├── .DS_Store
├── Images
├── 1.png
├── 2.png
├── 3.png
├── 4.png
├── 5.png
├── 6.png
├── 7.png
├── 8.png
├── Plot.png
├── Rplot.png
├── US Map.png
├── barplot.png
├── treemap.png
├── Clusters.png
├── Word Cloud.png
├── corel_mat1.png
├── corel_mat2.png
├── Scatterplot1.png
├── Optimal K Value.png
├── Choosing K Value.png
├── weights-density plot.png
├── wordcloud - industry.png
├── Kmeans Clustering K =3.png
├── KMeans - Clustering k=4.png
├── SP 500 Daily Change distribution.png
├── Ann returns vs Ann vol vs Clusters.png
├── Cluster wise beta value distribution.png
├── Cluster wise ann sharpe ratio distribution.png
├── Cluster wise annualized returns distribution.png
└── Cluster wise annualized volatility distribution.png
├── Data
├── .DS_Store
└── sp500_index.csv
├── README.md
└── S&P500-Porfolio Construction using Clustering.R
/.DS_Store:
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/README.md:
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1 | # Creating a Diversified Stock Portfolio Using Clustering Analysis
2 | [![LinkedIn][linkedin-shield]][linkedin-url]
3 | #
4 | 
5 | 
6 |
7 | ### About
8 |
9 | The aim of the project is to create a diversified portfolio of stocks using clustering analysis and back test its performance against the historical data of a stock index. For this we look at the S&P500 index, that is deemed to be the most accurate quantifier of the US economy. S&P500 is the comparable standard for many funds in the marketplace.
10 |
11 | The attempt is to use K-Means clustering based on Euclidian distances to understand the effect of different parameters that affect the stock performance. The comprehension of stock performance will be aided by dividing stocks into clusters that have stocks with similar performance. These clusters provide valuable information to create stock portfolios.
12 |
13 | ### Link to the dataset
14 | https://www.kaggle.com/datasets/andrewmvd/sp-500-stocks?select=sp500_companies.csv
15 |
16 | ### Exploring the dataset
17 |
18 |
19 | 
20 |
21 | 
22 |
23 |
24 |
25 |
26 |
27 | 
28 |
29 | 
30 |
31 |
32 |
33 | ### Approach
34 | The following features were calculated from the 10 year daily historical data for all the stocks in the S&P 500 index
35 | - Correlation with SP500 index value
36 | - Beta with SP500 index value
37 | - Annualized Return on equity (daily returns)
38 | - Annualized Volatility on equity (daily returns)
39 | - Sharpe Ratio
40 | - Daily Change in price
41 | - Daily Variation in price
42 |
43 | ### Exploring intra feature correlation matrix using correlogram
44 |
45 | The following plots show the correlogram plotted from the correlation matrix on the feature vectors.
46 |
47 |
48 | 
49 |
50 | 
51 |
52 |
53 | ### K-Means Clustering
54 | The following results depict the optimal value for choosing K value using a spree plot and the clusters convex formed after choosing K =4. The stock symbols are used to represent its relative position in the cluster.
55 |
56 |
57 | 
58 |
59 | 
60 |
61 |
62 | ### Correlation Analysis
63 |
64 | Post K- Means clustering, Cluster wise distribution of Annualized returns, Annualized Volatility, Sharpe ratio and Beta were plotted. It can be observed that there is a significant difference in at least two or more clusters both in terms of mean value and standard deviation.
65 |
66 |
67 | 
68 |
69 | 
70 |
71 |
72 |
73 | 
74 |
75 | 
76 |
77 |
78 |
79 | 
80 |
81 |
82 |
83 |
84 |
85 | ### Backtesting results KMeans Portfolio vs the S&P500 index cumulative returns
86 | For validating the process of using clustering for creating a diversified portfolio we back tested it performance on the test/validation data. The clustering was performed on the first 7 years of data and then the remaining 3 years of data were used to validate the results of our portfolio. For this, two portfolios containing 20 stocks were created
87 | 1. Portfolio created using top five stocks (as per Sharpe ratio) from each cluster - [RED]
88 | 2. Portfolio created using top 20 stocks out of all 500 as per Sharpe ratio from the 7-year historical
89 | performance - [ORANGE]
90 |
91 |
92 | 
93 |
94 |
95 | ### Conclusion
96 | - It is observed that the orange portfolio, which is a collection of stocks with the highest Sharpe ratio, outperformed the S&P500 index. The portfolio formed using k-means clustering (red line) has a better performance.
97 | - This indicates that the K-Means clustering successfully created a diversified portfolio in terms of all the features mentioned during clustering and not only outperformed the S&P 500 index but also a collection of stocks with best historical performance.
98 | - The back-testing results indicate that the k-means portfolio was correlated with the index during COVID- 19 and recovered slower than the orange index. However, as the portfolio was highly diversified the k- means portfolio had a far better long-term performance in comparison with the orange portfolio
99 |
100 | ### Contact
101 |
102 | Karthik Ram - [LinkedIn](https://www.linkedin.com/in/karthikramx/)
103 |
104 |
105 |
106 |
107 |
108 | [contributors-shield]: https://img.shields.io/github/contributors/Vincentho711/Interactive-Brokers-Trading-Bot?style=for-the-badge
109 | [contributors-url]: https://github.com/Vincentho711/Interactive-Brokers-Trading-Bot/graphs/contributors
110 | [forks-shield]: https://img.shields.io/github/forks/Vincentho711/Interactive-Brokers-Trading-Bot?style=for-the-badge
111 | [forks-url]: https://github.com/Vincentho711/Interactive-Brokers-Trading-Bot/network/members
112 | [stars-shield]: https://img.shields.io/github/stars/Vincentho711/Interactive-Brokers-Trading-Bot?style=for-the-badge
113 | [stars-url]: https://github.com/Vincentho711/Interactive-Brokers-Trading-Bot/stargazers
114 | [issues-shield]: https://img.shields.io/github/issues/Vincentho711/Interactive-Brokers-Trading-Bot?style=for-the-badge
115 | [issues-url]: https://github.com/Vincentho711/Interactive-Brokers-Trading-Bot/issues
116 | [license-shield]: https://img.shields.io/github/license/Vincentho711/Interactive-Brokers-Trading-Bot?style=for-the-badge
117 | [license-url]: https://github.com/github_username/repo/blob/master/LICENSE.txt
118 | [forthebadge made-with-python]: http://ForTheBadge.com/images/badges/made-with-python.svg
119 | [linkedin-shield]: https://img.shields.io/badge/-LinkedIn-black.svg?style=for-the-badge&logo=linkedin&colorB=555
120 | [linkedin-url]: https://www.linkedin.com/in/karthikramx/
121 |
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/S&P500-Porfolio Construction using Clustering.R:
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1 | # REFERENCES
2 | # https://uc-r.github.io/kmeans_clustering
3 | # https://scholarship.claremont.edu/cgi/viewcontent.cgi?article=3517&context=cmc_theses
4 |
5 | # DEPENDENCIES
6 | # devtools::install_github("hrbrmstr/hrbrthemes")
7 |
8 |
9 | # CLEAR WORKSPACE
10 | rm(list=ls())
11 | cat("\014")
12 |
13 |
14 | library(ggplot2)
15 | library(treemapify)
16 | library(usmap)
17 | library(wordcloud)
18 | library(DataCombine)
19 | library(RColorBrewer)
20 | library(purrr)
21 | library(factoextra)
22 | library(hrbrthemes)
23 | require(mosaic)
24 | library(tidyverse)
25 | library(corrplot)
26 | library(Hmisc)
27 |
28 |
29 | ####################################################################
30 | ################### LOADING & ORGANISING DATA ######################
31 | ####################################################################
32 |
33 | options(warn=-1)
34 | companies = read.csv('Data/sp500_companies.csv')
35 | index = read.csv('Data/sp500_index.csv')
36 | stocks = read.csv('Data/sp500_stocks.csv')
37 |
38 | str(companies)
39 | str(index)
40 | str(stocks)
41 |
42 | companies$Sector = as.factor(companies$Sector)
43 | companies$Exchange = as.factor(companies$Exchange)
44 | companies$Industry = as.factor(companies$Industry)
45 | companies$Country <- NULL
46 |
47 | na.omit(companies)
48 | summary(companies)
49 |
50 | ####################################################################
51 | ############# PLOTS / DATA VIZ / UNDERSTANDING DATA ################
52 | ####################################################################
53 |
54 | # PLOT 1: scatter plot of number of full time employees to market cap
55 | g <- ggplot(companies, aes(Fulltimeemployees, Marketcap))
56 | g + geom_point() + scale_y_continuous(trans='log10') + scale_x_continuous(trans='log10') + geom_point(aes(color=Weight))
57 |
58 |
59 | # PLOT 2: Density plot of weights
60 | d <- density(companies$Weight) # returns the density data
61 | plot(d) # plots the results
62 |
63 | # PLOT 3: Ordered bar plot sector wise weight
64 | sector_weight_agg <- aggregate(companies$Weight, by=list(companies$Sector), FUN=sum)
65 | colnames(sector_weight_agg) <- c("Sectors", "Weight")
66 | sector_weight_agg <- sector_weight_agg[order(sector_weight_agg$Weight), ]
67 | sector_weight_agg$Sectors <- factor(sector_weight_agg$Sectors, levels = sector_weight_agg$Sectors)
68 |
69 |
70 | ggplot(sector_weight_agg, aes(x=Sectors, y=Weight)) +
71 | geom_bar(stat="identity", width=.5, fill="tomato3") +
72 | labs(title="Ordered Bar Chart", subtitle="Sector Vs Weight") +
73 | theme(axis.text.x = element_text(angle=65, vjust=0.6))
74 |
75 | # PLOT 4: Tree map
76 | treemap_data <- aggregate(companies$Weight, by=list(companies$Industry, companies$Sector), FUN=sum)
77 | colnames(treemap_data) <- c("Industry","Sectors", "Weight")
78 | ggplot(treemap_data, aes(area = Weight, fill = Sectors, label = Industry, subgroup = Sectors)) +
79 | geom_treemap() +
80 | geom_treemap_text(colour = "white", place = "topleft", reflow = T)
81 |
82 |
83 | # PLOT 5: US Map
84 | usmap_data = aggregate(companies$Weight, by=list(companies$State), FUN=sum)
85 | df <-usmap_data[order(usmap_data$Weight,decreasing = TRUE),]
86 | colnames(usmap_data) <- c("State", "Weight")
87 | class(usmap_data)
88 | usmap_data = usmap_data[!(is.na(usmap_data$State) | usmap_data$State==""), ]
89 | usmap_data$fips <- fips(usmap_data$State)
90 |
91 | plot_usmap(data = usmap_data, values = "Weight", color = "black") +
92 | scale_fill_continuous(low = "white", high = "darkgreen", name = "S&P 500 Weight", label = scales::comma) + theme(legend.position = "right")
93 |
94 | # PLOT 6: Word Cloud
95 | pal <- brewer.pal(9,"BuGn")
96 | freq <- table(companies$Industry)
97 | wordcloud(names(freq),freq,random.order=FALSE,random.colors=TRUE,rot.per=0,colors = pal)
98 |
99 |
100 |
101 | ####################################################################
102 | ############## CALCULATING FEATURES FOR CLUSTERING #################
103 | ####################################################################
104 |
105 | ## Features
106 | # 1. Correlation with SP500 index value ***
107 | # 2. Beta value ***
108 | # 3. Annualized Return on equity (daily returns) ***
109 | # 4. Annualized Volatility on equity (daily returns) ***
110 | # 5. Sharpe Ratio ***
111 | # 6. Daily Change in price ***
112 | # 7. Daily Variation in price ***
113 |
114 |
115 |
116 | # SETTING UP DATA
117 |
118 | # Calculating daily change in S&P500 index
