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[blotter] Annotation of /pkg/quantstrat/demo/faber.R
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Annotation of /pkg/quantstrat/demo/faber.R

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1 : peter_carl 287 # This is a very simple trend following strategy for testing the results of:
2 :     # Faber, Mebane T., "A Quantitative Approach to Tactical Asset Allocation."
3 :     # Journal of Risk Management (Spring 2007).
4 :     # The article proposes a very simple quantitative market-timing model. They
5 :     # test the model in sample on the US stock market since 1900 before testing
6 :     # it out-of-sample in twenty other markets.
7 :    
8 :     # The article discusses a 200-day simple moving average, which is proposed
9 :     # in Jeremy Seigel's book "Stocks for the Long Run" for timing the DJIA. He
10 :     # concludes that a simple market timing strategy improves the absolute and
11 :     # risk adjusted returns over a buy-and-hold strategy. After all transaction
12 :     # costs are included, the timing strategy falls short on the absolute return,
13 :     # but still provides a better risk-adjusted return. Siegel also tests timing on
14 :     # the Nasdaq composite since 1972 and finds better absolute and risk adjusted
15 :     # returns.
16 :    
17 :     # The article implements a simpler version of the 200-day SMA, opting for a
18 :     # 10-month SMA. Monthly data is more easily available for long periods of time,
19 :     # and the lower granularity should translate to lower transaction costs.
20 :    
21 :     # The rules of the system are relatively simple:
22 :     # - Buy when monthly price > 10-month SMA
23 :     # - Sell and move to cash when monthly price < 10-month SMA
24 :    
25 :     # 1. All entry and exit prices are on the day of the signal at the close.
26 :     # 2. All data series are total return series including dividends, updated monthly.
27 :     # For the purposes of this demo, we only use price returns.
28 :     # 3. Cash returns are estimated with 90-day commercial paper. Margin rates for
29 :     # leveraged models are estimated with the broker call rate. Again, for the
30 :     # purposes of this demo, we ignore interest and leverage.
31 :     # 4. Taxes, commissions, and slippage are excluded.
32 :    
33 :     # This simple strategy is different from well-known trend-following systems in
34 :     # three respects. First, there's no shorting. Positions are converted to cash on
35 :     # a 'sell' signal, rather than taking a short position. Second, the entire position
36 :     # is put on at trade inception. No assumptions are made about increasing position
37 :     # size as the trend progresses. Third, there are no stops. If the trend reverts
38 :     # quickly, this system will wait for a sell signal before selling the position.
39 :    
40 :     # Data
41 :     # Instead of using total returns data, this demo uses monthly data for the SP500
42 :     # downloaded from Yahoo Finance. We'll use about 10 years of data, starting at
43 :     # the beginning of 1998.
44 :    
45 :     # Load required libraries
46 :     require(quantstrat)
47 :    
48 :     # Try to clean up in case the demo was run previously
49 : gsee 621 suppressWarnings(rm("account.faber","portfolio.faber",pos=.blotter))
50 :     suppressWarnings(rm("ltaccount", "ltportfolio", "ClosePrice", "CurrentDate", "equity",
51 :     "GSPC", "stratFaber", "initDate", "initEq", "Posn", "UnitSize", "verbose"))
52 :     suppressWarnings(rm("order_book.faber",pos=.strategy))
53 : peter_carl 287
54 :     # Set initial values
55 :     initDate='1997-12-31'
56 :     initEq=100000
57 :    
58 :     # Set up instruments with FinancialInstruments package
59 :     currency("USD")
60 :     symbols = c("XLF", "XLP", "XLE", "XLY", "XLV", "XLI", "XLB", "XLK", "XLU")
61 :     for(symbol in symbols){ # establish tradable instruments
62 :     stock(symbol, currency="USD",multiplier=1)
63 :     }
64 :    
65 :     # Load data with quantmod
66 :     #getSymbols(symbols, src='yahoo', index.class=c("POSIXt","POSIXct"), from='1998-01-01')
67 :     ### Download monthly data instead?
