Quality Money Management : Process Engineering and Best Practices for Systematic Trading and Investment

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● Endorsed by expert judgment. For example, financial engineers, either internal or

external, may widely agree that one method is superior.

● The same practice recurs. For example, a survey may find that one method is used

by all firms.

● Leadership position has been attained. For example, one execution algorithm may

prove time and time again to provide superior performance relative to a VWAP,

arrival price, or implementation shortfall, or pretrade, benchmark.

The research step permits the product team to survey all the relevant mathematical

and logical models. The goal of the research process is to speed the path to the design or

application of the best practice algorithms. Any quantitative method will fall into one of

four categories:

1. Usable in a production system.


2. Usable only in the absence of a better model.


3. Totally unusable.


4. Model in inventory. Maybe not appropriate for the problem at hand, but worthy of
   further research for other, later problems.

Benchmarking trading/investment strategy processes is a proactive search for superior

performance that includes gaining a concrete understanding of the competition as well as

trying out new ideas and proven practices and technology. Process benchmarking should

be approached on the basis of investigating industry practices first.^3 Capability maturity

advances when proven best practices are incorporated in trade selection, order manage-

ment algorithms, and risk management algorithms.

9.2. STEP 2, LOOP 1: Research Similar/

Competing Systems

The first loop of research begins to refine requirements into defined inputs the trad-

ing system will receive, actions taken by it, and defined outputs it will produce. Rarely,

though, do firms dream up completely new trading/investment strategies. More often,

they build on ideas of the past or of others, adding a twist or two here or there to enhance

performance; many trading ideas are simply copies of ones that were successful in the

past. The goal of a new system may in the first year be to simply imitate a competitor or

index benchmark, matching its performance. Down the road, in successive years, the goal

could be to improve on the results and outperform the benchmark. At some firms, the

goal is to make each new trading system or product team cash flow positive within some

timeframe. After that, algorithms are refined. Finally, the steady-state goal may be to con-

sistently perform in the top 10% of the peer group.

The SEC ’ s general push toward increased disclosure of holdings by mutual funds (and

inevitably hedge funds) allows one fund manager to mimic another. Such funds are called

copycats. In fact, research by Mary Margaret Frank et al. suggests that copycatters can

even outperform the copycattees. The study found that hypothetical funds copycatting the

100 largest equity mutual funds in the United States, updating the portfolios semiannually

based on publicly available information, generated returns “ statistically indistinguish-

able, and possibly higher ” than the returns of the copycatted funds. The disadvantage is

9.2. STEP 2, LOOP 1: RESEARCH SYSTEMS