├── README.md ├── amazon.csv ├── amtd.csv ├── disney.csv ├── draw.py ├── files ├── alldeliverables │ ├── ProjectMilestone.pdf │ ├── ProjectProposal.pdf │ └── final.pdf ├── images │ ├── amtd.png │ ├── amtdprediction.png │ ├── amtdzoomed.png │ ├── amzn.png │ ├── amznprediction.png │ ├── amznzoomed.png │ ├── dis.png │ ├── disprediction.png │ ├── diszoomed.png │ ├── final.jpg │ ├── sbux.png │ ├── sbuxprediction.png │ ├── sbuxzoomed.png │ ├── twlo.png │ ├── twloprediction.png │ ├── twlozoomed.png │ ├── twtr.png │ ├── twtrprediction.png │ ├── twtrzoomed.png │ ├── yhoo.png │ ├── yhooprediction.png │ └── yhoozoomed.png └── researchpapers │ ├── Efficient Capital Markets A Review of Theory and Empirical Work.pdf │ ├── Efficient Capital Markets: A Review of Theory and Empirical Work │ ├── Efficient markets II.pdf │ └── jordanmarketusingknn.pdf ├── knnAlgorithm.py ├── requirements.txt ├── sbux.csv ├── twlo.csv ├── twtr.csv └── yahoo.csv /README.md: -------------------------------------------------------------------------------- 1 | _Note: It has been a while since this project has been updated. As you work through the code, if you feel like this can be updated, even slightly, feel free to send in a PR_ 2 | 3 | # Stock Prediction Using *K*-Nearest Neighbor (*k*NN) Algorithm 4 | 5 | I applied k-nearest neighbor algorithm and non-linear regression approach in 6 | order to predict stock proces for a sample of six major companies listed on the 7 | NASDAQ stock exchange to assist investors, management, decision makers, and 8 | users in making correct and informed investments decisions. 9 | 10 | A more detailed paper on this can be found in 11 | [final.pdf](files/alldeliverables/final.pdf) 12 | 13 | ## To run 14 | ``` 15 | cd 16 | 17 | pip install -r requirements.txt 18 | 19 | python knnAlgorithm.py 20 | ``` 21 | 22 | ## Some Stock Market terminologies 23 | 24 | **OPEN** is the price of the stock at the beginning of the trading day (it 25 | need not be the closing price of the previous day). 26 | 27 | **High** is the highest price of the stock at closing time. 28 | 29 | **Low** is the lowest price of the stock on that trading day. 30 | 31 | **Close** is the price of the stock at closing time. 32 | 33 | **Volume** indicates how many stocks were traded. 34 | 35 | **Adjusted Close** is the closing price of the stock that adjusts the price of 36 | the stock for corporate actions. 37 | 38 | While stock prices are considered to be set mostly by traders, **stock** splits 39 | (when the company makes each extant stock worth two and halves the price) and 40 | **dividends** (payout of company profits per share) also affect the price of a 41 | stock and should be accounted for. 42 | 43 | ## *K* Nearest Neighbor (*k*NN) Algorithm 44 | 45 | The model for kNN is the entire training dataset. When a prediction is required 46 | for a unseen data instance, the kNN algorithm will search through the training 47 | dataset for the k-most similar instances. The prediction attribute of the most 48 | similar instances is summarised and returned as the prediction for the unseen 49 | instance. 50 | 51 | The similarity measure is dependent on the type of data. For real-valued data, 52 | the Euclidean distance can be used. For other types of data, such as categorical 53 | or binary data, Hamming distance can be used. 54 | 55 | In the case of regression problems, the average of the predicted attribute may 56 | be returned. 57 | 58 | In case of classification, the most prevalent class may be returned. 59 | 60 | ### How does it work? 61 | The kNN algorithm belongs to the family of 62 | [instance-based](https://en.wikipedia.org/wiki/Instance-based_learning "In 63 | machine learning, instance-based learning, sometimes called memory-based 64 | learning, is a family of learning algorithms that, instead of performing 65 | explicit generalization, compares new problem instances with instances seen in 66 | training, which have been stored in memory."), [competitive 67 | learning](https://en.wikipedia.org/wiki/Competitive_learning "Competitive 68 | learning is a form of unsupervised learning in artificial neural networks, in 69 | which nodes compete for the right to respond to a subset of the input data. A 70 | variant of Hebbian learning, competitive learning works by increasing the 71 | specialization of each node in the network.") 72 | and [lazy learning](https://en.wikipedia.org/wiki/Lazy_learning "lazy learning 73 | is a learning method in which generalization beyond the training data is 74 | delayed until a query is made to the system, as opposed to in eager learning, 75 | where the system tries to generalize the training data before receiving 76 | queries.") algorithms. 77 | 78 | Finally, kNN is powerful because it does not assume anything about the data, 79 | other than that distance measure can be calculated consistently between any two 80 | instances. As such, it is called *non-linear* as it does not assume a 81 | functional form. 82 | 83 | ### Implement kNN 84 | 1. Handle data: Open the dataset from CSV and split into test/train datasets 85 | 2. Similarity: Calculate the distance between two data instances 86 | 3. Neighbors: Locate k most similar data instances 87 | 4. Response: Generate a response from a set of data instances 88 | 5. Accuracy: Summarize the accuracy of predictions 89 | 6. Main: Tie it all together 90 | 91 | 92 | ### Results 93 | 94 | The following graphs show the result. We achieved a 70% accuracy in the 95 | prediction. So, a module that will predict, given a stock, will rise tommorow 96 | will be posted in coming days. For now, enjoy the graphs and be glad that there 97 | now exists a ML algorithm that give 70% certainty on if you should buy a certain 98 | stock or not. 99 | 100 | amtd 101 | ![Image](files/images/amtd.png) ![Image](files/images/amtdprediction.png) ![Image](files/images/amtdzoomed.png) 102 | amzn 103 | ![Image](files/images/amzn.png) ![Image](files/images/amznprediction.png) ![Image](files/images/amznzoomed.png) 104 | dis 105 | ![Image](files/images/dis.png) ![Image](files/images/disprediction.png) ![Image](files/images/diszoomed.png) 106 | sbux 107 | ![Image](files/images/sbux.png) ![Image](files/images/sbuxprediction.png) ![Image](files/images/sbuxzoomed.png) 108 | twlo 109 | ![Image](files/images/twlo.png) ![Image](files/images/twloprediction.png) ![Image](files/images/twlozoomed.png) 110 | twtr 111 | ![Image](files/images/twtr.png) ![Image](files/images/twtrprediction.png) ![Image](files/images/twtrzoomed.png) 112 | yhoo 113 | ![Image](files/images/yhoo.png) ![Image](files/images/yhooprediction.png) ![Image](files/images/yhoozoomed.png) 114 | 115 | ## Reference 116 | [Implement 117 | kNN](http://machinelearningmastery.com/tutorial-to-implement-k-nearest-neighbors-in-python-from-scratch/) 118 | 119 | 120 | -------------------------------------------------------------------------------- /draw.py: -------------------------------------------------------------------------------- 1 | import pandas as pd 2 | import pandas_datareader as pdr 3 | import pandas_datareader.data as web 4 | import datetime 5 | 6 | import matplotlib.pyplot as plt # Import matplotlib 7 | 8 | import plotly.plotly as py 9 | import plotly 10 | import plotly.graph_objs as go 11 | 12 | line_up, = plt.plot([1,2,3], label='Line 2') 13 | line_down, = plt.plot([3,2,1], label='Line 1') 14 | plt.legend(handles=[line_up, line_down]) 15 | 16 | plt.show() 17 | -------------------------------------------------------------------------------- /files/alldeliverables/ProjectMilestone.pdf: 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-------------------------------------------------------------------------------- /knnAlgorithm.py: -------------------------------------------------------------------------------- 1 | import csv 2 | import random 3 | import math 4 | import operator 5 | 6 | import pandas_datareader.data as web 7 | import datetime 8 | import pandas as pd 9 | 10 | import matplotlib.pyplot as plt # Import matplotlib 11 | import json 12 | 13 | # split the data into a trainingdataset and testdataset in ratio of 67/33 14 | 15 | def loadDataset(filename, split, trainingSet=[], testSet=[], content_header=[]): 16 | with open(filename, 'rb') as csvfile: 17 | # returns a reader object which will iterate over lines 18 | lines = csv.reader(csvfile) 19 | # dataset is a list of all data, where each item is a line as list 20 | dataset = list(lines) 21 | # minus 1 because we are predicting for next day 22 | for x in range(len(dataset) - 1): 23 | # convert the content to float 24 | # minus 1 because last is string for up or down 25 | for y in range(1, len(content_header) - 1): 26 | dataset[x][y] = float(dataset[x][y]) 27 | if random.random() < split: 28 | trainingSet.append(dataset[x]) 29 | else: 30 | testSet.append(dataset[x]) 31 | 32 | 33 | 34 | def euclideanDistance(instance1, instance2, length): 35 | distance = 0 36 | for x in range(1, length): 37 | distance += pow((instance1[x] - instance2[x]), 2) 38 | return math.sqrt(distance) 39 | 40 | 41 | # get k nearest neighbors of the testInstance among 42 | # trainingSet 43 | def getNeighbors(trainingSet, testInstance, k): 44 | distance = [] 45 | # minus 1 because we are splitting our data and test also has known class 46 | length = len(testInstance) - 1 47 | 48 | for x in range((len(trainingSet))): 49 | dist = euclideanDistance(testInstance, trainingSet[x], length) 50 | distance.append((trainingSet[x], dist)) 51 | # sort based on the the item at index 1 i.e the distance 52 | distance.sort(key=operator.itemgetter(1)) 53 | neighbors = [] 54 | for x in range(k): 55 | neighbors.append(distance[x][0]) 56 | return neighbors 57 | 58 | 59 | # make all responses vote their classification, the one with the highest vote 60 | # wins 61 | def getResponse(neighbors): 62 | classVotes = {} 63 | for x in range(len(neighbors)): 64 | response = neighbors[x][-1] 65 | if response in classVotes: 66 | classVotes[response] += 1 67 | else: 68 | classVotes[response] = 1 69 | sortedVotes = sorted(classVotes.iteritems(), key=operator.itemgetter(1), reverse=True) 70 | return sortedVotes[0][0] 71 | 72 | 73 | def getAccuracy(testSet, predictions): 74 | correct = 0 75 | for x in range(len(testSet)): 76 | if testSet[x][-1] == predictions[x]: 77 | correct += 1 78 | return (correct/float(len(testSet))) * 100.0 79 | 80 | 81 | def getAccuracy1(testSet, predictions): 82 | correct = 0 83 | for x in range(len(testSet)): 84 | if RMSD(testSet[x][-1], predictions[x]) < 1: 85 | correct += 1 86 | return (correct/float(len(testSet))) * 100.0 87 | 88 | 89 | def RMSD(X, Y): 90 | return math.sqrt(pow(Y - X, 2)) 91 | 92 | 93 | def change(today, yest): 94 | if today > yest: 95 | return 'up' 96 | return 'down' 97 | 98 | 99 | 100 | def getData(filename, stockname, startdate, enddate): 101 | stock = web.DataReader(stockname, 'yahoo', startdate, enddate) 102 | print("done making network call") 103 | ass = [stock.index] 104 | stck_json = stock.to_json(orient="index", date_format='iso') 105 | stck_dates = json.loads(stck_json) 106 | 107 | plt.plot(stock["Adj Close"]) 108 | plt.title("Stock movement of " + stockname) 109 | 110 | first_time = True 111 | with open(filename, 'wb') as pp: 112 | stockwriter = csv.writer(pp) 113 | stp = sorted(stck_dates.keys()) 114 | for i in stp: 115 | new_format_date = i[:10] 116 | if first_time: 117 | first_time = False 118 | prev_closing = stck_dates[i]["Adj Close"] 119 | continue 120 | stockwriter.writerow([new_format_date] + [stck_dates[i]["Open"]] + [stck_dates[i]["High"]] + [stck_dates[i]["Low"]] + [stck_dates[i]["Adj Close"]] + [change(stck_dates[i]["Adj Close"], prev_closing)]) 121 | prev_closing = stck_dates[i]["Adj Close"] 122 | 123 | 124 | def abc(filename, stockname, startdate, enddate): 125 | apple = web.DataReader(stockname, 'yahoo', startdate, enddate) 126 | with open(filename, 'wb') as csvfile: 127 | stockwriter = csv.writer(csvfile, quotechar=',') 128 | for ind in range(1, len(apple.Open)): 129 | stockwriter.writerow(["open: "] + [apple.Open[ind - 1]] + [" high: "] + [apple.High[ind - 1]] + [" low: "] + [apple.Low[ind - 1]] + [" yester close: "] + [apple['Adj Close'][ind - 1]] + [" volume: "] + [apple.Volume[ind - 1]] + [change(apple['Adj Close'][ind], apple['Adj Close'][ind - 1])]) 130 | 131 | 132 | 133 | def predictFor(k, filename, stockname, startdate, enddate, writeAgain, split): 134 | iv = ["date", "open", "high", "low", "yesterday closing adj", "state change"] 135 | trainingSet = [] 136 | testSet = [] 137 | totalCount = 0 138 | 139 | if writeAgain: 140 | print("making a network request") 141 | getData(filename, stockname, startdate, enddate) 142 | 143 | # open the file 144 | loadDataset(filename, split, trainingSet, testSet, iv) 145 | 146 | print("Predicting for ", stockname) 147 | print("Train: " + repr(len(trainingSet))) 148 | print("Test: " + repr(len(testSet))) 149 | totalCount += len(trainingSet) + len(testSet) 150 | print("Total: " + repr(totalCount)) 151 | 152 | # generate predictions 153 | predict_and_get_accuracy(testSet, trainingSet, k, stockname) 154 | 155 | 156 | def predict_and_get_accuracy(testSet, trainingSet, k, stockname): 157 | predictions = [] 158 | for x in range(len(testSet)): 159 | neighbors = getNeighbors(trainingSet, testSet[x], k) 160 | result = getResponse(neighbors) 161 | predictions.append(result) 162 | 163 | accuracy = getAccuracy(testSet, predictions) 164 | print('Accuracy: ' + repr(accuracy) + '%') 165 | 166 | # drawing another 167 | plt.figure(2) 168 | plt.title("Prediction vs Actual Trend of " + stockname) 169 | plt.legend(loc="best") 170 | row = [] 171 | col = [] 172 | for dates in range(len(testSet)): 173 | new_date = datetime.datetime.strptime(testSet[dates][0], "%Y-%M-%d") 174 | row.append(new_date) 175 | if predictions[dates]== "down": 176 | col.append(-1) 177 | else: 178 | col.append(1) 179 | predicted_plt, = plt.plot(row, col, 'r', label="Predicted Trend") 180 | 181 | row = [] 182 | col = [] 183 | for dates in range(len(testSet)): 184 | new_date = datetime.datetime.strptime(testSet[dates][0], "%Y-%M-%d") 185 | row.append(new_date) 186 | if testSet[dates][-1]== "down": 187 | col.append(-1) 188 | else: 189 | col.append(1) 190 | actual_plt, = plt.plot(row, col, 'b', label="Actual Trend") 191 | 192 | plt.legend(handles=[predicted_plt, actual_plt]) 193 | 194 | 195 | plt.show() 196 | 197 | 198 | def main(): 199 | split = 0.67 200 | # set data 201 | startdate = datetime.datetime(2002,1,1) 202 | enddate = datetime.date.today() 203 | 204 | predictFor(5, 'amtd.csv', 'AMTD', startdate, enddate, 1, split) 205 | predictFor(5, 'amazon.csv', 'AMZN', startdate, enddate, 1, split) 206 | predictFor(5, 'disney.csv', 'DIS', startdate, enddate, 1, split) 207 | predictFor(5, 'sbux.csv', 'SBUX', startdate, enddate, 1, split) 208 | predictFor(5, 'twlo.csv', 'TWLO', startdate, enddate, 1, split) 209 | predictFor(5, 'twtr.csv', 'TWTR', startdate, enddate, 1, split) 210 | predictFor(5, 'yahoo.csv', 'YHOO', startdate, enddate, 1, split) 211 | 212 | main() 213 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | appdirs==1.4.0 2 | cycler==0.10.0 3 | decorator==4.0.11 4 | enum34==1.1.6 5 | functools32==3.2.3.post2 6 | ipython-genutils==0.2.0 7 | jsonschema==2.6.0 8 | jupyter-core==4.3.0 9 | matplotlib==2.0.0 10 | nbformat==4.3.0 11 | numpy==1.12.1 12 | packaging==16.8 13 | pandas==0.19.2 14 | pandas-datareader==0.3.0.post0 15 | plotly==2.0.7 16 | pyparsing==2.1.10 17 | python-dateutil==2.6.0 18 | pytz==2017.2 19 | requests==2.13.0 20 | requests-file==1.4.1 21 | requests-ftp==0.3.1 22 | six==1.10.0 23 | subprocess32==3.2.7 24 | traitlets==4.3.2 25 | -------------------------------------------------------------------------------- /twlo.csv: -------------------------------------------------------------------------------- 1 | 2016-06-24,27.540001,28.739,26.049999,26.299999,down 2 | 2016-06-27,27.35,28.190001,26.299999,27.25,up 3 | 2016-06-28,30.4,33.410999,29.57,29.92,up 4 | 2016-06-29,31.98,37.189999,31.75,37.080002,up 5 | 2016-06-30,39.68,41.889999,34.799999,36.5,down 6 | 2016-07-01,36.970001,37.34,33.650002,34.029999,down 7 | 2016-07-05,34.869999,35.43,33.07,34.040001,up 8 | 2016-07-06,33.41,37.93,33.27,37.93,up 9 | 2016-07-07,38.41,38.619999,36.0,36.509998,down 10 | 2016-07-08,37.25,37.400002,35.25,35.540001,down 11 | 2016-07-11,36.299999,38.299999,35.790001,37.299999,up 12 | 2016-07-12,37.990002,38.939999,36.814999,38.299999,up 13 | 2016-07-13,41.290001,42.75,40.209999,42.25,up 14 | 2016-07-14,43.400002,44.799999,40.799999,41.75,down 15 | 2016-07-15,42.740002,43.75,41.200001,43.0,up 16 | 2016-07-18,41.25,42.484001,40.150002,41.029999,down 17 | 2016-07-19,40.529999,41.0,39.040001,39.07,down 18 | 2016-07-20,39.5,42.574001,38.509998,41.73,up 19 | 2016-07-21,41.709999,42.549999,39.830002,40.119999,down 20 | 2016-07-22,40.32,41.759998,40.099998,40.810001,up 21 | 2016-07-25,40.700001,41.490002,39.57,40.75,down 22 | 2016-07-26,40.549999,41.782001,39.75,40.389999,down 23 | 2016-07-27,40.919998,43.25,40.77,42.540001,up 24 | 2016-07-28,42.959999,43.700001,41.02,42.169998,down 25 | 2016-07-29,42.75,42.881001,40.549999,40.630001,down 26 | 2016-08-01,40.630001,41.639999,39.110001,39.330002,down 27 | 2016-08-02,39.099998,40.25,37.5,37.93,down 28 | 2016-08-03,38.099998,39.0,37.200001,38.549999,up 29 | 2016-08-04,38.900002,41.07,38.900002,40.59,up 30 | 2016-08-05,40.970001,41.720001,40.75,41.490002,up 31 | 2016-08-08,42.700001,42.919998,40.580002,42.5,up 32 | 2016-08-09,44.32,45.689999,41.349998,43.009998,up 33 | 2016-08-10,43.220001,43.950001,41.900002,43.630001,up 34 | 2016-08-11,43.450001,49.0,43.450001,48.709999,up 35 | 2016-08-12,49.049999,53.369999,48.599998,53.290001,up 36 | 2016-08-15,56.75,66.399002,55.132999,58.470001,up 37 | 2016-08-16,60.57,64.160004,59.060001,59.34,up 38 | 2016-08-17,60.900002,61.5,57.049999,58.860001,down 39 | 2016-08-18,59.139999,59.360001,54.150002,54.400002,down 40 | 2016-08-19,52.32,56.470001,51.849998,54.880001,up 41 | 2016-08-22,56.23,59.75,55.34,58.650002,up 42 | 2016-08-23,60.150002,61.349998,55.709999,56.080002,down 43 | 2016-08-24,56.080002,58.07,53.349998,53.599998,down 44 | 2016-08-25,54.25,55.099998,51.257,51.93,down 45 | 2016-08-26,51.93,54.330002,49.611,54.25,up 46 | 2016-08-29,54.549999,56.0,53.200001,53.82,down 47 | 2016-08-30,53.849998,54.93,53.509998,53.799999,down 48 | 2016-08-31,53.990002,54.59,52.139999,53.619999,down 49 | 2016-09-01,53.610001,56.740002,53.599998,54.380001,up 50 | 2016-09-02,54.93,57.740002,54.93,57.619999,up 51 | 2016-09-06,58.240002,60.689999,57.791,59.18,up 52 | 2016-09-07,60.200001,60.400002,56.310001,56.630001,down 53 | 2016-09-08,57.400002,58.450001,56.509998,57.450001,up 54 | 2016-09-09,57.0,58.0,55.02,56.0,down 55 | 2016-09-12,55.080002,57.880001,54.580002,56.700001,up 56 | 2016-09-13,55.779999,56.75,53.599998,53.970001,down 57 | 2016-09-14,54.970001,55.0,52.77,53.119999,down 58 | 2016-09-15,53.880001,54.849998,53.259998,54.0,up 59 | 2016-09-16,54.299999,56.990002,53.66,56.75,up 60 | 2016-09-19,57.540001,59.400002,56.900002,57.279999,up 61 | 2016-09-20,57.869999,58.988998,56.599998,56.759998,down 62 | 2016-09-21,57.5,61.849998,56.849998,61.700001,up 63 | 2016-09-22,62.450001,66.480003,62.029999,64.919998,up 64 | 2016-09-23,64.449997,68.400002,63.799999,64.07,down 65 | 2016-09-26,63.0,65.68,62.380001,64.239998,up 66 | 2016-09-27,66.0,68.989998,65.559998,68.220001,up 67 | 2016-09-28,70.489998,70.959999,67.440002,68.970001,up 68 | 2016-09-29,69.129997,69.900002,68.199997,68.720001,down 69 | 2016-09-30,69.5,69.610001,63.009998,64.360001,down 70 | 2016-10-03,62.5,66.639999,62.43,65.019997,up 71 | 2016-10-04,65.260002,65.730003,60.259998,60.939999,down 72 | 2016-10-05,62.09,63.139999,61.050999,61.470001,up 73 | 2016-10-06,60.720001,62.77,60.071999,60.689999,down 74 | 2016-10-07,61.330002,61.98,59.27,60.580002,down 75 | 2016-10-10,57.630001,58.91,51.389999,52.02,down 76 | 2016-10-11,54.43,54.599998,51.341,52.439999,up 77 | 2016-10-12,53.459999,53.59,50.040001,50.799999,down 78 | 2016-10-13,49.869999,49.950001,47.049999,47.240002,down 79 | 2016-10-14,47.799999,49.59,45.68,46.110001,down 80 | 2016-10-17,45.389999,47.217999,44.310001,44.450001,down 81 | 2016-10-18,45.889999,48.939999,44.410999,47.77,up 82 | 2016-10-19,48.099998,48.18,45.5,46.509998,down 83 | 2016-10-20,45.799999,46.949001,43.540001,44.139999,down 84 | 2016-10-21,41.0,43.099998,40.189999,41.060001,down 85 | 2016-10-24,42.200001,42.799999,40.639999,40.73,down 86 | 2016-10-25,40.73,41.630001,38.549999,38.599998,down 87 | 2016-10-26,38.419998,40.43,38.25,39.240002,up 88 | 2016-10-27,39.52,39.75,36.720001,37.259998,down 89 | 2016-10-28,36.790001,37.700001,34.740002,35.419998,down 90 | 2016-10-31,35.41,36.25,33.75,34.119999,down 91 | 2016-11-01,35.400002,36.790001,34.709999,35.880001,up 92 | 2016-11-02,35.73,36.369999,33.450001,34.150002,down 93 | 2016-11-03,33.869999,34.549999,32.41,32.599998,down 94 | 2016-11-04,34.16,35.200001,31.5,31.57,down 95 | 2016-11-07,32.970001,33.099998,30.43,30.52,down 96 | 2016-11-08,30.6,31.879999,29.92,31.41,up 97 | 2016-11-09,30.360001,33.700001,30.299999,31.809999,up 98 | 2016-11-10,33.139999,34.0,30.719999,31.5,down 99 | 2016-11-11,31.08,32.279999,31.030001,31.559999,up 100 | 2016-11-14,31.709999,32.970001,31.209999,31.389999,down 101 | 2016-11-15,31.700001,34.849998,31.389999,34.73,up 102 | 2016-11-16,35.389999,37.84,35.0,37.049999,up 103 | 2016-11-17,37.419998,37.439999,34.75,35.209999,down 104 | 2016-11-18,35.41,36.880001,34.549999,36.880001,up 105 | 2016-11-21,37.509998,38.880001,36.509998,36.799999,down 106 | 2016-11-22,37.599998,38.200001,36.799999,37.389999,up 107 | 2016-11-23,37.09,37.849998,35.529999,35.68,down 108 | 2016-11-25,35.68,35.84,34.849998,35.07,down 109 | 2016-11-28,34.810001,35.490002,33.720001,33.849998,down 110 | 2016-11-29,33.990002,34.290001,32.66,33.610001,down 111 | 2016-11-30,33.0,35.240002,33.0,33.919998,up 112 | 2016-12-01,33.66,33.799999,31.540001,31.870001,down 113 | 2016-12-02,31.549999,31.74,30.309999,30.379999,down 114 | 2016-12-05,30.889999,31.67,30.35,30.73,up 115 | 2016-12-06,30.809999,32.490002,30.809999,32.139999,up 116 | 2016-12-07,32.0,32.869999,30.98,31.02,down 117 | 2016-12-08,31.049999,31.780001,30.34,30.6,down 118 | 2016-12-09,30.6,30.950001,29.139999,29.34,down 119 | 2016-12-12,29.040001,29.5,28.370001,29.23,down 120 | 2016-12-13,29.0,30.370001,29.0,29.27,up 121 | 2016-12-14,29.23,29.940001,29.0,29.51,up 122 | 2016-12-15,29.610001,30.209999,29.25,29.65,up 123 | 2016-12-16,29.9,30.530001,28.711,29.25,down 124 | 2016-12-19,29.200001,29.5,28.709999,29.15,down 125 | 2016-12-20,29.610001,31.49,28.610001,29.92,up 126 | 2016-12-21,30.5,34.68,30.200001,34.59,up 127 | 2016-12-22,35.07,35.150002,31.52,31.709999,down 128 | 2016-12-23,32.119999,32.599998,31.530001,32.220001,up 129 | 2016-12-27,32.700001,33.049999,32.049999,32.610001,up 130 | 2016-12-28,32.450001,32.75,30.030001,30.209999,down 131 | 2016-12-29,30.02,30.24,28.851,29.27,down 132 | 2016-12-30,29.42,29.99,28.65,28.85,down 133 | 2017-01-03,29.25,29.450001,25.98,26.5,down 134 | 2017-01-04,26.549999,27.75,26.209999,27.51,up 135 | 2017-01-05,28.6,28.75,27.41,28.1,up 136 | 2017-01-06,28.059999,28.73,27.559999,27.629999,down 137 | 2017-01-09,27.77,28.35,27.24,28.1,up 138 | 2017-01-10,29.25,29.700001,27.719999,27.790001,down 139 | 2017-01-11,27.450001,28.0,27.33,27.940001,up 140 | 2017-01-12,28.459999,28.719999,27.559,27.879999,down 141 | 2017-01-13,27.85,28.110001,27.41,27.959999,up 142 | 2017-01-17,27.9,28.059999,27.75,27.85,down 143 | 2017-01-18,27.77,27.832001,27.030001,27.59,down 144 | 2017-01-19,27.73,28.68,27.42,28.559999,up 145 | 2017-01-20,28.549999,29.0,28.02,28.379999,down 146 | 2017-01-23,28.379999,28.799999,28.150999,28.5,up 147 | 2017-01-24,28.469999,29.440001,28.219999,28.73,up 148 | 2017-01-25,29.190001,30.469999,28.825001,29.049999,up 149 | 2017-01-26,30.15,30.5,29.35,29.85,up 150 | 2017-01-27,29.92,29.989,28.85,29.440001,down 151 | 2017-01-30,29.41,29.41,28.280001,29.01,down 152 | 2017-01-31,28.700001,28.940001,28.43,28.83,down 153 | 2017-02-01,29.74,30.365,29.360001,30.049999,up 154 | 2017-02-02,29.870001,30.84,29.620001,30.1,up 155 | 2017-02-03,30.1,31.6,30.07,31.370001,up 156 | 2017-02-06,31.5,32.419998,31.299999,31.82,up 157 | 2017-02-07,32.299999,32.310001,30.83,30.959999,down 158 | 2017-02-08,31.709999,32.689999,29.75,31.440001,up 159 | 2017-02-09,31.440001,34.240002,30.75,32.810001,up 160 | 2017-02-10,31.77,33.389999,31.58,31.959999,down 161 | 2017-02-13,32.060001,34.950001,32.060001,34.900002,up 162 | 2017-02-14,33.860001,34.439999,32.880001,33.650002,down 163 | 2017-02-15,33.400002,33.860001,33.110001,33.419998,down 164 | 2017-02-16,33.650002,34.279999,32.763,33.169998,down 165 | 2017-02-17,33.169998,33.362,32.200001,32.349998,down 166 | 2017-02-21,32.470001,32.630001,31.396,31.959999,down 167 | 2017-02-22,31.91,32.445,31.735001,32.16,up 168 | 2017-02-23,32.310001,32.490002,31.4,31.67,down 169 | 2017-02-24,31.280001,32.279999,31.01,32.259998,up 170 | 2017-02-27,32.080002,33.330002,31.860001,32.639999,up 171 | 2017-02-28,32.16,32.240002,31.33,31.719999,down 172 | 2017-03-01,32.0,32.41,31.67,32.32,up 173 | 2017-03-02,32.040001,32.66,30.790001,31.030001,down 174 | 2017-03-03,30.74,30.889999,29.351,29.809999,down 175 | 2017-03-06,30.4,31.030001,29.83,30.889999,up 176 | 2017-03-07,30.65,31.33,30.49,30.74,down 177 | 2017-03-08,30.809999,31.16,30.587999,31.08,up 178 | 2017-03-09,31.1,31.84,30.85,31.32,up 179 | 2017-03-10,31.42,31.709999,31.030001,31.23,down 180 | 2017-03-13,31.15,32.669998,31.1,32.07,up 181 | 2017-03-14,31.91,31.950001,30.790001,31.07,down 182 | 2017-03-15,31.209999,31.389999,30.344,31.299999,up 183 | 2017-03-16,31.389999,32.622002,31.263,31.41,up 184 | 2017-03-17,31.09,31.790001,30.51,31.030001,down 185 | 2017-03-20,31.059999,31.49,30.76,31.200001,up 186 | 2017-03-21,31.120001,31.33,29.23,29.6,down 187 | 2017-03-22,29.639999,29.889999,28.969999,29.17,down 188 | 2017-03-23,29.24,29.5,28.950001,29.049999,down 189 | 2017-03-24,29.1,29.5,28.823,29.190001,up 190 | 2017-03-27,28.799999,29.82,28.360001,29.629999,up 191 | 2017-03-28,29.530001,30.059999,29.208,29.27,down 192 | 2017-03-29,29.25,29.25,28.75,28.780001,down 193 | 2017-03-30,28.67,28.889999,28.120001,28.620001,down 194 | 2017-03-31,28.469999,29.26,28.26,28.870001,up 195 | 2017-04-03,28.76,28.889999,28.190001,28.690001,down 196 | 2017-04-04,28.51,28.85,26.950001,27.27,down 197 | 2017-04-05,27.27,27.719999,26.82,26.93,down 198 | 2017-04-06,26.940001,27.139999,26.76,26.93,down 199 | 2017-04-07,28.5,28.549999,27.709999,28.17,up 200 | 2017-04-10,28.309999,28.870001,27.65,28.469999,up 201 | 2017-04-11,28.42,29.629999,28.1,29.35,up 202 | 2017-04-12,29.67,30.190001,29.200001,29.559999,up 203 | 2017-04-13,29.43,30.639999,29.4,30.290001,up 204 | -------------------------------------------------------------------------------- /twtr.csv: -------------------------------------------------------------------------------- 1 | 2013-11-08,45.93,46.939999,40.689999,41.650002,down 2 | 2013-11-11,40.5,43.0,39.400002,42.900002,up 3 | 2013-11-12,43.66,43.779999,41.830002,41.900002,down 4 | 2013-11-13,41.029999,42.869999,40.759998,42.599998,up 5 | 2013-11-14,42.34,45.669998,42.240002,44.689999,up 6 | 2013-11-15,45.25,45.27,43.43,43.98,down 7 | 2013-11-18,43.5,43.950001,40.849998,41.139999,down 8 | 2013-11-19,41.389999,41.900002,40.0,41.75,up 