119 | index = change(index, Var = 'S.P500', NewVar = 'daily_change', slideBy = -1, type = "proportion")
120 |
121 | # function to extract the first 70% of the 10 year historical data for constructing the portfolio
122 | getstockdata<-function(symbol){
123 | print(paste("Calculaitng metrics and organizing data for:", symbol))
124 | data <- subset(stocks , Symbol == symbol)
125 | rows <- as.integer(nrow(data) * 0.7)
126 | data <- data[1: rows,]
127 | data$daily_Change = (data$Open-data$Close)/data$Close
128 | data$daily_variation = (data$High-data$Low)/data$Low
129 | change(data, Var = 'Adj.Close', NewVar = 'daily_returns', slideBy = -1, type = "proportion")
130 | }
131 |
132 |
133 | # List of data frames are contained here for all 500 stocks
134 | stocks_daily_data = list()
135 |
136 | # calculating features for all 500 stocks
137 | sp500_ann_returns = c()
138 | sp500_ann_volatility = c()
139 | sp500_ann_sharpe_ratio = c()
140 | sp500_ann_daily_change = c()
141 | sp500_ann_daily_variation = c()
142 | sp500_beta = c()
143 | sp500_cor = c()
144 |
145 | # Extracting historical data for s&p500 stocks
146 | symbols = companies$Symbol
147 | for(symbol in symbols){
148 |
149 | # data preparationg
150 | data = getstockdata(symbol)
151 | stocks_daily_data[[symbol]] = data
152 | df = merge(data,index,by="Date")
153 | na.omit(df)
154 |
155 | # calculating financial ratios from historical data
156 | annualized_returns = (tail(cumprod(na.omit(data$daily_returns) + 1),n=1) ** (252/2160)) - 1
157 | if(length(annualized_returns) == 0){annualized_returns = NA}
158 | annualized_volatilty = 252**(1/2) * sd(na.omit(data$daily_returns))
159 | annualized_sharpe_ratio = annualized_returns / annualized_volatilty
160 | annualized_daily_change = 252**(1/2) * mean(na.omit(data$daily_Change))
161 | annualized_daily_variation = 252**(1/2) * mean(na.omit(data$daily_variation))
162 | beta = cor(df$Adj.Close,df$S.P500) * ( sd(na.omit(df$daily_returns)) / sd(na.omit(df$daily_change)) )
163 | corr = cor(df$Adj.Close,df$S.P500)
164 |
165 | print(paste("Annualized Returns :",annualized_returns))
166 | print(paste("Annualized Volatility :",annualized_volatilty))
167 | print(paste("Annualized Sharpe Ratio :",annualized_sharpe_ratio))
168 | print(paste("Annualized Daily Change :",annualized_daily_change))
169 | print(paste("Annualized Daily Variation :",annualized_daily_variation))
170 | print(paste("Beta :",beta))
171 | print(paste("Corr :",corr))
172 | print("-----------------------------------------------------------------------")
173 |
174 | # appending data
175 | sp500_ann_returns = append(sp500_ann_returns,annualized_returns)
176 | sp500_ann_volatility = append(sp500_ann_volatility,annualized_volatilty)
177 | sp500_ann_sharpe_ratio = append(sp500_ann_sharpe_ratio,annualized_sharpe_ratio)
178 | sp500_ann_daily_change = append(sp500_ann_daily_change,annualized_daily_change)
179 | sp500_ann_daily_variation = append(sp500_ann_daily_variation,annualized_daily_variation)
180 | sp500_cor = append(sp500_cor,corr)
181 | sp500_beta = append(sp500_beta,beta)
182 |
183 | }
184 |
185 | # ORGANIZING DATA
186 | drops <- c("Country","Exchange", "Shortname","Longname","Currentprice","Ebitda","Revenuegrowth","Longbusinesssummary", "Fulltimeemployees", "Marketcap")
187 |
188 | cluster_features <- companies[ , !(names(companies) %in% drops)]
189 |
190 | cluster_features$ann_return = sp500_ann_returns
191 | cluster_features$ann_vol = sp500_ann_volatility
192 | cluster_features$ann_sharpe_ratio = sp500_ann_sharpe_ratio
193 | cluster_features$ann_daily_change = sp500_ann_daily_change
194 | cluster_features$ann_daily_variation = sp500_ann_daily_variation
195 | cluster_features$beta = sp500_beta
196 | cluster_features$cor = sp500_cor
197 |
198 | cluster_features <- na.omit(cluster_features)
199 |
200 | Symbols = cluster_features$Symbol
201 | City = cluster_features$City
202 | State = cluster_features$State
203 | Industry = cluster_features$Industry
204 | Sector = cluster_features$Sector
205 |
206 |
207 | drops <- c("Sector", "Industry", "City", "State", "Weight")
208 | cluster_features <- cluster_features[ , !(names(cluster_features) %in% drops)]
209 | row.names(cluster_features) <- cluster_features[,1]
210 |
211 | drops <- c("Symbol")
212 | cluster_features <- cluster_features[ , !(names(cluster_features) %in% drops)]
213 | cluster_features <- na.omit(cluster_features)
214 |
215 | head(cluster_features)
216 |
217 |
218 | ####################################################################
219 | #################### DIMENSIONALITY REDUCTION ######################
220 | ####################################################################
221 |
222 | correlation_matrix = rcorr(as.matrix(df.norm[,names(df.norm)]))
223 | corrplot(correlation_matrix$r, method="circle")
224 | corrplot(correlation_matrix$r, method="number")
225 |
226 | ####################################################################
227 | ########################## CLUSTERING ##############################
228 | ####################################################################
229 |
230 | # prep date frame
231 | set.seed(123)
232 | df.norm <- data.frame(sapply(cluster_features, scale))
233 | row.names(df.norm) <- row.names(cluster_features)
234 |
235 | # DETERMINING OPTIMAL NUMBER OF CLUSTERS USING total within-cluster sum of square
236 | set.seed(123)
237 |
238 | wss <- function(k) {
239 | kmeans(df.norm, k, nstart = 10 )$tot.withinss
240 | }
241 | wss_values <- map_dbl(1:15, wss)
242 | plot(1:15, wss_values,
243 | type="b", pch = 19, frame = FALSE,
244 | xlab="Number of clusters K",
245 | ylab="Total within-clusters sum of squares")
246 |
247 |
248 | # running clustering
249 | kmeans <- kmeans(df.norm, centers = 4, nstart = 20, iter.max = 50)
250 | fviz_cluster(kmeans, data = df.norm,pointsize = 0.5, labelsize = 6,ellipse.alpha=0.1)
251 | table(kmeans$cluster)
252 |
253 |
254 | ####################################################################
255 | ########## SUMMARY STATS / CONCLUSIONS / INTERPRETATION ############
256 | ####################################################################
257 |
258 | # Run summary statistics
259 | survey = cbind(cluster_features, cluster = kmeans$cluster)
260 | cluster.ann_returns <- favstats(ann_return ~ cluster, data=survey); cluster.ann_returns
261 | boxplot(ann_return~cluster,data=survey,
262 | main="Cluster wise Annualized Returns distribution",
263 | xlab="Cluster",
264 | ylab="Annualized Return",
265 | col="steelblue",
266 | border="black")
267 |
268 |
269 | favstats.diet <- favstats(ann_vol ~ cluster, data=survey); favstats.diet
270 | boxplot(ann_vol~cluster,data=survey,
271 | main="Cluster wise Annualized Volatility distribution",
272 | xlab="Cluster",
273 | ylab="Annualized Volatility",
274 | col="steelblue",
275 | border="black")
276 |
277 | favstats.diet <- favstats(ann_sharpe_ratio ~ cluster, data=survey); favstats.diet
278 | boxplot(ann_sharpe_ratio~cluster,data=survey,
279 | main="Cluster wise Annualized Sharpe Ratio distribution",
280 | xlab="Cluster",
281 | ylab="Sharpe Ratio",
282 | col="steelblue",
283 | border="black")
284 |
285 | favstats.diet <- favstats(beta ~ cluster, data=survey); favstats.diet
286 | boxplot(beta~cluster,data=survey,
287 | main="Cluster wise beta value distribution",
288 | xlab="Cluster",
289 | ylab="Beta",
290 | col="steelblue",
291 | border="black")
292 |
293 |
294 | aggdf <- aggregate(cbind(cor,ann_return,ann_vol,ann_sharpe_ratio,beta) ~ cluster, data=survey, mean )
295 | aggdf
296 |
297 |
298 |
299 | ## Plot few feature by clusters
300 | # Plot of Ann Returns vs. Volatility by cluster membership
301 | cluster_features$Cluster = kmeans$cluster
302 | cluster_features$Cluster = as.factor(cluster_features$Cluster)
303 | ggplot(cluster_features, aes(x=ann_return, y=ann_vol, color=Cluster)) + geom_point(size=4) + theme_ipsum() + xlab("Annualized Returns") + ylab("Annualized Volatility") + ggtitle("Cluster wise Annualized Returns VS Annualized Volatility ")
304 |
305 |
306 | ####################################################################
307 | ############ PORFOLIO VALIDATION / BACKTESTING ####################
308 | ####################################################################
309 |
310 | cluster_features$Symbols = Symbols
311 | cluster_features$City = City
312 | cluster_features$State = State
313 | cluster_features$Industry = Industry
314 | cluster_features$Sector = Sector
315 |
316 | nrow(cluster_features)
317 |
318 | SR_sorted_cluster <- cluster_features %>% arrange(desc(ann_sharpe_ratio))
319 | SR_sorted_cluster1 = subset(cluster_features, Cluster == 1) %>% arrange(desc(ann_sharpe_ratio))
320 | SR_sorted_cluster2 = subset(cluster_features, Cluster == 2) %>% arrange(desc(ann_sharpe_ratio))
321 | SR_sorted_cluster3 = subset(cluster_features, Cluster == 3) %>% arrange(desc(ann_sharpe_ratio))
322 | SR_sorted_cluster4 = subset(cluster_features, Cluster == 4) %>% arrange(desc(ann_sharpe_ratio))
323 |
324 | # CONSTRUCTING PORFOLIO USING TOP 5 STOCK BASED ON SHARPE RATIO FROM EACH CLUSTER
325 | Portfolio = rbind(SR_sorted_cluster1[1:5,],SR_sorted_cluster2[1:5,],SR_sorted_cluster3[1:5,],SR_sorted_cluster4[1:5,])
326 | Portfolio_Stocks = Portfolio$Symbols
327 |
328 | # CONSTRUCTING PORFOLIO USING TOP 20 STOCK BASED ON SHARPE RATIO
329 | Portfolio_ClusterX = SR_sorted_cluster[1:20,]
330 | ClusterX_Stocks = Portfolio_ClusterX$Symbols
331 |
332 |
333 | get_stock_validation_data<-function(symbol){
334 | print(paste("Calculaitng metrics and organizing data for:", symbol))
335 | data <- subset(stocks , Symbol == symbol)
336 | rows <- as.integer(nrow(data) * 0.7)
337 | data <- data[2160: nrow(data),]
338 | change(data, Var = 'Adj.Close', NewVar = 'daily_returns', slideBy = -1, type = "proportion")
339 | }
340 |
341 | portfolio_stocks_daily_data = c()
342 | clusterx_stocks_daily_data = c()
343 | index_validation_data = data_frame()
344 |
345 | # for constructed portfolio
346 | for(symbol in Portfolio_Stocks){
347 | # data preparation
348 | data = get_stock_validation_data(symbol)
349 | drops <- c("Open", "High", "Low", "Close", "Adj.Close","Volume","Symbol")
350 | data <- data[ , !(names(data) %in% drops)]
351 | colnames(data) <- c("Date",paste(symbol,"_dailty_change",sep=""))
352 | portfolio_stocks_daily_data[[symbol]] = data
353 | df = merge(data,index,by="Date")
354 | na.omit(df)
355 | index_validation_data = df
356 | }
357 |
358 |
359 | #for cluster X - top 20 stocks in 7 year historical data
360 | for(symbol in ClusterX_Stocks){
361 | # data preparation
362 | data = get_stock_validation_data(symbol)
363 | drops <- c("Open", "High", "Low", "Close", "Adj.Close","Volume","Symbol")
364 | data <- data[ , !(names(data) %in% drops)]
365 | colnames(data) <- c("Date",paste(symbol,"_dailty_change",sep=""))
366 | clusterx_stocks_daily_data[[symbol]] = data
367 | }
368 |
369 | # calculating index daily change
370 | index_validation_data <- change(index_validation_data, Var = 'S.P500', NewVar = 'sp500_daily_returns', slideBy = -1, type = "proportion")
371 | drops <- c("S.P500","Symbol","Volume","daily_change","VTR_dailty_change")
372 | index_validation_data <- index_validation_data[ , !(names(index_validation_data) %in% drops)];index_validation_data
