[Blotter-commits] r740 - pkg/quantstrat/man

[noreply at r-forge.r-project.org]

Author: braverock
Date: 2011-08-25 22:08:05 +0200 (Thu, 25 Aug 2011)
New Revision: 740

Modified:
   pkg/quantstrat/man/quantstrat-package.Rd
Log:
- update package overview by copy/edit on Josh Ulrich's FOSStrading post

Modified: pkg/quantstrat/man/quantstrat-package.Rd
===================================================================
--- pkg/quantstrat/man/quantstrat-package.Rd	2011-08-25 20:00:10 UTC (rev 739)
+++ pkg/quantstrat/man/quantstrat-package.Rd	2011-08-25 20:08:05 UTC (rev 740)
@@ -6,13 +6,87 @@
 Quantitative Strategy Model Framework
 }
 \description{
-Transaction-oriented infrastructure for constructing trading systems and simulation.  Provides support for multi-asset class and multi-currency portfolios for backtesting and other financial research.  Still in heavy development.
+Transaction-oriented infrastructure for constructing trading systems and
+simulation.  Provides support for multi-asset class and multi-currency
+portfolios for backtesting and other financial research.  Still in heavy
+development.
 }
 \details{
+quantstrat provides a generic infrastructure to model and backtest signal-based
+quantitative strategies.  It is a high-level abstraction layer (built on xts,
+FinancialInstrument, blotter, etc.) that allows you to build and test strategies
+in very few lines of code.  quantstrat is still under heavy development but is
+being used every day on real portfolios.  We encourage you to send contributions
+and test cases to the project forums.
+
+\emph{Generic Signal-Based Strategy Modeling}
+
+A signal-based strategy model first generates indicators.  Indicators are
+quantitative values derived from market data (e.g. moving averages, RSI,
+volatility bands, channels, momentum, etc.).  Indicators should be applied to
+market data in a vectorized (for fast backtesting) or streaming (for live
+execution) fashion, and are assumed to be path-independent (i.e. they do not
+depend on account / portfolio characteristics, current positions, or trades).
+
+The interaction between indicators and market data are used to generate signals
+(e.g. crossovers, thresholds, multiples, etc.).  These signals are points in
+time at which you may want to take some action, even though you may not be able
+to.  Like indicators, signals may be applied in a vectorized or streaming
+fashion, and are assumed to be path-independent.
+
+Rules use market data, indicators, signals, and current account / portfolio
+characteristics to generate orders.  Notice that rules about position sizing,
+fill simulation, order generation / management, etc. are separate from the
+indicator and signal generation process.  Unlike indicators and signals, rules
+are generally evaluated in a path-dependent fashion (path-independent rules are
+supported but are rare in real life) and are aware of all prior market data and
+current positions at the time of evaluation.  Rules may either generate new or
+modify existing orders (e.g. risk management, fill, rebalance, entry, exit).
+
+\emph{How quantstrat Models Strategies}
+
+quantstrat uses FinancialInstrument to specify instruments (including their
+currencies) and uses blotter to keep track of transactions, valuations, and
+P&L across portfolios and accounts.
+
+Indicators are often standard technical analysis functions like those found in
+TTR; and signals are often specified by the quantstrat sig* functions (i.e.
+sigComparison, sigCrossover, sigFormula, sigPeak, sigThreshold).  Rules are
+typically specified with the quantstrat ruleSignal function.
+
+The functions used to specify indicators, signals, and rules are not limited to
+those mentioned previously.  The name parameter to add.indicator, add.signal,
+and add.rule can be any R function.  Because the supporting toolchain is built
+using xts objects, custom functions will integrate most easily if they return
+xts objects.
+
+The strategy model is created in layers and makes use of delayed execution. 
+This means strategies can be applied--unmodified--to several different
+portfolios.  Before execution, quantstrat strategy objects do not know what
+instruments they will be applied to or what parameters will be passed to them.
+
+For example, indicator parameters such as moving average periods or thresholds
+are likely to affect strategy performance.  Default values for parameters may
+(optionally) be set in the strategy object, or set at call-time via the
+parameters argument of applyStrategy (parameters is a named list, used like the
+arguments lists).
+
+quantstrat models orders, which may or may not become transactions.  This
+provides a lot of extra ability to evaluate how the strategy is actually
+working, not working, or could be improved.  For example, the performance of strategies
+are often affected by how often resting limit orders are changed / replaced /
+canceled.  An order book allows the quantitative strategist to examine market
+conditions at the time these decisions are made. Also, the order history allows
+for easy computation of things that are important for many strategies, like
+order-to-fill ratios.
+
 }
 \author{
 Peter Carl
 Brian G. Peterson
+Josh Ulrich
+Garrett See
+Yu Chen
 
 Maintainer: Brian G. Peterson <brian at braverock.com>
 }