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Following the Smart Money

Eric D. Brown
2016-10-25
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Previously, I looked at using the Smart Money / Dumb Money Spread as a signal for trading both long and short.  Annual returns on that trading signal were 2.24% using no leverage.

We had a request come in to take a look at using the Smart Money model as a trading signal. The request was much bigger than the simple strategy below, but I wanted to use the request as a way to work through a couple blog posts on Smart Money and building signals / strategies from the model.

First off, as always, I like to take a look at the annualized threshold returns for the signal before building any strategies. The threshold returns for the Smart Money model shows a very positive skew when readings are above 0.70.

[caption id="attachment_911" align="aligncenter" width="564"]Threshold returns for the Smart Money Model Figure 1: Threshold returns for the Smart Money Model[/caption]

For this strategy, I'm going to use the same approach I've taken previously. This will be a long-only strategy. Trading rules are defined below.

Trading Rules

  1. Trading dates are Sept 16 1996 to Oct 21 2016 (entire history of the model)
  2. Long only
  3. No Margin. Account size is $250K.
  4. 1,000 shares of SPY ETF
  5. Commission of $10 per trade
  6. $0.01 per share slippage
  7. Go long when:

    • Smart Money closes above 0.70 (Excessive Optimism)

  8. Close when:

    • Smart Money closes below 0.30 (Excessive Pessimism)

  9. All orders are entered at the open of the next day’s trading session after a signal is given.

This strategy doesn't provide a large number of trades, but it does provide some very good returns.   Some basic trade statistics are provided below.

[caption id="attachment_913" align="aligncenter" width="392"]Trade statistics for the Smart Money Model Figure 2: Trade statistics for the Smart Money Model[/caption]

[caption id="attachment_915" align="aligncenter" width="281"]Win/Loss statistics for the Smart Money Model Figure 3: Win/Loss statistics for the Smart Money Model[/caption]

This simple strategy delivers some pretty good results with some volatility (see cumulative return volatility compared to benchmark chart below).  Overall, following the smart money delivers excellent results (2.91% annualized without leverage).  Performance charts for this strategy are provided below with in-sample and out-of-sample data (out-of-sample is all dates after Jan 1 2015).  Note: Out-of-sample returns are ~4% compared to the 2.91% returns found in-sample.

[caption id="attachment_917" align="aligncenter" width="600"]Performance Charts for the Smart Money Model Figure 4: Performance Charts for the Smart Money Model[/caption]

Check back next week for another look at using the Smart Money model as a signal.

 

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Risk Disclosure: Futures and forex trading contains substantial risk and is not for every investor. An investor could potentially lose all or more than the initial investment. Risk capital is money that can be lost without jeopardizing ones’ financial security or life style. Only risk capital should be used for trading and only those with sufficient risk capital should consider trading. Past performance is not necessarily indicative of future results.

Hypothetical Performance Disclosure: Hypothetical performance results have many inherent limitations, some of which are described below. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown; in fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any particular trading program. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk of actual trading. for example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all which can adversely affect trading results.

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