9 | 2013-11-20,41.400002,41.75,40.509998,41.049999,down 10 | 2013-11-21,41.25,42.490002,40.369999,42.060001,up 11 | 2013-11-22,41.810001,42.279999,40.970001,41.0,down 12 | 2013-11-25,41.080002,41.139999,38.799999,39.060001,down 13 | 2013-11-26,39.16,40.549999,38.919998,40.18,up 14 | 2013-11-27,40.470001,41.400002,40.349998,40.900002,up 15 | 2013-11-29,41.400002,41.580002,40.900002,41.57,up 16 | 2013-12-02,41.790001,42.0,40.400002,40.779999,down 17 | 2013-12-03,40.689999,41.599998,40.540001,41.369999,up 18 | 2013-12-04,41.27,43.919998,41.27,43.689999,up 19 | 2013-12-05,43.450001,46.349998,42.830002,45.619999,up 20 | 2013-12-06,45.75,45.799999,44.540001,44.950001,down 21 | 2013-12-09,45.59,49.84,45.02,49.139999,up 22 | 2013-12-10,48.900002,52.580002,48.700001,51.990002,up 23 | 2013-12-11,52.400002,53.869999,51.0,52.34,up 24 | 2013-12-12,52.200001,55.869999,50.689999,55.330002,up 25 | 2013-12-13,56.200001,59.41,55.450001,59.0,up 26 | 2013-12-16,57.860001,60.240002,55.759998,56.610001,down 27 | 2013-12-17,56.970001,57.380001,54.619999,56.450001,down 28 | 2013-12-18,57.0,57.0,54.23,55.509998,down 29 | 2013-12-19,55.080002,57.75,55.0,57.490002,up 30 | 2013-12-20,58.509998,60.25,58.009998,60.009998,up 31 | 2013-12-23,59.849998,64.989998,59.700001,64.540001,up 32 | 2013-12-24,66.339996,70.870003,65.559998,69.959999,up 33 | 2013-12-26,72.879997,74.730003,69.129997,73.309998,up 34 | 2013-12-27,70.099998,71.25,63.689999,63.75,down 35 | 2013-12-30,60.27,63.709999,58.57,60.509998,down 36 | 2013-12-31,62.360001,65.220001,61.650002,63.650002,up 37 | 2014-01-02,65.0,67.5,64.400002,67.5,up 38 | 2014-01-03,69.0,70.43,68.43,69.0,up 39 | 2014-01-06,64.830002,66.870003,63.5,66.290001,down 40 | 2014-01-07,67.669998,67.730003,61.389999,61.459999,down 41 | 2014-01-08,58.709999,61.259998,57.919998,59.290001,down 42 | 2014-01-09,59.540001,60.810001,55.59,57.049999,down 43 | 2014-01-10,57.5,58.759998,55.869999,57.0,down 44 | 2014-01-13,59.98,60.380001,57.290001,57.82,up 45 | 2014-01-14,58.880001,59.02,57.360001,58.209999,up 46 | 2014-01-15,59.110001,61.75,58.32,61.57,up 47 | 2014-01-16,61.450001,62.400002,60.459999,60.57,down 48 | 2014-01-17,63.599998,64.690002,61.59,62.200001,up 49 | 2014-01-21,63.330002,63.439999,61.5,62.529999,up 50 | 2014-01-22,63.110001,63.799999,61.759998,62.439999,down 51 | 2014-01-23,61.450001,62.810001,60.880001,62.799999,up 52 | 2014-01-24,62.169998,63.619999,61.299999,61.740002,down 53 | 2014-01-27,61.77,61.77,56.099998,57.91,down 54 | 2014-01-28,57.439999,60.849998,57.349998,60.439999,up 55 | 2014-01-29,59.619999,60.950001,58.599998,59.450001,down 56 | 2014-01-30,63.98,65.239998,62.799999,63.470001,up 57 | 2014-01-31,63.389999,65.370003,62.650002,64.5,up 58 | 2014-02-03,65.919998,66.480003,64.209999,65.25,up 59 | 2014-02-04,66.25,66.370003,64.5,66.32,up 60 | 2014-02-05,67.160004,67.239998,64.800003,65.970001,down 61 | 2014-02-06,50.610001,53.900002,49.990002,50.029999,down 62 | 2014-02-07,51.23,54.919998,50.75,54.349998,up 63 | 2014-02-10,54.5,54.59,52.34,52.919998,down 64 | 2014-02-11,53.200001,54.400002,53.099998,54.0,up 65 | 2014-02-12,55.049999,57.0,54.759998,56.849998,up 66 | 2014-02-13,56.07,58.98,55.459999,56.470001,down 67 | 2014-02-14,57.02,57.860001,56.700001,57.439999,up 68 | 2014-02-18,57.880001,58.639999,56.77,58.18,up 69 | 2014-02-19,58.470001,58.950001,54.619999,55.5,down 70 | 2014-02-20,55.82,57.080002,54.650002,56.630001,up 71 | 2014-02-21,57.099998,57.200001,55.700001,55.919998,down 72 | 2014-02-24,56.029999,56.490002,55.299999,55.779999,down 73 | 2014-02-25,55.889999,55.950001,54.5,54.959999,down 74 | 2014-02-26,55.0,56.990002,54.900002,55.869999,up 75 | 2014-02-27,56.34,56.689999,55.400002,55.77,down 76 | 2014-02-28,55.93,56.0,54.130001,54.91,down 77 | 2014-03-03,53.889999,54.400002,52.900002,53.709999,down 78 | 2014-03-04,54.25,55.279999,54.119999,54.279999,up 79 | 2014-03-05,54.529999,55.029999,53.75,54.380001,up 80 | 2014-03-06,54.91,56.09,54.700001,54.830002,up 81 | 2014-03-07,55.18,55.200001,53.310001,53.529999,down 82 | 2014-03-10,54.09,54.59,53.380001,53.880001,up 83 | 2014-03-11,54.16,55.84,53.799999,54.02,up 84 | 2014-03-12,54.25,55.299999,53.880001,54.5,up 85 | 2014-03-13,54.900002,55.450001,53.200001,53.57,down 86 | 2014-03-14,53.400002,53.91,51.799999,51.919998,down 87 | 2014-03-17,52.080002,52.490002,51.349998,52.049999,up 88 | 2014-03-18,52.029999,52.209999,50.290001,51.130001,down 89 | 2014-03-19,50.799999,51.98,50.709999,51.240002,up 90 | 2014-03-20,51.0,51.66,49.639999,50.119999,down 91 | 2014-03-21,50.240002,50.919998,49.509998,50.919998,up 92 | 2014-03-24,50.689999,50.939999,47.77,48.77,down 93 | 2014-03-25,49.349998,49.700001,47.580002,47.880001,down 94 | 2014-03-26,48.060001,48.299999,44.25,44.43,down 95 | 2014-03-27,45.09,46.400002,43.310001,46.32,up 96 | 2014-03-28,46.650002,47.34,45.700001,47.299999,up 97 | 2014-03-31,47.549999,47.75,46.43,46.669998,down 98 | 2014-04-01,46.709999,47.59,46.18,46.98,up 99 | 2014-04-02,47.400002,47.439999,45.509998,45.73,down 100 | 2014-04-03,45.48,45.610001,43.380001,44.049999,down 101 | 2014-04-04,44.200001,44.869999,42.369999,43.139999,down 102 | 2014-04-07,42.869999,44.599998,42.259998,42.450001,down 103 | 2014-04-08,43.419998,43.419998,41.549999,41.779999,down 104 | 2014-04-09,42.23,43.060001,41.77,42.490002,up 105 | 2014-04-10,42.849998,43.25,40.93,41.34,down 106 | 2014-04-11,40.790001,41.099998,39.68,40.049999,down 107 | 2014-04-14,41.400002,41.950001,40.119999,40.869999,up 108 | 2014-04-15,41.279999,45.549999,40.759998,45.52,up 109 | 2014-04-16,45.419998,45.560001,43.540001,44.419998,down 110 | 2014-04-17,44.66,46.549999,43.91,45.009998,up 111 | 2014-04-21,44.959999,46.299999,44.639999,46.130001,up 112 | 2014-04-22,46.23,47.09,45.799999,46.02,down 113 | 2014-04-23,45.880001,46.169998,44.869999,45.950001,down 114 | 2014-04-24,46.709999,46.790001,43.630001,44.82,down 115 | 2014-04-25,44.290001,44.439999,41.310001,41.610001,down 116 | 2014-04-28,41.759998,42.349998,39.299999,40.73,down 117 | 2014-04-29,40.529999,43.970001,40.169998,42.619999,up 118 | 2014-04-30,37.66,38.98,37.240002,38.970001,down 119 | 2014-05-01,39.009998,40.77,38.970001,39.09,up 120 | 2014-05-02,39.200001,39.860001,38.700001,39.02,down 121 | 2014-05-05,38.52,39.599998,38.049999,38.75,down 122 | 2014-05-06,35.610001,36.099998,31.719999,31.85,down 123 | 2014-05-07,31.969999,32.0,29.51,30.66,down 124 | 2014-05-08,31.48,32.98,31.129999,31.959999,up 125 | 2014-05-09,32.23,33.110001,31.75,32.049999,up 126 | 2014-05-12,33.080002,34.099998,32.400002,33.939999,up 127 | 2014-05-13,33.84,34.060001,32.889999,33.389999,down 128 | 2014-05-14,33.349998,33.830002,32.619999,32.849998,down 129 | 2014-05-15,33.02,33.290001,32.16,32.77,down 130 | 2014-05-16,32.950001,33.209999,32.02,32.259998,down 131 | 2014-05-19,32.049999,32.439999,31.639999,32.07,down 132 | 2014-05-20,32.0,32.389999,31.52,31.77,down 133 | 2014-05-21,31.85,31.950001,31.15,31.75,down 134 | 2014-05-22,31.33,32.25,30.52,31.52,down 135 | 2014-05-23,31.51,31.68,30.450001,30.5,down 136 | 2014-05-27,30.940001,31.200001,30.379999,30.51,up 137 | 2014-05-28,31.5,33.84,31.09,33.77,up 138 | 2014-05-29,34.669998,35.139999,33.880001,34.0,up 139 | 2014-05-30,33.73,33.860001,32.110001,32.439999,down 140 | 2014-06-02,32.889999,33.200001,31.620001,31.75,down 141 | 2014-06-03,31.73,32.689999,31.65,32.580002,up 142 | 2014-06-04,32.490002,33.32,31.85,32.900002,up 143 | 2014-06-05,33.669998,34.889999,33.110001,33.889999,up 144 | 2014-06-06,34.139999,34.41,33.220001,33.330002,down 145 | 2014-06-09,33.240002,34.549999,33.09,34.470001,up 146 | 2014-06-10,34.73,35.5,34.66,35.369999,up 147 | 2014-06-11,35.07,35.970001,34.93,35.540001,up 148 | 2014-06-12,35.060001,37.27,35.060001,36.790001,up 149 | 2014-06-13,36.849998,37.25,35.900002,36.900002,up 150 | 2014-06-16,36.700001,38.169998,36.439999,38.02,up 151 | 2014-06-17,38.029999,38.549999,37.299999,38.02,down 152 | 2014-06-18,38.16,38.830002,37.75,38.740002,up 153 | 2014-06-19,38.73,39.299999,38.32,38.900002,up 154 | 2014-06-20,38.82,39.240002,37.77,39.240002,up 155 | 2014-06-23,39.07,39.580002,38.73,39.52,up 156 | 2014-06-24,39.439999,39.639999,38.259998,38.48,down 157 | 2014-06-25,38.240002,39.59,38.009998,39.459999,up 158 | 2014-06-26,40.049999,42.0,39.810001,41.439999,up 159 | 2014-06-27,40.700001,41.150002,40.110001,40.93,down 160 | 2014-06-30,40.810001,41.34,40.349998,40.970001,up 161 | 2014-07-01,42.060001,42.950001,41.91,42.049999,up 162 | 2014-07-02,42.830002,42.830002,41.419998,41.77,down 163 | 2014-07-03,41.939999,42.0,40.830002,41.330002,down 164 | 2014-07-07,41.080002,41.450001,40.139999,40.23,down 165 | 2014-07-08,39.959999,40.040001,36.84,37.41,down 166 | 2014-07-09,37.82,38.349998,37.349998,38.060001,up 167 | 2014-07-10,36.490002,38.099998,36.110001,37.84,down 168 | 2014-07-11,38.150002,38.790001,38.0,38.330002,up 169 | 2014-07-14,38.57,39.380001,38.200001,38.310001,down 170 | 2014-07-15,38.59,38.990002,37.619999,37.880001,down 171 | 2014-07-16,38.310001,38.52,37.099998,37.43,down 172 | 2014-07-17,36.799999,37.169998,36.380001,36.869999,down 173 | 2014-07-18,36.810001,37.080002,35.950001,37.049999,up 174 | 