When re-reading the first post I saw that I'd used the term "trading strategy" and so feel a need to define this as I am using it.
Quantitative trading generally means using quantitatively derived information to trade. This can be thought of a three stage system. The first is using quantitative methods to forecast alphas, or asset specific (i.e. idiosyncratic) returns. I view most alphas as stochastic (i.e. random) with a zero mean longitudenally, but that does not mean that they cannot be conditionally forecast.
Once one has a set of forecasts one has to decide when to trade. This is what I mean by trading strategy: given private or semi-private forecasts of asset returns, knowledge of trading costs, and forecasts of risk, how do you combine this information to produce a decision to trade.
The third element is how much capital to commit to a given trade. This, you would call risk management.
The nice thing about making this devision is that it makes it easier to work and easier to evaluate one's work. One could call a trading system "separable" if it's analysis can be cleanly divided in this way (sort of in the way in which a partial differential equation is separable if f(x,y,z) is written X(x)Y(y)Z(z), for example).
The job of forecasting, or alpha generation, is a cleanly defined piece of statistical analysis: viz, to construct a forecasting system that is consistently reliable out-of-sample, meaning when used on data not used to develop it. This is unambiguously a piece of science.
The job of trading strategy is a cleanly defined piece of mathematical logic. Given a forecast set, when should one trade? This is applied mathematics, nothing more nor less. We have no need of backtesting if our forecasts are good and our logic is correct.
The job of risk management is more fuzzy, as this is the point at which economic theory enters the picture. Given a trade decision and a risk estimate, how much should I invest relative to capital.
Note how the paradigm described above differs from what one would call a "technical trading" system. Which is a black box system that takes in market data and outputs trades, based on parameters which are optimized through backtesting. Of course, this method can also work.
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