advanced-algorithmic-trading

Chapter 25
Introductory Portfolio Strategies
In this chapter we are going to gently introduce the usage of QSTrader via the backtesting
of long-only portfolios comprised solely of Exchange Traded Funds (ETF). Such strategies are
easy to interpret. They serve to provide insight into the mechanics of the software in a more
elementary setting.
25.1 Motivation
Many institutional global asset managers are constrained by the need to invest in long-only
strategies with zero or minimal leverage. This means that their strategies are often highly
correlated to "the market" (usually the S&P500 index). While it is difficult to minimise this
correlation without applying a short market hedge, it can be reduced by investing in non-equities
based ETFs.
These portfolios usually possess an infrequent rebalance rate–often weekly or monthly. They
differ substantially from a classic intraday stat-arb quant strategy but are nevertheless fully
systematic in their approach.
In this chapter a simple fixed proportion portfolio framework is presented to demonstrate the
basics of QSTrader. The strategies themselves are not novel–they are straightforward examples of
classic diversified ETF mixes–but it does serve to demonstrate the rebalancing mechanic within
the software.
Some of the portfolio mixes presented here are extremely well known but the latter "strategic
mix" was inspired by a recent article[80] over at the The Capital Spectator blog.
25.2 The Trading Strategies
The trading strategies are extremely similar, only varying in portfolio weights and starting dates.
At the end of every month the strategy fully liquidates the portfolio. It then rebalances each
asset to be dollar-weighted according to the initially specified fixed proportion of the current
account equity.
The first strategy simply carries a 60%/40% weighting of equities and bonds using the ETFs
with tickers SPY and AGG. They represent large-cap US equities and investment-grade US
bonds respectively.
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