Category Archives: Uncategorized

  • 0

Quick Table for Converting Different Dates to Stata Format

Category:Uncategorized

Daily Dates

Copying data from the internet, CSV files, or other sources into Stata will record the date as a string variable, shown with red color. Before we can use the Stata time-series or panel data commands, we need to convert the string date to Stata date. In the following table, the first columns show different date formats in which the date is already recorded and brought into Stata. To convert them into Stata date, an example code is shown in the second column. Once the date is converted into Stata readable format, we need to format the date so the visual display of the date is human readable. We can do that by using the %td format, for example, we can use the code format mydate %td

text Code Output
15/1/2015
gen mydate=date(text, "MDY")
15feb2015
15/1/2015
gen mydate=date(text, "MDY")
15feb2015
2015/1/15
gen mydate=date(text, "YMD")
15feb2015
201502
gen mydate=date(text, "MY")
1feb2015
1/15/08
gen mydate=date(text,"MDY",1999)
15jan1908
1/15/08
gen mydate=date(text,"MDY",2019)
15jan2008
1/15/51
gen mydate=date(text,"MDY",2000)
15jan1951
1/15/01
gen mydate=date(text,"MDY",2050)
15jan2001
1/15/00
gen mydate=date(text,"MDY",2050)
15jan2000
20060125
gen mydate=date(text, "YMD")
25jan2006
060125
gen mydate=date(text, "20YMD")
25jan2006


Example using some data

* Enter example data
clear
input str9 text
"15/1/2015"
end

* Now convert the variable text to Stata date
gen mydate=date(text, "MDY")

* Change the display format
format mydate %td

 

From daily to other frequencies

From daily to Code
weekly
gen weekly_date = wofd(daily_date)
Monthly
gen monthly_date = mofd(daily_date)
Quarterly
gen qyarterly_date = qofd(daily_date)
Yearly
gen year = year(daily_date)

 

 

Example using some data

* Enter example data
clear
input str9 text
"15/1/2015"
end

* Now convert the variable text to Stata date
gen daily_date=date(text, "MDY")
format daily_date %td


* Create a weekly date
gen weekly_date = wofd(daily_date)
format weekly_date %tw

* Create a monthly date
gen monthly_date = mofd(daily_date)
format monthly_date %tm

* Create a quarterly date
gen quarterly_date = qofd(daily_date)
format quarterly_date %tq

* Create a yearly date
gen year = year(daily_date)

 

 

From other frequencies to daily

If we already have dates in weekly, monthly, or quarterly frequencies, we can convert them back to daily dates. The second column in the following table provides an example of a given format in which the date is already recorded, and the third column presents the code which shall create a daily date. To see the codes in action, download this do file and execute. The file extension should be changed from doc to do after download. 

From  given_date Code
weekly
2018w46
gen daily_date = dofw(given_date)
Monthly
2018m11
gen daily_date = dofm(given_date)
Quarterly
2018q4
gen daily_date = dofq(given_date)
Yearly
2018
gen daily_date = dofy(given_date)

 

Complex Conversions

If we already have dates in weekly, monthly, or quarterly frequencies, we can convert them back to daily dates and then to other frequencies. The second column in the following table provides an example of a given format in which the date is already recorded, and the third column presents the code which shall convert the date to the desired frequency.  

From  given_date Code
Weekly to monthly
2018w46
gen monthly_date = dofm(dofw(given_date))
Monthly to weekly
2018m11
gen weekly_date = dofw(dofm(given_date))
Quarterly to monthly
2018q4
gen monthly_date = dofm(dofq(given_date))
Monthly to quarterly
2018m11
gen quarterly_date = qofd(dofm(given_date))
Weekly to quarterly
2018w46
gen quarterly_date = qofd(dofw(given_date))
Quarterly to Weekly
2018q4
gen weekly_date = dofw(dofq(given_date))

 

 

  • 4

asdoc version 2 : Summary of New features | export Stata output to MS Word

Category:Uncategorized

Version 2.0 of asdoc is here. This version brings several improvements, adds new features, and fixes minor bugs in the earlier version. Following is the summary of new features and updates.

 

Brief Introduction of asdoc

asdoc sends Stata output to Word / RTF format. asdoc creates high-quality, publication-ready tables from various Stata commands such as summarize, correlate, pwcorr, tab1, tab2, tabulate1, tabulate2, tabstat, ttest, regress, table, amean, proportions, means, and many more. Using asdoc is pretty easy. We need to just add asdoc as a prefix to Stata commands. asdoc has several built-in routines for dedicated calculations and making nicely formatted tables.

 

How to update

The program can be updated by using the following command from Stata command window

ssc install asdoc, replace

 

New Features in Version 2.0

1.  Wide regression tables

This is a new format in which regression tables can be reported. In this format, the variables are shown in columns and one regression is reported per row. Therefore, this type of regressions tables is ideal for portfolios, industries, years, etc. Here is one example of a wide regression table. asdoc allows a significant amount of customization for wide tables including asterisks for showing significance, reporting t-statistics and standard errors either below regression coefficients or sideways, controlling decimal points, reporting additional regression statistics such adjusted R2, RMSE, RSS, etc., adding multiple tables in the same file, and several other features. Read this post to know more about wide table format.

 

2. Allowing by-group regressions

Version 2.0 of asdoc provides the convenience of estimating regressions over groups and summarizing the regression estimates in nicely formatted tables. This feature follows the Stata default of bysort prefix. This feature works with all three types of regression tables of asdoc that include detailed regression tables, nested tables, and wide tables. In this blog post, I show some examples of by-group regressions.

 

3. Allowing by-group descriptive statistics

Using the bysort prefix with asdoc, we can now find default, detailed, and customized summary statistics over groups. Details related to this feature will be added later on in a blog post.

 

4. Option label with tabulate and regress commands

Option label can now be used with regression and tabulation commands. Using this option, asdoc will report variable labels instead of variable names. In case variable labels are empty, then the variable names are reported.

 

5. Developing tables row by row using option row

Option row is a new feature in version 2. Option row allows building a table row by row from text and statistics. In each run of asdoc with option row, a row is added to the output table. This is a useful feature when statistics are collected from different Stata commands to build customized tables. To know more about this option, read this blog post.

 

6.  Accumulate text or numbers with option accum

Option accum allows accumulating text or numbers in a global macro. Once accumulated, the contents of the macro can then be written to an output file using option row.

 

7. Saving files in different folders

One additional feature of version 2.0 is the ability to write new files or append to existing files in different folders.

