I was trying to create a volume weighted average price using python.
Here is my code:
vwap = []
for i in range(window, int(price_times_qty)):
vol_total = 0
vol_price = 0
for j in range(window):
vol_total = vol_total + lastqty[i-j]
vol_price = vol_price + lastqty[i-j] * lastprice[i-j]
vwap.append( vol_price / vol_total )
I believe my idea is right, but when I execute the code, I have the error:
Traceback (most recent call last):
File "<ipython-input-9-9724942aa7be>", line 1, in <module>
runfile('/home/intern2/Desktop/VWAP/vwap-v1.py', wdir='/home/intern2/Desktop/VWAP')
File "/usr/lib/python3/dist-packages/spyderlib/widgets/externalshell/sitecustomize.py", line 586, in runfile
execfile(filename, namespace)
File "/usr/lib/python3/dist-packages/spyderlib/widgets/externalshell/sitecustomize.py", line 48, in execfile
exec(compile(open(filename, 'rb').read(), filename, 'exec'), namespace)
File "/home/intern2/Desktop/VWAP/vwap-v1.py", line 25, in <module>
vol_total = vol_total + lastqty[i-j]
IndexError: index out of bounds
I just have no idea why the error is index out of bound. When I check my code, I think the index is well within the bound.
Could anyone please help me with it?
Related
I am trying to run the following strategy:
def max_n(array, n):
return np.argpartition(array, -n)[-n:]
class CrossSectionalMR(bt.Strategy):
params = (
('num_positions', 100),
)
def __init__(self, temp):
self.inds = {}
for d in self.datas:
self.inds[d] = {}
self.inds[d]["pct"] = bt.indicators.PercentChange(d.close, period=1)
def prenext(self):
self.next()
def next(self):
available = list(filter(lambda d: len(d), self.datas)) # only look at data that existed yesterday
rets = np.zeros(len(available))
for i, d in enumerate(available):
rets[i] = self.inds[d]['pct'][0]
market_ret = np.mean(rets)
weights = -(rets - market_ret)
max_weights_index = max_n(np.abs(weights), self.params.num_positions)
max_weights = weights[max_weights_index]
weights = weights / np.sum(np.abs(max_weights))
for i, d in enumerate(available):
if i in max_weights_index:
self.order_target_percent(d, target=weights[i])
else:
self.order_target_percent(d, 0)
The full error is:
Traceback (most recent call last):
File "/home/poblivsig/Software/pycharm-2020.3.1/plugins/python/helpers/pydev/pydevd.py", line 1477, in _exec
pydev_imports.execfile(file, globals, locals) # execute the script
File "/home/poblivsig/Software/pycharm-2020.3.1/plugins/python/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "/home/poblivsig/Dropbox/meanrev/main.py", line 190, in <module>
dd, cagr, sharpe = backtest(datas, CrossSectionalMR, plot=True, num_positions=100)
File "/home/poblivsig/Dropbox/meanrev/main.py", line 181, in backtest
results = cerebro.run()
File "/home/poblivsig/Dropbox/meanrev/venv/lib/python3.8/site-packages/backtrader/cerebro.py", line 1127, in run
runstrat = self.runstrategies(iterstrat)
File "/home/poblivsig/Dropbox/meanrev/venv/lib/python3.8/site-packages/backtrader/cerebro.py", line 1293, in runstrategies
self._runonce(runstrats)
File "/home/poblivsig/Dropbox/meanrev/venv/lib/python3.8/site-packages/backtrader/cerebro.py", line 1652, in _runonce
strat._once()
File "/home/poblivsig/Dropbox/meanrev/venv/lib/python3.8/site-packages/backtrader/lineiterator.py", line 297, in _once
indicator._once()
File "/home/poblivsig/Dropbox/meanrev/venv/lib/python3.8/site-packages/backtrader/lineiterator.py", line 297, in _once
indicator._once()
File "/home/poblivsig/Dropbox/meanrev/venv/lib/python3.8/site-packages/backtrader/linebuffer.py", line 630, in _once
self.oncestart(self._minperiod - 1, self._minperiod)
File "/home/poblivsig/Dropbox/meanrev/venv/lib/python3.8/site-packages/backtrader/lineroot.py", line 165, in oncestart
self.once(start, end)
File "/home/poblivsig/Dropbox/meanrev/venv/lib/python3.8/site-packages/backtrader/linebuffer.py", line 672, in once
dst[i] = src[i + ago]
IndexError: array assignment index out of range
python-BaseExceptio
Any help would be greatly appreciated.
I grab the data from Yahoo and store it in csv files which are then loaded up and added to Cerebro. Sometimes, the code cannot get the full list of the SPY, but I don't think that is the problem here.
I am getting the above error.
