QUANTSTRAT - 如何针对某项资产制定策略并将其用于另一项资产？
QUANTSTRAT - How to build a strategy on a certain asset and use it on another one?
我正在写我的 MSc 期末论文，我一直在尝试使用 quantstrat 包开发交易策略。我想做的是通过观察基于 VIX 的 MACD 生成的信号来交易 SPY。
我很难在 VIX 上制定策略，然后在 SPY 上使用它。
我想获取 VIX 并计算 MACD。当 VIX 的 MACD 向下穿过信号线时，我希望算法买入 SPY。当 VIX 的 MACD 向上穿过信号线时，我希望算法平仓。
这是我写到现在的代码：
# MACD strategy on VIX and SPY (SPDR S&P500 FUND)
#
# I will use MACD as trend indicator.
#
# This is the main idea.
#
# I want to make prediction on SPY's returns. Due to the EMH, returns are not predictable.
# Otherwise, the volatility clustering effect allows us to forecast volatility.
# The VIX is the S&P500's implied volatility index. I can make previsions about it and use them
# to forecast the SPY returns. This is because S&P500 and VIX have a strong negative correlation.
#
# This strategy consists of buying/selling the SPY when the VIX's MACD generates sell/buy signal
#
# Author: Matteo Cavaggioni, 2016
######################################################################################################################
require(quantstrat)
ttz <- Sys.getenv('TZ')
Sys.setenv(TZ = 'UTC')
#startDate <- '2000-01-01'
initDate <- '2004-01-02'
endDate <- '2015-12-31'
initEq <- 1e6
fastMA <- 12
slowMA <- 26
signalMA <- 9
maType <- "EMA"
symb1 <- '^VIX'
symb2 <- 'SPY'
portfolio1.st <- "vmacd"
portfolio2.st <- "smacd"
account.st <- "vsmacd"
getSymbols(c(symb1, symb2), from = initDate, to = endDate, adjust = TRUE, index.class = c("POSIXt", "POSIXct"))
symb1 <- 'VIX'
currency("USD")
stock(symb1, currency = "USD", multiplier = 1)
stock(symb2, currency = "USD", multiplier = 1)
volStrat <- 'volStrat'
rm.strat(volStrat)
initPortf(name = portfolio1.st, symbols = symb1, initDate = initDate) # portafoglio contenente il VIX
initPortf(name = portfolio2.st, symbols = symb2, initDate = initDate) # portafoglio contenente lo SPY
initAcct(name = account.st, portfolios = c(portfolio1.st, portfolio2.st), initEq = initEq, initDate = initDate)
initOrders(portfolio = portfolio2.st, initDate = initDate)
volStrat <- strategy('volStrat', store = TRUE, assets = symb1)
volStrat <- add.indicator(strategy = volStrat, name = "MACD",
arguments = list(x = quote(Ad(mktdata)),
nFast = fastMA,
nSlow = slowMA,
nSig = signalMA,
maType = maType),
label = 'macd.out')
#####
volStrat <- add.signal(strategy = volStrat, name = "sigCrossover",
arguments = list(columns = c("macd.macd.out", "signal.macd.out"),
relationship = "gt"),
label = "macd.gt.signal")
volStrat <- add.signal(strategy = volStrat, name = "sigCrossover",
arguments = list(columns = c("macd.macd.out", "signal.macd.out"),
relationship = "lt"),
label = "macd.lt.signal")
# go long when macd < signal
volStrat <- add.rule(strategy = volStrat, name = "ruleSignal",
arguments = list(sigcol = "macd.lt.signal", sigval = TRUE,
orderqty = 1000,