 


  • 1

Plotting cumulative average abnormal (CAAR) on a graph in Stata

Category:Uncategorized

In Stata, we can use the two-way graph type for plotting abnormal returns or cumulative average abnormal returns against the days of the event window. Suppose that we have event window of 7 days, and have the following data

 

 
days caar1 caar2 caar3 caar4
-3 0 0 0 0
-2 -.0043456 -.0050911 .0000683 .0000504
-1 -.0034961 -.0023533 .0037439 .0042783
0 -.0034278 .0019828 .0090661 .0106628
1 .0016178 .0067894 .0131572 .0156011
2 .0039689 .0104367 .0190594 .0221428
3 .0040022 .0129478 .0218878 .0267722

to plot the first caar1, we shall type :

graph twoway line caar1 days, xline(0)

 

If we were to plot all caars, then

graph twoway line caar* days, xline(0)

 


  • 0

Rolling regressions, beta, t-statistics, and SE in Stata

Category:Uncategorized

asreg can easily estimate rolling regressions, betas, t-statistics and SE in Stata. To understand the syntax and basic use of asreg, you can watch this Youtube video. In this post, I show how to use asreg for reporting standard errors, fitted values, and t-statistics in a rolling window.

To install asreg, type the following on the Stata command window

ssc install asreg

 

Report standard errors and fitted values 

We shall use the grunfeld data set for our examples. Using a rolling window of 15 observations, let us fit a regression model where our dependent variable is invest and independent variables are mvalue and kstock. We shall estimate the rolling regression separately for each company, therefore, we shall use the prefix bys company : 

Please note that option se and fit are used for reporting standard errors and fitted values, respectively.

webuse grunfeld, clear

bys company: asreg invest mvalue kstock, wind(year 15) fit se

 

Find t-statistics in the rolling window

Once we have the standard errors and coefficients, we can generate t-statistics by dividing respective coefficients on their standard errors. Therefore, to find t-values for the variable mvalue and kstock, we can generate new variables:

gen t_mvalue = _b_mvalue / _se_mvalue

gen t_kstock = _b_kstock / _se_kstock



  • 0

Log vs simple returns: Examples and comparisons

Category:Uncategorized Tags : 

Simple vs log returns | Conversion from daily to other frequencies

MS Excel Example 

[Download Example]

In the above table, we have data from 1/1/2010 to 1/7/2010.  The first column had firm id; the second column has dates; the third column has stock prices.

id date prices simple ri log_ri ri+1
1 1/1/2010 70
1 1/2/2010 72 2.857% 2.817% 102.857%
1 1/3/2010 75 4.167% 4.082% 104.167%
1 1/4/2010 73 -2.667% -2.703% 97.333%
1 1/5/2010 74 1.370% 1.361% 101.370%
1 1/6/2010 76 2.703% 2.667% 102.703%
1 1/7/2010 77 1.316% 1.307% 101.316%

The fourth and fifth columns have simple and log returns, calculated as:

simple ri = (Price[i] - Price[i-1] ) /  Price[i-1]  --- (Eq. 1)
log ri = ln( Price[i]  /  Price[i-1]  --- (Eq. 2)

where Price[i] is the stock price in the current period,  Price[i-1] is the stock price in the previous period, ln is the natural log. To convert simple returns to n-period cumulative returns, we can use the products of the terms (1 + ri) up to period n. Therefore, the fifth column adds a value of 1 to the simple period returns.

Weekly cumulative simple returns

Suppose we wish to find weekly cumulative simple returns from the stock prices, we shall just use the first and the last stock prices of the week and apply equation (1). Therefore, our cumulative weekly simple return is as follows:

weekly simple ri = ( 77 - 70) /  70 = 10.00%

And if we were to find weekly cumulative simple returns from the daily returns, then we would add 1 to each of the period simple_ri, find its product, and deduct 1 at the end. Therefore, the formula for converting simple periodic daily returns to weekly cumulative returns would be :

Cumulative n-period simple returns =

(1+simple_r1) * (1+simple_r2) *(1+simple_r3)
  ... (1+simple_rn- 1     --- (Eq. 3)

Therefore, applying Equation 3 to our example;

Cumulative weekly simple returns =
102.857% * 104.167% * 97.333% * 101.370% * 102.703% 
* 101.316% - 1 = 10.00%

Weekly cumulative log returns

Now suppose we wish to find weekly cumulative log returns from the stock prices, again we shall use the first and the last of the stock prices of the week in equation (2). So, our cumulative weekly log return is as follows:

weekly log ri = ln( 77 /  70) = 9.53%

Since log returns are continuously compounded returns, it is normal to see that the log returns are lower than simple returns. To find n-period log returns from daily log returns, we need to just sum up the daily log returns. Therefore :

Cumulative weekly simple returns2.817% + 4.082% +  (-2.703%) + 
1.361% +2.667% +  1.307% = 9.53%

Stata Example


We shall continue to use the same data as above. The Stata do file for all of the following steps can be downloaded from here.

The following lines of code will generate the required data

clear
input float date byte(id prices) float wofd
18263 1 70 2600
18264 1 72 2600
18265 1 75 2600
18266 1 73 2600
18267 1 74 2600
18268 1 76 2600
18269 1 77 2600
end
format %td date
format %tw wofd
tsset id date

Now to generate simple and log returns

bys id (date) : gen simple_ri = (price / L.price) -1
bys id (date) : gen log_ri = ln(price / L.price)

Cumulative weekly simple returns

we shall use ascol program. This program can be downloaded from SSC by typing:

ssc install ascol

If daily returns were calculated with Eq. 1 above (i.e. simple returns) and they needed to be converted to cumulative n-periods returns, we shall use the option returns(simple). For this purpose, we would type the following command:

 
ascol simple_ri, returns(simple) keep(all) toweek

For syntax and option details of ascol, you can type help ascol at the Stata command prompt. We shall just briefly list the option used in the above command. After typing ascol, we need to mention the name of the variable for which cumulative returns are needed.

In our case, it is the simple_ri. Then after the comma, we invoke various program options. Our first option is returns(simple), which tells ascol that our data have simple returns. ascol will apply product method of converting from daily to weekly see Eq. 3 above ).  Then we use keep(all)  to stop ascol from collapsing the data set to a weekly frequency. Absent this option, the data will be reduced to one observation per ID and weekly_period identifier.  The other possibility in this regard is the option price, which can be used if the variable is stock prices.  And finally, we used toweek option for converting the data to a weekly frequency. Other possible options in this regard are tomonth, toquarter, and toyear.