373 | index_validation_data
374 |
375 | # REORGANISING DATA AND BACKTESTING
376 | portfolio_returns = portfolio_stocks_daily_data %>% reduce(full_join, by='Date')
377 | portfolio_returnsx = portfolio_stocks_daily_data %>% reduce(full_join, by='Date')
378 | portfolio_returnsx$Date = NULL
379 | portfolio_returns$weighted_portfolio_returns <- rowMeans(portfolio_returnsx)
380 | head(portfolio_returns)
381 |
382 | # organizing data and performing calculations
383 | clusterx_returns = clusterx_stocks_daily_data %>% reduce(full_join, by='Date')
384 | clusterx_returnsx = clusterx_stocks_daily_data %>% reduce(full_join, by='Date')
385 | clusterx_returnsx$Date = NULL
386 | clusterx_returns$weighted_clusterx_returns <- rowMeans(clusterx_returnsx)
387 | head(clusterx_returns)
388 | merged_data = merge(portfolio_returns,index_validation_data)
389 | merged_clusterx_data = merge(clusterx_returns,index_validation_data)
390 | keep = c("weighted_portfolio_returns","sp500_daily_returns","Date")
391 | merged_data <- merged_data[ , (names(merged_data) %in% keep)];
392 | keep = c("weighted_clusterx_returns","sp500_daily_returns","Date")
393 | merged_clusterx_data <- merged_clusterx_data[ , (names(merged_clusterx_data) %in% keep)];
394 | merged_data <- na.omit(merged_data)
395 | merged_clusterx_data <- na.omit(merged_clusterx_data)
396 | merged_data$portfolio_cumulative_returns <- cumsum(merged_data$weighted_portfolio_returns)
397 | merged_data$sp500_cumulative_return <- cumsum(merged_data$sp500_daily_returns)
398 | merged_clusterx_data$clusterx_cumulative_returns <- cumsum(merged_clusterx_data$weighted_clusterx_returns)
399 | final_cluster_analysis = data_frame()
400 | final_cluster_analysis = merged_data
401 | final_cluster_analysis$clusterx_cumulative_returns = merged_clusterx_data$clusterx_cumulative_returns
402 | tail(final_cluster_analysis,n=50)
403 | str(final_cluster_analysis)
404 | final_cluster_analysis$Date <- as.Date(final_cluster_analysis$Date)
405 |
406 | # PLOTTING performance of portfolio and index in the last 3 years
407 | df <- final_cluster_analysis %>%
408 | select(Date, sp500_cumulative_return,portfolio_cumulative_returns, clusterx_cumulative_returns) %>%
409 | gather(key = "Legend", value = "value", -Date)
410 | head(df)
411 |
412 | ggplot(df, aes(x = Date, y = value)) +
413 | geom_line(aes(color = Legend)) +
414 | scale_color_manual(values = c("orange", "red", "steelblue")) + xlab("Years") + ylab("Cumulative Returns") + ggtitle("K Means Portfolio vs S&P500 performance") + theme_ipsum()
415 |
416 | # Industry types in portfolio
417 | table(Portfolio$Industry)
418 |
419 | # Sector types in portfolio
420 | table(Portfolio$Sector)
421 |
422 | # Stocks in portfolio
423 | Portfolio$Symbols
424 |
425 |
426 |
--------------------------------------------------------------------------------
/Data/sp500_index.csv:
--------------------------------------------------------------------------------
1 | Date,S&P500
2 | 2012-03-29,1403.28
3 | 2012-03-30,1408.47
4 | 2012-04-02,1419.04
5 | 2012-04-03,1413.38
6 | 2012-04-04,1398.96
7 | 2012-04-05,1398.08
8 | 2012-04-09,1382.2
9 | 2012-04-10,1358.59
10 | 2012-04-11,1368.71
11 | 2012-04-12,1387.57
12 | 2012-04-13,1370.26
13 | 2012-04-16,1369.57
14 | 2012-04-17,1390.78
15 | 2012-04-18,1385.14
16 | 2012-04-19,1376.92
17 | 2012-04-20,1378.53
18 | 2012-04-23,1366.94
19 | 2012-04-24,1371.97
20 | 2012-04-25,1390.69
21 | 2012-04-26,1399.98
22 | 2012-04-27,1403.36
23 | 2012-04-30,1397.91
24 | 2012-05-01,1405.82
25 | 2012-05-02,1402.31
26 | 2012-05-03,1391.57
27 | 2012-05-04,1369.1
28 | 2012-05-07,1369.58
29 | 2012-05-08,1363.72
30 | 2012-05-09,1354.58
31 | 2012-05-10,1357.99
32 | 2012-05-11,1353.39
33 | 2012-05-14,1338.35
34 | 2012-05-15,1330.66
35 | 2012-05-16,1324.8
36 | 2012-05-17,1304.86
37 | 2012-05-18,1295.22
38 | 2012-05-21,1315.99
39 | 2012-05-22,1316.63
40 | 2012-05-23,1318.86
41 | 2012-05-24,1320.68
42 | 2012-05-25,1317.82
43 | 2012-05-29,1332.42
44 | 2012-05-30,1313.32
45 | 2012-05-31,1310.33
46 | 2012-06-01,1278.04
47 | 2012-06-04,1278.18
48 | 2012-06-05,1285.5
49 | 2012-06-06,1315.13
50 | 2012-06-07,1314.99
51 | 2012-06-08,1325.66
52 | 2012-06-11,1308.93
53 | 2012-06-12,1324.18
54 | 2012-06-13,1314.88
55 | 2012-06-14,1329.1
56 | 2012-06-15,1342.84
57 | 2012-06-18,1344.78
58 | 2012-06-19,1357.98
59 | 2012-06-20,1355.69
60 | 2012-06-21,1325.51
61 | 2012-06-22,1335.02
62 | 2012-06-25,1313.72
63 | 2012-06-26,1319.99
64 | 2012-06-27,1331.85
65 | 2012-06-28,1329.04
66 | 2012-06-29,1362.16
67 | 2012-07-02,1365.51
68 | 2012-07-03,1374.02
69 | 2012-07-05,1367.58
70 | 2012-07-06,1354.68
71 | 2012-07-09,1352.46
72 | 2012-07-10,1341.47
73 | 2012-07-11,1341.45
74 | 2012-07-12,1334.76
75 | 2012-07-13,1356.78
76 | 2012-07-16,1353.64
77 | 2012-07-17,1363.67
78 | 2012-07-18,1372.78
79 | 2012-07-19,1376.51
80 | 2012-07-20,1362.66
81 | 2012-07-23,1350.52
82 | 2012-07-24,1338.31
83 | 2012-07-25,1337.89
84 | 2012-07-26,1360.02
85 | 2012-07-27,1385.97
86 | 2012-07-30,1385.3
87 | 2012-07-31,1379.32
88 | 2012-08-01,1375.14
89 | 2012-08-02,1365.0
90 | 2012-08-03,1390.99
91 | 2012-08-06,1394.23
92 | 2012-08-07,1401.35
93 | 2012-08-08,1402.22
94 | 2012-08-09,1402.8
95 | 2012-08-10,1405.87
96 | 2012-08-13,1404.11
97 | 2012-08-14,1403.93
98 | 2012-08-15,1405.53
99 | 2012-08-16,1415.51
100 | 2012-08-17,1418.16
101 | 2012-08-20,1418.13
102 | 2012-08-21,1413.17
103 | 2012-08-22,1413.49
104 | 2012-08-23,1402.08
105 | 2012-08-24,1411.13
106 | 2012-08-27,1410.44
107 | 2012-08-28,1409.3
108 | 2012-08-29,1410.49
109 | 2012-08-30,1399.48
110 | 2012-08-31,1406.58
111 | 2012-09-04,1404.94
112 | 2012-09-05,1403.44
113 | 2012-09-06,1432.12
114 | 2012-09-07,1437.92
115 | 2012-09-10,1429.08
116 | 2012-09-11,1433.56
117 | 2012-09-12,1436.56
118 | 2012-09-13,1459.99
119 | 2012-09-14,1465.77
120 | 2012-09-17,1461.19
121 | 2012-09-18,1459.32
122 | 2012-09-19,1461.05
123 | 2012-09-20,1460.26
124 | 2012-09-21,1460.15
125 | 2012-09-24,1456.89
126 | 2012-09-25,1441.59
127 | 2012-09-26,1433.32
128 | 2012-09-27,1447.15
129 | 2012-09-28,1440.67
130 | 2012-10-01,1444.49
131 | 2012-10-02,1445.75
132 | 2012-10-03,1450.99
133 | 2012-10-04,1461.4
134 | 2012-10-05,1460.93
135 | 2012-10-08,1455.88
136 | 2012-10-09,1441.48
137 | 2012-10-10,1432.56
138 | 2012-10-11,1432.84
139 | 2012-10-12,1428.59
140 | 2012-10-15,1440.13
141 | 2012-10-16,1454.92
142 | 2012-10-17,1460.91
143 | 2012-10-18,1457.34
144 | 2012-10-19,1433.19
145 | 2012-10-22,1433.82
146 | 2012-10-23,1413.11
147 | 2012-10-24,1408.75
148 | 2012-10-25,1412.97
149 | 2012-10-26,1411.94
150 | 2012-10-31,1412.16
151 | 2012-11-01,1427.59
152 | 2012-11-02,1414.2
153 | 2012-11-05,1417.26
154 | 2012-11-06,1428.39
155 | 2012-11-07,1394.53
156 | 2012-11-08,1377.51
157 | 2012-11-09,1379.85
158 | 2012-11-12,1380.03
159 | 2012-11-13,1374.53
160 | 2012-11-14,1355.49
161 | 2012-11-15,1353.33
162 | 2012-11-16,1359.88
163 | 2012-11-19,1386.89
164 | 2012-11-20,1387.81
165 | 2012-11-21,1391.03
166 | 2012-11-23,1409.15
167 | 2012-11-26,1406.29
168 | 2012-11-27,1398.94
169 | 2012-11-28,1409.93
170 | 2012-11-29,1415.95
171 | 2012-11-30,1416.18
172 | 2012-12-03,1409.46
173 | 2012-12-04,1407.05
174 | 2012-12-05,1409.28
175 | 2012-12-06,1413.94
176 | 2012-12-07,1418.07
177 | 2012-12-10,1418.55
178 | 2012-12-11,1427.84
179 | 2012-12-12,1428.48
180 | 2012-12-13,1419.45
181 | 2012-12-14,1413.58
182 | 2012-12-17,1430.36
183 | 2012-12-18,1446.79
184 | 2012-12-19,1435.81
185 | 2012-12-20,1443.69
186 | 2012-12-21,1430.15
187 | 2012-12-24,1426.66
188 | 2012-12-26,1419.83
189 | 2012-12-27,1418.1
190 | 2012-12-28,1402.43
191 | 2012-12-31,1426.19
192 | 2013-01-02,1462.42
193 | 2013-01-03,1459.37
194 | 2013-01-04,1466.47
195 | 2013-01-07,1461.89
196 | 2013-01-08,1457.15
197 | 2013-01-09,1461.02
198 | 2013-01-10,1472.12
199 | 2013-01-11,1472.05
200 | 2013-01-14,1470.68
201 | 2013-01-15,1472.34
202 | 2013-01-16,1472.63
203 | 2013-01-17,1480.94
204 | 2013-01-18,1485.98
205 | 2013-01-22,1492.56
206 | 2013-01-23,1494.81
207 | 2013-01-24,1494.82
208 | 2013-01-25,1502.96
209 | 2013-01-28,1500.18
210 | 2013-01-29,1507.84
211 | 2013-01-30,1501.96
212 | 2013-01-31,1498.11
213 | 2013-02-01,1513.17
214 | 2013-02-04,1495.71
215 | 2013-02-05,1511.29
216 | 2013-02-06,1512.12
217 | 2013-02-07,1509.39
218 | 2013-02-08,1517.93
219 | 2013-02-11,1517.01
220 | 2013-02-12,1519.43
221 | 2013-02-13,1520.33
222 | 2013-02-14,1521.38
223 | 2013-02-15,1519.79
224 | 2013-02-19,1530.94
225 | 2013-02-20,1511.95
226 | 2013-02-21,1502.42
227 | 2013-02-22,1515.6
228 | 2013-02-25,1487.85
229 | 2013-02-26,1496.94
230 | 2013-02-27,1515.99
231 | 2013-02-28,1514.68
232 | 2013-03-01,1518.2
233 | 2013-03-04,1525.2
234 | 2013-03-05,1539.79
235 | 2013-03-06,1541.46
236 | 2013-03-07,1544.26
237 | 2013-03-08,1551.18
238 | 2013-03-11,1556.22
239 | 2013-03-12,1552.48
240 | 2013-03-13,1554.52
241 | 2013-03-14,1563.23
242 | 2013-03-15,1560.7
243 | 2013-03-18,1552.1
244 | 2013-03-19,1548.34
245 | 2013-03-20,1558.71
246 | 2013-03-21,1545.8
247 | 2013-03-22,1556.89
248 | 2013-03-25,1551.69
249 | 2013-03-26,1563.77
250 | 2013-03-27,1562.85
251 | 2013-03-28,1569.19
252 | 2013-04-01,1562.17
253 | 2013-04-02,1570.25
254 | 2013-04-03,1553.69
255 | 2013-04-04,1559.98
256 | 2013-04-05,1553.28
257 | 2013-04-08,1563.07
258 | 2013-04-09,1568.61
259 | 2013-04-10,1587.73
260 | 2013-04-11,1593.37
261 | 2013-04-12,1588.85
262 | 2013-04-15,1552.36
263 | 2013-04-16,1574.57
264 | 2013-04-17,1552.01
265 | 2013-04-18,1541.61
266 | 2013-04-19,1555.25
267 | 2013-04-22,1562.5
268 | 2013-04-23,1578.78
269 | 2013-04-24,1578.79
270 | 2013-04-25,1585.16
271 | 2013-04-26,1582.24
272 | 2013-04-29,1593.61
273 | 2013-04-30,1597.57
274 | 2013-05-01,1582.7
275 | 2013-05-02,1597.59
276 | 2013-05-03,1614.42
277 | 2013-05-06,1617.5
278 | 2013-05-07,1625.96
279 | 2013-05-08,1632.69
280 | 2013-05-09,1626.67
281 | 2013-05-10,1633.7
282 | 2013-05-13,1633.77
283 | 2013-05-14,1650.34
284 | 2013-05-15,1658.78
285 | 2013-05-16,1650.47
286 | 2013-05-17,1667.47
287 | 2013-05-20,1666.29
288 | 2013-05-21,1669.16
289 | 2013-05-22,1655.35
290 | 2013-05-23,1650.51
291 | 2013-05-24,1649.6
292 | 2013-05-28,1660.06
293 | 2013-05-29,1648.36
294 | 2013-05-30,1654.41
295 | 2013-05-31,1630.74
296 | 2013-06-03,1640.42
297 | 2013-06-04,1631.38
298 | 2013-06-05,1608.9
299 | 2013-06-06,1622.56
300 | 2013-06-07,1643.38
301 | 2013-06-10,1642.81
302 | 2013-06-11,1626.13
303 | 2013-06-12,1612.52
304 | 2013-06-13,1636.36
305 | 2013-06-14,1626.73
306 | 2013-06-17,1639.04
307 | 2013-06-18,1651.81
308 | 2013-06-19,1628.93
309 | 2013-06-20,1588.19
310 | 2013-06-21,1592.43
311 | 2013-06-24,1573.09
312 | 2013-06-25,1588.03
313 | 2013-06-26,1603.26
314 | 2013-06-27,1613.2
315 | 2013-06-28,1606.28
316 | 2013-07-01,1614.96
317 | 2013-07-02,1614.08
318 | 2013-07-03,1615.41
319 | 2013-07-05,1631.89
320 | 2013-07-08,1640.46
321 | 2013-07-09,1652.32
322 | 2013-07-10,1652.62
323 | 2013-07-11,1675.02
324 | 2013-07-12,1680.19
325 | 2013-07-15,1682.5
326 | 2013-07-16,1676.26
327 | 2013-07-17,1680.91
328 | 2013-07-18,1689.37
329 | 2013-07-19,1692.09
330 | 2013-07-22,1695.53
331 | 2013-07-23,1692.39
332 | 2013-07-24,1685.94
