Daily Commentary - Posted on Tuesday, December 22, 2009, 9:42 PM GMT +1
How To Make A Million (%) Trading The SPYDER – Part I
Due to the fact that I’m very busy these days building and moving into a new home in a couple of weeks, I spent the majority of the time left for trading and blogging (sorry about the latter) with working on a market model (a concise mathematical formula which would stand the test of time forecasting the next sessions S&P 500‘ performance on the close with maximum accuracy), trying to make gread and fear as the never changing driving forces behind maket movements somewhat ‘quantifiable’.
I started the process of developing such a ‘market model‘ (financial trading strategy) a couple of month ago, but up to now never had the necessary desire and time (unfortunately developing a reliable trading system is a complex venture) to make any substantial progress. But being booked to capacity by serveral personal and business matters, and additionally being inspired by Michael Stokes’ posting Wasting a Good Life Trading, I thought it would be the right time to resume working on the model.
So this will be the first in a series of posts about my my step-by-step approach, initial basic parameters, and respective results.
In order to keep things as simple as possible right at the start (leaving room for further improvements), my initial basic parameters were:
- For backtesting the SPY (SPDR S&P 500 ETF) will be utilized (adjusted for dividend and cash payments in order to track the S&P 500 as close as possible) which corresponds generally to the price and yield performance, before fees and expenses, of the S&P 500 Index.
- Positions will be entered into or an open position closed at the market’s regular close only (market-on-close orders).
- No (intraday) stops (buy and/or sell stops) will be used even if the SPY (S&P 500 EFF) is being utilized.
- No position sizing, the model is always ‘all in‘ (e.g. no Kelly, optimal f, fixed fraction, …).
- No leverage taken (no double or triple-leveraged ETFs are used).
- No abnormal market filter will be used (e.g. during phases of extremly high/low volatility, strong trending markets, the market’s lacking compliance to the model’s forecasts with a resultant number of consecutive losses and/or serious drawdown, and and and)
- No adaptations (no changes and/or cancellations/additions of formulas, conditions, and model parameters over the course of the lifetime of the model/during backtesting).
- The model (and respective performance figures) does not account for slippage, transactions costs (commissions, exchange and regulatory fees), and interest on idle balances.
In a first step the model is simply taking a long or short position (never being market neutral, means if no buy setup is triggered, a short position will be taken) on the close (e.g. buying/selling short the SPY), and the model is always ‘all in‘ (as already pointed out no position sizing and/or leverage). Using buy/sell stops, position sizing, adaptations, abnormal market filters, optimization of short positions (no buy setup trigged does not necessarily mean that a short position has to be taken, market neutral may be a better decision if no edge is provided) may be subject to a future optimization process.
Assessment criteria (in absolute terms and in comparison to the general market) for the market model and the selection of setups, conditions and the set of parameters will be (in the order of precedence):
- Cumulative Returns and CAGR (Compounded Annual Growth Rate = geometric mean growth rate on an annualized basis)
- Growth Rate per Trade (geometric mean growth rate on a ‘per trade‘ basis, means a trades’s average contribution to cumulative profits / geometric growth)
- Maximum Drawdown (the maximum decline from a historical peak in cumulative profits)
- Sharpe Ratio (excess returns per unit of risk of a financial trading strategy)
The model’s setups and conditions can in principle be grouped into three categories:
- Extreme Market Conditions
- Regular Market Conditions
To cut a long story short: The stats and figures belwo represent my current status quo, I’m still working on the model trying to streamline conditions, the set of parameters and their respective dependencies and will report about my progress and my step-by-step approach over the course of the next couple of weeks. But already at this stage it is interesting to note that even without adaptations, market filters, positions sizing, stops and and and it would’ve been possible
- to achieve positive returns (not a single losing year) in every year since 1990 (I don’t have breadth and other -except index- data before 1990),
- to achieve returns in excess of +50% in 10 out of the last 20 years, and returns in excess of +100% in 4 out of the last 20 years,
- to achieve an compounded annual growth rate of 65.14% over the course of the last 20 years,
- to out-perform the index (regularly by a very wide margin) in 18 out of the last 20 years,
- to face a maximum drawdown of 16.05% only during the last 20 years,
- that one would’ve never been in a drawdown more than 118 trading days (6 month).