Cumulative weekly log returns

If daily returns were calculated using Eq. 2 above  (i.e. log returns) and they need to be converted to cumulative n-periods returns, we shall use the option returns(log). For this purpose, we would type the following command:

 ascol log_ri , returns(log) keep(all) toweek gen(log_cumRi)

The syntax details remain the same as given above. We have used one additional option gen(log_cum) for naming the new variable as log_cumRi

date wofd simple_ri log_ri week_s~i log_cumRi
01jan2010 2010w1 . . .1 .09531018
02jan2010 2010w1 .0285714 .0281709 .1 .09531018
03jan2010 2010w1 .0416667 .040822 .1 .09531018
04jan2010 2010w1 -.0266667 -.0270287 .1 .09531018
05jan2010 2010w1 .0136986 .0136057 .1 .09531018
06jan2010 2010w1 .027027 .0266682 .1 .09531018
07jan2010 2010w1 .0131579 .0130721 .1 .09531018

  • 0

Stata Dates: Conversion from one format to another

Category:Uncategorized

Case 1: From String to Stata format

Usually, when we import data manually into the Stata Editor, the dates are shown in string format. For example, Nov202011, November202011, or  etc. We can use the gen command with date function

gen newdate = date(oldDate, "MDY")

 

Case 2: From daily to monthly

gen monthly = mofd(daily_date)

 

Case 3: From daily to weekly

gen monthly = wofd(daily_date)

Case 4: From daily to quarterly

gen monthly = qofd(daily_date)

 

Case 5: From daily to yearly

gen monthly = year(daily_date)

 

Case 6: From monthly to daily

If our date is recorded in monthly numeric format such as 2001m1, 2001m2, etc, then:

gen daily = dofm(monthly_date)

  • 0

Research Topics in Islamic Banking and Finance

Category:Uncategorized

 


 How Islamic financial instruments can be used in international trade?

 A mechanism for inter-bank transactions for Islamic and conventional banks

Can Sharia board play a role in the development of Islamic instruments?

4 Tawarruq as a tool of inter-bank borrowing

5  Risk management framework for Islamic banks: do we need something special?

6  Have the challenges faced by Islamic banks changed over the last decade?

7  The dynamics of financial crisis: Conventional vs Islamic finance

8  Can Zakat be used as a microfinancing tools?

9  Value at Risk of Sukuk and conventional bonds

10  Risk analysis of Murabaha financing and leasing

11  What customers say about Islamic banking? Values vs religious perspectives

12  Can ownership structure affect earning management?

13 Collaborative Islamic Banking Service: The Case of Ijarah

14 Success factors of collaboration in Islamic banks

15 Constraints in the application of partnerships in Islamic banks

16  Can Islamic finance reduce nonperforming loans?

17  Which firms use Islamic financing?

18  Can SME’s benefit more from Islamic financing?

19  Islamic banking development and access to credit

20  Islamic finance and economic growth


  • 0

Research Topics in Finance: Earning Management

Category:Uncategorized Tags : 

 


 The relationship between earning management and market liquidity

 Are top management pays and earning management practices related?

 Can financial crisis affect earning management practices?

 The effect of the earning transparency on cost of capital 

4  The impact of leverage on accrual-based earnings management

5  Can institutional investors exploit the accrual anomaly?

6  Accrual-based and real earnings management: Are investors protected?

7  Cost of capital and earnings transparency

8  The effect of accounting comparability on the accrual-based and real earnings management

9  Earnings management and accrual anomaly across market states and business cycles

10  Short-term debt maturity, monitoring and accruals-based earnings management

11  The effect of mandatory IFRS adoption on real and accrual-based earnings management activities

12  Can ownership structure affect earning management?

13  Regulatory Risk and the Cost of Capital

14  Accrual-based and real earnings management activities around seasoned equity offerings

15  Time-varying risk, mispricing attributes, and the accrual premium

16  Accruals, cash flows, and operating profitability in the cross section of stock returns

17  Does family involvement explain why corporate social responsibility affects earnings management?

18  How excess control and earning management practices are related?

19  Managerial entrenchment and earnings management

20  Product market competition and earnings management


  • 0

How to convert numeric date to Stata date

Category:Uncategorized Tags : 

Real-life data can come in a variety of formats.  In this post, I would like to show how to convert a numeric date to Stata date.

The problem

Let’s use an example.  Say that we have date variable in the following format and we want to convert it to Stata format.

 +----------+
 | datevar  |
 |----------|
 | 20170520 |
 | 20170521 |
 | 20170522 |
 | 20170524 |
 | 20170524 |
 +----------+

Solution

There are two steps involved to convert numeric variable to Stata format. These are:

tostring date, replace
gen date2 = date(datevar, "YMD")
format date2 %td

Explanation

The first line of code converts the numeric variable to string variable. This is necessary as the date function can work only on string variables. The second line of code uses the date function to generate a new variable date2 from the existing variable datevar . The “YMD” sepcifies how the datevar has the sorting of  year, month, and day. The last line of code just formats the new variable so that human can easily read it.