2014-07-21,37.23,38.290001,36.849998,38.049999,up 175 | 2014-07-22,38.310001,38.599998,37.450001,37.650002,down 176 | 2014-07-23,37.650002,38.189999,37.560001,37.75,up 177 | 2014-07-24,38.709999,39.0,37.849998,38.709999,up 178 | 2014-07-25,38.200001,38.799999,38.02,38.16,down 179 | 2014-07-28,38.299999,38.439999,37.560001,37.93,down 180 | 2014-07-29,38.110001,38.919998,37.990002,38.59,up 181 | 2014-07-30,47.009998,48.0,45.650002,46.299999,up 182 | 2014-07-31,44.619999,45.84,44.299999,45.189999,down 183 | 2014-08-01,45.009998,45.540001,43.810001,44.130001,down 184 | 2014-08-04,43.700001,44.529999,43.439999,43.470001,down 185 | 2014-08-05,43.25,44.48,43.02,43.830002,up 186 | 2014-08-06,43.389999,44.040001,42.75,43.459999,down 187 | 2014-08-07,43.369999,44.369999,42.889999,43.0,down 188 | 2014-08-08,43.02,43.360001,42.509998,43.130001,up 189 | 2014-08-11,43.48,43.599998,42.709999,43.27,up 190 | 2014-08-12,44.380001,44.720001,43.610001,43.810001,up 191 | 2014-08-13,44.119999,44.34,43.619999,44.150002,up 192 | 2014-08-14,44.400002,45.34,44.040001,45.330002,up 193 | 2014-08-15,45.470001,45.5,44.439999,44.759998,down 194 | 2014-08-18,45.060001,45.330002,44.77,45.119999,up 195 | 2014-08-19,45.240002,45.450001,45.029999,45.09,down 196 | 2014-08-20,44.93,45.209999,44.759998,45.060001,down 197 | 2014-08-21,45.290001,45.349998,44.84,45.110001,up 198 | 2014-08-22,45.040001,46.139999,44.799999,45.98,up 199 | 2014-08-25,46.220001,46.360001,45.700001,46.099998,up 200 | 2014-08-26,46.099998,48.200001,46.040001,48.169998,up 201 | 2014-08-27,48.240002,48.459999,47.18,48.060001,down 202 | 2014-08-28,47.98,49.880001,47.860001,49.43,up 203 | 2014-08-29,49.889999,50.349998,49.130001,49.75,up 204 | 2014-09-02,50.02,51.34,49.900002,51.02,up 205 | 2014-09-03,51.830002,51.849998,49.049999,49.330002,down 206 | 2014-09-04,49.689999,50.860001,49.220001,50.240002,up 207 | 2014-09-05,50.09,50.880001,49.52,50.700001,up 208 | 2014-09-08,51.799999,52.68,51.68,52.0,up 209 | 2014-09-09,52.23,52.400002,50.220001,50.610001,down 210 | 2014-09-10,52.110001,53.330002,51.849998,52.91,up 211 | 2014-09-11,52.549999,53.639999,52.18,52.639999,down 212 | 2014-09-12,52.549999,52.82,52.02,52.110001,down 213 | 2014-09-15,51.599998,51.93,47.560001,49.380001,down 214 | 2014-09-16,48.700001,50.91,48.400002,50.830002,up 215 | 2014-09-17,50.970001,51.599998,50.16,50.700001,down 216 | 2014-09-18,50.970001,51.880001,50.529999,50.880001,up 217 | 2014-09-19,50.779999,53.0,50.18,53.0,up 218 | 2014-09-22,52.380001,52.900002,51.360001,51.939999,down 219 | 2014-09-23,51.459999,52.560001,51.02,52.169998,up 220 | 2014-09-24,52.549999,53.34,52.130001,52.959999,up 221 | 2014-09-25,52.709999,53.23,51.27,51.450001,down 222 | 2014-09-26,51.970001,52.610001,51.700001,51.889999,up 223 | 2014-09-29,51.09,52.18,50.880001,51.740002,down 224 | 2014-09-30,52.0,52.189999,51.169998,51.580002,down 225 | 2014-10-01,51.080002,51.290001,49.150002,50.060001,down 226 | 2014-10-02,51.029999,52.099998,50.009998,51.849998,up 227 | 2014-10-03,52.75,54.73,52.110001,53.939999,up 228 | 2014-10-06,53.939999,54.450001,53.23,53.490002,down 229 | 2014-10-07,53.119999,54.990002,53.099998,53.529999,up 230 | 2014-10-08,53.619999,55.669998,52.599998,55.419998,up 231 | 2014-10-09,55.290001,55.990002,54.919998,55.290001,down 232 | 2014-10-10,54.57,55.66,50.299999,50.400002,down 233 | 2014-10-13,50.540001,51.91,48.259998,48.490002,down 234 | 2014-10-14,49.060001,49.529999,47.080002,48.580002,up 235 | 2014-10-15,47.110001,50.52,46.380001,49.990002,up 236 | 2014-10-16,48.34,49.82,47.169998,48.23,down 237 | 2014-10-17,49.720001,50.25,48.650002,48.77,up 238 | 2014-10-20,49.07,50.889999,48.799999,50.700001,up 239 | 2014-10-21,51.759998,52.150002,50.299999,50.630001,down 240 | 2014-10-22,51.130001,51.84,49.0,49.080002,down 241 | 2014-10-23,50.130001,50.400002,49.200001,49.669998,up 242 | 2014-10-24,50.16,50.189999,49.150002,49.950001,up 243 | 2014-10-27,50.02,50.240002,47.18,48.560001,down 244 | 2014-10-28,42.25,44.580002,41.759998,43.779999,down 245 | 2014-10-29,43.849998,44.16,41.810001,42.080002,down 246 | 2014-10-30,41.560001,42.48,39.939999,41.799999,down 247 | 2014-10-31,42.689999,42.849998,41.34,41.470001,down 248 | 2014-11-03,40.549999,41.200001,40.16,40.209999,down 249 | 2014-11-04,40.029999,41.099998,39.75,40.900002,up 250 | 2014-11-05,41.689999,41.799999,40.130001,40.369999,down 251 | 2014-11-06,40.189999,41.349998,40.099998,40.84,up 252 | 2014-11-07,40.740002,40.740002,39.700001,40.310001,down 253 | 2014-11-10,40.34,40.689999,39.419998,39.59,down 254 | 2014-11-11,39.310001,39.84,38.810001,39.59,down 255 | 2014-11-12,39.939999,42.939999,39.599998,42.540001,up 256 | 2014-11-13,43.549999,43.950001,39.950001,40.040001,down 257 | 2014-11-14,40.02,41.849998,39.77,41.849998,up 258 | 2014-11-17,41.459999,41.68,40.41,40.470001,down 259 | 2014-11-18,40.689999,41.169998,39.950001,40.610001,up 260 | 2014-11-19,40.349998,40.470001,39.209999,39.709999,down 261 | 2014-11-20,39.490002,40.549999,39.32,39.810001,up 262 | 2014-11-21,40.25,40.279999,39.799999,40.029999,up 263 | 2014-11-24,39.990002,40.470001,39.580002,40.189999,up 264 | 2014-11-25,40.119999,40.299999,39.560001,39.759998,down 265 | 2014-11-26,39.830002,41.560001,39.740002,41.130001,up 266 | 2014-11-28,41.09,42.080002,40.830002,41.740002,up 267 | 2014-12-01,41.290001,41.290001,39.0,39.040001,down 268 | 2014-12-02,39.400002,39.400002,38.330002,38.91,down 269 | 2014-12-03,39.0,39.419998,38.380001,39.060001,up 270 | 2014-12-04,38.799999,39.66,38.619999,38.790001,down 271 | 2014-12-05,38.970001,39.07,38.349998,38.490002,down 272 | 2014-12-08,38.080002,38.119999,35.75,36.290001,down 273 | 2014-12-09,34.970001,37.09,34.619999,37.049999,up 274 | 2014-12-10,36.91,37.779999,36.25,36.349998,down 275 | 2014-12-11,36.450001,37.23,36.25,36.700001,up 276 | 2014-12-12,36.310001,37.709999,36.099998,37.099998,up 277 | 2014-12-15,38.130001,38.380001,36.73,36.849998,down 278 | 2014-12-16,36.5,36.709999,35.09,35.130001,down 279 | 2014-12-17,35.560001,35.900002,34.950001,35.57,up 280 | 2014-12-18,36.130001,37.27,35.950001,36.73,up 281 | 2014-12-19,36.700001,37.450001,36.5,37.080002,up 282 | 2014-12-22,37.5,38.82,37.310001,38.43,up 283 | 2014-12-23,38.580002,39.25,37.459999,37.57,down 284 | 2014-12-24,37.669998,38.349998,37.560001,37.610001,up 285 | 2014-12-26,37.759998,38.099998,37.540001,37.599998,down 286 | 2014-12-29,37.389999,37.509998,36.380001,36.419998,down 287 | 2014-12-30,36.02,36.240002,35.459999,35.860001,down 288 | 2014-12-31,35.889999,36.490002,35.470001,35.869999,up 289 | 2015-01-02,36.23,36.740002,35.540001,36.560001,up 290 | 2015-01-05,36.259998,37.110001,35.639999,36.380001,down 291 | 2015-01-06,36.27,39.450001,36.040001,38.759998,up 292 | 2015-01-07,39.099998,39.099998,37.060001,37.279999,down 293 | 2015-01-08,37.419998,39.189999,37.09,39.09,up 294 | 2015-01-09,39.220001,40.34,38.259998,40.169998,up 295 | 2015-01-12,40.279999,40.950001,39.299999,39.369999,down 296 | 2015-01-13,39.740002,40.349998,39.23,39.650002,up 297 | 2015-01-14,38.889999,40.18,38.799999,39.849998,up 298 | 2015-01-15,39.700001,39.700001,36.860001,36.93,down 299 | 2015-01-16,37.18,38.130001,36.849998,37.310001,up 300 | 2015-01-20,37.59,38.139999,36.540001,37.57,up 301 | 2015-01-21,37.650002,38.27,37.330002,37.830002,up 302 | 2015-01-22,37.98,39.25,37.549999,39.07,up 303 | 2015-01-23,39.48,39.970001,38.779999,39.419998,up 304 | 2015-01-26,39.330002,40.130001,39.040001,40.099998,up 305 | 2015-01-27,39.560001,39.610001,38.380001,38.919998,down 306 | 2015-01-28,38.43,38.779999,37.029999,37.150002,down 307 | 2015-01-29,37.389999,37.57,36.07,36.68,down 308 | 2015-01-30,36.650002,38.150002,36.41,37.529999,up 309 | 2015-02-02,37.700001,38.07,36.919998,37.459999,down 310 | 2015-02-03,38.0,40.189999,37.689999,39.790001,up 311 | 2015-02-04,40.049999,40.830002,39.82,40.720001,up 312 | 2015-02-05,42.040001,42.470001,40.91,41.259998,up 313 | 2015-02-06,46.119999,48.5,45.799999,48.009998,up 314 | 2015-02-09,46.73,47.689999,46.5,47.32,down 315 | 2015-02-10,47.349998,47.389999,45.57,46.259998,down 316 | 2015-02-11,46.27,47.779999,46.110001,47.5,up 317 | 2015-02-12,47.98,48.450001,46.880001,47.950001,up 318 | 2015-02-13,47.93,48.82,47.57,48.5,up 319 | 2015-02-17,48.200001,49.09,47.889999,48.029999,down 320 | 2015-02-18,48.0,48.790001,47.360001,47.82,down 321 | 2015-02-19,47.84,48.939999,47.419998,48.700001,up 322 | 2015-02-20,48.759998,49.880001,48.650002,49.110001,up 323 | 2015-02-23,49.02,49.240002,48.349998,48.470001,down 324 | 2015-02-24,48.330002,49.299999,48.060001,48.689999,up 325 | 2015-02-25,48.799999,49.18,48.25,48.549999,down 326 | 2015-02-26,48.810001,50.009998,48.639999,49.41,up 327 | 2015-02-27,49.189999,49.900002,47.959999,48.080002,down 328 | 2015-03-02,48.259998,48.299999,47.310001,48.150002,up 329 | 2015-03-03,48.130001,48.799999,47.439999,47.709999,down 330 | 2015-03-04,47.509998,47.849998,46.41,47.57,down 331 | 2015-03-05,47.59,48.43,47.200001,47.349998,down 332 | 2015-03-06,47.259998,48.07,46.57,46.75,down 333 | 2015-03-09,47.220001,48.080002,47.130001,47.59,up 334 | 2015-03-10,47.23,47.259998,45.790001,45.84,down 335 | 