I Already installed opencv-contrib module but still not working out
def dictionary(descriptors, N):
em = cv2.EM(N)
em.train(descriptors)
Traceback (most recent call last):
File "", line 1, in
runfile('C:/Users/Ankuran Das/Desktop/Pyhton/Case/fishvec.py', wdir='C:/Users/Ankuran Das/Desktop/Pyhton/Case')
File "D:\Anaconda\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
execfile(filename, namespace)
File "D:\Anaconda\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "C:/Users/Ankuran Das/Desktop/Pyhton/Case/fishvec.py", line 141, in
gmm = generate_gmm(working_folder,args.number)
File "C:/Users/Ankuran Das/Desktop/Pyhton/Case/fishvec.py", line 87, in generate_gmm
means, covs, weights = dictionary(words, N)
File "C:/Users/Ankuran Das/Desktop/Pyhton/Case/fishvec.py", line 16, in dictionary
em = cv2.EM.train(N)
AttributeError: module 'cv2.cv2' has no attribute 'EM'
Try the following lines of codes:
em = cv2.ml.EM_create()
em.setClustersNumber(N)
em.trainEM(descriptors)
I am trying to use XGBoost library using .train function and DMatrix but I am a little stuck because of an error :
Traceback (most recent call last):
File "", line 1, in
runfile('E:/CrossValidation.py', wdir='E:/')
File
"C:\Users\users\Anaconda3\envs\Lightgbm\lib\site-packages\spyder\utils\site\sitecustomize.py",
line 705, in runfile
execfile(filename, namespace)
File
"C:\Users\users\Anaconda3\envs\Lightgbm\lib\site-packages\spyder\utils\site\sitecustomize.py",
line 102, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "E:/CrossValidation.py", line 218, in
mainXGB()
File "E:/CrossValidation.py", line 214, in mainXGB
crossval_preds, val_preds = cv.train(X_data=X_train.values, y_data=y_train.values, X_test=X_val.values, params=xgb_params)
File "E:/CrossValidation.py", line 136, in train
early_stopping_rounds=early_stopping_rounds)
File
"C:\Users\users\Anaconda3\envs\Lightgbm\lib\site-packages\xgboost\training.py",
line 204, in train
xgb_model=xgb_model, callbacks=callbacks)
File
"C:\Users\users\Anaconda3\envs\Lightgbm\lib\site-packages\xgboost\training.py",
line 32, in _train_internal
bst = Booster(params, [dtrain] + [d[0] for d in evals])
File
"C:\Users\users\Anaconda3\envs\Lightgbm\lib\site-packages\xgboost\training.py",
line 32, in
bst = Booster(params, [dtrain] + [d[0] for d in evals])
TypeError: 'DMatrix' object does not support indexing
Here my piece of code :
dtrain = xgb.DMatrix(X_data[train_idx], label=np.log1p(y_data[train_idx])) # datas.slice(train_idx)
dtest = xgb.DMatrix(X_data[val_idx], label=np.log1p(y_data[val_idx]))
print('data created for xgboost')
model = self.model_base.train(params=params, dtrain=dtrain, num_boost_round=number_iteration, evals=[dtest], early_stopping_rounds=early_stopping_rounds)
Does anyone know how to solve the problem ?
The problem is with the evals argument. A list of tuples is expected, so change evals=[dtest] to evals=[(dtest, "Test")].
I am trying to run a regression using the following dataframe dfMyRoll the head of the dataframe looks like:
SCORE SCORE_LAG
date
2007-10-29 -0.031551 NaN
2007-10-30 0.000100 -0.031551
2007-10-31 0.000100 0.000100
2007-11-01 0.000100 0.000100
2007-11-02 0.000100 0.000100
The code that I am using is :
import glob
import pandas as pd
import os.path
import scipy
from scipy.stats import linregress
def main():
dataPath = "C:/Users/Stacey/Documents/data/Roll"
roll = 4
1ID = "BBG.XNGS.AAPL.S"
2ID = "BBG.XNGS.AMAT.S"
print(1ID,1ID)
cointergration = getCointergration(dataPath,1ID,2ID,roll)
return
def getCointergration(dataPath,1ID,2ID,roll):
for myRoll in range((roll-4),roll,1):
path = dataPath+str(myRoll)+'/'
filename='PairData_'+1ID+'_'+2ID+'.csv'
for fname in glob.iglob(path+filename):
dfMyRoll = pd.read_csv(fname, header=0, usecols=[0,31],parse_dates=[0], dayfirst=True,index_col=[0], names=['date', 'SCORE'])
dfMyRoll['SCORE_LAG'] = dfMyRoll['SCORE'].shift(1)
print('cointergration',dfMyRoll.head())
X = dfMyRoll[1:,'SCORE']
Y = dfMyRoll[1:,'SCORE_LAG']
slope,intercept,_,_,stderr=linregress(dfMyRoll[1:,'SCORE'],dfMyRoll[1:,'SCORE_LAG'])
if __name__ == "__main__":
print ("CointergrationTest...19/05/17")
try:
main()
except KeyboardInterrupt:
print ("Ctrl+C pressed. Stopping...")