333 | 2013-07-25,1690.25
334 | 2013-07-26,1691.65
335 | 2013-07-29,1685.33
336 | 2013-07-30,1685.96
337 | 2013-07-31,1685.73
338 | 2013-08-01,1706.87
339 | 2013-08-02,1709.67
340 | 2013-08-05,1707.14
341 | 2013-08-06,1697.37
342 | 2013-08-07,1690.91
343 | 2013-08-08,1697.48
344 | 2013-08-09,1691.42
345 | 2013-08-12,1689.47
346 | 2013-08-13,1694.16
347 | 2013-08-14,1685.39
348 | 2013-08-15,1661.32
349 | 2013-08-16,1655.83
350 | 2013-08-19,1646.06
351 | 2013-08-20,1652.35
352 | 2013-08-21,1642.8
353 | 2013-08-22,1656.96
354 | 2013-08-23,1663.5
355 | 2013-08-26,1656.78
356 | 2013-08-27,1630.48
357 | 2013-08-28,1634.96
358 | 2013-08-29,1638.17
359 | 2013-08-30,1632.97
360 | 2013-09-03,1639.77
361 | 2013-09-04,1653.08
362 | 2013-09-05,1655.08
363 | 2013-09-06,1655.17
364 | 2013-09-09,1671.71
365 | 2013-09-10,1683.99
366 | 2013-09-11,1689.13
367 | 2013-09-12,1683.42
368 | 2013-09-13,1687.99
369 | 2013-09-16,1697.6
370 | 2013-09-17,1704.76
371 | 2013-09-18,1725.52
372 | 2013-09-19,1722.34
373 | 2013-09-20,1709.91
374 | 2013-09-23,1701.84
375 | 2013-09-24,1697.42
376 | 2013-09-25,1692.77
377 | 2013-09-26,1698.67
378 | 2013-09-27,1691.75
379 | 2013-09-30,1681.55
380 | 2013-10-01,1695.0
381 | 2013-10-02,1693.87
382 | 2013-10-03,1678.66
383 | 2013-10-04,1690.5
384 | 2013-10-07,1676.12
385 | 2013-10-08,1655.45
386 | 2013-10-09,1656.4
387 | 2013-10-10,1692.56
388 | 2013-10-11,1703.2
389 | 2013-10-14,1710.14
390 | 2013-10-15,1698.06
391 | 2013-10-16,1721.54
392 | 2013-10-17,1733.15
393 | 2013-10-18,1744.5
394 | 2013-10-21,1744.66
395 | 2013-10-22,1754.67
396 | 2013-10-23,1746.38
397 | 2013-10-24,1752.07
398 | 2013-10-25,1759.77
399 | 2013-10-28,1762.11
400 | 2013-10-29,1771.95
401 | 2013-10-30,1763.31
402 | 2013-10-31,1756.54
403 | 2013-11-01,1761.64
404 | 2013-11-04,1767.93
405 | 2013-11-05,1762.97
406 | 2013-11-06,1770.49
407 | 2013-11-07,1747.15
408 | 2013-11-08,1770.61
409 | 2013-11-11,1771.89
410 | 2013-11-12,1767.69
411 | 2013-11-13,1782.0
412 | 2013-11-14,1790.62
413 | 2013-11-15,1798.18
414 | 2013-11-18,1791.53
415 | 2013-11-19,1787.87
416 | 2013-11-20,1781.37
417 | 2013-11-21,1795.85
418 | 2013-11-22,1804.76
419 | 2013-11-25,1802.48
420 | 2013-11-26,1802.75
421 | 2013-11-27,1807.23
422 | 2013-11-29,1805.81
423 | 2013-12-02,1800.9
424 | 2013-12-03,1795.15
425 | 2013-12-04,1792.81
426 | 2013-12-05,1785.03
427 | 2013-12-06,1805.09
428 | 2013-12-09,1808.37
429 | 2013-12-10,1802.62
430 | 2013-12-11,1782.22
431 | 2013-12-12,1775.5
432 | 2013-12-13,1775.32
433 | 2013-12-16,1786.54
434 | 2013-12-17,1781.0
435 | 2013-12-18,1810.65
436 | 2013-12-19,1809.6
437 | 2013-12-20,1818.32
438 | 2013-12-23,1827.99
439 | 2013-12-24,1833.32
440 | 2013-12-26,1842.02
441 | 2013-12-27,1841.4
442 | 2013-12-30,1841.07
443 | 2013-12-31,1848.36
444 | 2014-01-02,1831.98
445 | 2014-01-03,1831.37
446 | 2014-01-06,1826.77
447 | 2014-01-07,1837.88
448 | 2014-01-08,1837.49
449 | 2014-01-09,1838.13
450 | 2014-01-10,1842.37
451 | 2014-01-13,1819.2
452 | 2014-01-14,1838.88
453 | 2014-01-15,1848.38
454 | 2014-01-16,1845.89
455 | 2014-01-17,1838.7
456 | 2014-01-21,1843.8
457 | 2014-01-22,1844.86
458 | 2014-01-23,1828.46
459 | 2014-01-24,1790.29
460 | 2014-01-27,1781.56
461 | 2014-01-28,1792.5
462 | 2014-01-29,1774.2
463 | 2014-01-30,1794.19
464 | 2014-01-31,1782.59
465 | 2014-02-03,1741.89
466 | 2014-02-04,1755.2
467 | 2014-02-05,1751.64
468 | 2014-02-06,1773.43
469 | 2014-02-07,1797.02
470 | 2014-02-10,1799.84
471 | 2014-02-11,1819.75
472 | 2014-02-12,1819.26
473 | 2014-02-13,1829.83
474 | 2014-02-14,1838.63
475 | 2014-02-18,1840.76
476 | 2014-02-19,1828.75
477 | 2014-02-20,1839.78
478 | 2014-02-21,1836.25
479 | 2014-02-24,1847.61
480 | 2014-02-25,1845.12
481 | 2014-02-26,1845.16
482 | 2014-02-27,1854.29
483 | 2014-02-28,1859.45
484 | 2014-03-03,1845.73
485 | 2014-03-04,1873.91
486 | 2014-03-05,1873.81
487 | 2014-03-06,1877.03
488 | 2014-03-07,1878.04
489 | 2014-03-10,1877.17
490 | 2014-03-11,1867.63
491 | 2014-03-12,1868.2
492 | 2014-03-13,1846.34
493 | 2014-03-14,1841.13
494 | 2014-03-17,1858.83
495 | 2014-03-18,1872.25
496 | 2014-03-19,1860.77
497 | 2014-03-20,1872.01
498 | 2014-03-21,1866.52
499 | 2014-03-24,1857.44
500 | 2014-03-25,1865.62
501 | 2014-03-26,1852.56
502 | 2014-03-27,1849.04
503 | 2014-03-28,1857.62
504 | 2014-03-31,1872.34
505 | 2014-04-01,1885.52
506 | 2014-04-02,1890.9
507 | 2014-04-03,1888.77
508 | 2014-04-04,1865.09
509 | 2014-04-07,1845.04
510 | 2014-04-08,1851.96
511 | 2014-04-09,1872.18
512 | 2014-04-10,1833.08
513 | 2014-04-11,1815.69
514 | 2014-04-14,1830.61
515 | 2014-04-15,1842.98
516 | 2014-04-16,1862.31
517 | 2014-04-17,1864.85
518 | 2014-04-21,1871.89
519 | 2014-04-22,1879.55
520 | 2014-04-23,1875.39
521 | 2014-04-24,1878.61
522 | 2014-04-25,1863.4
523 | 2014-04-28,1869.43
524 | 2014-04-29,1878.33
525 | 2014-04-30,1883.95
526 | 2014-05-01,1883.68
527 | 2014-05-02,1881.14
528 | 2014-05-05,1884.66
529 | 2014-05-06,1867.72
530 | 2014-05-07,1878.21
531 | 2014-05-08,1875.63
532 | 2014-05-09,1878.48
533 | 2014-05-12,1896.65
534 | 2014-05-13,1897.45
535 | 2014-05-14,1888.53
536 | 2014-05-15,1870.85
537 | 2014-05-16,1877.86
538 | 2014-05-19,1885.08
539 | 2014-05-20,1872.83
540 | 2014-05-21,1888.03
541 | 2014-05-22,1892.49
542 | 2014-05-23,1900.53
543 | 2014-05-27,1911.91
544 | 2014-05-28,1909.78
545 | 2014-05-29,1920.03
546 | 2014-05-30,1923.57
547 | 2014-06-02,1924.97
548 | 2014-06-03,1924.24
549 | 2014-06-04,1927.88
550 | 2014-06-05,1940.46
551 | 2014-06-06,1949.44
552 | 2014-06-09,1951.27
553 | 2014-06-10,1950.79
554 | 2014-06-11,1943.89
555 | 2014-06-12,1930.11
556 | 2014-06-13,1936.16
557 | 2014-06-16,1937.78
558 | 2014-06-17,1941.99
559 | 2014-06-18,1956.98
560 | 2014-06-19,1959.48
561 | 2014-06-20,1962.87
562 | 2014-06-23,1962.61
563 | 2014-06-24,1949.98
564 | 2014-06-25,1959.53
565 | 2014-06-26,1957.22
566 | 2014-06-27,1960.96
567 | 2014-06-30,1960.23
568 | 2014-07-01,1973.32
569 | 2014-07-02,1974.62
570 | 2014-07-03,1985.44
571 | 2014-07-07,1977.65
572 | 2014-07-08,1963.71
573 | 2014-07-09,1972.83
574 | 2014-07-10,1964.68
575 | 2014-07-11,1967.57
576 | 2014-07-14,1977.1
577 | 2014-07-15,1973.28
578 | 2014-07-16,1981.57
579 | 2014-07-17,1958.12
580 | 2014-07-18,1978.22
581 | 2014-07-21,1973.63
582 | 2014-07-22,1983.53
583 | 2014-07-23,1987.01
584 | 2014-07-24,1987.98
585 | 2014-07-25,1978.34
586 | 2014-07-28,1978.91
587 | 2014-07-29,1969.95
588 | 2014-07-30,1970.07
589 | 2014-07-31,1930.67
590 | 2014-08-01,1925.15
591 | 2014-08-04,1938.99
592 | 2014-08-05,1920.21
593 | 2014-08-06,1920.24
594 | 2014-08-07,1909.57
595 | 2014-08-08,1931.59
596 | 2014-08-11,1936.92
597 | 2014-08-12,1933.75
598 | 2014-08-13,1946.72
599 | 2014-08-14,1955.18
600 | 2014-08-15,1955.06
601 | 2014-08-18,1971.74
602 | 2014-08-19,1981.6
603 | 2014-08-20,1986.51
604 | 2014-08-21,1992.37
605 | 2014-08-22,1988.4
606 | 2014-08-25,1997.92
607 | 2014-08-26,2000.02
608 | 2014-08-27,2000.12
609 | 2014-08-28,1996.74
610 | 2014-08-29,2003.37
611 | 2014-09-02,2002.28
612 | 2014-09-03,2000.72
613 | 2014-09-04,1997.65
614 | 2014-09-05,2007.71
615 | 2014-09-08,2001.54
616 | 2014-09-09,1988.44
617 | 2014-09-10,1995.69
618 | 2014-09-11,1997.45
619 | 2014-09-12,1985.54
620 | 2014-09-15,1984.13
621 | 2014-09-16,1998.98
622 | 2014-09-17,2001.57
623 | 2014-09-18,2011.36
624 | 2014-09-19,2010.4
625 | 2014-09-22,1994.29
626 | 2014-09-23,1982.77
627 | 2014-09-24,1998.3
628 | 2014-09-25,1965.99
629 | 2014-09-26,1982.85
630 | 2014-09-29,1977.8
631 | 2014-09-30,1972.29
632 | 2014-10-01,1946.16
633 | 2014-10-02,1946.17
634 | 2014-10-03,1967.9
635 | 2014-10-06,1964.82
636 | 2014-10-07,1935.1
637 | 2014-10-08,1968.89
638 | 2014-10-09,1928.21
639 | 2014-10-10,1906.13
640 | 2014-10-13,1874.74
641 | 2014-10-14,1877.7
642 | 2014-10-15,1862.49
643 | 2014-10-16,1862.76
644 | 2014-10-17,1886.76
645 | 2014-10-20,1904.01
646 | 2014-10-21,1941.28
647 | 2014-10-22,1927.11
648 | 2014-10-23,1950.82
649 | 2014-10-24,1964.58
650 | 2014-10-27,1961.63
651 | 2014-10-28,1985.05
652 | 2014-10-29,1982.3
653 | 2014-10-30,1994.65
654 | 2014-10-31,2018.05
655 | 2014-11-03,2017.81
656 | 2014-11-04,2012.1
657 | 2014-11-05,2023.57
658 | 2014-11-06,2031.21
659 | 2014-11-07,2031.92
660 | 2014-11-10,2038.26
661 | 2014-11-11,2039.68
662 | 2014-11-12,2038.25
663 | 2014-11-13,2039.33
664 | 2014-11-14,2039.82
665 | 2014-11-17,2041.32
666 | 2014-11-18,2051.8
667 | 2014-11-19,2048.72
668 | 2014-11-20,2052.75
669 | 2014-11-21,2063.5
670 | 2014-11-24,2069.41
671 | 2014-11-25,2067.03
672 | 2014-11-26,2072.83
673 | 2014-11-28,2067.56
674 | 2014-12-01,2053.44
675 | 2014-12-02,2066.55
676 | 2014-12-03,2074.33
677 | 2014-12-04,2071.92
678 | 2014-12-05,2075.37
679 | 2014-12-08,2060.31
680 | 2014-12-09,2059.82
681 | 2014-12-10,2026.14
682 | 2014-12-11,2035.33
683 | 2014-12-12,2002.33
684 | 2014-12-15,1989.63
685 | 2014-12-16,1972.74
686 | 2014-12-17,2012.89
687 | 2014-12-18,2061.23
688 | 2014-12-19,2070.65
689 | 2014-12-22,2078.54
690 | 2014-12-23,2082.17
691 | 2014-12-24,2081.88
692 | 2014-12-26,2088.77
693 | 2014-12-29,2090.57
694 | 2014-12-30,2080.35
695 | 2014-12-31,2058.9
696 | 2015-01-02,2058.2
697 | 2015-01-05,2020.58
698 | 2015-01-06,2002.61
699 | 2015-01-07,2025.9
700 | 2015-01-08,2062.14
701 | 2015-01-09,2044.81
702 | 2015-01-12,2028.26
703 | 2015-01-13,2023.03
704 | 2015-01-14,2011.27
705 | 2015-01-15,1992.67
706 | 2015-01-16,2019.42
707 | 2015-01-20,2022.55
708 | 2015-01-21,2032.12
709 | 2015-01-22,2063.15
710 | 2015-01-23,2051.82
711 | 2015-01-26,2057.09
712 | 2015-01-27,2029.55
713 | 2015-01-28,2002.16
714 | 2015-01-29,2021.25
715 | 2015-01-30,1994.99
716 | 2015-02-02,2020.85
717 | 2015-02-03,2050.03
718 | 2015-02-04,2041.51
719 | 2015-02-05,2062.52
720 | 2015-02-06,2055.47
721 | 2015-02-09,2046.74
722 | 2015-02-10,2068.59
723 | 2015-02-11,2068.53
724 | 2015-02-12,2088.48
725 | 2015-02-13,2096.99
726 | 2015-02-17,2100.34
727 | 2015-02-18,2099.68
728 | 2015-02-19,2097.45
729 | 2015-02-20,2110.3
730 | 2015-02-23,2109.66
731 | 2015-02-24,2115.48
732 | 2015-02-25,2113.86
733 | 2015-02-26,2110.74
734 | 2015-02-27,2104.5
735 | 2015-03-02,2117.39
736 | 2015-03-03,2107.78
737 | 2015-03-04,2098.53
738 | 2015-03-05,2101.04
739 | 2015-03-06,2071.26
740 | 2015-03-09,2079.43
741 | 2015-03-10,2044.16
742 | 2015-03-11,2040.24
743 | 2015-03-12,2065.95
744 | 2015-03-13,2053.4
745 | 2015-03-16,2081.19
746 | 2015-03-17,2074.28
747 | 2015-03-18,2099.5
748 | 2015-03-19,2089.27
749 | 2015-03-20,2108.1
750 | 2015-03-23,2104.42
751 | 2015-03-24,2091.5
752 | 2015-03-25,2061.05
753 | 2015-03-26,2056.15
754 | 2015-03-27,2061.02
755 | 2015-03-30,2086.24
756 | 2015-03-31,2067.89
757 | 2015-04-01,2059.69
758 | 2015-04-02,2066.96
759 | 2015-04-06,2080.62
760 | 2015-04-07,2076.33
761 | 2015-04-08,2081.9
762 | 2015-04-09,2091.18
763 | 2015-04-10,2102.06
764 | 2015-04-13,2092.43
765 | 2015-04-14,2095.84
766 | 2015-04-15,2106.63
767 | 2015-04-16,2104.99
768 | 2015-04-17,2081.18
769 | 2015-04-20,2100.4
770 | 2015-04-21,2097.29
771 | 2015-04-22,2107.96
772 | 2015-04-23,2112.93
773 | 2015-04-24,2117.69
774 | 2015-04-27,2108.92
775 | 2015-04-28,2114.76
776 | 2015-04-29,2106.85
777 | 2015-04-30,2085.51
778 | 2015-05-01,2108.29
779 | 2015-05-04,2114.49
780 | 2015-05-05,2089.46
