TradingSystems

                 Enhanced Probability Technical Trading  Strategy Methodology



Strategy Methodology- The idea was to combine technical analysis with statistical methods (distribution theory) in order to identify long term trends and turning points in the market considered.   The idea is to create a strategy that both outperforms the underlying market with less volatility than the underlier.    Several proprietary technical indicators are considered and there statistical distributions analyzed to determine buy and sell levels which are incorporated into a signal generator.  

Trades are only entered only after confirmation of several statistical and technical factors (this leads to a higher probability of a successful trade).   The trades are long term in nature as they go with the trend.   The period of analysis uses data from the 1999 or the inception of the ETF whichever is available.  It considers several bear markets including the most recent one which help stress test the strategy and set acceptable risk levels.   The strategy deploys a framework that increases the likelihood of a successful trade; stops are used to exit losing trades.  The strategy is deployed in various markets where there are high volume ETFs available.

Asset Selection- The strategy focuses on identifying appropriate entry and exit points in the most liquid exchange traded funds (ETF’s).   The reason for this is for both liquidity and scalability (numerous strategies focus on asset selection but ignore the need to scale for commercial viability).   The ETF’s selected are as follows SP500 Spider, NASDAQ (QQQQ’s), Emerging Market Index (EEM), Gold (GLD), Silver (SLV) and Oil (OIH). Note that in this initial phase of development the asset markets selected are diverse in that they comprise NASDAQ, SP500, emerging markets and commodities.   The same methodology can also be applied to individual stocks however the results I present here are for major market indices in the form of ETF’s.

Results

In this document I post the results for the NASDAQ, SPY, EWZ and EEM ETF (see below).  The other models are available in the spreadsheet attached along with Trade Statistics. (See attached)

The data considers several periods of dislocation in analyzing the system.  Namely NASDAQ Bubble Bursting, 2001-2002 bear market, 2008 credit crisis.  For example the NASDAQ Model did well in 2000 and stayed out of the market during this period and stays out during 2008.  The best year dollar wise is 2009 for the NASDAQ Model.   $1million dollars invested in the NASDAQ Model would result in total balance of over $3.28million by Nov 2010 compared with a loss of over 40% over the same period if invested in the underlyer.  The SPY Model increases by almost 100% for this period vs a slightly negative performance in the SPY ETF.





Strategy Deployment-- The strategy is ideally suited for a wealth management firm, mutual fund, or long only hedge fund that would deploy client capital in accordance with the signals to establish  a “technical long fund or fund of fund (via allocation to multiple asset classes)”.    These strategies are also ideally suited to institutions/family offices/insurance companies/endowment funds.

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