem: Object "pcTicks.msft" not found
Use traceback() to see the call stack
> pcLead.msft = pcTicks.msft[2:nrow(pcTicks.msft),]
Problem: Object "pcTicks.msft" not found
Use traceback() to see the call stack
>
> pcLagFactor.msft = cut(seriesData(pcLag.msft), breaks=c(min(pcLag.msft), -1:0, max(pcLag.msft)), include.lowest =T,
+                         labels = paste("Lag.PC", c("-", "0", "+")), factor.result=T)
Problem: Object "pcLag.msft" not found
Use traceback() to see the call stack
> pcLeadFactor.msft = cut(seriesData(pcLead.msft), breaks=c(min(pcLead.msft), -1:0, max(pcLead.msft)), include.lowest =T,
+                         labels = paste("Lead.PC", c("-", "0", "+")), factor.result=T)
Problem: Object "pcLead.msft" not found
Use traceback() to see the call stack
>
> table(pcLagFactor.msft, pcLeadFactor.msft)
Problem: Object "pcLagFactor.msft" not found
Use traceback() to see the call stack
>
>
> #### 3.3 Calendar Patterns in Market Activities #######
>
> ### 3.3.1 Calendar patterns in volatility ###
>
> ## MSFT ##
> ## 5-min realized volatility ##
> rv5min.msft = Genr.RealVol(ts = log(msftt.ts[, "Price"])*100,
+                 interv.type = "daily", bound.hours = c("9:30", "16:00"),
+                 rv.span = timeSpan("5m"), rt.span = timeSpan("1m"))
Problem in sub(ts@data, !na.idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> rv5min.msft[1:5,]
Problem: Object "rv5min.msft" not found
Use traceback() to see the call stack
>
> # Average 5-min realized volatility across days
> args(SmoothAcrossIntervs)
function(ts, n.subinterv, n.interv, FUN)
NULL
> rv5min.ave.msft = SmoothAcrossIntervs(ts = rv5min.msft, n.subinterv = 78,
+                                    n.interv = 11, FUN = mean)
Problem: Object "rv5min.msft" not found
Use traceback() to see the call stack
> rv5min.ave.msft@title = "5-min Realized Volatility: MSFT\n(averaging across 11 trading days)"
Problem: Object "rv5min.ave.msft" not found
Use traceback() to see the call stack
>
> par(mfrow = c(1,2))
> # ACF of the 5-min realized volatility for MSFT
> acf.plot(acf(rv5min.msft, lag.max = 234, plot = F),
+      main = "ACF of 5-min Realized Volatility:\nMSFT (lags up to 3 days)")
Problem: Object "rv5min.msft" not found
Use traceback() to see the call stack
> # Plots of Calendar pattern in realized volatility for MSFT
> plot(rv5min.ave.msft, reference.grid = F,
+      x.axis.args = list(format.label = c("%H:%02M", "%Z"),
+                        time.of.day.style = "24:00"))
Problem: Object "rv5min.ave.msft" not found
Use traceback() to see the call stack
>
> ## USD/EUR ##
> ## 5-min realized volatility ##
> rv5min.eurusd = Genr.RealVol(ts = log(mq.eurusd)*100, interv.type = "weekly", bound.hours = c("22:00", "22:00"),
+                                                                 rv.span = timeSpan("5m"), rt.span = timeSpan("1m"))
Problem in sub(ts@data, !na.idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> rv5min.eurusd[1:5, ]
Problem: Object "rv5min.eurusd" not found
Use traceback() to see the call stack
>
> # Average 5-min realized volatility across days
> rv5min.ave.eurusd = SmoothAcrossIntervs(ts = rv5min.eurusd, n.subinterv = 288,
+                          n.interv = 5, FUN = mean)
Problem: Object "rv5min.eurusd" not found
Use traceback() to see the call stack
> rv5min.ave.eurusd@title = "5-min Realized Volatility: USD/EUR\n(averaging across 5 trading days)"
Problem: Object "rv5min.ave.eurusd" not found
Use traceback() to see the call stack
>
> par(mfrow = c(1,2))
> # ACF of the 5-min realized volatility for USD/EUR
> acf.plot(acf(rv5min.eurusd, lag.max = 864, plot = F),
+      main = "ACF of 5-min Realized Volatility:\nUSD/EUR (lags up to 3 days)")
Problem: Object "rv5min.eurusd" not found
Use traceback() to see the call stack
> # Plots of Calendar pattern in realized volatility for USD/EUR
> plot(rv5min.ave.eurusd, reference.grid = F,
+      x.axis.args = list(format.label = c("%H:%02M", "%Z"),
+                        time.of.day.style = "24:00"))
Problem: Object "rv5min.ave.eurusd" not found
Use traceback() to see the call stack
>
> ### 3.3.2 Calendar patterns in duration ###
> ## MSFT
> ## mean durations in 5-min intervals
> args(aggregateSeriesHF)
function(ts, interv.type = "daily", bound.hours = c("9:30", "16:00"), by, k.by, FUN, adj, drop.empty = F,
        ...)