781 | 2015-05-06,2080.15
782 | 2015-05-07,2088.0
783 | 2015-05-08,2116.1
784 | 2015-05-11,2105.33
785 | 2015-05-12,2099.12
786 | 2015-05-13,2098.48
787 | 2015-05-14,2121.1
788 | 2015-05-15,2122.73
789 | 2015-05-18,2129.2
790 | 2015-05-19,2127.83
791 | 2015-05-20,2125.85
792 | 2015-05-21,2130.82
793 | 2015-05-22,2126.06
794 | 2015-05-26,2104.2
795 | 2015-05-27,2123.48
796 | 2015-05-28,2120.79
797 | 2015-05-29,2107.39
798 | 2015-06-01,2111.73
799 | 2015-06-02,2109.6
800 | 2015-06-03,2114.07
801 | 2015-06-04,2095.84
802 | 2015-06-05,2092.83
803 | 2015-06-08,2079.28
804 | 2015-06-09,2080.15
805 | 2015-06-10,2105.2
806 | 2015-06-11,2108.86
807 | 2015-06-12,2094.11
808 | 2015-06-15,2084.43
809 | 2015-06-16,2096.29
810 | 2015-06-17,2100.44
811 | 2015-06-18,2121.24
812 | 2015-06-19,2109.99
813 | 2015-06-22,2122.85
814 | 2015-06-23,2124.2
815 | 2015-06-24,2108.58
816 | 2015-06-25,2102.31
817 | 2015-06-26,2101.49
818 | 2015-06-29,2057.64
819 | 2015-06-30,2063.11
820 | 2015-07-01,2077.42
821 | 2015-07-02,2076.78
822 | 2015-07-06,2068.76
823 | 2015-07-07,2081.34
824 | 2015-07-08,2046.68
825 | 2015-07-09,2051.31
826 | 2015-07-10,2076.62
827 | 2015-07-13,2099.6
828 | 2015-07-14,2108.95
829 | 2015-07-15,2107.4
830 | 2015-07-16,2124.29
831 | 2015-07-17,2126.64
832 | 2015-07-20,2128.28
833 | 2015-07-21,2119.21
834 | 2015-07-22,2114.15
835 | 2015-07-23,2102.15
836 | 2015-07-24,2079.65
837 | 2015-07-27,2067.64
838 | 2015-07-28,2093.25
839 | 2015-07-29,2108.57
840 | 2015-07-30,2108.63
841 | 2015-07-31,2103.84
842 | 2015-08-03,2098.04
843 | 2015-08-04,2093.32
844 | 2015-08-05,2099.84
845 | 2015-08-06,2083.56
846 | 2015-08-07,2077.57
847 | 2015-08-10,2104.18
848 | 2015-08-11,2084.07
849 | 2015-08-12,2086.05
850 | 2015-08-13,2083.39
851 | 2015-08-14,2091.54
852 | 2015-08-17,2102.44
853 | 2015-08-18,2096.92
854 | 2015-08-19,2079.61
855 | 2015-08-20,2035.73
856 | 2015-08-21,1970.89
857 | 2015-08-24,1893.21
858 | 2015-08-25,1867.61
859 | 2015-08-26,1940.51
860 | 2015-08-27,1987.66
861 | 2015-08-28,1988.87
862 | 2015-08-31,1972.18
863 | 2015-09-01,1913.85
864 | 2015-09-02,1948.86
865 | 2015-09-03,1951.13
866 | 2015-09-04,1921.22
867 | 2015-09-08,1969.41
868 | 2015-09-09,1942.04
869 | 2015-09-10,1952.29
870 | 2015-09-11,1961.05
871 | 2015-09-14,1953.03
872 | 2015-09-15,1978.09
873 | 2015-09-16,1995.31
874 | 2015-09-17,1990.2
875 | 2015-09-18,1958.03
876 | 2015-09-21,1966.97
877 | 2015-09-22,1942.74
878 | 2015-09-23,1938.76
879 | 2015-09-24,1932.24
880 | 2015-09-25,1931.34
881 | 2015-09-28,1881.77
882 | 2015-09-29,1884.09
883 | 2015-09-30,1920.03
884 | 2015-10-01,1923.82
885 | 2015-10-02,1951.36
886 | 2015-10-05,1987.05
887 | 2015-10-06,1979.92
888 | 2015-10-07,1995.83
889 | 2015-10-08,2013.43
890 | 2015-10-09,2014.89
891 | 2015-10-12,2017.46
892 | 2015-10-13,2003.69
893 | 2015-10-14,1994.24
894 | 2015-10-15,2023.86
895 | 2015-10-16,2033.11
896 | 2015-10-19,2033.66
897 | 2015-10-20,2030.77
898 | 2015-10-21,2018.94
899 | 2015-10-22,2052.51
900 | 2015-10-23,2075.15
901 | 2015-10-26,2071.18
902 | 2015-10-27,2065.89
903 | 2015-10-28,2090.35
904 | 2015-10-29,2089.41
905 | 2015-10-30,2079.36
906 | 2015-11-02,2104.05
907 | 2015-11-03,2109.79
908 | 2015-11-04,2102.31
909 | 2015-11-05,2099.93
910 | 2015-11-06,2099.2
911 | 2015-11-09,2078.58
912 | 2015-11-10,2081.72
913 | 2015-11-11,2075.0
914 | 2015-11-12,2045.97
915 | 2015-11-13,2023.04
916 | 2015-11-16,2053.19
917 | 2015-11-17,2050.44
918 | 2015-11-18,2083.58
919 | 2015-11-19,2081.24
920 | 2015-11-20,2089.17
921 | 2015-11-23,2086.59
922 | 2015-11-24,2089.14
923 | 2015-11-25,2088.87
924 | 2015-11-27,2090.11
925 | 2015-11-30,2080.41
926 | 2015-12-01,2102.63
927 | 2015-12-02,2079.51
928 | 2015-12-03,2049.62
929 | 2015-12-04,2091.69
930 | 2015-12-07,2077.07
931 | 2015-12-08,2063.59
932 | 2015-12-09,2047.62
933 | 2015-12-10,2052.23
934 | 2015-12-11,2012.37
935 | 2015-12-14,2021.94
936 | 2015-12-15,2043.41
937 | 2015-12-16,2073.07
938 | 2015-12-17,2041.89
939 | 2015-12-18,2005.55
940 | 2015-12-21,2021.15
941 | 2015-12-22,2038.97
942 | 2015-12-23,2064.29
943 | 2015-12-24,2060.99
944 | 2015-12-28,2056.5
945 | 2015-12-29,2078.36
946 | 2015-12-30,2063.36
947 | 2015-12-31,2043.94
948 | 2016-01-04,2012.66
949 | 2016-01-05,2016.71
950 | 2016-01-06,1990.26
951 | 2016-01-07,1943.09
952 | 2016-01-08,1922.03
953 | 2016-01-11,1923.67
954 | 2016-01-12,1938.68
955 | 2016-01-13,1890.28
956 | 2016-01-14,1921.84
957 | 2016-01-15,1880.33
958 | 2016-01-19,1881.33
959 | 2016-01-20,1859.33
960 | 2016-01-21,1868.99
961 | 2016-01-22,1906.9
962 | 2016-01-25,1877.08
963 | 2016-01-26,1903.63
964 | 2016-01-27,1882.95
965 | 2016-01-28,1893.36
966 | 2016-01-29,1940.24
967 | 2016-02-01,1939.38
968 | 2016-02-02,1903.03
969 | 2016-02-03,1912.53
970 | 2016-02-04,1915.45
971 | 2016-02-05,1880.05
972 | 2016-02-08,1853.44
973 | 2016-02-09,1852.21
974 | 2016-02-10,1851.86
975 | 2016-02-11,1829.08
976 | 2016-02-12,1864.78
977 | 2016-02-16,1895.58
978 | 2016-02-17,1926.82
979 | 2016-02-18,1917.83
980 | 2016-02-19,1917.78
981 | 2016-02-22,1945.5
982 | 2016-02-23,1921.27
983 | 2016-02-24,1929.8
984 | 2016-02-25,1951.7
985 | 2016-02-26,1948.05
986 | 2016-02-29,1932.23
987 | 2016-03-01,1978.35
988 | 2016-03-02,1986.45
989 | 2016-03-03,1993.4
990 | 2016-03-04,1999.99
991 | 2016-03-07,2001.76
992 | 2016-03-08,1979.26
993 | 2016-03-09,1989.26
994 | 2016-03-10,1989.57
995 | 2016-03-11,2022.19
996 | 2016-03-14,2019.64
997 | 2016-03-15,2015.93
998 | 2016-03-16,2027.22
999 | 2016-03-17,2040.59
1000 | 2016-03-18,2049.58
1001 | 2016-03-21,2051.6
1002 | 2016-03-22,2049.8
1003 | 2016-03-23,2036.71
1004 | 2016-03-24,2035.94
1005 | 2016-03-28,2037.05
1006 | 2016-03-29,2055.01
1007 | 2016-03-30,2063.95
1008 | 2016-03-31,2059.74
1009 | 2016-04-01,2072.78
1010 | 2016-04-04,2066.13
1011 | 2016-04-05,2045.17
1012 | 2016-04-06,2066.66
1013 | 2016-04-07,2041.91
1014 | 2016-04-08,2047.6
1015 | 2016-04-11,2041.99
1016 | 2016-04-12,2061.72
1017 | 2016-04-13,2082.42
1018 | 2016-04-14,2082.78
1019 | 2016-04-15,2080.73
1020 | 2016-04-18,2094.34
1021 | 2016-04-19,2100.8
1022 | 2016-04-20,2102.4
1023 | 2016-04-21,2091.48
1024 | 2016-04-22,2091.58
1025 | 2016-04-25,2087.79
1026 | 2016-04-26,2091.7
1027 | 2016-04-27,2095.15
1028 | 2016-04-28,2075.81
1029 | 2016-04-29,2065.3
1030 | 2016-05-02,2081.43
1031 | 2016-05-03,2063.37
1032 | 2016-05-04,2051.12
1033 | 2016-05-05,2050.63
1034 | 2016-05-06,2057.14
1035 | 2016-05-09,2058.69
1036 | 2016-05-10,2084.39
1037 | 2016-05-11,2064.46
1038 | 2016-05-12,2064.11
1039 | 2016-05-13,2046.61
1040 | 2016-05-16,2066.66
1041 | 2016-05-17,2047.21
1042 | 2016-05-18,2047.63
1043 | 2016-05-19,2040.04
1044 | 2016-05-20,2052.32
1045 | 2016-05-23,2048.04
1046 | 2016-05-24,2076.06
1047 | 2016-05-25,2090.54
1048 | 2016-05-26,2090.1
1049 | 2016-05-27,2099.06
1050 | 2016-05-31,2096.96
1051 | 2016-06-01,2099.33
1052 | 2016-06-02,2105.26
1053 | 2016-06-03,2099.13
1054 | 2016-06-06,2109.41
1055 | 2016-06-07,2112.13
1056 | 2016-06-08,2119.12
1057 | 2016-06-09,2115.48
1058 | 2016-06-10,2096.07
1059 | 2016-06-13,2079.06
1060 | 2016-06-14,2075.32
1061 | 2016-06-15,2071.5
1062 | 2016-06-16,2077.99
1063 | 2016-06-17,2071.22
1064 | 2016-06-20,2083.25
1065 | 2016-06-21,2088.9
1066 | 2016-06-22,2085.45
1067 | 2016-06-23,2113.32
1068 | 2016-06-24,2037.41
1069 | 2016-06-27,2000.54
1070 | 2016-06-28,2036.09
1071 | 2016-06-29,2070.77
1072 | 2016-06-30,2098.86
1073 | 2016-07-01,2102.95
1074 | 2016-07-05,2088.55
1075 | 2016-07-06,2099.73
1076 | 2016-07-07,2097.9
1077 | 2016-07-08,2129.9
1078 | 2016-07-11,2137.16
1079 | 2016-07-12,2152.14
1080 | 2016-07-13,2152.43
1081 | 2016-07-14,2163.75
1082 | 2016-07-15,2161.74
1083 | 2016-07-18,2166.89
1084 | 2016-07-19,2163.78
1085 | 2016-07-20,2173.02
1086 | 2016-07-21,2165.17
1087 | 2016-07-22,2175.03
1088 | 2016-07-25,2168.48
1089 | 2016-07-26,2169.18
1090 | 2016-07-27,2166.58
1091 | 2016-07-28,2170.06
1092 | 2016-07-29,2173.6
1093 | 2016-08-01,2170.84
1094 | 2016-08-02,2157.03
1095 | 2016-08-03,2163.79
1096 | 2016-08-04,2164.25
1097 | 2016-08-05,2182.87
1098 | 2016-08-08,2180.89
1099 | 2016-08-09,2181.74
1100 | 2016-08-10,2175.49
1101 | 2016-08-11,2185.79
1102 | 2016-08-12,2184.05
1103 | 2016-08-15,2190.15
1104 | 2016-08-16,2178.15
1105 | 2016-08-17,2182.22
1106 | 2016-08-18,2187.02
1107 | 2016-08-19,2183.87
1108 | 2016-08-22,2182.64
1109 | 2016-08-23,2186.9
1110 | 2016-08-24,2175.44
1111 | 2016-08-25,2172.47
1112 | 2016-08-26,2169.04
1113 | 2016-08-29,2180.38
1114 | 2016-08-30,2176.12
1115 | 2016-08-31,2170.95
1116 | 2016-09-01,2170.86
1117 | 2016-09-02,2179.98
1118 | 2016-09-06,2186.48
1119 | 2016-09-07,2186.16
1120 | 2016-09-08,2181.3
1121 | 2016-09-09,2127.81
1122 | 2016-09-12,2159.04
1123 | 2016-09-13,2127.02
1124 | 2016-09-14,2125.77
1125 | 2016-09-15,2147.26
1126 | 2016-09-16,2139.16
1127 | 2016-09-19,2139.12
1128 | 2016-09-20,2139.76
1129 | 2016-09-21,2163.12
1130 | 2016-09-22,2177.18
1131 | 2016-09-23,2164.69
1132 | 2016-09-26,2146.1
1133 | 2016-09-27,2159.93
1134 | 2016-09-28,2171.37
1135 | 2016-09-29,2151.13
1136 | 2016-09-30,2168.27
1137 | 2016-10-03,2161.2
1138 | 2016-10-04,2150.49
1139 | 2016-10-05,2159.73
1140 | 2016-10-06,2160.77
1141 | 2016-10-07,2153.74
1142 | 2016-10-10,2163.66
1143 | 2016-10-11,2136.73
1144 | 2016-10-12,2139.18
1145 | 2016-10-13,2132.55
1146 | 2016-10-14,2132.98
1147 | 2016-10-17,2126.5
1148 | 2016-10-18,2139.6
1149 | 2016-10-19,2144.29
1150 | 2016-10-20,2141.34
1151 | 2016-10-21,2141.16
1152 | 2016-10-24,2151.33
1153 | 2016-10-25,2143.16
1154 | 2016-10-26,2139.43
1155 | 2016-10-27,2133.04
1156 | 2016-10-28,2126.41
1157 | 2016-10-31,2126.15
1158 | 2016-11-01,2111.72
1159 | 2016-11-02,2097.94
1160 | 2016-11-03,2088.66
1161 | 2016-11-04,2085.18
1162 | 2016-11-07,2131.52
1163 | 2016-11-08,2139.56
1164 | 2016-11-09,2163.26
1165 | 2016-11-10,2167.48
1166 | 2016-11-11,2164.45
1167 | 2016-11-14,2164.2
1168 | 2016-11-15,2180.39
1169 | 2016-11-16,2176.94
1170 | 2016-11-17,2187.12
1171 | 2016-11-18,2181.9
1172 | 2016-11-21,2198.18
1173 | 2016-11-22,2202.94
1174 | 2016-11-23,2204.72
1175 | 2016-11-25,2213.35
1176 | 2016-11-28,2201.72
1177 | 2016-11-29,2204.66
1178 | 2016-11-30,2198.81
1179 | 2016-12-01,2191.08
1180 | 2016-12-02,2191.95
1181 | 2016-12-05,2204.71
1182 | 2016-12-06,2212.23
1183 | 2016-12-07,2241.35
1184 | 2016-12-08,2246.19
1185 | 2016-12-09,2259.53
1186 | 2016-12-12,2256.96
1187 | 2016-12-13,2271.72
1188 | 2016-12-14,2253.28
1189 | 2016-12-15,2262.03
1190 | 2016-12-16,2258.07
1191 | 2016-12-19,2262.53
1192 | 2016-12-20,2270.76
1193 | 2016-12-21,2265.18
1194 | 2016-12-22,2260.96
1195 | 2016-12-23,2263.79
1196 | 2016-12-27,2268.88
1197 | 2016-12-28,2249.92
1198 | 2016-12-29,2249.26
1199 | 2016-12-30,2238.83
1200 | 2017-01-03,2257.83
1201 | 2017-01-04,2270.75
1202 | 2017-01-05,2269.0
1203 | 2017-01-06,2276.98
1204 | 2017-01-09,2268.9
1205 | 2017-01-10,2268.9
1206 | 2017-01-11,2275.32
1207 | 2017-01-12,2270.44
1208 | 2017-01-13,2274.64
1209 | 2017-01-17,2267.89
1210 | 2017-01-18,2271.89
1211 | 2017-01-19,2263.69
1212 | 2017-01-20,2271.31
1213 | 2017-01-23,2265.2
1214 | 2017-01-24,2280.07
1215 | 2017-01-25,2298.37
1216 | 2017-01-26,2296.68
1217 | 2017-01-27,2294.69
1218 | 2017-01-30,2280.9
1219 | 2017-01-31,2278.87