ordertype = "market",
orderside = "long"),
type = "enter")
# exit long when macd > signal
volStrat <- add.rule(strategy = volStrat, name = "ruleSignal",
arguments = list(sigcol = "macd.gt.signal", sigval = TRUE,
orderqty = "all",
ordertype = "market",
orderside = "long"),
type = "exit")
#####
start_t <- Sys.time()
out <- applyStrategy(strategy = volStrat, portfolios = portfolio2.st,
parameters = list(nFast = fastMA, nSlow = slowMA, nSig = signalMA, maType = maType), verbose = T)
end_t <- Sys.time()
print(end_t - start_t)
start_t<-Sys.time()
updatePortf(Portfolio='smacd',Dates=paste('::',as.Date(Sys.time()),sep=''))
updateAcct(account.st)
updateEndEq(account.st)
end_t<-Sys.time()
print(end_t-start_t)
book = getOrderBook('smacd')
stats = tradeStats('smacd')
ptstats = perTradeStats('smacd')
rets = PortfReturns(account.st)
txns = getTxns('smacd', symb2)
chart.Posn(Portfolio = 'smacd',Symbol = symb2)
plot(add_MACD(fast = fastMA, slow = slowMA, signal = signalMA, maType = "EMA"))
# COMPARING STRATEGY WITH SPY
instRets <- PortfReturns(account.st)
portfRets <- xts(rowMeans(instRets) * ncol(instRets), order.by = index(instRets))
portfRets <- portfRets[!is.na(portfRets)]
cumPortfRets <- cumprod(1 + portfRets)
firstNonZeroDay <- as.character(index(portfRets)[min(which(portfRets != 0))])
getSymbols("SPY", from = firstNonZeroDay, to = endDate)
SPYrets <- diff(log(Cl(SPY)))[-1]
cumSPYrets <- cumprod(1 + SPYrets)
comparison <- cbind(cumPortfRets, cumSPYrets)
colnames(comparison) <- c("strategy", "SPY")
chart.TimeSeries(comparison, legend.loc = "topleft", colors = c("green", "red"))
#
Sys.setenv(TZ=ttz)
任何人都可以帮我找出问题所在吗？
非常感谢。
这很有趣，我出于好奇随机点击了你的问题。我目前正在对 VIX 指数进行大量研究。
利用 MACD 的负相关性...它可以工作，但技术分析对随机序列毫无用处。如果您对 VIX 执行随机性测试，它不会拒绝假设。
此外，VIX 有随机的盘中峰值，这不会反映在收盘价中（由 getSybmols 得出——不是可靠的研究来源）。在现实生活中，您可能会在数据集实际代表它之前就被止损或达到您的价格目标。您可以通过使用此处强烈推荐的更高频率来避免这种情况。
以下是您应该阅读的 2 篇论文：
VIX 期货基础：证据和交易策略 - David P.Simon（2013 年）
以上策略与下一篇论文中的yield策略相同：
简单的波动性投资 - Tony Cooper (2013)
上一篇论文除了 yield 之外还有 4 种其他策略。
与代码相关，因为你几乎没有任何帖子，所以值得一提的是，它不太可能有人会检查你的整个代码。除非你可能付钱给他们，但你仍然会相信一个陌生人的计算吗？
Zorro 是实现此类策略并与 R 集成的一种非常简单的方法。请查看。
You're using a very complex package for something very simple. I haven't looked at yoru code but if I were you i would try something like this:
1. calculate MACD for VIX
2. Create a trade signal - Make new column by SPY with 1s for periods where VIX MACD >0 and zeros for VIX MACD <0
3. Simply add up SPY returns for rows that contain either 0s or 1s in the $MACD column / multiply by -1 if you want to go short..
P.S. use the xts package - helps u keep track of dates and not missmatch data
祝你好运，我也在做我的论文 atm，但不是在这个。
我正在写我的 MSc 期末论文，我一直在尝试使用 quantstrat 包开发交易策略。我想做的是通过观察基于 VIX 的 MACD 生成的信号来交易 SPY。
我很难在 VIX 上制定策略，然后在 SPY 上使用它。 我想获取 VIX 并计算 MACD。当 VIX 的 MACD 向下穿过信号线时，我希望算法买入 SPY。当 VIX 的 MACD 向上穿过信号线时，我希望算法平仓。