NULL
> meanDur5min.msft = aggregateSeriesHF(duration.msftt, interv.type = "daily",
+                       bound.hours = c("9:30", "16:00"), FUN = mean,
+                      by = "minutes", k.by = 5, adj = 1, drop.empty = F, together = T)
Problem: Object "duration.msftt" not found
Use traceback() to see the call stack
> meanDur5min.msft[1:5,]
Problem: Object "meanDur5min.msft" not found
Use traceback() to see the call stack
>
> # averaging 5-min mean durations across trading days
> meanDur5min.ave.msft = SmoothAcrossIntervs(ts = meanDur5min.msft, n.subinterv = 78,
+                                    n.interv = 11, FUN = mean)
Problem: Object "meanDur5min.msft" not found
Use traceback() to see the call stack
> meanDur5min.ave.msft@title = "5-min Mean Durations: MSFT\n(averaging across 11 trading days)"
Problem: Object "meanDur5min.ave.msft" not found
Use traceback() to see the call stack
>
> # plots of ACF and calendar pattern in durations
> par(mfrow = c(1,2))
> acf.plot(acf(meanDur5min.msft, lag.max = 234, plot = F),
+      main = "ACF of 5-min Mean Durations:\nMSFT (lags up to 3 days)")
Problem: Object "meanDur5min.msft" not found
Use traceback() to see the call stack
> plot(meanDur5min.ave.msft, reference.grid = F,
+      x.axis.args = list(format.label = c("%H:%02M", "%Z"),
+                        time.of.day.style = "24:00"))
Problem: Object "meanDur5min.ave.msft" not found
Use traceback() to see the call stack
>
> ## USD/EUR
> ## mean durations in 5-min intervals
> meanDur5min.eurusd = aggregateSeriesHF(duration.eurusd, interv.type = "weekly",
+                       bound.hours = c("22:00", "22:00"), FUN = mean,
+                      by = "minutes", k.by = 5, adj = 1, drop.empty = F, together = T)
Problem: Object "duration.eurusd" not found
Use traceback() to see the call stack
> meanDur5min.eurusd[1:5,]
Problem: Object "meanDur5min.eurusd" not found
Use traceback() to see the call stack
>
> # averaging 5-min mean durations across trading days
> meanDur5min.ave.eurusd = SmoothAcrossIntervs(ts = meanDur5min.eurusd, n.subinterv = 288,
+                                    n.interv = 5, FUN = mean)
Problem: Object "meanDur5min.eurusd" not found
Use traceback() to see the call stack
> meanDur5min.ave.eurusd@title = "5-min Mean Durations: USD/EUR\n(averaging across 11 trading days)"
Problem: Object "meanDur5min.ave.eurusd" not found
Use traceback() to see the call stack
>
> # plots of ACF and calendar pattern in durations
>         #removing the NAs in meanDur5min before plotting ACF
>         na.idx = is.na(seriesData(meanDur5min.eurusd))
Problem: Object "meanDur5min.eurusd" not found
Use traceback() to see the call stack
> par(mfrow = c(1,2))


>

hist.factor(seriesData(spread.msft), prob = T, xlab = "Spread.MSFT",
+                                 main = "Histogram of MSFT\nSpread in Ticks")
>
> hist.factor(seriesData(spread.eurusd), prob = T, xlab = "Spread.USD/EUR",
+                                 main = "Histogram of USD/EUR\nSpread in Ticks")
>
> ## Summary Stats of durations
> summaryStats(duration.msftt)
Problem: Object "duration.msftt" not found
Use traceback() to see the call stack
Problem: Object "duration.msftt" not found
Use traceback() to see the call stack
> summaryStats(duration.eurusd)