1220 | 2017-02-01,2279.55
1221 | 2017-02-02,2280.85
1222 | 2017-02-03,2297.42
1223 | 2017-02-06,2292.56
1224 | 2017-02-07,2293.08
1225 | 2017-02-08,2294.67
1226 | 2017-02-09,2307.87
1227 | 2017-02-10,2316.1
1228 | 2017-02-13,2328.25
1229 | 2017-02-14,2337.58
1230 | 2017-02-15,2349.25
1231 | 2017-02-16,2347.22
1232 | 2017-02-17,2351.16
1233 | 2017-02-21,2365.38
1234 | 2017-02-22,2362.82
1235 | 2017-02-23,2363.81
1236 | 2017-02-24,2367.34
1237 | 2017-02-27,2369.75
1238 | 2017-02-28,2363.64
1239 | 2017-03-01,2395.96
1240 | 2017-03-02,2381.92
1241 | 2017-03-03,2383.12
1242 | 2017-03-06,2375.31
1243 | 2017-03-07,2368.39
1244 | 2017-03-08,2362.98
1245 | 2017-03-09,2364.87
1246 | 2017-03-10,2372.6
1247 | 2017-03-13,2373.47
1248 | 2017-03-14,2365.45
1249 | 2017-03-15,2385.26
1250 | 2017-03-16,2381.38
1251 | 2017-03-17,2378.25
1252 | 2017-03-20,2373.47
1253 | 2017-03-21,2344.02
1254 | 2017-03-22,2348.45
1255 | 2017-03-23,2345.96
1256 | 2017-03-24,2343.98
1257 | 2017-03-27,2341.59
1258 | 2017-03-28,2358.57
1259 | 2017-03-29,2361.13
1260 | 2017-03-30,2368.06
1261 | 2017-03-31,2362.72
1262 | 2017-04-03,2358.84
1263 | 2017-04-04,2360.16
1264 | 2017-04-05,2352.95
1265 | 2017-04-06,2357.49
1266 | 2017-04-07,2355.54
1267 | 2017-04-10,2357.16
1268 | 2017-04-11,2353.78
1269 | 2017-04-12,2344.93
1270 | 2017-04-13,2328.95
1271 | 2017-04-17,2349.01
1272 | 2017-04-18,2342.19
1273 | 2017-04-19,2338.17
1274 | 2017-04-20,2355.84
1275 | 2017-04-21,2348.69
1276 | 2017-04-24,2374.15
1277 | 2017-04-25,2388.61
1278 | 2017-04-26,2387.45
1279 | 2017-04-27,2388.77
1280 | 2017-04-28,2384.2
1281 | 2017-05-01,2388.33
1282 | 2017-05-02,2391.17
1283 | 2017-05-03,2388.13
1284 | 2017-05-04,2389.52
1285 | 2017-05-05,2399.29
1286 | 2017-05-08,2399.38
1287 | 2017-05-09,2396.92
1288 | 2017-05-10,2399.63
1289 | 2017-05-11,2394.44
1290 | 2017-05-12,2390.9
1291 | 2017-05-15,2402.32
1292 | 2017-05-16,2400.67
1293 | 2017-05-17,2357.03
1294 | 2017-05-18,2365.72
1295 | 2017-05-19,2381.73
1296 | 2017-05-22,2394.02
1297 | 2017-05-23,2398.42
1298 | 2017-05-24,2404.39
1299 | 2017-05-25,2415.07
1300 | 2017-05-26,2415.82
1301 | 2017-05-30,2412.91
1302 | 2017-05-31,2411.8
1303 | 2017-06-01,2430.06
1304 | 2017-06-02,2439.07
1305 | 2017-06-05,2436.1
1306 | 2017-06-06,2429.33
1307 | 2017-06-07,2433.14
1308 | 2017-06-08,2433.79
1309 | 2017-06-09,2431.77
1310 | 2017-06-12,2429.39
1311 | 2017-06-13,2440.35
1312 | 2017-06-14,2437.92
1313 | 2017-06-15,2432.46
1314 | 2017-06-16,2433.15
1315 | 2017-06-19,2453.46
1316 | 2017-06-20,2437.03
1317 | 2017-06-21,2435.61
1318 | 2017-06-22,2434.5
1319 | 2017-06-23,2438.3
1320 | 2017-06-26,2439.07
1321 | 2017-06-27,2419.38
1322 | 2017-06-28,2440.69
1323 | 2017-06-29,2419.7
1324 | 2017-06-30,2423.41
1325 | 2017-07-03,2429.01
1326 | 2017-07-05,2432.54
1327 | 2017-07-06,2409.75
1328 | 2017-07-07,2425.18
1329 | 2017-07-10,2427.43
1330 | 2017-07-11,2425.53
1331 | 2017-07-12,2443.25
1332 | 2017-07-13,2447.83
1333 | 2017-07-14,2459.27
1334 | 2017-07-17,2459.14
1335 | 2017-07-18,2460.61
1336 | 2017-07-19,2473.83
1337 | 2017-07-20,2473.45
1338 | 2017-07-21,2472.54
1339 | 2017-07-24,2469.91
1340 | 2017-07-25,2477.13
1341 | 2017-07-26,2477.83
1342 | 2017-07-27,2475.42
1343 | 2017-07-28,2472.1
1344 | 2017-07-31,2470.3
1345 | 2017-08-01,2476.35
1346 | 2017-08-02,2477.57
1347 | 2017-08-03,2472.16
1348 | 2017-08-04,2476.83
1349 | 2017-08-07,2480.91
1350 | 2017-08-08,2474.92
1351 | 2017-08-09,2474.02
1352 | 2017-08-10,2438.21
1353 | 2017-08-11,2441.32
1354 | 2017-08-14,2465.84
1355 | 2017-08-15,2464.61
1356 | 2017-08-16,2468.11
1357 | 2017-08-17,2430.01
1358 | 2017-08-18,2425.55
1359 | 2017-08-21,2428.37
1360 | 2017-08-22,2452.51
1361 | 2017-08-23,2444.04
1362 | 2017-08-24,2438.97
1363 | 2017-08-25,2443.05
1364 | 2017-08-28,2444.24
1365 | 2017-08-29,2446.3
1366 | 2017-08-30,2457.59
1367 | 2017-08-31,2471.65
1368 | 2017-09-01,2476.55
1369 | 2017-09-05,2457.85
1370 | 2017-09-06,2465.54
1371 | 2017-09-07,2465.1
1372 | 2017-09-08,2461.43
1373 | 2017-09-11,2488.11
1374 | 2017-09-12,2496.48
1375 | 2017-09-13,2498.37
1376 | 2017-09-14,2495.62
1377 | 2017-09-15,2500.23
1378 | 2017-09-18,2503.87
1379 | 2017-09-19,2506.65
1380 | 2017-09-20,2508.24
1381 | 2017-09-21,2500.6
1382 | 2017-09-22,2502.22
1383 | 2017-09-25,2496.66
1384 | 2017-09-26,2496.84
1385 | 2017-09-27,2507.04
1386 | 2017-09-28,2510.06
1387 | 2017-09-29,2519.36
1388 | 2017-10-02,2529.12
1389 | 2017-10-03,2534.58
1390 | 2017-10-04,2537.74
1391 | 2017-10-05,2552.07
1392 | 2017-10-06,2549.33
1393 | 2017-10-09,2544.73
1394 | 2017-10-10,2550.64
1395 | 2017-10-11,2555.24
1396 | 2017-10-12,2550.93
1397 | 2017-10-13,2553.17
1398 | 2017-10-16,2557.64
1399 | 2017-10-17,2559.36
1400 | 2017-10-18,2561.26
1401 | 2017-10-19,2562.1
1402 | 2017-10-20,2575.21
1403 | 2017-10-23,2564.98
1404 | 2017-10-24,2569.13
1405 | 2017-10-25,2557.15
1406 | 2017-10-26,2560.4
1407 | 2017-10-27,2581.07
1408 | 2017-10-30,2572.83
1409 | 2017-10-31,2575.26
1410 | 2017-11-01,2579.36
1411 | 2017-11-02,2579.85
1412 | 2017-11-03,2587.84
1413 | 2017-11-06,2591.13
1414 | 2017-11-07,2590.64
1415 | 2017-11-08,2594.38
1416 | 2017-11-09,2584.62
1417 | 2017-11-10,2582.3
1418 | 2017-11-13,2584.84
1419 | 2017-11-14,2578.87
1420 | 2017-11-15,2564.62
1421 | 2017-11-16,2585.64
1422 | 2017-11-17,2578.85
1423 | 2017-11-20,2582.14
1424 | 2017-11-21,2599.03
1425 | 2017-11-22,2597.08
1426 | 2017-11-24,2602.42
1427 | 2017-11-27,2601.42
1428 | 2017-11-28,2627.04
1429 | 2017-11-29,2626.07
1430 | 2017-11-30,2647.58
1431 | 2017-12-01,2642.22
1432 | 2017-12-04,2639.44
1433 | 2017-12-05,2629.57
1434 | 2017-12-06,2629.27
1435 | 2017-12-07,2636.98
1436 | 2017-12-08,2651.5
1437 | 2017-12-11,2659.99
1438 | 2017-12-12,2664.11
1439 | 2017-12-13,2662.85
1440 | 2017-12-14,2652.01
1441 | 2017-12-15,2675.81
1442 | 2017-12-18,2690.16
1443 | 2017-12-19,2681.47
1444 | 2017-12-20,2679.25
1445 | 2017-12-21,2684.57
1446 | 2017-12-22,2683.34
1447 | 2017-12-26,2680.5
1448 | 2017-12-27,2682.62
1449 | 2017-12-28,2687.54
1450 | 2017-12-29,2673.61
1451 | 2018-01-02,2695.81
1452 | 2018-01-03,2713.06
1453 | 2018-01-04,2723.99
1454 | 2018-01-05,2743.15
1455 | 2018-01-08,2747.71
1456 | 2018-01-09,2751.29
1457 | 2018-01-10,2748.23
1458 | 2018-01-11,2767.56
1459 | 2018-01-12,2786.24
1460 | 2018-01-16,2776.42
1461 | 2018-01-17,2802.56
1462 | 2018-01-18,2798.03
1463 | 2018-01-19,2810.3
1464 | 2018-01-22,2832.97
1465 | 2018-01-23,2839.13
1466 | 2018-01-24,2837.54
1467 | 2018-01-25,2839.25
1468 | 2018-01-26,2872.87
1469 | 2018-01-29,2853.53
1470 | 2018-01-30,2822.43
1471 | 2018-01-31,2823.81
1472 | 2018-02-01,2821.98
1473 | 2018-02-02,2762.13
1474 | 2018-02-05,2648.94
1475 | 2018-02-06,2695.14
1476 | 2018-02-07,2681.66
1477 | 2018-02-08,2581.0
1478 | 2018-02-09,2619.55
1479 | 2018-02-12,2656.0
1480 | 2018-02-13,2662.94
1481 | 2018-02-14,2698.63
1482 | 2018-02-15,2731.2
1483 | 2018-02-16,2732.22
1484 | 2018-02-20,2716.26
1485 | 2018-02-21,2701.33
1486 | 2018-02-22,2703.96
1487 | 2018-02-23,2747.3
1488 | 2018-02-26,2779.6
1489 | 2018-02-27,2744.28
1490 | 2018-02-28,2713.83
1491 | 2018-03-01,2677.67
1492 | 2018-03-02,2691.25
1493 | 2018-03-05,2720.94
1494 | 2018-03-06,2728.12
1495 | 2018-03-07,2726.8
1496 | 2018-03-08,2738.97
1497 | 2018-03-09,2786.57
1498 | 2018-03-12,2783.02
1499 | 2018-03-13,2765.31
1500 | 2018-03-14,2749.48
1501 | 2018-03-15,2747.33
1502 | 2018-03-16,2752.01
1503 | 2018-03-19,2712.92
1504 | 2018-03-20,2716.94
1505 | 2018-03-21,2711.93
1506 | 2018-03-22,2643.69
1507 | 2018-03-23,2588.26
1508 | 2018-03-26,2658.55
1509 | 2018-03-27,2612.62
1510 | 2018-03-28,2605.0
1511 | 2018-03-29,2640.87
1512 | 2018-04-02,2581.88
1513 | 2018-04-03,2614.45
1514 | 2018-04-04,2644.69
1515 | 2018-04-05,2662.84
1516 | 2018-04-06,2604.47
1517 | 2018-04-09,2613.16
1518 | 2018-04-10,2656.87
1519 | 2018-04-11,2642.19
1520 | 2018-04-12,2663.99
1521 | 2018-04-13,2656.3
1522 | 2018-04-16,2677.84
1523 | 2018-04-17,2706.39
1524 | 2018-04-18,2708.64
1525 | 2018-04-19,2693.13
1526 | 2018-04-20,2670.14
1527 | 2018-04-23,2670.29
1528 | 2018-04-24,2634.56
1529 | 2018-04-25,2639.4
1530 | 2018-04-26,2666.94
1531 | 2018-04-27,2669.91
1532 | 2018-04-30,2648.05
1533 | 2018-05-01,2654.8
1534 | 2018-05-02,2635.67
1535 | 2018-05-03,2629.73
1536 | 2018-05-04,2663.42
1537 | 2018-05-07,2672.63
1538 | 2018-05-08,2671.92
1539 | 2018-05-09,2697.79
1540 | 2018-05-10,2723.07
1541 | 2018-05-11,2727.72
1542 | 2018-05-14,2730.13
1543 | 2018-05-15,2711.45
1544 | 2018-05-16,2722.46
1545 | 2018-05-17,2720.13
1546 | 2018-05-18,2712.97
1547 | 2018-05-21,2733.01
1548 | 2018-05-22,2724.44
1549 | 2018-05-23,2733.29
1550 | 2018-05-24,2727.76
1551 | 2018-05-25,2721.33
1552 | 2018-05-29,2689.86
1553 | 2018-05-30,2724.01
1554 | 2018-05-31,2705.27
1555 | 2018-06-01,2734.62
1556 | 2018-06-04,2746.87
1557 | 2018-06-05,2748.8
1558 | 2018-06-06,2772.35
1559 | 2018-06-07,2770.37
1560 | 2018-06-08,2779.03
1561 | 2018-06-11,2782.0
1562 | 2018-06-12,2786.85
1563 | 2018-06-13,2775.63
1564 | 2018-06-14,2782.49
1565 | 2018-06-15,2779.66
1566 | 2018-06-18,2773.75
1567 | 2018-06-19,2762.59
1568 | 2018-06-20,2767.32
1569 | 2018-06-21,2749.76
1570 | 2018-06-22,2754.88
1571 | 2018-06-25,2717.07
1572 | 2018-06-26,2723.06
1573 | 2018-06-27,2699.63
1574 | 2018-06-28,2716.31
1575 | 2018-06-29,2718.37
1576 | 2018-07-02,2726.71
1577 | 2018-07-03,2713.22
1578 | 2018-07-05,2736.61
1579 | 2018-07-06,2759.82
1580 | 2018-07-09,2784.17
1581 | 2018-07-10,2793.84
1582 | 2018-07-11,2774.02
1583 | 2018-07-12,2798.29
1584 | 2018-07-13,2801.31
1585 | 2018-07-16,2798.43
1586 | 2018-07-17,2809.55
1587 | 2018-07-18,2815.62
1588 | 2018-07-19,2804.49
1589 | 2018-07-20,2801.83
1590 | 2018-07-23,2806.98
1591 | 2018-07-24,2820.4
1592 | 2018-07-25,2846.07
1593 | 2018-07-26,2837.44
1594 | 2018-07-27,2818.82
1595 | 2018-07-30,2802.6
1596 | 2018-07-31,2816.29
1597 | 2018-08-01,2813.36
1598 | 2018-08-02,2827.22
1599 | 2018-08-03,2840.35
1600 | 2018-08-06,2850.4
1601 | 2018-08-07,2858.45
1602 | 2018-08-08,2857.7
1603 | 2018-08-09,2853.58
1604 | 2018-08-10,2833.28
1605 | 2018-08-13,2821.93
1606 | 2018-08-14,2839.96
1607 | 2018-08-15,2818.37
1608 | 2018-08-16,2840.69
1609 | 2018-08-17,2850.13
1610 | 2018-08-20,2857.05
1611 | 2018-08-21,2862.96
1612 | 2018-08-22,2861.82
1613 | 2018-08-23,2856.98
1614 | 2018-08-24,2874.69
1615 | 2018-08-27,2896.74
1616 | 2018-08-28,2897.52
1617 | 2018-08-29,2914.04
1618 | 2018-08-30,2901.13
1619 | 2018-08-31,2901.52
1620 | 2018-09-04,2896.72
1621 | 2018-09-05,2888.6
1622 | 2018-09-06,2878.05
1623 | 2018-09-07,2871.68
1624 | 2018-09-10,2877.13
1625 | 2018-09-11,2887.89
1626 | 2018-09-12,2888.92
1627 | 2018-09-13,2904.18
1628 | 2018-09-14,2904.98
1629 | 2018-09-17,2888.8
1630 | 2018-09-18,2904.31
1631 | 2018-09-19,2907.95
1632 | 2018-09-20,2930.75
1633 | 2018-09-21,2929.67
1634 | 2018-09-24,2919.37
1635 | 2018-09-25,2915.56
1636 | 2018-09-26,2905.97
1637 | 2018-09-27,2914.0
1638 | 2018-09-28,2913.98
1639 | 2018-10-01,2924.59
1640 | 2018-10-02,2923.43
1641 | 2018-10-03,2925.51
1642 | 2018-10-04,2901.61
1643 | 2018-10-05,2885.57
1644 | 2018-10-08,2884.43
1645 | 2018-10-09,2880.34
1646 | 2018-10-10,2785.68
1647 | 2018-10-11,2728.37
1648 | 2018-10-12,2767.13
1649 | 2018-10-15,2750.79
1650 | 2018-10-16,2809.92