  • 2

T-bills rates, auction dates, bids and offer prices

Category:Uncategorized Tags : 
Auction No. Auction Date Realized Amount 3-Months 6-Months 12-Months
1st 6/25/1998 23,623.24 15.70%
2nd 7/14/1998 7,708.23 14.62% 15.41% 16.00%
3rd 7/23/1998 2,305.36 15.74%
4th 8/5/1998 21,261.33 13.82% 15.29% 15.90%
5th 8/18/1998 19,628.07 13.71% 14.94% 15.78%
6th 9/4/1998 20,526.84 13.85% 15.39%
7th 9/29/1998 9,255.20 13.55% 15.17%
8th 10/12/1998 1,910.04 15.18%
9th 10/23/1998
10th 11/4/1998 23,149.34 14.13%
11th 11/16/1998 6,981.53 9.50% 11.96% 12.99%
12th 12/4/1998 5,998.96 11.93% 12.99%
13th 12/22/1998 2,207.54 11.87% 12.98%
14th 1/10/1999 5,310.86 12.10% 12.98%
15th 1/20/1999 8,364.98 12.11% 12.46% 13.17%
16th 2/1/1999 20,217.27 12.43% 12.87% 13.54%
17th 2/14/1999 15,086.10 12.71% 13.30% 13.81%
18th 3/3/1999 10,978.54 12.37% 12.96%
19th 3/25/1999 3,860.06 10.73% 11.35% 11.80%
20th 4/21/1999 211.15 10.60% 11.50%
21st 5/12/1999
22nd 5/26/1999 2,449.45 8.37%
23rd 6/9/1999 10,210.51 7.53%
24th 6/23/1999 12,580.09 6.66% 10.10%
25th 7/7/1999 2,063.78 10.33%
26th 7/21/1999 6,403.10 6.96% 10.29%
27th 8/11/1999 15,569.91 6.94% 10.18%
28th 8/25/1999 9,919.75 7.86% 9.43% 10.20%
29th 9/8/1999 17,856.24 8.80% 10.05% 10.32%
30th 9/22/1999 5,428.64 8.96% 10.25% 10.73%
31st 10/6/1999 2,187.07 10.36%
32nd 10/20/1999
33rd 11/3/1999 26,708.09 8.78% 9.94% 10.61%
34th 11/17/1999 5,884.40 8.82% 10.13% 10.87%
35th 12/1/1999 1,742.63 8.87% 10.16% 10.77%
36th 12/15/1999 1,833.81 10.10% 10.33%
37th 12/29/1999 201.77 10.31%
38th 1/12/2000 95.94 8.49%
39th 1/26/2000 2,719.69 8.01% 8.43% 8.95%
40th 2/9/2000 8,746.78 7.54% 7.96% 8.44%
41st 2/23/2000 2,642.95 7.29% 7.45% 7.90%
42nd 3/8/2000 71.35 7.89%
43rd 3/23/2000 870.03 7.29% 7.44% 7.89%
44th 4/5/2000 8,318.59 7.11% 7.20% 7.69%
45th 4/19/2000 4,674.80 6.98% 7.13% 7.59%
46th 5/3/2000 20,762.14 6.94% 7.09% 7.58%
47th 5/17/2000 2,263.23 6.98% 7.20% 7.62%
48th 5/31/2000 1,198.66 6.95% 7.22% 7.61%
49th 6/14/2000 984.3 6.93%
50th 6/28/2000
51st 7/12/2000 8,750.29 6.85% 7.14%
52nd 7/26/2000 7,780.42 7.03% 7.23% 7.78%
53rd 8/9/2000 698.65 7.38% 7.96%
54th 8/23/2000 1,520.62 7.38% 8.01%
55th 9/6/2000 255.08 7.45% 8.10%
56th 9/20/2000 11,834.92 7.95% 8.14% 8.93%
57th 10/4/2000 11,036.69 10.23% 10.47% 10.91%
58th 10/18/2000 189.6 11.00%
59th 11/1/2000 12,790.27 10.99% 11.48%
60th 11/15/2000 426.69 10.96%
61st 11/29/2000 993.03 10.92% 11.49%
62nd 12/13/2000 585.28 10.96% 11.49%
63rd 1/10/2001
64th 1/24/2001 5,217.19 10.50% 10.96%
65th 2/7/2001 2,861.88 10.50% 10.96% 11.44%
66th 2/21/2001 2,926.20 10.96%
67th 3/7/2001 7,510.58 10.96%
68th 3/21/2001 13,203.74 11.16% 11.55% 11.95%
69th 4/5/2001 18,511.96 11.08% 11.54% 11.96%
70th 4/18/2001 4,392.58 11.54% 11.98%
71st 5/2/2001 19,718.56 11.13% 11.51% 11.97%
72nd 5/16/2001 4,252.95 11.57% 11.98%
73rd 5/30/2001 20,613.56 11.17% 11.60% 11.99%
74th 6/13/2001 10,915.78 11.79% 12.17% 12.53%
75th 6/27/2001 15,491.42 12.22% 12.88% 12.94%
76th 7/11/2001 6,132.91 12.15% 12.56%
77th 7/25/2001 11,315.59 11.33% 11.58% 11.98%
78th 8/8/2001 8,415.58 11.17% 11.36% 11.73%
79th 8/22/2001 16,532.72 10.04% 10.47% 10.82%
80th 9/5/2001 11,430.17 10.22% 10.49% 10.84%
81st 9/19/2001 1,178.84 10.18% 10.50% 10.87%
82nd 10/3/2001 7,737.85 10.00% 10.40% 10.76%
83rd 10/17/2001 3,231.11 10.29% 10.72%
84th 10/31/2001 9,208.18 8.18% 8.50% 9.00%
85th 11/14/2001 7,508.83 7.96% 8.30% 8.90%
86th 11/28/2001 9,806.76 7.96% 8.26% 8.74%
87th 12/12/2001 2,622.99 8.14% 8.54%
88th 12/26/2001 9,307.36 7.65% 7.93% 8.40%
89th 1/9/2002 8,089.56 7.77% 8.20%
90th 1/23/2002 11,744.50 6.13% 6.35% 6.82%
91st 2/6/2002 24,777.97 5.36% 5.65% 6.38%
92nd 2/20/2002 13,093.08 6.39% 6.90%
93rd 3/6/2002 11,392.48 5.81% 6.47% 7.01%
94th 3/20/2002 25,575.82 5.74% 6.44% 6.95%
95th 4/3/2002 3,693.80 6.48% 7.01%
96th 4/17/2002 5,882.04 6.45% 6.98%
97th 5/1/2002 32,973.06 5.77% 6.38% 6.96%
98th 5/15/2002 38,733.14 6.39% 6.95%
99th 5/29/2002 9,142.53 5.80% 6.43% 6.97%
100th 6/12/2002 4,105.12 6.42% 6.99%
101st 6/26/2002 10,520.51 6.28%
102nd 7/10/2002 66,055.70 5.81% 6.27% 6.82%
103rd 7/24/2002 10,417.33 6.40%