I get the error: TypeError: unhashable type: 'slice'. I have looked at previous posts on this subject and tried adding iloc to the X and Y time series in the following way:
X = dfMyRoll.iloc[1:,'SCORE']
Y = dfMyRoll.iloc[1:,'SCORE_LAG']
but unfortunately I can't seem to find a solution. Please see below for a stack trace:
Traceback (most recent call last):
File "<ipython-input-3-431422978139>", line 1, in <module>
runfile('C:/Users/Stacey/Documents/scripts/cointergrationTest.py', wdir='C:/Users/Stacey/Documents/scripts')
File "C:\Anaconda\lib\site-packages\spyder\utils\site\sitecustomize.py", line 866, in runfile
execfile(filename, namespace)
File "C:\Anaconda\lib\site-packages\spyder\utils\site\sitecustomize.py", line 102, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "C:/Users/Stacey/Documents/scripts/cointergrationTest.py", line 64, in <module>
main()
File "C:/Users/Stacey/Documents/scripts/cointergrationTest.py", line 23, in main
cointergration = getCointergration(dataPath,1ID,2ID,roll)
File "C:/Users/Stacey/Documents/scripts/cointergrationTest.py", line 42, in getCointergration
X = dfMyRoll[1:,'SCORE']
File "C:\Anaconda\lib\site-packages\pandas\core\frame.py", line 2059, in __getitem__
return self._getitem_column(key)
File "C:\Anaconda\lib\site-packages\pandas\core\frame.py", line 2066, in _getitem_column
return self._get_item_cache(key)
File "C:\Anaconda\lib\site-packages\pandas\core\generic.py", line 1384, in _get_item_cache
res = cache.get(item)
TypeError: unhashable type: 'slice'
You need to use loc rather than iloc:
X = dfMyRoll.loc[1:,'SCORE']
Y = dfMyRoll.loc[1:,'SCORE_LAG']
iloc is read as "integer location", and only accepts integer position. loc is somewhat more forgiving and allows both (you can also use ix).
I am trying to run some simle example with Pyomo + glpk Solver (Anaconda2 64bit Spyder):
from pyomo.environ import *
model = ConcreteModel()
model.x_1 = Var(within=NonNegativeReals)
model.x_2 = Var(within=NonNegativeReals)
model.obj = Objective(expr=model.x_1 + 2*model.x_2)
model.con1 = Constraint(expr=3*model.x_1 + 4*model.x_2 >= 1)
model.con2 = Constraint(expr=2*model.x_1 + 5*model.x_2 >= 2)
opt = SolverFactory("glpk")
instance = model.create()
#results = opt.solve(instance)
#results.write()
But i get the following error message:
invalid literal for int() with base 10: 'c'
Traceback (most recent call last):
File "<ipython-input-5-e074641da66d>", line 1, in <module>
runfile('D:/..../Exampe.py', wdir='D:.../exercises/pyomo')
File "C:\...\Continuum\Anaconda21\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 699, in runfile
execfile(filename, namespace)
File "C:\....\Continuum\Anaconda21\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 74, in execfile
exec(compile(scripttext, filename, 'exec'), glob, loc)
File "D:/...pyomo/Exampe.py", line 34, in <module>
results = opt.solve(instance)
File "C:\....\Continuum\Anaconda21\lib\site-packages\pyomo\opt\base\solvers.py", line 580, in solve
result = self._postsolve()
File "C:\...Continuum\Anaconda21\lib\site-packages\pyomo\opt\solver\shellcmd.py", line 267, in _postsolve
results = self.process_output(self._rc)
File "C:\...\Continuum\Anaconda21\lib\site-packages\pyomo\opt\solver\shellcmd.py", line 329, in process_output
self.process_soln_file(results)
File "C:\....\Continuum\Anaconda21\lib\site-packages\pyomo\solvers\plugins\solvers\GLPK.py", line 454, in process_soln_file
raise ValueError(msg)
ValueError: Error parsing solution data file, line 1
I downloaded glpk from http://winglpk.sourceforge.net/ --> unziped + added parth to the environmental variable "path".
Hope someone can help me - thank you!
This is a known problem with GLPK 4.60 (glpsol changed the format of their output which broke Pyomo 4.3's parser). You can either download an older release of GLPK, or upgrade Pyomo to 4.4.1 (which contains an updated parser).