1651 | 2018-10-17,2809.21
1652 | 2018-10-18,2768.78
1653 | 2018-10-19,2767.78
1654 | 2018-10-22,2755.88
1655 | 2018-10-23,2740.69
1656 | 2018-10-24,2656.1
1657 | 2018-10-25,2705.57
1658 | 2018-10-26,2658.69
1659 | 2018-10-29,2641.25
1660 | 2018-10-30,2682.63
1661 | 2018-10-31,2711.74
1662 | 2018-11-01,2740.37
1663 | 2018-11-02,2723.06
1664 | 2018-11-05,2738.31
1665 | 2018-11-06,2755.45
1666 | 2018-11-07,2813.89
1667 | 2018-11-08,2806.83
1668 | 2018-11-09,2781.01
1669 | 2018-11-12,2726.22
1670 | 2018-11-13,2722.18
1671 | 2018-11-14,2701.58
1672 | 2018-11-15,2730.2
1673 | 2018-11-16,2736.27
1674 | 2018-11-19,2690.73
1675 | 2018-11-20,2641.89
1676 | 2018-11-21,2649.93
1677 | 2018-11-23,2632.56
1678 | 2018-11-26,2673.45
1679 | 2018-11-27,2682.17
1680 | 2018-11-28,2743.79
1681 | 2018-11-29,2737.76
1682 | 2018-11-30,2760.17
1683 | 2018-12-03,2790.37
1684 | 2018-12-04,2700.06
1685 | 2018-12-06,2695.95
1686 | 2018-12-07,2633.08
1687 | 2018-12-10,2637.72
1688 | 2018-12-11,2636.78
1689 | 2018-12-12,2651.07
1690 | 2018-12-13,2650.54
1691 | 2018-12-14,2599.95
1692 | 2018-12-17,2545.94
1693 | 2018-12-18,2546.16
1694 | 2018-12-19,2506.96
1695 | 2018-12-20,2467.42
1696 | 2018-12-21,2416.62
1697 | 2018-12-24,2351.1
1698 | 2018-12-26,2467.7
1699 | 2018-12-27,2488.83
1700 | 2018-12-28,2485.74
1701 | 2018-12-31,2506.85
1702 | 2019-01-02,2510.03
1703 | 2019-01-03,2447.89
1704 | 2019-01-04,2531.94
1705 | 2019-01-07,2549.69
1706 | 2019-01-08,2574.41
1707 | 2019-01-09,2584.96
1708 | 2019-01-10,2596.64
1709 | 2019-01-11,2596.26
1710 | 2019-01-14,2582.61
1711 | 2019-01-15,2610.3
1712 | 2019-01-16,2616.1
1713 | 2019-01-17,2635.96
1714 | 2019-01-18,2670.71
1715 | 2019-01-22,2632.9
1716 | 2019-01-23,2638.7
1717 | 2019-01-24,2642.33
1718 | 2019-01-25,2664.76
1719 | 2019-01-28,2643.85
1720 | 2019-01-29,2640.0
1721 | 2019-01-30,2681.05
1722 | 2019-01-31,2704.1
1723 | 2019-02-01,2706.53
1724 | 2019-02-04,2724.87
1725 | 2019-02-05,2737.7
1726 | 2019-02-06,2731.61
1727 | 2019-02-07,2706.05
1728 | 2019-02-08,2707.88
1729 | 2019-02-11,2709.8
1730 | 2019-02-12,2744.73
1731 | 2019-02-13,2753.03
1732 | 2019-02-14,2745.73
1733 | 2019-02-15,2775.6
1734 | 2019-02-19,2779.76
1735 | 2019-02-20,2784.7
1736 | 2019-02-21,2774.88
1737 | 2019-02-22,2792.67
1738 | 2019-02-25,2796.11
1739 | 2019-02-26,2793.9
1740 | 2019-02-27,2792.38
1741 | 2019-02-28,2784.49
1742 | 2019-03-01,2803.69
1743 | 2019-03-04,2792.81
1744 | 2019-03-05,2789.65
1745 | 2019-03-06,2771.45
1746 | 2019-03-07,2748.93
1747 | 2019-03-08,2743.07
1748 | 2019-03-11,2783.3
1749 | 2019-03-12,2791.52
1750 | 2019-03-13,2810.92
1751 | 2019-03-14,2808.48
1752 | 2019-03-15,2822.48
1753 | 2019-03-18,2832.94
1754 | 2019-03-19,2832.57
1755 | 2019-03-20,2824.23
1756 | 2019-03-21,2854.88
1757 | 2019-03-22,2800.71
1758 | 2019-03-25,2798.36
1759 | 2019-03-26,2818.46
1760 | 2019-03-27,2805.37
1761 | 2019-03-28,2815.44
1762 | 2019-03-29,2834.4
1763 | 2019-04-01,2867.19
1764 | 2019-04-02,2867.24
1765 | 2019-04-03,2873.4
1766 | 2019-04-04,2879.39
1767 | 2019-04-05,2892.74
1768 | 2019-04-08,2895.77
1769 | 2019-04-09,2878.2
1770 | 2019-04-10,2888.21
1771 | 2019-04-11,2888.32
1772 | 2019-04-12,2907.41
1773 | 2019-04-15,2905.58
1774 | 2019-04-16,2907.06
1775 | 2019-04-17,2900.45
1776 | 2019-04-18,2905.03
1777 | 2019-04-22,2907.97
1778 | 2019-04-23,2933.68
1779 | 2019-04-24,2927.25
1780 | 2019-04-25,2926.17
1781 | 2019-04-26,2939.88
1782 | 2019-04-29,2943.03
1783 | 2019-04-30,2945.83
1784 | 2019-05-01,2923.73
1785 | 2019-05-02,2917.52
1786 | 2019-05-03,2945.64
1787 | 2019-05-06,2932.47
1788 | 2019-05-07,2884.05
1789 | 2019-05-08,2879.42
1790 | 2019-05-09,2870.72
1791 | 2019-05-10,2881.4
1792 | 2019-05-13,2811.87
1793 | 2019-05-14,2834.41
1794 | 2019-05-15,2850.96
1795 | 2019-05-16,2876.32
1796 | 2019-05-17,2859.53
1797 | 2019-05-20,2840.23
1798 | 2019-05-21,2864.36
1799 | 2019-05-22,2856.27
1800 | 2019-05-23,2822.24
1801 | 2019-05-24,2826.06
1802 | 2019-05-28,2802.39
1803 | 2019-05-29,2783.02
1804 | 2019-05-30,2788.86
1805 | 2019-05-31,2752.06
1806 | 2019-06-03,2744.45
1807 | 2019-06-04,2803.27
1808 | 2019-06-05,2826.15
1809 | 2019-06-06,2843.49
1810 | 2019-06-07,2873.34
1811 | 2019-06-10,2886.73
1812 | 2019-06-11,2885.72
1813 | 2019-06-12,2879.84
1814 | 2019-06-13,2891.64
1815 | 2019-06-14,2886.98
1816 | 2019-06-17,2889.67
1817 | 2019-06-18,2917.75
1818 | 2019-06-19,2926.46
1819 | 2019-06-20,2954.18
1820 | 2019-06-21,2950.46
1821 | 2019-06-24,2945.35
1822 | 2019-06-25,2917.38
1823 | 2019-06-26,2913.78
1824 | 2019-06-27,2924.92
1825 | 2019-06-28,2941.76
1826 | 2019-07-01,2964.33
1827 | 2019-07-02,2973.01
1828 | 2019-07-03,2995.82
1829 | 2019-07-05,2990.41
1830 | 2019-07-08,2975.95
1831 | 2019-07-09,2979.63
1832 | 2019-07-10,2993.07
1833 | 2019-07-11,2999.91
1834 | 2019-07-12,3013.77
1835 | 2019-07-15,3014.3
1836 | 2019-07-16,3004.04
1837 | 2019-07-17,2984.42
1838 | 2019-07-18,2995.11
1839 | 2019-07-19,2976.61
1840 | 2019-07-22,2985.03
1841 | 2019-07-23,3005.47
1842 | 2019-07-24,3019.56
1843 | 2019-07-25,3003.67
1844 | 2019-07-26,3025.86
1845 | 2019-07-29,3020.97
1846 | 2019-07-30,3013.18
1847 | 2019-07-31,2980.38
1848 | 2019-08-01,2953.56
1849 | 2019-08-02,2932.05
1850 | 2019-08-05,2844.74
1851 | 2019-08-06,2881.77
1852 | 2019-08-07,2883.98
1853 | 2019-08-08,2938.09
1854 | 2019-08-09,2918.65
1855 | 2019-08-12,2883.75
1856 | 2019-08-13,2926.32
1857 | 2019-08-14,2840.6
1858 | 2019-08-15,2847.6
1859 | 2019-08-16,2888.68
1860 | 2019-08-19,2923.65
1861 | 2019-08-20,2900.51
1862 | 2019-08-21,2924.43
1863 | 2019-08-22,2922.95
1864 | 2019-08-23,2847.11
1865 | 2019-08-26,2878.38
1866 | 2019-08-27,2869.16
1867 | 2019-08-28,2887.94
1868 | 2019-08-29,2924.58
1869 | 2019-08-30,2926.46
1870 | 2019-09-03,2906.27
1871 | 2019-09-04,2937.78
1872 | 2019-09-05,2976.0
1873 | 2019-09-06,2978.71
1874 | 2019-09-09,2978.43
1875 | 2019-09-10,2979.39
1876 | 2019-09-11,3000.93
1877 | 2019-09-12,3009.57
1878 | 2019-09-13,3007.39
1879 | 2019-09-16,2997.96
1880 | 2019-09-17,3005.7
1881 | 2019-09-18,3006.73
1882 | 2019-09-19,3006.79
1883 | 2019-09-20,2992.07
1884 | 2019-09-23,2991.78
1885 | 2019-09-24,2966.6
1886 | 2019-09-25,2984.87
1887 | 2019-09-26,2977.62
1888 | 2019-09-27,2961.79
1889 | 2019-09-30,2976.74
1890 | 2019-10-01,2940.25
1891 | 2019-10-02,2887.61
1892 | 2019-10-03,2910.63
1893 | 2019-10-04,2952.01
1894 | 2019-10-07,2938.79
1895 | 2019-10-08,2893.06
1896 | 2019-10-09,2919.4
1897 | 2019-10-10,2938.13
1898 | 2019-10-11,2970.27
1899 | 2019-10-14,2966.15
1900 | 2019-10-15,2995.68
1901 | 2019-10-16,2989.69
1902 | 2019-10-17,2997.95
1903 | 2019-10-18,2986.2
1904 | 2019-10-21,3006.72
1905 | 2019-10-22,2995.99
1906 | 2019-10-23,3004.52
1907 | 2019-10-24,3010.29
1908 | 2019-10-25,3022.55
1909 | 2019-10-28,3039.42
1910 | 2019-10-29,3036.89
1911 | 2019-10-30,3046.77
1912 | 2019-10-31,3037.56
1913 | 2019-11-01,3066.91
1914 | 2019-11-04,3078.27
1915 | 2019-11-05,3074.62
1916 | 2019-11-06,3076.78
1917 | 2019-11-07,3085.18
1918 | 2019-11-08,3093.08
1919 | 2019-11-11,3087.01
1920 | 2019-11-12,3091.84
1921 | 2019-11-13,3094.04
1922 | 2019-11-14,3096.63
1923 | 2019-11-15,3120.46
1924 | 2019-11-18,3122.03
1925 | 2019-11-19,3120.18
1926 | 2019-11-20,3108.46
1927 | 2019-11-21,3103.54
1928 | 2019-11-22,3110.29
1929 | 2019-11-25,3133.64
1930 | 2019-11-26,3140.52
1931 | 2019-11-27,3153.63
1932 | 2019-11-29,3140.98
1933 | 2019-12-02,3113.87
1934 | 2019-12-03,3093.2
1935 | 2019-12-04,3112.76
1936 | 2019-12-05,3117.43
1937 | 2019-12-06,3145.91
1938 | 2019-12-09,3135.96
1939 | 2019-12-10,3132.52
1940 | 2019-12-11,3141.63
1941 | 2019-12-12,3168.57
1942 | 2019-12-13,3168.8
1943 | 2019-12-16,3191.45
1944 | 2019-12-17,3192.52
1945 | 2019-12-18,3191.14
1946 | 2019-12-19,3205.37
1947 | 2019-12-20,3221.22
1948 | 2019-12-23,3224.01
1949 | 2019-12-24,3223.38
1950 | 2019-12-26,3239.91
1951 | 2019-12-27,3240.02
1952 | 2019-12-30,3221.29
1953 | 2019-12-31,3230.78
1954 | 2020-01-02,3257.85
1955 | 2020-01-03,3234.85
1956 | 2020-01-06,3246.28
1957 | 2020-01-07,3237.18
1958 | 2020-01-08,3253.05
1959 | 2020-01-09,3274.7
1960 | 2020-01-10,3265.35
1961 | 2020-01-13,3288.13
1962 | 2020-01-14,3283.15
1963 | 2020-01-15,3289.29
1964 | 2020-01-16,3316.81
1965 | 2020-01-17,3329.62
1966 | 2020-01-21,3320.79
1967 | 2020-01-22,3321.75
1968 | 2020-01-23,3325.54
1969 | 2020-01-24,3295.47
1970 | 2020-01-27,3243.63
1971 | 2020-01-28,3276.24
1972 | 2020-01-29,3273.4
1973 | 2020-01-30,3283.66
1974 | 2020-01-31,3225.52
1975 | 2020-02-03,3248.92
1976 | 2020-02-04,3297.59
1977 | 2020-02-05,3334.69
1978 | 2020-02-06,3345.78
1979 | 2020-02-07,3327.71
1980 | 2020-02-10,3352.09
1981 | 2020-02-11,3357.75
1982 | 2020-02-12,3379.45
1983 | 2020-02-13,3373.94
1984 | 2020-02-14,3380.16
1985 | 2020-02-18,3370.29
1986 | 2020-02-19,3386.15
1987 | 2020-02-20,3373.23
1988 | 2020-02-21,3337.75
1989 | 2020-02-24,3225.89
1990 | 2020-02-25,3128.21
1991 | 2020-02-26,3116.39
1992 | 2020-02-27,2978.76
1993 | 2020-02-28,2954.22
1994 | 2020-03-02,3090.23
1995 | 2020-03-03,3003.37
1996 | 2020-03-04,3130.12
1997 | 2020-03-05,3023.94
1998 | 2020-03-06,2972.37
1999 | 2020-03-09,2746.56
2000 | 2020-03-10,2882.23
2001 | 2020-03-11,2741.38
2002 | 2020-03-12,2480.64
2003 | 2020-03-13,2711.02
2004 | 2020-03-16,2386.13
2005 | 2020-03-17,2529.19
2006 | 2020-03-18,2398.1
2007 | 2020-03-19,2409.39
2008 | 2020-03-20,2304.92
2009 | 2020-03-23,2237.4
2010 | 2020-03-24,2447.33
2011 | 2020-03-25,2475.56
2012 | 2020-03-26,2630.07
2013 | 2020-03-27,2541.47
2014 | 2020-03-30,2626.65
2015 | 2020-03-31,2584.59
2016 | 2020-04-01,2470.5
2017 | 2020-04-02,2526.9
2018 | 2020-04-03,2488.65
2019 | 2020-04-06,2663.68
2020 | 2020-04-07,2659.41
2021 | 2020-04-08,2749.98
2022 | 2020-04-09,2789.82
2023 | 2020-04-13,2761.63
2024 | 2020-04-14,2846.06
2025 | 2020-04-15,2783.36
2026 | 2020-04-16,2799.55
2027 | 2020-04-17,2874.56
2028 | 2020-04-20,2823.16
2029 | 2020-04-21,2736.56
2030 | 2020-04-22,2799.31
2031 | 2020-04-23,2797.8
2032 | 2020-04-24,2836.74
2033 | 2020-04-27,2878.48
2034 | 2020-04-28,2863.39
2035 | 2020-04-29,2939.51
2036 | 2020-04-30,2912.43
2037 | 2020-05-01,2830.71
2038 | 2020-05-04,2842.74
2039 | 2020-05-05,2868.44
2040 | 2020-05-06,2848.42
2041 | 2020-05-07,2881.19
2042 | 2020-05-08,2929.8
2043 | 2020-05-11,2930.32
2044 | 2020-05-12,2870.12
2045 | 2020-05-13,2820.0
2046 | 2020-05-14,2852.5
2047 | 2020-05-15,2863.7
2048 | 2020-05-18,2953.91
2049 | 2020-05-19,2922.94
2050 | 2020-05-20,2971.61
2051 | 2020-05-21,2948.51
2052 | 2020-05-22,2955.45
2053 | 2020-05-26,2991.77
2054 | 2020-05-27,3036.13
2055 | 2020-05-28,3029.73
2056 | 2020-05-29,3044.31
2057 | 2020-06-01,3055.73
2058 | 2020-06-02,3080.82
2059 | 2020-06-03,3122.87
2060 | 2020-06-04,3112.35
2061 | 2020-06-05,3193.93
2062 | 2020-06-08,3232.39
2063 | 2020-06-09,3207.18
2064 | 2020-06-10,3190.14
2065 | 2020-06-11,3002.1
2066 | 2020-06-12,3041.31
2067 | 2020-06-15,3066.59
2068 | 2020-06-16,3124.74
2069 | 2020-06-17,3113.49
2070 | 2020-06-18,3115.34
2071 | 2020-06-19,3097.74
2072 | 2020-06-22,3117.86
2073 | 2020-06-23,3131.29
2074 | 2020-06-24,3050.33
2075 | 2020-06-25,3083.76
2076 | 2020-06-26,3009.05
2077 | 2020-06-29,3053.24
2078 | 2020-06-30,3100.29
2079 | 2020-07-01,3115.86
2080 | 2020-07-02,3130.01