104th 8/7/2002 27,909.56 6.40%
105th 8/21/2002 24,642.81 5.80% 6.94%
106th 9/4/2002 17,080.61 6.39%
107th 9/18/2002 26,314.81 6.37%
108th 10/2/2002
109th 10/16/2002 19,144.33 6.34%
110th 10/30/2002 37,434.87 6.87%
111th 11/13/2002 20,936.25 6.36%
112th 11/27/2002 24,469.00 4.76%
113th 12/11/2002 12,970.31 4.32%
114th 12/25/2002 19,324.67 3.90% 4.36%
115th 1/8/2003 33,164.54 3.84%
116th 1/22/2003 27,601.98 3.18% 3.63%
117th 2/5/2003 43,925.37 3.19%
118th 2/19/2003 9,887.64 3.17% 3.60%
119th 3/5/2003 30,333.65 2.09%
120th 3/19/2003 40,237.07 1.96% 2.66%
121st 4/2/2003 4,116.36 1.64%
122nd 4/16/2003 24,308.65 1.66% 2.61%
123rd 5/1/2003 12,100.75 1.65%
124th 5/15/2003 40,882.17 2.58%
125th 5/28/2003 23,489.29 1.80%
126th 6/11/2003 25,403.20 2.36%
127th 6/25/2003 1,487.65 1.66%
128th 7/9/2003 75,718.12 1.66% 2.15%
129th 7/23/2003 26,937.27 1.21%
130th 8/6/2003 51,353.89 0.99% 1.40%
131st 8/20/2003 36,479.06 1.21%
132nd 9/3/2003 19,484.35 1.38% 1.93%
133rd 9/17/2003 14,434.33 1.61%
134th 10/1/2003 1,494.90 1.47%
135th 10/15/2003
136th 10/29/2003 38,469.42 1.46% 1.95%
137th 11/12/2003 198.36 1.66%
138th 11/30/2003 196.16 1.98%
139th 12/10/2003 297.56 1.64%
140th 12/25/2003 196.12 1.99%
141st 1/7/2004 8,232.56 1.64%
142nd 1/21/2004 9,918.87 1.48% 1.96%
143rd 2/11/2004 29,324.50 1.68%
144th 2/18/2004 39,155.67 1.49% 1.97%
145th 3/3/2004 18,276.83 1.74%
146th 3/17/2004 41,124.52 1.52% 2.00%
147th 3/31/2004 20,500.73 1.80%
148th 4/14/2004 16,814.94 1.61% 2.07%
149th 4/28/2004 990.9 1.84%
150th 5/12/2004 57,159.13 1.70% 2.19%
151st 5/26/2004 1,583.61 2.08%
152nd 6/9/2004
153rd 6/23/2004
154th 7/7/2004 65,185.55 2.02% 2.69%
155th 7/21/2004 66,908.30 2.52%
156th 8/4/2004 50,888.52 2.13% 2.83%
157th 8/18/2004 46,789.58 2.62%
158th 9/1/2004 61,055.09 2.23% 2.97%
159th 9/15/2004 1,083.79 3.00%
160th 9/29/2004 17,332.44 2.95%
161st 10/13/2004 1,230.44 3.19%
162nd 10/27/2004 20,194.27 3.22% 3.84%
163rd 11/10/2004 2,405.24 3.73%
164th 11/24/2004 26,261.46 3.78% 4.43%
165th 12/8/2004
166th 12/22/2004 15,113.79 3.92%
167th 1/5/2005 26,892.39 4.16%
168th 1/23/2005 77,002.01 4.14% 4.96%
169th 2/2/2005 976.65 4.79%
170th 2/16/2005 62,346.87 4.70% 5.49%
171st 3/2/2005 15,421.34 5.18%
172nd 3/16/2005 78,792.50 4.94% 5.72%
173rd 3/30/2005 21,947.34 5.51%
174th 4/13/2005 98,772.43 5.81% 7.10%
175th 4/27/2005 7,881.90 7.08%
176th 5/11/2005 86,138.23 7.03% 7.91%
177th 5/25/2005 40.95 7.82%
178th 6/8/2005 490.85 7.38% 7.90% 8.30%
179th 6/22/2005 105,576.70 7.48% 7.94% 8.40%
180th 7/6/2005 76,414.86 7.55% 7.98% 8.46%
181st 7/20/2005 17,443.35 7.69% 7.97% 8.69%
182nd 8/3/2005 54,781.02 7.75% 8.02% 8.70%
183rd 8/17/2005 14,152.57 7.84% 8.11% 8.79%
184th 8/31/2005 105,887.67 7.99% 8.12% 8.78%
185th 9/14/2005 9,269.17 8.10% 8.14% 8.79%
186th 9/28/2005 8,232.56 8.10% 8.14% 8.79%
187th 10/12/2005 4,270.70 8.10% 8.14% 8.79%
188th 10/26/2005 18,476.57 8.10% 8.14% 8.77%
189th 11/8/2005 7,063.96 8.10% 8.14% 8.77%
190th 11/23/2005 57,208.62 8.10% 8.26% 8.77%
191st 12/7/2005 18,020.78 8.79%
192nd 12/21/2005 68,479.04 8.09% 8.25% 8.76%
193rd 1/4/2006 46,726.17 8.10% 8.27% 8.78%
194th 1/18/2006 8,447.61 8.10% 8.29% 8.75%
195th 2/1/2006 14,161.78 8.10% 8.29% 8.78%
196th 2/15/2006 5,868.49 8.10% 8.79%
197th 3/1/2006 7,477.28 8.10% 8.29% 8.78%
198th 3/15/2006 25,003.28 8.10% 8.29% 8.78%
199th 3/29/2006 37,463.37 8.10% 8.29% 8.79%
200th 4/12/2006 13,663.76 8.10% 8.29% 8.79%
201st 4/26/2006 459.7 8.79%
202nd 5/10/2006 653.88 8.10% 8.29% 8.79%
203rd 5/24/2006 1,113.60 8.10% 8.29% 8.79%
204th 6/7/2006 25,711.77 8.25% 8.42% 8.79%
205th 6/21/2006 5,399.03 8.33% 8.49% 8.79%
206th 7/5/2006 76,207.78 8.31% 8.49% 8.79%
207th 7/19/2006 14,754.83 8.33% 8.49% 8.79%
208th 8/2/2006 6,263.67 8.61% 8.81% 9.00%
209th 8/16/2006 11,452.90 8.63% 8.81% 9.00%
210th 8/30/2006 11,086.99 8.64% 8.81% 9.00%
211th 9/13/2006 19,786.91 8.64% 8.81% 9.00%
212th 9/27/2006 17,966.59 8.64% 8.81% 9.00%
213th 10/11/2006 15,367.91 8.64% 8.81% 9.00%
214th 10/21/2006 21,623.30 8.64% 8.81% 9.00%
215th 11/8/2006 44,883.38 8.64% 8.82% 9.00%
216th 11/22/2006 60,680.82 8.64% 8.81% 9.00%