Problem: Object "duration.eurusd" not found
Use traceback() to see the call stack
>
> ## Histograms of durations
> durFactor.msftt = cut(seriesData(duration.msftt), left.include=T,
+                                                 breaks=c(0:10, max(duration.msftt)), include.lowest =T,
+                                                 labels = c(paste(0:9), ">= 10"), factor.result=T)
Problem: Object "duration.msftt" not found
Use traceback() to see the call stack
> durFactor.eurusd = cut(seriesData(duration.eurusd), left.include=T,
+                                                 breaks=c(0:10, max(duration.eurusd)), include.lowest =T,
+                                                 labels = c(paste(0:9), ">= 10"), factor.result=T)
Problem: Object "duration.eurusd" not found
Use traceback() to see the call stack
>
> par(mfrow = c(1,2))
> hist.factor(durFactor.msftt, prob = T, xlab = "Duration.MSFT",
+                                 main = "Histogram of MSFT\nTransaction Durations in Seconds")
Problem: Object "durFactor.msftt" not found
Use traceback() to see the call stack
>
> hist.factor(durFactor.eurusd, prob = T, xlab = "Duration.USD/EUR",
+                                 main = "Histogram of USD/EUR\nQuote Durations in Seconds")
Problem: Object "durFactor.eurusd" not found
Use traceback() to see the call stack
>
> ### Temporal dependence in price changes and bid-ask bounce
> ## Two-way classification table of lead-lag price changes
> pcLag.msft = pcTicks.msft[1:(nrow(pcTicks.msft)-1),]
Problem: Object "pcTicks.msft" not found
Use traceback() to see the call stack
> pcLead.msft = pcTicks.msft[2:nrow(pcTicks.msft),]
Problem: Object "pcTicks.msft" not found
Use traceback() to see the call stack
>
> pcLagFactor.msft = cut(seriesData(pcLag.msft), breaks=c(min(pcLag.msft), -1:0, max(pcLag.msft)), include.lowest =T,
+                         labels = paste("Lag.PC", c("-", "0", "+")), factor.result=T)
Problem: Object "pcLag.msft" not found
Use traceback() to see the call stack
> pcLeadFactor.msft = cut(seriesData(pcLead.msft), breaks=c(min(pcLead.msft), -1:0, max(pcLead.msft)), include.lowest =T,
+                         labels = paste("Lead.PC", c("-", "0", "+")), factor.result=T)
Problem: Object "pcLead.msft" not found
Use traceback() to see the call stack
>
> table(pcLagFactor.msft, pcLeadFactor.msft)
Problem: Object "pcLagFactor.msft" not found
Use traceback() to see the call stack
>
>
> #### 3.3 Calendar Patterns in Market Activities #######
>
> ### 3.3.1 Calendar patterns in volatility ###
>
> ## MSFT ##
> ## 5-min realized volatility ##
> rv5min.msft = Genr.RealVol(ts = log(msftt.ts[, "Price"])*100,
+                 interv.type = "daily", bound.hours = c("9:30", "16:00"),
+                 rv.span = timeSpan("5m"), rt.span = timeSpan("1m"))
Problem in sub(ts@data, !na.idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> rv5min.msft[1:5,]
Problem: Object "rv5min.msft" not found
Use traceback() to see the call stack
>
> # Average 5-min realized volatility across days
> args(SmoothAcrossIntervs)
function(ts, n.subinterv, n.interv, FUN)
NULL
> rv5min.ave.msft = SmoothAcrossIntervs(ts = rv5min.msft, n.subinterv = 78,
+                                    n.interv = 11, FUN = mean)