2081 | 2020-07-06,3179.72
2082 | 2020-07-07,3145.32
2083 | 2020-07-08,3169.94
2084 | 2020-07-09,3152.05
2085 | 2020-07-10,3185.04
2086 | 2020-07-13,3155.22
2087 | 2020-07-14,3197.52
2088 | 2020-07-15,3226.56
2089 | 2020-07-16,3215.57
2090 | 2020-07-17,3224.73
2091 | 2020-07-20,3251.84
2092 | 2020-07-21,3257.3
2093 | 2020-07-22,3276.02
2094 | 2020-07-23,3235.66
2095 | 2020-07-24,3215.63
2096 | 2020-07-27,3239.41
2097 | 2020-07-28,3218.44
2098 | 2020-07-29,3258.44
2099 | 2020-07-30,3246.22
2100 | 2020-07-31,3271.12
2101 | 2020-08-03,3294.61
2102 | 2020-08-04,3306.51
2103 | 2020-08-05,3327.77
2104 | 2020-08-06,3349.16
2105 | 2020-08-07,3351.28
2106 | 2020-08-10,3360.47
2107 | 2020-08-11,3333.69
2108 | 2020-08-12,3380.35
2109 | 2020-08-13,3373.43
2110 | 2020-08-14,3372.85
2111 | 2020-08-17,3381.99
2112 | 2020-08-18,3389.78
2113 | 2020-08-19,3374.85
2114 | 2020-08-20,3385.51
2115 | 2020-08-21,3397.16
2116 | 2020-08-24,3431.28
2117 | 2020-08-25,3443.62
2118 | 2020-08-26,3478.73
2119 | 2020-08-27,3484.55
2120 | 2020-08-28,3508.01
2121 | 2020-08-31,3500.31
2122 | 2020-09-01,3526.65
2123 | 2020-09-02,3580.84
2124 | 2020-09-03,3455.06
2125 | 2020-09-04,3426.96
2126 | 2020-09-08,3331.84
2127 | 2020-09-09,3398.96
2128 | 2020-09-10,3339.19
2129 | 2020-09-11,3340.97
2130 | 2020-09-14,3383.54
2131 | 2020-09-15,3401.2
2132 | 2020-09-16,3385.49
2133 | 2020-09-17,3357.01
2134 | 2020-09-18,3319.47
2135 | 2020-09-21,3281.06
2136 | 2020-09-22,3315.57
2137 | 2020-09-23,3236.92
2138 | 2020-09-24,3246.59
2139 | 2020-09-25,3298.46
2140 | 2020-09-28,3351.6
2141 | 2020-09-29,3335.47
2142 | 2020-09-30,3363.0
2143 | 2020-10-01,3380.8
2144 | 2020-10-02,3348.44
2145 | 2020-10-05,3408.63
2146 | 2020-10-06,3360.95
2147 | 2020-10-07,3419.45
2148 | 2020-10-08,3446.83
2149 | 2020-10-09,3477.13
2150 | 2020-10-12,3534.22
2151 | 2020-10-13,3511.93
2152 | 2020-10-14,3488.67
2153 | 2020-10-15,3483.34
2154 | 2020-10-16,3483.81
2155 | 2020-10-19,3426.92
2156 | 2020-10-20,3443.12
2157 | 2020-10-21,3435.56
2158 | 2020-10-22,3453.49
2159 | 2020-10-23,3465.39
2160 | 2020-10-26,3400.97
2161 | 2020-10-27,3390.68
2162 | 2020-10-28,3271.03
2163 | 2020-10-29,3310.11
2164 | 2020-10-30,3269.96
2165 | 2020-11-02,3310.24
2166 | 2020-11-03,3369.16
2167 | 2020-11-04,3443.44
2168 | 2020-11-05,3510.45
2169 | 2020-11-06,3509.44
2170 | 2020-11-09,3550.5
2171 | 2020-11-10,3545.53
2172 | 2020-11-11,3572.66
2173 | 2020-11-12,3537.01
2174 | 2020-11-13,3585.15
2175 | 2020-11-16,3626.91
2176 | 2020-11-17,3609.53
2177 | 2020-11-18,3567.79
2178 | 2020-11-19,3581.87
2179 | 2020-11-20,3557.54
2180 | 2020-11-23,3577.59
2181 | 2020-11-24,3635.41
2182 | 2020-11-25,3629.65
2183 | 2020-11-27,3638.35
2184 | 2020-11-30,3621.63
2185 | 2020-12-01,3662.45
2186 | 2020-12-02,3669.01
2187 | 2020-12-03,3666.72
2188 | 2020-12-04,3699.12
2189 | 2020-12-07,3691.96
2190 | 2020-12-08,3702.25
2191 | 2020-12-09,3672.82
2192 | 2020-12-10,3668.1
2193 | 2020-12-11,3663.46
2194 | 2020-12-14,3647.49
2195 | 2020-12-15,3694.62
2196 | 2020-12-16,3701.17
2197 | 2020-12-17,3722.48
2198 | 2020-12-18,3709.41
2199 | 2020-12-21,3694.92
2200 | 2020-12-22,3687.26
2201 | 2020-12-23,3690.01
2202 | 2020-12-24,3703.06
2203 | 2020-12-28,3735.36
2204 | 2020-12-29,3727.04
2205 | 2020-12-30,3732.04
2206 | 2020-12-31,3756.07
2207 | 2021-01-04,3700.65
2208 | 2021-01-05,3726.86
2209 | 2021-01-06,3748.14
2210 | 2021-01-07,3803.79
2211 | 2021-01-08,3824.68
2212 | 2021-01-11,3799.61
2213 | 2021-01-12,3801.19
2214 | 2021-01-13,3809.84
2215 | 2021-01-14,3795.54
2216 | 2021-01-15,3768.25
2217 | 2021-01-19,3798.91
2218 | 2021-01-20,3851.85
2219 | 2021-01-21,3853.07
2220 | 2021-01-22,3841.47
2221 | 2021-01-25,3855.36
2222 | 2021-01-26,3849.62
2223 | 2021-01-27,3750.77
2224 | 2021-01-28,3787.38
2225 | 2021-01-29,3714.24
2226 | 2021-02-01,3773.86
2227 | 2021-02-02,3826.31
2228 | 2021-02-03,3830.17
2229 | 2021-02-04,3871.74
2230 | 2021-02-05,3886.83
2231 | 2021-02-08,3915.59
2232 | 2021-02-09,3911.23
2233 | 2021-02-10,3909.88
2234 | 2021-02-11,3916.38
2235 | 2021-02-12,3934.83
2236 | 2021-02-16,3932.59
2237 | 2021-02-17,3931.33
2238 | 2021-02-18,3913.97
2239 | 2021-02-19,3906.71
2240 | 2021-02-22,3876.5
2241 | 2021-02-23,3881.37
2242 | 2021-02-24,3925.43
2243 | 2021-02-25,3829.34
2244 | 2021-02-26,3811.15
2245 | 2021-03-01,3901.82
2246 | 2021-03-02,3870.29
2247 | 2021-03-03,3819.72
2248 | 2021-03-04,3768.47
2249 | 2021-03-05,3841.94
2250 | 2021-03-08,3821.35
2251 | 2021-03-09,3875.44
2252 | 2021-03-10,3898.81
2253 | 2021-03-11,3939.34
2254 | 2021-03-12,3943.34
2255 | 2021-03-15,3968.94
2256 | 2021-03-16,3962.71
2257 | 2021-03-17,3974.12
2258 | 2021-03-18,3915.46
2259 | 2021-03-19,3913.1
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2261 | 2021-03-23,3910.52
2262 | 2021-03-24,3889.14
2263 | 2021-03-25,3909.52
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2265 | 2021-03-29,3971.09
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2278 | 2021-04-16,4185.47
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2282 | 2021-04-22,4134.98
2283 | 2021-04-23,4180.17
2284 | 2021-04-26,4187.62
2285 | 2021-04-27,4186.72
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2287 | 2021-04-29,4211.47
2288 | 2021-04-30,4181.17
2289 | 2021-05-03,4192.66
2290 | 2021-05-04,4164.66
2291 | 2021-05-05,4167.59
2292 | 2021-05-06,4201.62
2293 | 2021-05-07,4232.6
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2298 | 2021-05-14,4173.85
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2302 | 2021-05-20,4159.12
2303 | 2021-05-21,4155.86
2304 | 2021-05-24,4197.05
2305 | 2021-05-25,4188.13
2306 | 2021-05-26,4195.99
2307 | 2021-05-27,4200.88
2308 | 2021-05-28,4204.11
2309 | 2021-06-01,4202.04
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2311 | 2021-06-03,4192.85
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2317 | 2021-06-11,4247.44
2318 | 2021-06-14,4255.15
2319 | 2021-06-15,4246.59
2320 | 2021-06-16,4223.7
2321 | 2021-06-17,4221.86
2322 | 2021-06-18,4166.45
2323 | 2021-06-21,4224.79
2324 | 2021-06-22,4246.44
2325 | 2021-06-23,4241.84
2326 | 2021-06-24,4266.49
2327 | 2021-06-25,4280.7
2328 | 2021-06-28,4290.61
2329 | 2021-06-29,4291.8
2330 | 2021-06-30,4297.5
2331 | 2021-07-01,4319.94
2332 | 2021-07-02,4352.34
2333 | 2021-07-06,4343.54
2334 | 2021-07-07,4358.13
2335 | 2021-07-08,4320.82
2336 | 2021-07-09,4369.55
2337 | 2021-07-12,4384.63
2338 | 2021-07-13,4369.21
2339 | 2021-07-14,4374.3
2340 | 2021-07-15,4360.03
2341 | 2021-07-16,4327.16
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2344 | 2021-07-21,4358.69
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2346 | 2021-07-23,4411.79
2347 | 2021-07-26,4422.3
2348 | 2021-07-27,4401.46
2349 | 2021-07-28,4400.64
2350 | 2021-07-29,4419.15
2351 | 2021-07-30,4395.26
2352 | 2021-08-02,4387.16
2353 | 2021-08-03,4423.15
2354 | 2021-08-04,4402.66
2355 | 2021-08-05,4429.1
2356 | 2021-08-06,4436.52
2357 | 2021-08-09,4432.35
2358 | 2021-08-10,4436.75
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2360 | 2021-08-12,4460.83
2361 | 2021-08-13,4468.0
2362 | 2021-08-16,4479.71
2363 | 2021-08-17,4448.08
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2367 | 2021-08-23,4479.53
2368 | 2021-08-24,4486.23
2369 | 2021-08-25,4496.19
2370 | 2021-08-26,4470.0
2371 | 2021-08-27,4509.37
2372 | 2021-08-30,4528.79
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2376 | 2021-09-03,4535.43
2377 | 2021-09-07,4520.03
2378 | 2021-09-08,4514.07
2379 | 2021-09-09,4493.28
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2382 | 2021-09-14,4443.05
2383 | 2021-09-15,4480.7
2384 | 2021-09-16,4473.75
2385 | 2021-09-17,4432.99
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2387 | 2021-09-21,4354.19
2388 | 2021-09-22,4395.64
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2392 | 2021-09-28,4352.63
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2394 | 2021-09-30,4307.54
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2397 | 2021-10-05,4345.72
2398 | 2021-10-06,4363.55
2399 | 2021-10-07,4399.76
2400 | 2021-10-08,4391.34
2401 | 2021-10-11,4361.19
2402 | 2021-10-12,4350.65
2403 | 2021-10-13,4363.8
2404 | 2021-10-14,4438.26
2405 | 2021-10-15,4471.37
2406 | 2021-10-18,4486.46
2407 | 2021-10-19,4519.63
2408 | 2021-10-20,4536.19
2409 | 2021-10-21,4549.78
2410 | 2021-10-22,4544.9
2411 | 2021-10-25,4566.48
2412 | 2021-10-26,4574.79
2413 | 2021-10-27,4551.68
2414 | 2021-10-28,4596.42
2415 | 2021-10-29,4605.38
2416 | 2021-11-01,4613.67
2417 | 2021-11-02,4630.65
2418 | 2021-11-03,4660.57
2419 | 2021-11-04,4680.06
2420 | 2021-11-05,4697.53
2421 | 2021-11-08,4701.7
2422 | 2021-11-09,4685.25
2423 | 2021-11-10,4646.71
2424 | 2021-11-11,4649.27
2425 | 2021-11-12,4682.85
2426 | 2021-11-15,4682.8
2427 | 2021-11-16,4700.9
2428 | 2021-11-17,4688.67
2429 | 2021-11-18,4704.54
2430 | 2021-11-19,4697.96
2431 | 2021-11-22,4682.94
2432 | 2021-11-23,4690.7
2433 | 2021-11-24,4701.46
2434 | 2021-11-26,4594.62
2435 | 2021-11-29,4655.27
2436 | 2021-11-30,4567.0
2437 | 2021-12-01,4513.04
2438 | 2021-12-02,4577.1
2439 | 2021-12-03,4538.43
2440 | 2021-12-06,4591.67
2441 | 2021-12-07,4686.75
2442 | 2021-12-08,4701.21
2443 | 2021-12-09,4667.45
2444 | 2021-12-10,4712.02
2445 | 2021-12-13,4668.97
2446 | 2021-12-14,4634.09
2447 | 2021-12-15,4709.85
2448 | 2021-12-16,4668.67
2449 | 2021-12-17,4620.64
2450 | 2021-12-20,4568.02
2451 | 2021-12-21,4649.23
2452 | 2021-12-22,4696.56
2453 | 2021-12-23,4725.79
2454 | 2021-12-27,4791.19
2455 | 2021-12-28,4786.35
2456 | 2021-12-29,4793.06
2457 | 2021-12-30,4778.73
2458 | 2021-12-31,4766.18
2459 | 2022-01-03,4796.56
2460 | 2022-01-04,4793.54
2461 | 2022-01-05,4700.58
2462 | 2022-01-06,4696.05
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2465 | 2022-01-11,4713.07
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2467 | 2022-01-13,4659.03
2468 | 2022-01-14,4662.85
2469 | 2022-01-18,4577.11
2470 | 2022-01-19,4532.76
2471 | 2022-01-20,4482.73
2472 | 2022-01-21,4397.94
2473 | 2022-01-24,4410.13
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2475 | 2022-01-26,4349.93
2476 | 2022-01-27,4326.51
2477 | 2022-01-28,4431.85
2478 | 2022-01-31,4515.55
2479 | 2022-02-01,4546.54
2480 | 2022-02-02,4589.38
2481 | 2022-02-03,4477.44
2482 | 2022-02-04,4500.53
2483 | 2022-02-07,4483.87
2484 | 2022-02-08,4521.54
2485 | 2022-02-09,4587.18
2486 | 2022-02-10,4504.08
2487 | 2022-02-11,4418.64
2488 | 2022-02-14,4401.67
2489 | 2022-02-15,4471.07
2490 | 2022-02-16,4475.01
2491 | 2022-02-17,4380.26
2492 | 2022-02-18,4348.87
2493 | 2022-02-22,4304.76
2494 | 2022-02-23,4225.5
2495 | 2022-02-24,4288.7
2496 | 2022-02-25,4384.65
2497 | 2022-02-28,4373.94
2498 | 2022-03-01,4306.26
2499 | 2022-03-02,4386.54
2500 | 2022-03-03,4363.49
2501 | 2022-03-04,4328.87
2502 | 2022-03-07,4201.09
2503 | 2022-03-08,4170.7
2504 | 2022-03-09,4277.88
2505 | 2022-03-10,4259.52
2506 | 2022-03-11,4204.31
2507 | 2022-03-14,4173.11
2508 | 2022-03-15,4262.45
2509 | 2022-03-16,4357.86
2510 | 2022-03-17,4411.67
2511 | 2022-03-18,4463.12
2512 | 2022-03-21,4461.18
2513 | 2022-03-22,4511.61
2514 | 2022-03-23,4456.24
2515 | 2022-03-24,4520.16
2516 | 2022-03-25,4543.06
2517 | 2022-03-28,4575.52
2518 |
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