217th 12/6/2006 37,050.33 8.64% 8.81% 9.00%
218th 12/20/2006 16,450.42 8.64% 8.81% 9.00%
219th 12/30/2006 34,271.89 8.64% 8.81% 9.00%
220th 1/17/2007 36,088.07 8.64% 8.81% 9.00%
221st 1/31/2007 70,358.36 8.64% 8.81% 9.00%
222nd 2/14/2007 48,419.52 8.64% 8.81% 9.00%
223rd 2/28/2007 37,515.55 8.64% 8.81% 9.00%
224th 3/14/2007 24,821.43 9.00%
225th 3/28/2007 45,259.22 8.65% 8.83% 9.02%
226th 4/11/2007 52,094.66 8.69% 8.87% 9.05%
227th 4/25/2007 47,802.52 8.69% 8.90% 9.08%
228th 5/9/2007 19,515.83 8.69% 8.90% 9.09%
229th 5/23/2007 7,322.27 8.69% 8.90% 9.10%
230th 6/7/2007 42,948.92 8.90% 9.12%
231st 6/21/2007 7,330.40 9.16%
232nd 7/4/2007 56,426.11 8.69% 8.90% 9.16%
233rd 7/18/2007 52,869.76 8.90% 9.16%
234th 8/1/2007 9,644.55 9.10% 9.37%
235th 8/15/2007 30,734.26 9.05% 9.14% 9.40%
236th 8/29/2007 5,485.80 9.40%
237th 9/12/2007 23,058.65 9.40%
238th 9/26/2007 19,383.16 9.40%
239th 10/10/2007 15,497.11 9.40%
240th 10/24/2007 9,366.71 9.14% 9.40%
241st 11/7/2007 32,230.74 9.14% 9.39%
242nd 11/21/2007 11,458.84 9.21% 9.40%
243rd 12/5/2007 45,158.40 9.11% 9.22% 9.41%
244th 12/19/2007 6,714.09 9.12% 9.26% 9.44%
245th 1/2/2008 23,597.09 9.09% 9.25% 9.44%
246th 1/16/2008 7,049.43 9.30% 9.45%
247th 1/30/2008
248th 2/13/2008 45,576.88 9.38% 9.61% 9.87%
249th 2/27/2008 35,434.70 9.46% 9.74% 9.99%
250th 3/12/2008 28,217.88 9.55% 9.82% 10.08%
251st 3/26/2008 9.08 10.12%
252nd 4/9/2008 37,677.86 9.56% 9.87% 10.13%
253rd 4/23/2008 516.94 9.87% 10.14%
254th 5/7/2008 29,523.08 9.67% 9.89% 10.17%
255th 5/21/2008 3,505.35 9.95% 10.32%
256th 6/4/2008 63,460.37 10.98% 11.19% 11.39%
257th 6/18/2008 15,198.29 11.32% 11.47% 11.69%
258th 7/2/2008 76,844.14 11.45% 11.78%
259th 7/16/2008 52,613.62 11.65% 11.83%
260th 7/30/2008 39,951.17 12.17%
261st 8/13/2008 35,999.61 12.22%
262nd 8/27/2008 34,712.03 12.39%
263rd 9/10/2008 14,759.57 12.56%
264th 9/24/2008 34,264.95 12.56% 12.69%
265th 10/8/2008 51,111.02 12.55%
266th 10/22/2008 60,782.88 12.56% 12.66% 12.79%
267th 11/5/2008 51,540.01 12.91%
268th 11/19/2008 103,467.68 13.69% 14.01%
269th 12/3/2008 81,473.36 13.84% 14.01%
270th 12/17/2008 70,543.29 13.84% 14.01%
271st 12/31/2008 67,795.02 13.85% 14.00% 14.25%
272nd 1/14/2009 79,356.69 13.85% 14.01% 14.26%
273rd 1/28/2009 79,504.93 13.73% 14.00% 14.16%
274th 2/11/2009 155,220.30 13.46% 13.74% 13.84%
275th 2/25/2009 124,923.53 12.56% 12.96% 12.99%
276th 3/11/2009 111,094.24 11.48% 11.67% 11.78%
277th 3/25/2009 81,395.94 11.65% 11.77% 11.85%
278th 4/8/2009 63,107.59 12.53% 12.76% 12.97%
279th 4/22/2009 64,724.62 12.89% 12.95% 13.14%
280th 5/6/2009 71,772.24 12.97% 13.11% 13.23%
281st 5/20/2009 29,489.02 13.14% 13.26%
282nd 6/3/2009 53,578.79 13.14% 13.23%
283rd 6/17/2009 56,979.58 12.01% 12.09%
284th 7/15/2009 58,349.25 11.31% 11.38% 11.47%
285th 7/29/2009 44,266.78 11.75%
286th 8/12/2009 79,908.16 12.16%
287th 8/26/2009 39,622.53 12.36% 12.44% 12.42%
288th 9/9/2009 51,657.20 12.43% 12.58% 12.46%
289th 9/25/2009 59,418.83 12.44% 12.58% 12.48%
290th 10/7/2009 23,392.02 12.42% 12.57% 12.58%
291st 10/21/2009 21,940.45 12.44% 12.59% 12.61%
292nd 11/4/2009 20,788.11 12.43% 12.55% 12.52%
293rd 11/18/2009 24,871.09 12.29% 12.32% 12.19%
294th 12/2/2009 14,601.76 12.14% 12.15% 12.09%
295th 12/16/2009 26,138.09 12.14% 12.22% 12.19%
296th 12/30/2009 15,954.30 12.06% 12.10% 12.09%
297th 1/13/2010 58,720.82 11.92% 12.03% 12.02%
298th 1/27/2010 29,852.61 11.87% 11.90% 11.98%
299th 2/10/2010 61,780.54 11.92% 12.02% 12.05%
300th 2/24/2010 108,618.66 12.17% 12.22% 12.27%
301st 3/10/2010 85,850.73 12.18% 12.30% 12.36%
302nd 3/24/2010 87,547.46 12.20% 12.34% 12.36%
303rd 4/7/2010 71,435.99 12.09% 12.24% 12.30%
304th 4/21/2010 84,065.07 12.14% 12.27% 12.34%
305th 5/5/2010 80,868.51 11.96% 12.13% 12.21%
306th 5/19/2010 77,146.93 11.88% 12.09% 12.17%
307th 6/2/2010 94,147.89 11.99% 12.17% 12.30%
308th 6/16/2010 121,821.02 12.06% 12.27% 12.38%
309th 7/14/2010 109,716.23 12.09% 12.32% 12.44%
310th 7/28/2010 125,137.18 12.08% 12.33% 12.45%
311th 8/11/2010 118,519.14 12.45% 12.65% 12.78%
312th 8/26/2010 91,556.98 12.51% 12.65% 12.78%