2015-03-11,45.66,46.740002,45.130001,46.27,up 336 | 2015-03-12,46.57,47.32,46.509998,47.07,up 337 | 2015-03-13,46.939999,47.720001,46.450001,46.66,down 338 | 2015-03-16,46.900002,47.07,46.049999,46.43,down 339 | 2015-03-17,46.66,47.290001,46.439999,46.93,up 340 | 2015-03-18,46.75,47.389999,46.16,47.200001,up 341 | 2015-03-19,46.959999,48.150002,46.450001,47.93,up 342 | 2015-03-20,48.360001,49.150002,48.25,48.439999,up 343 | 2015-03-23,48.240002,49.25,47.869999,48.459999,up 344 | 2015-03-24,48.669998,51.790001,48.540001,51.470001,up 345 | 2015-03-25,51.5,51.869999,49.310001,49.5,down 346 | 2015-03-26,49.650002,50.900002,49.400002,49.919998,up 347 | 2015-03-27,50.349998,50.889999,49.939999,50.009998,up 348 | 2015-03-30,50.450001,50.709999,48.66,49.889999,down 349 | 2015-03-31,49.619999,51.240002,49.540001,50.080002,up 350 | 2015-04-01,51.0,51.689999,50.169998,50.470001,up 351 | 2015-04-02,50.639999,50.950001,49.880001,50.419998,down 352 | 2015-04-06,50.029999,51.16,49.869999,50.84,up 353 | 2015-04-07,51.009998,53.279999,50.860001,52.869999,up 354 | 2015-04-08,53.32,53.490002,51.950001,52.299999,down 355 | 2015-04-09,52.150002,52.990002,51.540001,52.169998,down 356 | 2015-04-10,52.290001,52.450001,51.380001,51.939999,down 357 | 2015-04-13,51.990002,52.290001,51.450001,51.619999,down 358 | 2015-04-14,51.75,51.810001,50.68,51.200001,down 359 | 2015-04-15,51.330002,51.869999,50.91,51.299999,up 360 | 2015-04-16,51.299999,52.34,51.139999,52.029999,up 361 | 2015-04-17,51.709999,52.16,50.189999,50.66,down 362 | 2015-04-20,51.07,51.48,50.509998,51.400002,up 363 | 2015-04-21,51.68,51.849998,51.099998,51.32,down 364 | 2015-04-22,51.48,52.09,51.32,51.73,up 365 | 2015-04-23,51.869999,52.200001,51.220001,51.41,down 366 | 2015-04-24,51.849998,51.959999,50.240002,50.82,down 367 | 2015-04-27,50.84,52.540001,50.82,51.66,up 368 | 2015-04-28,52.16,52.220001,38.380001,42.27,down 369 | 2015-04-29,40.209999,41.09,38.07,38.490002,down 370 | 2015-04-30,39.279999,39.740002,38.48,38.959999,up 371 | 2015-05-01,39.189999,39.240002,37.369999,37.84,down 372 | 2015-05-04,38.720001,38.959999,37.549999,37.880001,up 373 | 2015-05-05,38.0,38.610001,37.360001,37.419998,down 374 | 2015-05-06,37.689999,37.779999,36.52,37.259998,down 375 | 2015-05-07,37.240002,37.880001,36.950001,37.709999,up 376 | 2015-05-08,38.02,38.200001,37.549999,37.59,down 377 | 2015-05-11,37.580002,37.860001,37.200001,37.310001,down 378 | 2015-05-12,37.290001,37.799999,37.060001,37.48,up 379 | 2015-05-13,37.66,38.200001,37.529999,37.720001,up 380 | 2015-05-14,37.93,38.09,37.27,37.330002,down 381 | 2015-05-15,37.360001,37.799999,37.0,37.099998,down 382 | 2015-05-18,37.099998,37.57,36.900002,37.279999,up 383 | 2015-05-19,37.139999,37.880001,36.900002,37.5,up 384 | 2015-05-20,37.490002,37.939999,36.540001,36.779999,down 385 | 2015-05-21,36.810001,36.939999,36.389999,36.68,down 386 | 2015-05-22,36.700001,36.98,36.57,36.599998,down 387 | 2015-05-26,36.669998,36.830002,36.369999,36.509998,down 388 | 2015-05-27,36.5,36.650002,36.099998,36.41,down 389 | 2015-05-28,36.490002,37.330002,36.369999,36.830002,up 390 | 2015-05-29,37.049999,37.07,36.529999,36.669998,down 391 | 2015-06-01,36.689999,36.830002,36.43,36.630001,down 392 | 2015-06-02,36.450001,36.599998,36.16,36.400002,down 393 | 2015-06-03,36.509998,37.169998,36.48,37.0,up 394 | 2015-06-04,37.169998,37.790001,36.509998,36.709999,down 395 | 2015-06-05,36.790001,37.23,36.650002,37.0,up 396 | 2015-06-08,36.91,36.98,36.41,36.459999,down 397 | 2015-06-09,36.5,36.5,35.57,35.880001,down 398 | 2015-06-10,36.009998,36.169998,35.599998,35.849998,down 399 | 2015-06-11,35.919998,36.169998,35.790001,35.84,down 400 | 2015-06-12,36.900002,37.25,35.549999,35.900002,up 401 | 2015-06-15,35.240002,35.259998,34.310001,34.669998,down 402 | 2015-06-16,34.23,35.200001,33.509998,34.82,up 403 | 2015-06-17,34.990002,35.119999,34.169998,34.689999,down 404 | 2015-06-18,34.630001,35.040001,34.450001,34.66,down 405 | 2015-06-19,34.970001,36.279999,34.849998,35.860001,up 406 | 2015-06-22,35.950001,36.0,35.34,35.549999,down 407 | 2015-06-23,35.779999,36.200001,34.959999,35.369999,down 408 | 2015-06-24,35.400002,35.75,35.099998,35.169998,down 409 | 2015-06-25,35.360001,35.360001,34.970001,35.169998,down 410 | 2015-06-26,34.970001,35.330002,34.669998,35.259998,up 411 | 2015-06-29,34.470001,35.09,34.150002,34.209999,down 412 | 2015-06-30,34.5,36.419998,34.439999,36.220001,up 413 | 2015-07-01,36.049999,36.110001,35.240002,35.400002,down 414 | 2015-07-02,35.400002,35.970001,35.099998,35.720001,up 415 | 2015-07-06,35.169998,35.689999,35.0,35.43,down 416 | 2015-07-07,35.349998,35.720001,34.549999,35.52,up 417 | 2015-07-08,35.41,36.049999,34.669998,34.759998,down 418 | 2015-07-09,35.169998,35.43,34.310001,34.360001,down 419 | 2015-07-10,34.68,35.119999,34.459999,34.91,up 420 | 2015-07-13,34.990002,36.139999,34.75,35.779999,up 421 | 2015-07-14,35.779999,38.82,35.77,36.720001,up 422 | 2015-07-15,36.66,37.09,35.549999,35.66,down 423 | 2015-07-16,35.889999,36.450001,35.75,36.099998,up 424 | 2015-07-17,36.459999,36.66,35.599998,35.669998,down 425 | 2015-07-20,35.75,35.990002,35.209999,35.810001,up 426 | 2015-07-21,35.82,36.75,35.709999,36.630001,up 427 | 2015-07-22,36.23,36.369999,35.509998,36.09,down 428 | 2015-07-23,36.0,36.73,35.950001,36.189999,up 429 | 2015-07-24,36.41,36.41,35.299999,35.419998,down 430 | 2015-07-27,35.110001,35.150002,33.880001,34.700001,down 431 | 2015-07-28,34.700001,36.669998,34.139999,36.540001,up 432 | 2015-07-29,32.59,33.240002,31.059999,31.24,down 433 | 2015-07-30,31.1,31.83,31.049999,31.469999,up 434 | 2015-07-31,31.379999,31.620001,30.85,31.01,down 435 | 2015-08-03,30.85,31.09,28.690001,29.27,down 436 | 2015-08-04,29.110001,29.9,28.9,29.34,up 437 | 2015-08-05,29.41,29.5,28.43,28.48,down 438 | 2015-08-06,28.4,28.43,27.23,27.540001,down 439 | 2015-08-07,27.799999,27.9,26.870001,27.040001,down 440 | 2015-08-10,28.09,29.629999,27.82,29.5,up 441 | 2015-08-11,29.01,29.889999,28.530001,29.620001,up 442 | 2015-08-12,29.110001,29.5,28.51,29.389999,down 443 | 2015-08-13,29.6,29.6,28.440001,28.540001,down 444 | 2015-08-14,28.5,29.27,28.450001,29.059999,up 445 | 2015-08-17,29.190001,29.34,28.93,29.059999,down 446 | 2015-08-18,28.91,29.0,28.299999,28.299999,down 447 | 2015-08-19,28.059999,28.09,27.16,27.610001,down 448 | 2015-08-20,27.15,27.48,25.92,26.0,down 449 | 2015-08-21,25.65,26.74,25.51,25.870001,down 450 | 2015-08-24,23.610001,26.23,21.01,25.17,down 451 | 2015-08-25,26.290001,26.33,24.379999,24.379999,down 452 | 2015-08-26,24.799999,25.290001,23.83,25.030001,up 453 | 2015-08-27,25.440001,26.799999,25.24,26.459999,up 454 | 2015-08-28,26.190001,26.93,26.059999,26.83,up 455 | 2015-08-31,27.639999,28.49,27.35,27.790001,up 456 | 2015-09-01,27.23,28.120001,26.77,27.030001,down 457 | 2015-09-02,27.469999,27.83,26.870001,27.82,up 458 | 2015-09-03,28.030001,29.0,27.809999,28.299999,up 459 | 2015-09-04,27.950001,28.549999,27.799999,28.15,down 460 | 2015-09-08,28.15,28.200001,27.01,27.18,down 461 | 2015-09-09,27.17,27.85,26.42,27.18,down 462 | 2015-09-10,27.07,27.83,26.950001,27.709999,up 463 | 2015-09-11,27.629999,27.65,27.17,27.389999,down 464 | 2015-09-14,27.209999,27.549999,26.799999,26.9,down 465 | 2015-09-15,27.040001,27.549999,27.0,27.17,up 466 | 2015-09-16,27.139999,28.0,27.0,27.75,up 467 | 2015-09-17,27.540001,27.93,27.030001,27.41,down 468 | 2015-09-18,27.040001,28.25,26.99,27.959999,up 469 | 2015-09-21,27.98,28.09,27.190001,27.379999,down 470 | 2015-09-22,27.049999,27.48,26.620001,26.83,down 471 | 2015-09-23,26.969999,27.280001,26.58,26.790001,down 472 | 2015-09-24,26.51,26.639999,25.4,26.6,down 473 | 2015-09-25,26.84,26.91,25.139999,25.290001,down 474 | 2015-09-28,24.959999,25.610001,24.6,25.26,down 475 | 2015-09-29,25.23,25.76,24.92,25.59,up 476 | 2015-09-30,25.940001,27.33,25.879999,26.940001,up 477 | 2015-10-01,26.469999,26.84,24.65,24.68,down 478 | 2015-10-02,24.5,26.48,24.34,26.309999,up 479 | 2015-10-05,26.99,28.25,26.33,28.15,up 480 | 2015-10-06,28.16,28.4,26.75,27.620001,down 481 | 2015-10-07,28.35,29.950001,28.01,29.83,up 482 | 2015-10-08,29.57,31.5,29.030001,30.32,up 483 | 2015-10-09,30.9,31.41,30.280001,30.85,up 484 | 2015-10-12,30.299999,30.77,28.6,28.75,down 485 | 2015-10-13,29.549999,30.68,28.84,29.059999,up 486 | 2015-10-14,29.459999,29.82,28.379999,29.379999,up 487 | 2015-10-15,29.459999,30.280001,29.01,29.709999,up 488 | 2015-10-16,30.08,31.4,29.360001,31.15,up 489 | 2015-10-19,31.15,31.6,30.57,30.91,down 490 | 2015-10-20,30.940001,31.389999,30.41,30.91,down 491 | 2015-10-21,29.5,29.66,28.65,29.299999,down 492 | 2015-10-22,29.24,29.799999,28.74,29.15,down 493 | 2015-10-23,29.969999,30.719999,29.610001,30.280001,up 494 | 2015-10-26,30.629999,31.219999,30.48,30.889999,up 495 | 2015-10-27,31.02,31.870001,30.65,31.34,up 496 | 2015-10-28,28.129999,31.34,27.76,30.870001,down 497 | 2015-10-29,30.58,30.700001,28.93,29.059999,down 498 | 2015-10-30,29.129999,29.57,28.35,28.459999,down 499 | 2015-11-02,28.540001,29.290001,28.049999,29.200001,up 500 | 2015-11-03,29.09,29.629999,29.040001,29.129999,down 501 | 2015-11-04,29.360001,30.15,29.23,29.360001,up 502 | 2015-11-05,29.469999,29.549999,28.450001,28.66,down 