#Benchmark analytics stock series#

The usual 'go to' benchmark is a geographic market cap weighted index, such as the S&P500 for the US or the FTSE100 for the UK.

Consider an active long-only equities strategy run by a large institutional fund.

In particular, for a certain set of investor risk/reward preferences if the benchmark cannot be beaten with an active complex trading strategy then why spend operational time on its implementation?Ĭhoosing a benchmark is not as straightforward as it seems. One can think of the benchmark as the 'default option'. A benchmark is a particular choice of portfolio that provides a comparison mechanism against another trading strategy. This motivates the concept of a strategy benchmark. If we are to consider running a complex TAA strategy with non-trivial weighting rules it is necessary to ask whether one can achieve similar-or better-performance solely with simple static allocations. Some will utilise sophisticated portfolio construction methods to tactically weight allocations on a more frequent basis.Īs with all forms of investing it is prudent to be aware of the opportunity cost of allocating capital to one strategy or portfolio over another. Many TAA strategies consist of straightforward static asset allocations that are periodically rebalanced. All of the asset allocation approaches discussed in our TAA articles will have backtests provided via interactive charts helping you to determine if such a strategy should be added to your portfolio. QSTrader has recently been redeveloped 'from the ground up' to be easier to use, allowing straightforward implementation of TAA strategies. In addition to learning a new set of investment skills we are also going to make use of the current development version of our freely available open source backtesting engine QSTrader.

#Benchmark analytics stock series#

The goal will be to provide a solid overview of TAA, via a series of example strategies, which you can then use a 'tool' in your systematic trading toolbox, potentially to diversify against higher frequency strategies. In this and subsequent articles we are going to start delving into some of these issues. The typical monthly rebalance frequency of these strategies lends itself to spending more time on research and less time on operational implementation. Many-if not all-TAA strategies rely on a good understanding of macroeconomic trends and an awareness of the behaviour of various asset classes over the long-term. In a recent article we introduced systematic tactical asset allocation (TAA) as a low-frequency example of quantitative trading strategy.įor those who are taking their first steps in systematic trading, are wanting to consider systematic trading in the context of their retirement planning or are simply wishing to minimise the day-to-day work of running a strategy TAA can be a great choice.ĭespite its seeming simplicity as a systematic trading mechanism there is a substantial body of theory behind some of the more complex implementations.