313th 9/9/2010 81,176.34 12.55% 12.69% 12.79%
314th 9/23/2010 60,752.48 12.69% 12.82%
315th 10/6/2010 90,255.92 12.83% 13.07% 13.22%
316th 10/20/2010 127,822.74 12.77% 13.08%
317th 11/3/2010 159,140.03 12.75% 13.11% 13.24%
318th 11/15/2010 56,752.85 12.81% 13.18% 13.30%
319th 12/1/2010 125,597.80 13.10% 13.37% 13.65%
320th 12/15/2010 121,351.43 13.17% 13.39% 13.69%
321st 12/29/2010 96,519.20 13.20% 13.41% 13.73%
322nd 1/12/2011 166,201.41 13.37% 13.50%
323rd 1/26/2011 196,898.43 13.57% 13.62% 13.87%
324th 2/9/2011 169,904.85 13.52% 13.66% 13.83%
325th 2/23/2011 158,970.32 13.44% 13.68% 13.85%
326th 3/9/2011 177,824.33 13.39% 13.65% 13.84%
327th 3/22/2011 172,557.27 13.25% 13.61% 13.77%
328th 4/6/2011 209,925.86 13.25% 13.66% 13.83%
329th 4/20/2011 239,577.35 13.25% 13.61% 13.83%
330th 5/4/2011 264,157.31 13.06% 13.45% 13.78%
331st 5/18/2011 171,930.44 13.15% 13.54% 13.82%
332nd 6/1/2011 138,856.55 13.43% 13.68% 13.88%
333rd 6/15/2011 181,611.20 13.47% 13.71% 13.88%
334th 6/29/2011 72,755.64 13.46% 13.73% 13.90%
335th 7/13/2011 115,896.41 13.48% 13.74% 13.90%
336th 7/27/2011 126,149.89 13.52% 13.76% 13.91%
337th 8/10/2011 182,830.51 13.04% 13.25% 13.35%
338th 8/25/2011 114,025.56 13.03% 13.28% 13.34%
339th 9/7/2011 160,233.71 13.04% 13.26% 13.37%
340th 9/21/2011 151,390.00 13.04% 13.20% 13.29%
341st 10/5/2011 182,154.33 12.69% 12.74% 12.81%
342nd 10/19/2011 121,359.99 11.87% 11.90% 11.93%
343rd 11/2/2011 292,977.95 11.78% 11.79% 11.85%
344th 11/16/2011 126,705.31 11.78% 11.80% 11.87%
345th 11/30/2011 113,262.98 11.65% 11.67% 11.78%
346th 12/14/2011
347th 12/28/2011 3,543.49 11.83% 11.90%
348th 1/11/2012 107,264.62 11.78% 11.78% 11.89%
349th 1/25/2012 120,311.47 11.56% 11.63% 11.69%
350th 2/8/2012 158,132.48 11.71% 11.77% 11.84%
351st 2/22/2012 13,349.03 11.74% 11.81%
352nd 3/7/2012 125,196.20 11.80% 11.87% 11.92%
353rd 3/21/2012 71,060.57 11.86% 11.93% 11.94%
354th 4/4/2012 151,759.31 11.87% 11.93% 11.94%
355th 4/18/2012 164,602.00 11.87% 11.94%
356th 5/2/2012 172,604.79 11.87% 11.94%
357th 5/16/2012 159,422.53 11.87% 11.94% 11.95%
358th 5/30/2012 118,081.58 11.87% 11.94%
359th 6/13/2012 69,159.00 11.90% 11.94% 11.95%
360th 6/27/2012 99,649.00 11.92% 11.94% 11.95%
361st 7/11/2012 308,151.26 11.87% 11.92% 11.93%
362nd 7/25/2012 365,238.01 11.82% 11.84% 11.85%
363rd 8/8/2012 355,563.12 11.44% 11.49% 11.59%
364th 8/17/2012 147,839.32 10.41% 10.43% 10.46%
365th 9/5/2012 302,341.09 10.26% 10.28% 10.29%
366th 9/19/2012 284,393.79 10.23% 10.23% 10.23%
367th 10/3/2012 191,626.12 9.73% 9.74% 9.73%
368th 10/17/2012 192,649.12 9.64% 9.65% 9.69%
369th 10/31/2012 305,161.99 9.23% 9.23% 9.28%
370th 11/14/2012 151,824.56 9.24% 9.26% 9.34%
371st 11/28/2012 165,621.85 9.28% 9.32% 9.38%
372nd 12/12/2012 151,824.56 9.28% 9.28% 9.36%
373rd 12/26/2012
374th 1/9/2013 224,087.93 9.18% 9.19% 9.28%
375th 1/23/2013 324,496.47 9.09% 9.14% 9.24%
376th 2/6/2013 233,071.29 9.09% 9.15% 9.24%
377th 2/20/2013 103,811.35 9.21% 9.34% 9.37%
378th 3/6/2013 146,023.93 9.29% 9.40% 9.41%
379th 3/20/2013 131,035.44 9.38% 9.42%
380th 4/3/2013 163,222.93 9.40% 9.41% 9.44%
381st 4/17/2013 39,628.74 9.41% 9.43%
382nd 4/30/2013 168,625.58 9.43% 9.43% 9.43%
383rd 5/15/2013 261,575.59 9.40% 9.41% 9.41%
384th 5/29/2013 261,653.07 9.36% 9.33% 9.34%
385th 6/12/2013 224,513.56 9.23% 9.23% 9.21%
386th 6/26/2013 153,426.57 8.93% 8.92% 8.96%
387th 7/10/2013 240,325.29 8.89% 8.94% 8.96%
388th 7/24/2013 275,516.25 8.95% 8.96% 8.97%
389th 8/6/2013 195,712.53 8.95% 8.98%
390th 8/21/2013 33,082.81 8.96% 8.99%
391st 9/4/2013 88,293.25 8.96%
392nd 9/18/2013 515,937.91 9.35% 9.45%
393rd 10/2/2013 342,103.25 9.40% 9.45%
394th 10/14/2013 130,764.72 9.42%
395th 10/30/2013 350,174.47 9.41% 9.46%
396th 11/13/2013 64,896.16 9.43% 9.46%
397th 11/27/2013 546,352.22 9.83%
398th 12/11/2013 519,558.66 9.88% 9.98%
399th 12/24/2013 393,233.76 9.90% 9.98%
400th 1/8/2014 95,002.18 9.94% 9.95% 9.99%
401st 1/22/2014 730,802.43 9.92% 9.98% 9.99%
402nd 2/4/2014 32,408.69 9.97% 9.98% 9.99%
403rd 2/19/2014 332,680.98 9.95% 9.98%
404th 3/5/2014 284,578.72 9.96% 9.98% 9.99%
