marketcalls

_SECTION_BEGIN("Volume For 1st Hour");

//Cumulative Volume Monitor Start Time and End Time

starttime = ParamTime( "Start Time", "09:15" );
endtime = ParamTime( "End Time", "10:15" );


Bars_so_far_today = 1 + BarsSince( Day() != Ref(Day(), -1));
StartBar = ValueWhen(TimeNum() == starttime, BarIndex());

marketcalls

#Compute Percentage Change
rets = d.pct_change()

#Compute Correlation
corr = rets.corr()

#Plot Correlation Matrix using Matplotlib
%pylab inline
plt.figure(figsize=(10, 10))
plt.imshow(corr, cmap='RdYlGn', interpolation='none', aspect='auto')

marketcalls

d= pd.DataFrame()
j=0
for i in sym:
    result = get_price_history(stock=i, start=date(2016,10,1), end=date(2016,11,15))
    if result.empty:
        pass
    else: 
        s2=result[['Close']]
        s2=s2.rename(columns = {'Close':i})
        if j==0:

marketcalls

#Import Python Packages

from nsepy.archives import get_price_history
from datetime import date
import pandas as pd
import matplotlib.pyplot as plt

#Create Stocks Watchlist for which correlation martrix is to be plotted.

sym=["SBIN","BHEL","ACC","GAIL","TATAMOTORS","TCS","INFY","SUNPHARMA","IDEA","RELIANCE"]

marketcalls

////////////////////////////////////////////////////////////
//  Copyright by Rajandran R v1.0 22/08/2016
//  Website : www.marketcalls.in 
////////////////////////////////////////////////////////////
study(title="Sentimental RSI - Marketcalls")
source = hlc3, length = input(7, minval=1)
hullma = wma(2*wma(source, length/2)-wma(source, length), round(sqrt(length)))
hrsi = rsi(hullma,length)
bcolor = iff( hrsi-50 > 0, 
            iff( hrsi > nz(hrsi[1]), lime, blue),

marketcalls

SetPositionSize(1,spsShares);

Buy = ROC(C,1)< -0.5 AND DayOfWeek()==5;
BuyPrice = Close;

Sell = DayOfWeek()!=5; //Sell on Next Day
//Sell = DayOfWeek()==1; //Sell on Monday
SellPrice = Close;

marketcalls

////////////////////////////////////////////////////////////
//  Copyright by Rajandran R v1.0 22/08/2016
//  Website : www.marketcalls.in 
////////////////////////////////////////////////////////////
study(title="Sentimental RSI - Marketcalls")
source = hlc3, length = input(7, minval=1)
hullma = wma(2*wma(source, length/2)-wma(source, length), round(sqrt(length)))
hrsi = rsi(hullma,length)
bcolor = iff( hrsi-50 > 0, 
            iff( hrsi > nz(hrsi[1]), lime, blue),

marketcalls

//Coded by Rajandran R
//Website : www.marketcalls.in


_SECTION_BEGIN("Predict Cycle");
SetChartOptions(0,chartShowArrows|chartShowDates);

_N(Title = StrFormat("{{NAME}} - {{INTERVAL}} {{DATE}} Open %g, Hi %g, Lo %g, Close %g (%.1f%%) {{VALUES}} - Cycle analysis indicator from www.marketcalls.in", O, H, L, C, SelectedValue( ROC( C, 1 ) ) ));

Plot( C, "Close", colorDefault, styleNoTitle | ParamStyle("Style") | GetPriceStyle() ); 

marketcalls

FixedDollarAmount = 5000; //SIP monthly Rs5000
MonthBegin = Month() != Ref( Month(), -1 ); 

FirstPurchase = Cum( MonthBegin ) == 1; 

Buy = IIf( FirstPurchase, 1, // True (or 1) represents regular buy signal 
      IIf( MonthBegin, sigScaleIn, // each month increase position 
           0 ) ); // otherwise no signal 

Sell = 0; // we do not sell 

marketcalls

_SECTION_BEGIN("Price");
SetChartOptions(0,chartShowArrows|chartShowDates);
_N(Title = StrFormat("{{NAME}} - {{INTERVAL}} {{DATE}} Open %g, Hi %g, Lo %g, Close %g (%.1f%%) {{VALUES}}", O, H, L, C, SelectedValue( ROC( C, 1 ) ) ));
Plot( C, "Close", ParamColor("Color", colorBlack ), styleNoTitle | ParamStyle("Style") | GetPriceStyle() ); 
_SECTION_END();


_SECTION_BEGIN("Ichimoku Hayo Kinko");
GraphXSpace =1;
prds = Param("Standard Line Periods?", 12,5,26,1);