Problem: Object "rv5min.msft" not found
Use traceback() to see the call stack
> rv5min.ave.msft@title = "5-min Realized Volatility: MSFT\n(averaging across 11 trading days)"
Problem: Object "rv5min.ave.msft" not found
Use traceback() to see the call stack
>
> par(mfrow = c(1,2))
> # ACF of the 5-min realized volatility for MSFT
> acf.plot(acf(rv5min.msft, lag.max = 234, plot = F),
+      main = "ACF of 5-min Realized Volatility:\nMSFT (lags up to 3 days)")
Problem: Object "rv5min.msft" not found
Use traceback() to see the call stack
> # Plots of Calendar pattern in realized volatility for MSFT
> plot(rv5min.ave.msft, reference.grid = F,
+      x.axis.args = list(format.label = c("%H:%02M", "%Z"),
+                        time.of.day.style = "24:00"))
Problem: Object "rv5min.ave.msft" not found
Use traceback() to see the call stack
>
> ## USD/EUR ##
> ## 5-min realized volatility ##
> rv5min.eurusd = Genr.RealVol(ts = log(mq.eurusd)*100, interv.type = "weekly", bound.hours = c("22:00", "22:00"),
+                                                                 rv.span = timeSpan("5m"), rt.span = timeSpan("1m"))
Problem in sub(ts@data, !na.idx,  ): argument "x" is missing with no default
Use traceback() to see the call stack
> rv5min.eurusd[1:5, ]
Problem: Object "rv5min.eurusd" not found
Use traceback() to see the call stack
>
> # Average 5-min realized volatility across days
> rv5min.ave.eurusd = SmoothAcrossIntervs(ts = rv5min.eurusd, n.subinterv = 288,
+                          n.interv = 5, FUN = mean)
Problem: Object "rv5min.eurusd" not found
Use traceback() to see the call stack
> rv5min.ave.eurusd@title = "5-min Realized Volatility: USD/EUR\n(averaging across 5 trading days)"
Problem: Object "rv5min.ave.eurusd" not found
Use traceback() to see the call stack
>
> par(mfrow = c(1,2))
> # ACF of the 5-min realized volatility for USD/EUR
> acf.plot(acf(rv5min.eurusd, lag.max = 864, plot = F),
+      main = "ACF of 5-min Realized Volatility:\nUSD/EUR (lags up to 3 days)")
Problem: Object "rv5min.eurusd" not found
Use traceback() to see the call stack
> # Plots of Calendar pattern in realized volatility for USD/EUR
> plot(rv5min.ave.eurusd, reference.grid = F,
+      x.axis.args = list(format.label = c("%H:%02M", "%Z"),
+                        time.of.day.style = "24:00"))
Problem: Object "rv5min.ave.eurusd" not found
Use traceback() to see the call stack
>
> ### 3.3.2 Calendar patterns in duration ###
> ## MSFT
> ## mean durations in 5-min intervals
> args(aggregateSeriesHF)
function(ts, interv.type = "daily", bound.hours = c("9:30", "16:00"), by, k.by, FUN, adj, drop.empty = F,
        ...)
NULL
> meanDur5min.msft = aggregateSeriesHF(duration.msftt, interv.type = "daily",
+                       bound.hours = c("9:30", "16:00"), FUN = mean,
+                      by = "minutes", k.by = 5, adj = 1, drop.empty = F, together = T)
Problem: Object "duration.msftt" not found
Use traceback() to see the call stack
> meanDur5min.msft[1:5,]
Problem: Object "meanDur5min.msft" not found
Use traceback() to see the call stack
>
> # averaging 5-min mean durations across trading days
> meanDur5min.ave.msft = SmoothAcrossIntervs(ts = meanDur5min.msft, n.subinterv = 78,
+                                    n.interv = 11, FUN = mean)