405th 3/19/2014 243,271.45 9.96% 9.98% 9.98%
406th 4/2/2014 35,176.18 9.96% 9.98% 9.99%
407th 4/16/2014 281,988.21 9.96% 9.98% 9.99%
408th 4/30/2014 331,426.34 9.94% 9.97% 9.99%
409th 5/14/2014 360,476.26 9.96% 9.97% 9.99%
410th 5/28/2014 83,262.76 9.96% 9.98%
411th 6/11/2014 92,442.76 9.96% 9.98% 9.99%
412th 6/25/2014 42,949.85 9.96% 9.97% 9.99%
413th 7/9/2014 141,029.59 9.96% 9.98% 9.99%
414th 7/23/2014 123,714.48 9.96% 9.98% 9.99%
415th 8/6/2014 92,910.08 9.96% 9.97% 9.99%
416th 8/20/2014 77,214.50 9.96% 9.98% 9.99%
417 9/3/2014 196266.929 9.96% 9.98% 9.99%
418 9/17/2014 9411.497 9.96% 9.98% 9.99%
419 10/2/2014 41950.658 9.97% 9.98% 9.99%
420 10/15/2014 121437.914 9.96% 9.98% 9.99%
421 10/29/2014 195088.301 9.96% 9.95% 9.98%
422 11/12/2014 302425.556 9.93% 9.92% 9.96%
423 11/26/2014 190559.725 9.45% 9.47% 9.48%
424 12/10/2014 73795.611 9.46% 9.49% 9.49%
425 12/24/2014 50152.228 9.48% 9.47% 9.42%
426 1/7/2015 222022.15 9.07% 9.13% 9.10%
427 1/21/2015 175586.389 8.92% 8.96% 8.64%
428 2/4/2015 192528.697 8.34% 8.39% 8.34%
429 2/18/2015 109237.517 8.32% 8.34% 8.28%
430 3/4/2015 94758.488 8.18% 8.12% 7.98%
431 3/18/2015 249835.795 8.16% 7.89% 7.77%
432 4/1/2015 83088.273 7.96% 7.93% 7.84%
433 4/15/2015 163371.545 7.92% 7.84% 7.75%
434 4/29/2015 251400.211 7.38% 7.26% 7.17%
435 5/13/2015 109270.849 6.86% 6.72% 6.77%
436 5/27/2015 102196.194 6.61% 6.64% 6.72%
437 6/10/2015 74174.603 6.74% 6.75% 6.78%
438 6/24/2015 93356.076 6.86% 6.94% 6.97%
439 7/8/2015 111660.639 6.93% 6.95% 6.97%
440 7/22/2015 219900.886 6.92% 6.95% 6.94%
441 8/5/2015 354999.594 6.92% 6.92% 6.93%
442 8/19/2015 236486.905 6.93% 6.95% 6.95%
443 9/2/2015 196421.301 6.93% 6.95% 6.97%
444 9/16/2015 147537.751 6.46% 6.45%
445 9/30/2015 58861.994 6.47% 6.48%
446 10/14/2015 177754.57 6.44% 6.47% 6.47%
447 10/28/2015 223051.067 6.30% 6.30% 6.31%
448 11/11/2015 262844.615 6.26% 6.28% 6.29%
449 11/25/2015 138925.026 6.37% 6.38%
450 12/9/2015 92386.556 6.38% 6.39%
451 12/23/2015 30393.361 6.34% 6.36% 6.39%
452 1/6/2016 246064.088 6.30% 6.28% 6.28%
453 1/20/2016 316374.633 6.16% 6.17% 6.17%
454 2/3/2016 330490.656 6.25% 6.24% 6.22%
455 2/17/2016 196591.968 6.21% 6.22% 6.22%
456 3/2/2016 184986.521 6.17% 6.19% 6.20%
457 3/16/2016 223278.825 6.15% 6.20% 6.21%
458 3/30/2016 56397.282 6.17% 6.18% 6.20%
459 4/13/2016 66721.213 6.17% 6.17% 6.21%
460 4/27/2016
461 5/11/2016 245679.052 6.20% 6.24% 6.25%
462 5/25/2016 278103.844 5.99% 6.00% 6.02%
463 6/8/2016 139185.129 5.95% 5.96% 6.00%
464 6/22/2016 193110.955 5.90% 5.89% 5.91%
465 7/4/2016 218245.065 5.87% 5.89% 5.91%
466 7/20/2016 424360.814 5.79% 5.82% 5.84%
467 8/3/2016 378348.707 5.85% 5.89% 5.90%
468 8/17/2016 386601.458 5.86% 5.90% 5.91%
469 8/31/2016 179097.296 5.86% 5.90% 5.91%
470 9/9/2016 85898.684 5.86% 5.90% 5.91%
471 9/28/2016 34308.28 5.86% 5.90% 5.91%
472 10/10/2016 72547.472 5.86% 5.90% 5.91%
473 10/26/2016 97514.684 5.88% 5.90% 5.91%
473rd 10/26/2016 97,514.68 5.88% 5.90% 5.91%
474th 11/9/2016 306,282.09 5.92% 5.92% Bids Rejected
475th 11/23/2016 296,659.92 5.95% 5.94% 5.95%
476th 12/7/2016 154,838.47 5.95% 5.95% Bids Rejected
477th 12/21/2016 152,202.24 5.96% 5.98% Bids Rejected
478th 1/4/2017 256,025.10 5.96% 5.98% 5.99%
479th 1/18/2017 538,376.80 5.88% 5.90% 5.93%
480th 2/1/2017 606,392.13 5.92% 5.97% 5.95%
481st 2/15/2017 640,235.80 5.94% 5.99% 5.99%
482nd 3/1/2017 397,079.46 5.95% 5.99% 5.99%
483rd 3/15/2017 286,640.28 5.95% 5.99% Bids Rejected
484th 3/29/2017 162,456.36 5.97% 5.99% No Bids Received
485th 4/12/2017 267,163.99 5.98% Bids Rejected Bids Rejected
486th 4/26/2017 376,024.81 5.99% 6.01% 6.00%
487th 5/10/2017 371,684.48 5.99% 6.01% 6.03%
488th 5/24/2017 341,492.97 5.99% 6.01% 6.05%
489th 6/7/2017 160,796.06 5.99% 6.01% 6.05%
490th 6/21/2017 354,774.75 5.99% 6.01% 6.04%
491st 7/5/2017 544,940.31 5.99% 6.01% 6.04%
492nd 7/19/2017 1,071,255.38 5.99% 6.01% 6.04%
493rd 8/2/2017 733,603.49 5.99% 6.01% 6.04%
494th 8/16/2017 615,802.41 5.99% 6.01% Bids Rejected
495th 8/31/2017 520,572.10 5.99% 6.01% 6.04%
496th 9/13/2017 371,820.49 5.99% 6.01% 6.04%