这是我写到现在的代码：
# MACD strategy on VIX and SPY (SPDR S&P500 FUND)
#
# I will use MACD as trend indicator.
#
# This is the main idea.
#
# I want to make prediction on SPY's returns. Due to the EMH, returns are not predictable.
# Otherwise, the volatility clustering effect allows us to forecast volatility.
# The VIX is the S&P500's implied volatility index. I can make previsions about it and use them
# to forecast the SPY returns. This is because S&P500 and VIX have a strong negative correlation.
#
# This strategy consists of buying/selling the SPY when the VIX's MACD generates sell/buy signal
#
# Author: Matteo Cavaggioni, 2016
######################################################################################################################
require(quantstrat)
ttz <- Sys.getenv('TZ')
Sys.setenv(TZ = 'UTC')
#startDate <- '2000-01-01'
initDate <- '2004-01-02'
endDate <- '2015-12-31'
initEq <- 1e6
fastMA <- 12
slowMA <- 26
signalMA <- 9
maType <- "EMA"
symb1 <- '^VIX'
symb2 <- 'SPY'
portfolio1.st <- "vmacd"
portfolio2.st <- "smacd"
account.st <- "vsmacd"
getSymbols(c(symb1, symb2), from = initDate, to = endDate, adjust = TRUE, index.class = c("POSIXt", "POSIXct"))
symb1 <- 'VIX'
currency("USD")
stock(symb1, currency = "USD", multiplier = 1)
stock(symb2, currency = "USD", multiplier = 1)
volStrat <- 'volStrat'
rm.strat(volStrat)
initPortf(name = portfolio1.st, symbols = symb1, initDate = initDate) # portafoglio contenente il VIX
initPortf(name = portfolio2.st, symbols = symb2, initDate = initDate) # portafoglio contenente lo SPY
initAcct(name = account.st, portfolios = c(portfolio1.st, portfolio2.st), initEq = initEq, initDate = initDate)
initOrders(portfolio = portfolio2.st, initDate = initDate)
volStrat <- strategy('volStrat', store = TRUE, assets = symb1)
volStrat <- add.indicator(strategy = volStrat, name = "MACD",
arguments = list(x = quote(Ad(mktdata)),
nFast = fastMA,
nSlow = slowMA,
nSig = signalMA,
maType = maType),
label = 'macd.out')
#####
volStrat <- add.signal(strategy = volStrat, name = "sigCrossover",
arguments = list(columns = c("macd.macd.out", "signal.macd.out"),
relationship = "gt"),
label = "macd.gt.signal")
volStrat <- add.signal(strategy = volStrat, name = "sigCrossover",
arguments = list(columns = c("macd.macd.out", "signal.macd.out"),
relationship = "lt"),
label = "macd.lt.signal")
# go long when macd < signal
volStrat <- add.rule(strategy = volStrat, name = "ruleSignal",
arguments = list(sigcol = "macd.lt.signal", sigval = TRUE,
orderqty = 1000,
ordertype = "market",
orderside = "long"),
type = "enter")
# exit long when macd > signal
volStrat <- add.rule(strategy = volStrat, name = "ruleSignal",
arguments = list(sigcol = "macd.gt.signal", sigval = TRUE,
orderqty = "all",
ordertype = "market",
orderside = "long"),
type = "exit")
#####
start_t <- Sys.time()
out <- applyStrategy(strategy = volStrat, portfolios = portfolio2.st,
parameters = list(nFast = fastMA, nSlow = slowMA, nSig = signalMA, maType = maType), verbose = T)
end_t <- Sys.time()
print(end_t - start_t)
start_t<-Sys.time()
updatePortf(Portfolio='smacd',Dates=paste('::',as.Date(Sys.time()),sep=''))
updateAcct(account.st)
updateEndEq(account.st)
end_t<-Sys.time()
print(end_t-start_t)
book = getOrderBook('smacd')
stats = tradeStats('smacd')
ptstats = perTradeStats('smacd')
rets = PortfReturns(account.st)
txns = getTxns('smacd', symb2)
chart.Posn(Portfolio = 'smacd',Symbol = symb2)
plot(add_MACD(fast = fastMA, slow = slowMA, signal = signalMA, maType = "EMA"))
# COMPARING STRATEGY WITH SPY
instRets <- PortfReturns(account.st)
portfRets <- xts(rowMeans(instRets) * ncol(instRets), order.by = index(instRets))
portfRets <- portfRets[!is.na(portfRets)]
cumPortfRets <- cumprod(1 + portfRets)
firstNonZeroDay <- as.character(index(portfRets)[min(which(portfRets != 0))])
getSymbols("SPY", from = firstNonZeroDay, to = endDate)
SPYrets <- diff(log(Cl(SPY)))[-1]
cumSPYrets <- cumprod(1 + SPYrets)
comparison <- cbind(cumPortfRets, cumSPYrets)
colnames(comparison) <- c("strategy", "SPY")
chart.TimeSeries(comparison, legend.loc = "topleft", colors = c("green", "red"))
#
Sys.setenv(TZ=ttz)
任何人都可以帮我找出问题所在吗？
非常感谢。
这很有趣，我出于好奇随机点击了你的问题。我目前正在对 VIX 指数进行大量研究。
利用 MACD 的负相关性...它可以工作，但技术分析对随机序列毫无用处。如果您对 VIX 执行随机性测试，它不会拒绝假设。
此外，VIX 有随机的盘中峰值，这不会反映在收盘价中（由 getSybmols 得出——不是可靠的研究来源）。在现实生活中，您可能会在数据集实际代表它之前就被止损或达到您的价格目标。您可以通过使用此处强烈推荐的更高频率来避免这种情况。
以下是您应该阅读的 2 篇论文：
VIX 期货基础：证据和交易策略 - David P.Simon（2013 年）
以上策略与下一篇论文中的yield策略相同： 简单的波动性投资 - Tony Cooper (2013)
上一篇论文除了 yield 之外还有 4 种其他策略。
与代码相关，因为你几乎没有任何帖子，所以值得一提的是，它不太可能有人会检查你的整个代码。除非你可能付钱给他们，但你仍然会相信一个陌生人的计算吗？
Zorro 是实现此类策略并与 R 集成的一种非常简单的方法。请查看。
You're using a very complex package for something very simple. I haven't looked at yoru code but if I were you i would try something like this:
1. calculate MACD for VIX
2. Create a trade signal - Make new column by SPY with 1s for periods where VIX MACD >0 and zeros for VIX MACD <0
3. Simply add up SPY returns for rows that contain either 0s or 1s in the $MACD column / multiply by -1 if you want to go short..
P.S. use the xts package - helps u keep track of dates and not missmatch data
祝你好运，我也在做我的论文 atm，但不是在这个。