503 | 2015-11-06,28.58,28.700001,28.049999,28.280001,down 504 | 2015-11-09,28.07,28.209999,26.68,27.09,down 505 | 2015-11-10,26.809999,27.17,26.25,27.049999,down 506 | 2015-11-11,27.08,27.139999,26.370001,26.5,down 507 | 2015-11-12,26.08,26.610001,25.85,26.129999,down 508 | 2015-11-13,25.889999,26.16,25.16,25.18,down 509 | 2015-11-16,25.33,25.780001,25.0,25.41,up 510 | 2015-11-17,25.540001,25.690001,24.9,25.23,down 511 | 2015-11-18,25.17,26.09,25.16,25.9,up 512 | 2015-11-19,25.940001,26.58,25.93,26.32,up 513 | 2015-11-20,26.32,26.700001,26.030001,26.27,down 514 | 2015-11-23,26.110001,26.27,25.02,25.200001,down 515 | 2015-11-24,25.17,25.549999,25.02,25.52,up 516 | 2015-11-25,25.620001,26.41,25.59,26.059999,up 517 | 2015-11-27,25.98,26.07,25.67,25.75,down 518 | 2015-11-30,25.780001,25.82,25.059999,25.4,down 519 | 2015-12-01,25.389999,25.58,25.0,25.530001,up 520 | 2015-12-02,25.309999,25.719999,25.17,25.4,down 521 | 2015-12-03,25.48,26.059999,24.91,25.9,up 522 | 2015-12-04,25.809999,25.85,25.01,25.02,down 523 | 2015-12-07,24.99,25.16,24.129999,24.459999,down 524 | 2015-12-08,24.040001,25.1,23.540001,24.99,up 525 | 2015-12-09,24.98,24.98,24.190001,24.309999,down 526 | 2015-12-10,24.360001,26.25,24.34,25.91,up 527 | 2015-12-11,25.91,26.200001,24.799999,24.84,down 528 | 2015-12-14,24.68,24.940001,23.700001,24.92,up 529 | 2015-12-15,24.52,24.690001,23.700001,23.950001,down 530 | 2015-12-16,23.959999,24.48,23.799999,24.299999,up 531 | 2015-12-17,24.469999,24.75,23.290001,23.309999,down 532 | 2015-12-18,23.35,23.440001,22.66,22.99,down 533 | 2015-12-21,23.02,23.040001,21.99,22.139999,down 534 | 2015-12-22,22.26,22.67,22.09,22.559999,up 535 | 2015-12-23,22.68,22.950001,22.370001,22.67,up 536 | 2015-12-24,22.700001,23.059999,22.549999,22.969999,up 537 | 2015-12-28,22.9,23.32,22.5,22.530001,down 538 | 2015-12-29,22.629999,22.82,22.309999,22.469999,down 539 | 2015-12-30,22.450001,22.940001,22.209999,22.23,down 540 | 2015-12-31,22.17,23.280001,22.15,23.139999,up 541 | 2016-01-04,22.639999,22.84,22.110001,22.559999,down 542 | 2016-01-05,22.790001,23.0,21.85,21.92,down 543 | 2016-01-06,21.620001,22.18,21.18,21.389999,down 544 | 2016-01-07,21.0,21.48,20.200001,20.26,down 545 | 2016-01-08,20.51,20.719999,19.6,19.98,down 546 | 2016-01-11,20.120001,20.200001,19.26,19.65,down 547 | 2016-01-12,19.870001,20.41,19.32,19.620001,down 548 | 2016-01-13,19.700001,19.76,18.469999,18.68,down 549 | 2016-01-14,18.549999,19.16,17.27,19.0,up 550 | 2016-01-15,18.23,18.530001,17.610001,17.940001,down 551 | 2016-01-19,18.18,18.18,16.43,16.690001,down 552 | 2016-01-20,16.16,19.040001,15.48,17.379999,up 553 | 2016-01-21,17.440001,18.32,16.799999,17.83,up 554 | 2016-01-22,18.290001,18.559999,17.73,17.84,up 555 | 2016-01-25,16.799999,17.450001,16.51,17.02,down 556 | 2016-01-26,17.219999,17.280001,16.4,17.01,down 557 | 2016-01-27,17.01,17.620001,16.77,16.780001,down 558 | 2016-01-28,17.209999,17.34,16.450001,16.49,down 559 | 2016-01-29,16.639999,17.07,16.51,16.799999,up 560 | 2016-02-01,17.889999,18.77,17.299999,17.91,up 561 | 2016-02-02,17.219999,17.27,16.01,16.08,down 562 | 2016-02-03,16.33,16.74,15.55,16.559999,up 563 | 2016-02-04,16.4,17.18,16.290001,16.91,up 564 | 2016-02-05,16.610001,16.639999,15.62,15.72,down 565 | 2016-02-08,15.51,15.55,14.73,14.9,down 566 | 2016-02-09,14.62,15.55,14.31,14.4,down 567 | 2016-02-10,14.55,15.28,14.52,14.98,up 568 | 2016-02-11,14.07,14.79,13.91,14.31,down 569 | 2016-02-12,14.54,15.94,14.53,15.88,up 570 | 2016-02-16,16.09,16.4,15.67,16.360001,up 571 | 2016-02-17,16.469999,17.6,16.43,17.459999,up 572 | 2016-02-18,18.1,18.549999,17.52,18.43,up 573 | 2016-02-19,18.16,18.879999,17.77,18.309999,down 574 | 2016-02-22,18.620001,18.68,17.76,18.299999,down 575 | 2016-02-23,18.559999,18.959999,18.1,18.299999,down 576 | 2016-02-24,18.0,18.09,17.110001,18.0,down 577 | 2016-02-25,17.93,17.950001,17.309999,17.59,down 578 | 2016-02-26,17.719999,18.030001,17.5,17.940001,up 579 | 2016-02-29,17.959999,18.57,17.780001,18.120001,up 580 | 2016-03-01,18.469999,18.48,17.59,17.85,down 581 | 2016-03-02,17.85,18.74,17.719999,18.540001,up 582 | 2016-03-03,18.530001,19.440001,18.48,19.309999,up 583 | 2016-03-04,19.450001,20.32,19.059999,19.360001,up 584 | 2016-03-07,19.110001,19.73,18.77,19.17,down 585 | 2016-03-08,19.1,19.15,18.33,18.33,down 586 | 2016-03-09,18.610001,18.74,17.52,17.66,down 587 | 2016-03-10,17.690001,17.77,16.379999,16.610001,down 588 | 2016-03-11,16.77,16.940001,16.459999,16.809999,up 589 | 2016-03-14,16.809999,17.32,16.790001,17.120001,up 590 | 2016-03-15,17.0,17.040001,16.139999,16.190001,down 591 | 2016-03-16,16.33,16.77,16.129999,16.700001,up 592 | 2016-03-17,16.65,17.15,16.620001,16.85,up 593 | 2016-03-18,17.08,17.379999,16.76,16.85,down 594 | 2016-03-21,16.83,17.049999,16.68,16.889999,up 595 | 2016-03-22,16.75,17.01,16.700001,16.860001,down 596 | 2016-03-23,16.860001,16.91,16.01,16.01,down 597 | 2016-03-24,15.94,15.99,15.57,15.91,down 598 | 2016-03-28,15.98,16.01,15.4,15.6,down 599 | 2016-03-29,15.69,15.99,15.33,15.97,up 600 | 2016-03-30,16.16,16.719999,16.01,16.360001,up 601 | 2016-03-31,16.4,16.84,16.209999,16.549999,up 602 | 2016-04-01,16.41,16.43,15.83,15.98,down 603 | 2016-04-04,16.0,17.540001,15.96,17.09,up 604 | 2016-04-05,17.59,17.83,16.889999,17.049999,down 605 | 2016-04-06,17.120001,17.48,16.9,17.26,up 606 | 2016-04-07,16.879999,17.59,16.85,16.98,down 607 | 2016-04-08,17.120001,17.25,16.41,16.65,down 608 | 2016-04-11,16.74,16.98,16.41,16.51,down 609 | 2016-04-12,16.5,16.77,16.15,16.57,up 610 | 2016-04-13,16.68,17.4,16.68,17.370001,up 611 | 2016-04-14,17.379999,17.700001,17.139999,17.530001,up 612 | 2016-04-15,17.52,17.91,17.309999,17.58,up 613 | 2016-04-18,17.709999,17.719999,17.059999,17.309999,down 614 | 2016-04-19,17.370001,17.389999,16.68,16.92,down 615 | 2016-04-20,16.940001,17.52,16.9,17.4,up 616 | 2016-04-21,17.48,17.77,17.42,17.51,up 617 | 2016-04-22,17.33,17.51,17.02,17.23,down 618 | 2016-04-25,17.200001,17.75,16.879999,17.09,down 619 | 2016-04-26,17.209999,17.98,17.08,17.75,up 620 | 2016-04-27,15.15,15.28,14.81,14.86,down 621 | 2016-04-28,14.85,15.09,14.62,14.64,down 622 | 2016-04-29,14.7,14.93,14.32,14.62,down 623 | 2016-05-02,14.73,14.77,14.17,14.4,down 624 | 2016-05-03,14.22,14.25,13.9,14.01,down 625 | 2016-05-04,13.95,14.88,13.92,14.84,up 626 | 2016-05-05,14.93,14.98,14.08,14.12,down 627 | 2016-05-06,14.12,14.4,13.98,14.4,up 628 | 2016-05-09,14.28,14.47,14.15,14.2,down 629 | 2016-05-10,14.17,14.69,14.16,14.63,up 630 | 2016-05-11,14.61,14.86,14.44,14.59,down 631 | 2016-05-12,14.63,14.68,14.0,14.08,down 632 | 2016-05-13,14.06,14.28,14.0,14.1,up 633 | 2016-05-16,14.09,14.37,14.06,14.29,up 634 | 2016-05-17,14.21,14.59,14.13,14.34,up 635 | 2016-05-18,14.35,14.57,14.05,14.14,down 636 | 2016-05-19,14.15,14.31,14.04,14.15,up 637 | 2016-05-20,14.2,14.51,14.16,14.43,up 638 | 2016-05-23,14.4,14.6,14.33,14.41,down 639 | 2016-05-24,14.22,14.22,13.73,14.03,down 640 | 2016-05-25,14.07,14.57,14.06,14.41,up 641 | 2016-05-26,14.45,14.48,14.19,14.3,down 642 | 2016-05-27,14.25,15.1,14.23,15.1,up 643 | 2016-05-31,15.12,15.49,15.08,15.22,up 644 | 2016-06-01,15.22,15.22,14.62,15.02,down 645 | 2016-06-02,15.04,15.26,14.85,15.2,up 646 | 2016-06-03,15.11,15.35,14.96,15.2,down 647 | 2016-06-06,15.22,15.45,15.18,15.27,up 648 | 2016-06-07,15.36,15.37,14.91,15.0,down 649 | 2016-06-08,15.07,15.12,14.81,14.95,down 650 | 2016-06-09,14.84,14.86,14.59,14.6,down 651 | 2016-06-10,14.45,14.45,14.0,14.02,down 652 | 2016-06-13,14.63,15.3,14.51,14.55,up 653 | 2016-06-14,14.82,15.42,14.8,15.36,up 654 | 2016-06-15,15.71,16.440001,15.71,15.96,up 655 | 2016-06-16,15.9,15.95,15.4,15.87,down 656 | 2016-06-17,16.16,16.370001,15.96,16.1,up 657 | 2016-06-20,16.34,16.639999,16.15,16.34,up 658 | 2016-06-21,16.48,16.559999,16.17,16.32,down 659 | 2016-06-22,16.27,16.32,16.049999,16.129999,down 660 | 2016-06-23,16.299999,17.07,16.280001,17.040001,up 661 | 2016-06-24,16.24,16.9,16.200001,16.440001,down 662 | 2016-06-27,16.290001,16.4,15.46,15.84,down 663 | 2016-06-28,16.24,16.639999,16.16,16.42,up 664 | 2016-06-29,16.6,17.01,16.43,16.83,up 665 | 2016-06-30,16.799999,17.0,16.73,16.91,up 666 | 2016-07-01,16.93,17.5,16.9,17.280001,up 667 | 2016-07-05,17.25,17.280001,16.76,17.139999,down 668 | 2016-07-06,17.02,17.34,16.809999,17.200001,up 669 | 2016-07-07,17.24,17.68,17.24,17.370001,up 670 | 2016-07-08,17.530001,18.16,17.469999,18.08,up 671 | 2016-07-11,17.59,17.879999,17.52,17.709999,down 672 | 2016-07-12,17.98,18.379999,17.92,18.1,up 673 | 2016-07-13,18.209999,18.32,17.5,17.74,down 674 | 2016-07-14,18.02,18.280001,17.91,17.959999,up 675 | 2016-07-15,17.98,18.18,17.809999,18.08,up 676 | 2016-07-18,18.290001,18.75,18.049999,18.65,up 677 | 2016-07-19,18.51,18.9,18.27,18.33,down 678 | 2016-07-20,18.52,18.76,18.450001,18.559999,up 679 | 2016-07-21,18.57,18.799999,18.35,18.389999,down 680 | 2016-07-22,18.120001,18.389999,17.76,18.370001,down 681 | 2016-07-25,18.43,18.700001,18.17,18.65,up 682 | 2016-07-26,18.52,18.65,18.16,18.450001,down 683 | 2016-07-27,16.34,16.59,15.69,15.77,down 684 | 2016-07-28,15.89,16.34,15.88,16.309999,up 685 | 2016-07-29,16.389999,16.74,16.24,16.639999,up 686 | 2016-08-01,16.65,16.85,16.4,16.639999,down 687 | 2016-08-02,16.610001,16.700001,16.200001,16.42,down 688 | 2016-08-03,16.34,17.879999,16.33,17.610001,up 689 | 2016-08-04,17.57,18.309999,17.360001,18.129999,up 690 | 2016-08-05,18.190001,18.58,18.139999,18.26,up 691 | 2016-08-08,18.25,18.48,17.93,18.200001,down 692 | 2016-08-09,18.17,18.790001,17.969999,18.68,up 693 | 2016-08-10,18.67,19.57,18.559999,19.040001,up 694 | 2016-08-11,19.17,19.83,19.110001,19.780001,up 695 | 2016-08-12,19.709999,19.709999,19.01,19.540001,down 696 | 2016-08-15,19.85,21.1,19.83,20.860001,up 697 | 2016-08-16,20.780001,20.790001,20.290001,20.4,down 698 | 2016-08-17,20.43,20.440001,19.9,20.17,down 699 | 2016-08-18,19.559999,19.6,18.92,19.0,down 700 | 2016-08-19,18.959999,19.309999,18.76,18.98,down 701 | 2016-08-22,18.950001,18.959999,18.52,18.549999,down 702 | 2016-08-23,18.65,18.93,18.65,18.690001,up 703 | 2016-08-24,18.799999,18.969999,18.200001,18.25,down 704 | 2016-08-25,18.33,18.65,18.23,18.32,up 705 | 2016-08-26,18.4,18.530001,18.1,18.299999,down 706 | 2016-08-29,18.389999,18.549999,18.299999,18.469999,up 707 | 2016-08-30,18.59,18.690001,18.32,18.379999,down 708 | 2016-08-31,18.389999,19.6,18.379999,19.209999,up 709 | 2016-09-01,19.370001,20.139999,19.27,19.5,up 710 | 2016-09-02,19.620001,19.870001,19.35,19.549999,up 711 | 2016-09-06,19.74,20.139999,19.48,19.93,up 712 | 2016-09-07,20.049999,20.65,19.799999,19.870001,down 713 | 2016-09-08,18.809999,19.309999,18.59,18.700001,down 714 | 2016-09-09,18.4,18.82,17.92,18.110001,down 715 | 2016-09-12,17.959999,18.24,17.68,18.15,up 716 | 2016-09-13,17.99,18.1,17.52,17.76,down 717 | 2016-09-14,17.93,18.389999,17.9,18.08,up 718 | 2016-09-15,18.299999,18.42,18.059999,18.299999,up 719 | 2016-09-16,18.9,19.25,18.74,19.110001,up 720 | 2016-09-19,19.219999,19.24,18.280001,18.360001,down 721 | 2016-09-20,18.299999,18.639999,18.23,18.389999,up 722 | 2016-09-21,18.440001,18.5,18.129999,18.49,up 723 | 2016-09-22,18.52,18.92,18.440001,18.629999,up 724 | 2016-09-23,21.5,22.889999,21.110001,22.620001,up 725 | 2016-09-26,21.790001,23.57,21.65,23.370001,up 726 | 2016-09-27,23.209999,23.98,22.9,23.719999,up 727 | 2016-09-28,23.42,23.629999,22.440001,22.959999,down 728 | 2016-09-29,22.92,23.360001,22.860001,23.01,up 729 | 2016-09-30,23.02,23.25,22.82,23.049999,up 730 | 2016-10-03,23.780001,24.25,23.459999,24.0,up 731 | 2016-10-04,23.75,23.790001,23.34,23.52,down 732 | 2016-10-05,24.32,25.25,24.129999,24.870001,up 733 | 2016-10-06,20.459999,21.0,19.6,19.870001,down 734 | 2016-10-07,19.950001,20.530001,19.65,19.85,down 735 | 2016-10-10,17.49,18.24,16.93,17.559999,down 736 | 2016-10-11,18.18,18.200001,17.65,18.0,up 737 | 2016-10-12,18.190001,18.190001,17.809999,18.049999,up 738 | 2016-10-13,17.860001,17.99,17.67,17.790001,down 739 | 2016-10-14,17.879999,18.049999,16.280001,16.879999,down 740 | 2016-10-17,16.76,16.98,16.43,16.73,down 741 | 2016-10-18,16.860001,17.129999,16.790001,16.83,up 742 | 2016-10-19,16.940001,17.26,16.879999,17.07,up 743 | 2016-10-20,17.040001,17.07,16.82,16.9,down 744 | 2016-10-21,16.950001,18.35,16.74,18.09,up 745 | 2016-10-24,17.6,18.370001,17.49,18.030001,down 746 | 2016-10-25,17.82,17.84,17.15,17.26,down 747 | 2016-10-26,17.58,17.66,17.17,17.290001,up 748 | 2016-10-27,17.290001,18.120001,17.07,17.4,up 749 | 2016-10-28,17.700001,18.0,17.5,17.66,up 750 | 2016-10-31,17.65,18.040001,17.639999,17.950001,up 751 | 2016-11-01,17.84,18.0,17.26,17.49,down 752 | 2016-11-02,17.43,17.950001,17.379999,17.610001,up 753 | 2016-11-03,17.549999,17.860001,17.26,17.58,down 754 | 2016-11-04,17.52,18.34,17.5,18.02,up 755 | 2016-11-07,18.110001,18.690001,18.110001,18.41,up 756 | 2016-11-08,18.219999,18.559999,17.77,18.379999,down 757 | 2016-11-09,17.959999,19.24,17.91,19.129999,up 758 | 2016-11-10,19.040001,19.299999,18.030001,18.370001,down 759 | 2016-11-11,18.35,18.73,18.07,18.549999,up 760 | 2016-11-14,18.75,19.200001,18.5,19.139999,up 761 | 2016-11-15,19.15,19.51,18.91,18.98,down 762 | 2016-11-16,18.98,19.15,18.59,18.629999,down 763 | 2016-11-17,18.700001,18.959999,18.530001,18.549999,down 764 | 2016-11-18,18.73,18.91,18.639999,18.73,up 765 | 2016-11-21,18.719999,18.91,18.59,18.6,down 766 | 2016-11-22,18.66,18.870001,18.51,18.629999,up 767 | 2016-11-23,18.450001,18.59,18.08,18.219999,down 768 | 2016-11-25,18.27,18.309999,18.030001,18.059999,down 769 | 2016-11-28,18.0,18.299999,17.85,18.299999,up 770 | 2016-11-29,18.219999,18.68,18.129999,18.190001,down 771 | 2016-11-30,18.200001,18.799999,18.18,18.49,up 772 | 2016-12-01,18.82,18.83,17.74,18.030001,down 773 | 2016-12-02,18.0,18.16,17.860001,17.93,down 774 | 2016-12-05,17.959999,18.360001,17.870001,18.23,up 775 | 2016-12-06,18.309999,18.5,18.129999,18.23,down 776 | 2016-12-07,18.26,19.549999,18.200001,19.48,up 777 | 2016-12-08,19.5,19.709999,19.08,19.639999,up 778 | 2016-12-09,19.559999,19.84,19.379999,19.65,up 779 | 2016-12-12,19.48,19.700001,18.9,18.93,down 780 | 2016-12-13,18.969999,19.59,18.940001,19.370001,up 781 | 2016-12-14,19.4,19.620001,18.889999,18.93,down 782 | 2016-12-15,18.940001,19.15,18.709999,18.790001,down 783 | 2016-12-16,18.76,18.889999,18.530001,18.629999,down 784 | 2016-12-19,18.6,18.700001,18.219999,18.24,down 785 | 2016-12-20,18.23,18.32,17.870001,17.92,down 786 | 2016-12-21,17.52,17.549999,17.01,17.08,down 787 | 2016-12-22,16.82,16.889999,16.27,16.41,down 788 | 2016-12-23,16.34,16.67,16.16,16.5,up 789 | 2016-12-27,16.52,16.870001,16.42,16.610001,up 790 | 2016-12-28,16.629999,16.73,16.290001,16.389999,down 791 | 2016-12-29,16.389999,16.65,16.299999,16.389999,down 792 | 2016-12-30,16.309999,16.57,16.219999,16.299999,down 793 | 2017-01-03,16.309999,16.450001,16.209999,16.440001,up 794 | 2017-01-04,16.5,16.940001,16.5,16.860001,up 795 | 2017-01-05,16.91,17.27,16.799999,17.09,up 796 | 2017-01-06,17.24,17.43,17.110001,17.17,up 797 | 2017-01-09,17.219999,17.559999,17.190001,17.5,up 798 | 2017-01-10,17.51,17.780001,17.32,17.370001,down 799 | 2017-01-11,17.459999,17.6,17.17,17.299999,down 800 | 2017-01-12,17.129999,17.389999,16.959999,17.379999,up 801 | 2017-01-13,17.379999,17.66,17.23,17.25,down 802 | 2017-01-17,17.07,17.09,16.860001,16.959999,down 803 | 2017-01-18,17.01,17.139999,16.83,17.110001,up 804 | 2017-01-19,17.09,17.15,16.75,16.790001,down 805 | 2017-01-20,16.82,16.9,16.459999,16.58,down 806 | 2017-01-23,16.57,16.809999,16.459999,16.610001,up 807 | 2017-01-24,16.610001,16.66,16.33,16.52,down 808 | 2017-01-25,16.700001,16.790001,16.59,16.73,up 809 | 2017-01-26,16.860001,17.07,16.790001,16.809999,up 810 | 2017-01-27,16.91,16.969999,16.530001,16.57,down 811 | 2017-01-30,16.57,17.1,16.41,16.940001,up 812 | 2017-01-31,16.950001,17.74,16.91,17.620001,up 813 | 2017-02-01,17.84,17.92,17.1,17.24,down 814 | 2017-02-02,17.33,17.860001,17.120001,17.780001,up 815 | 2017-02-03,17.719999,17.85,17.440001,17.610001,down 816 | 2017-02-06,17.700001,17.969999,17.41,17.93,up 817 | 2017-02-07,18.0,18.67,17.99,18.26,up 818 | 2017-02-08,18.77,18.77,18.049999,18.719999,up 819 | 2017-02-09,18.719999,18.719999,16.26,16.41,down 820 | 2017-02-10,15.96,16.0,15.5,15.58,down 821 | 2017-02-13,15.63,15.99,15.51,15.81,up 822 | 2017-02-14,15.92,16.6,15.85,16.52,up 823 | 2017-02-15,16.85,16.889999,16.299999,16.74,up 824 | 2017-02-16,16.690001,16.790001,16.32,16.35,down 825 | 2017-02-17,16.360001,16.629999,16.360001,16.620001,up 826 | 2017-02-21,16.639999,16.690001,16.299999,16.42,down 827 | 2017-02-22,16.4,16.51,16.01,16.08,down 828 | 2017-02-23,16.120001,16.27,15.9,16.030001,down 829 | 2017-02-24,15.95,15.99,15.85,15.98,down 830 | 2017-02-27,15.93,16.129999,15.72,16.059999,up 831 | 2017-02-28,16.0,16.040001,15.74,15.77,down 832 | 2017-03-01,15.87,15.9,15.59,15.79,up 833 | 2017-03-02,15.77,16.0,15.72,15.79,down 834 | 2017-03-03,15.84,16.1,15.68,15.75,down 835 | 2017-03-06,15.75,15.78,15.5,15.56,down 836 | 2017-03-07,15.52,15.73,15.16,15.18,down 837 | 2017-03-08,15.19,15.36,15.08,15.24,up 838 | 2017-03-09,15.24,15.39,15.03,15.22,down 839 | 2017-03-10,15.23,15.27,14.94,15.12,down 840 | 2017-03-13,15.1,15.27,15.1,15.21,up 841 | 2017-03-14,15.2,15.58,15.15,15.32,up 842 | 2017-03-15,15.25,15.3,14.85,15.03,down 843 | 2017-03-16,15.08,15.28,15.04,15.19,up 844 | 2017-03-17,15.2,15.23,15.03,15.08,down 845 | 2017-03-20,15.11,15.11,14.82,15.09,up 846 | 2017-03-21,15.08,15.1,14.5,14.54,down 847 | 2017-03-22,14.5,14.99,14.32,14.98,up 848 | 2017-03-23,14.99,15.05,14.73,14.93,down 849 | 2017-03-24,15.06,15.37,15.03,15.14,up 850 | 2017-03-27,15.02,15.06,14.75,14.99,down 851 | 2017-03-28,15.0,15.17,14.8,14.94,down 852 | 2017-03-29,14.86,15.06,14.7,15.04,up 853 | 2017-03-30,15.05,15.08,14.9,14.92,down 854 | 2017-03-31,14.93,15.06,14.91,14.95,up 855 | 2017-04-03,14.97,14.98,14.65,14.84,down 856 | 2017-04-04,14.75,14.76,14.58,14.69,down 857 | 2017-04-05,14.61,14.82,14.41,14.53,down 858 | 2017-04-06,14.53,14.62,14.3,14.39,down 859 | 2017-04-07,14.36,14.43,14.25,14.29,down 860 | 2017-04-10,14.3,14.46,14.2,14.36,up 861 | 2017-04-11,14.3,14.4,14.2,14.31,down 862 | 2017-04-12,14.34,14.78,14.26,14.42,up 863 | 2017-04-13,14.49,14.5,14.22,14.3,down 864 | --------------------------------------------------------------------------------