68 :     ### GSPC=to.monthly(GSPC, indexAt='endof')
69 :     getSymbols(symbols, src='yahoo', index.class=c("POSIXt","POSIXct"), from='1999-01-01')
70 :     for(symbol in symbols) {
71 :     x<-get(symbol)
72 :     x<-to.monthly(x,indexAt='lastof',drop.time=TRUE)
73 :     indexFormat(x)<-'%Y-%m-%d'
74 :     colnames(x)<-gsub("x",symbol,colnames(x))
75 :     assign(symbol,x)
76 :     }
77 :    
78 :     # Initialize portfolio and account
79 : braverock 362 initPortf('faber', symbols=symbols, initDate=initDate)
80 : braverock 599 initAcct('faber', portfolios='faber', initDate=initDate, initEq=100000)
81 : braverock 362 initOrders(portfolio='faber', initDate=initDate)
82 : peter_carl 287
83 :     print("setup completed")
84 :    
85 :     # Initialize a strategy object
86 : braverock 370 stratFaber <- strategy("faber")
87 : peter_carl 287
88 :     # Add an indicator
89 : braverock 371 stratFaber <- add.indicator(strategy = stratFaber, name = "SMA", arguments = list(x = quote(Cl(mktdata)), n=10), label="SMA10")
90 : peter_carl 287
91 :     # There are two signals:
92 :     # The first is when monthly price crosses over the 10-month SMA
93 : gsee 639 stratFaber <- add.signal(stratFaber,name="sigCrossover",arguments = list(columns=c("Close","SMA10"),relationship="gte"),label="Cl.gt.SMA")
94 : peter_carl 287 # The second is when the monthly price crosses under the 10-month SMA
95 : braverock 371 stratFaber <- add.signal(stratFaber,name="sigCrossover",arguments = list(columns=c("Close","SMA10"),relationship="lt"),label="Cl.lt.SMA")
96 : peter_carl 287
97 :     # There are two rules:
98 :     # The first is to buy when the price crosses above the SMA
99 : braverock 599 stratFaber <- add.rule(stratFaber, name='ruleSignal', arguments = list(sigcol="Cl.gt.SMA", sigval=TRUE, orderqty=1000, ordertype='market', orderside='long', pricemethod='market',TxnFees=-5), type='enter', path.dep=TRUE)
100 : peter_carl 287 # The second is to sell when the price crosses below the SMA
101 : braverock 599 stratFaber <- add.rule(stratFaber, name='ruleSignal', arguments = list(sigcol="Cl.lt.SMA", sigval=TRUE, orderqty='all', ordertype='market', orderside='long', pricemethod='market',TxnFees=-5), type='exit', path.dep=TRUE)
102 : peter_carl 287
103 :     # Process the indicators and generate trades
104 :     start_t<-Sys.time()
105 : braverock 370 out<-try(applyStrategy(strategy=stratFaber , portfolios='faber'))
106 : peter_carl 287 end_t<-Sys.time()
107 :     print("Strategy Loop:")
108 :     print(end_t-start_t)
109 :    
110 :     # look at the order book
111 : braverock 362 #print(getOrderBook('faber'))
112 : peter_carl 287
113 :     start_t<-Sys.time()
114 : braverock 362 updatePortf(Portfolio='faber',Dates=paste('::',as.Date(Sys.time()),sep=''))
115 : peter_carl 287 end_t<-Sys.time()
116 :     print("trade blotter portfolio update:")
117 :     print(end_t-start_t)
118 :    
119 : braverock 309 # hack for new quantmod graphics, remove later
120 :     themelist<-chart_theme()
121 : braverock 450 themelist$col$up.col<-'lightgreen'
122 :     themelist$col$dn.col<-'pink'
123 : peter_carl 287 for(symbol in symbols){
124 :     dev.new()
125 : braverock 362 chart.Posn(Portfolio='faber',Symbol=symbol,theme=themelist)
126 : braverock 309 plot(add_SMA(n=10,col='darkgreen', on=1))
127 : peter_carl 287 }
128 :    
129 : braverock 599 ret1 <- PortfReturns('faber')
130 :     ret1$total<-rowSums(ret1)
131 :     ret1
132 : peter_carl 287
133 : braverock 599 if("package:PerformanceAnalytics" %in% search() || require("PerformanceAnalytics",quietly=TRUE)){
134 :     getSymbols("SPY", src='yahoo', index.class=c("POSIXt","POSIXct"), from='1999-01-01')
135 :     SPY<-to.monthly(SPY)
136 :     SPY.ret<-Return.calculate(SPY$SPY.Close)
137 :     index(SPY.ret)<-index(ret1)
138 :     dev.new()
139 :     charts.PerformanceSummary(cbind(ret1$total,SPY.ret), geometric=FALSE, wealth.index=TRUE)
140 :     }
141 :    
142 : braverock 1212 faber.stats<-tradeStats('faber')[,c('Net.Trading.PL','Max.Drawdown','Num.Trades','Profit.Factor','Std.Dev.Trade.PL','Largest.Winner','Largest.Loser','Max.Equity','Min.Equity')]
143 : braverock 599 faber.stats
144 :    
145 : peter_carl 287 ###############################################################################
146 :     # R (http://r-project.org/) Quantitative Strategy Model Framework
147 :     #
148 : braverock 1194 # Copyright (c) 2009-2012
149 : gsee 639 # Peter Carl, Dirk Eddelbuettel, Brian G. Peterson,
150 :     # Jeffrey Ryan, Joshua Ulrich, and Garrett See
151 : peter_carl 287 #
152 :     # This library is distributed under the terms of the GNU Public License (GPL)
153 :     # for full details see the file COPYING
154 :     #
155 :     # $Id$
156 :     #
157 : braverock 599 ###############################################################################

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