Listed below are some details with respect to the strategy’s setups, conditions, parameters and dependencies (>indicator x< is a placeholder for a proprietary indicator).
(1.1) it is the session preceding Memorial Day, Labor Day, Thanksgiving Day, or Christmas Day,
(1.2) it is the last business day of the month,
(1.3) it is the session immediately preceding Jobs Report Friday (regularly the first Friday of a month), and the index closed up,
(1.4) it is the session immediately preceding an FOMC announcement day,
(1.5) it is an FOMC announcement day, and the index did NOT closed higher greater than +0.45%.
2. Extreme Market Conditions
(2.1) the index did NOT close 2 standard deviations above it’s 11-day EMA (Exponential Moving Average),
(2.2) the VIX (CBOE Volatility Index) did NOT close lower less than -15%,
(2.3) the 2-day RSI did NOT close above 94, and the >indicator 1< did NOT close above xxx,
(2.4) the CBOE Equity Put/Call Ratio closed higher at least 45% above it’s simple moving average of the previous two sessions.
2. Regular Market Conditions
(2.1) SPY volume came in at least 55% above the previous session’s volume and S&P 500 Advancing/Declining Issues closed above 0.85 and the ratio of S&P 500 stocks penetrating their previous session’s high vs. those penetrating their previous session’s low closed above 0.50,
(2.2) SPY volume did NOT close 30% above the previous session’s volume and S&P 500 Advancing/Declining Issues did NOT close above 1.30 and the ratio of S&P 500 stocks penetrating their previous session’s high vs. those penetrating their previous session’s low did NOT close above 1.40,
(2.3) the index closed above it’s 19-day EMA (Exponential Moving Average) and
- the index did NOT post an intraday high less than -0.30% below the previous session’s high, OR
- the index did NOT post an intraday low less than -0.50% below the previous session’s low, OR
- the >indicator 2< did NOT close above yyy,
the index closed above it’s 19-day EMA (Exponential Moving Average) and (the ratio of the 2-day +DI (Wilder’s Directional Movement Indicator) vs. the 2-day -DI closed below 0.65 OR the >indicator 3< close below zzz) and
- the index did NOT post an intraday high below the previous session’s high, OR
- the index did NOT post an intraday low less than -0.15% below the previous session’s low.
(2.5) to be continued …
A long position is taken at the close in the event a buy setup (in extracts listed above) had been triggered, and a short position if no buy setup had been triggered (up to now the strategy is NOT optimized for the short side of the market, sometimes it would be wise to take no position at all if no edge is provided on the long side).
Table I shows the SPY‘s (S&P 500 ETF) performance (cumulative returns) since 01/01/1990. Setup 2 represents the long side (long trades only) of the strategy, setup 3 represents the short side (short trades only) of the strategy, and setup 1 the overall stratgey as a combination of long and short trades.
Figure I shows the respective equity curve (setup 2 -longs only- and setup 3 -shorts only-) from 01/01/1990 to 12/31/1999.
Figure II shows the equity curve, now including setup 1 as the combination of long and shorts, from 01/01/1990 to 12/31/1999.
Figure III shows the respective equity curve (setup 2 -longs only- and setup 3 -shorts only-) from 01/01/2000 to 12/18/2009 (the SPY’s equity curve is the thin black line at and around the 0%-line).
Table II shows the SPY‘s (S&P 500 ETF) performance (cumulative returns) since 01/01/2009 (year-to-date). Setup 2 represents the long side (long trades only) of the strategy, setup 3 represents the short side (short trades only) of the strategy, and setup 1 the overall stratgey as a combination of long and short trades.
Accordingly figure IV shows the respective year-to-date (01/01/2009 to 12/18/2009) equity curve.
Disclaimer: No position in the securities mentioned in this post at time of writing.
The information on this site is provided for statistical and informational purposes only. Nothing herein should be interpreted or regarded as personalized investment advice or to state or imply that past results are an indication of future performance. The author of this website is not a licensed financial advisor and will not accept liability for any loss or damage, including without limitation to, any loss of profit, which may arise directly or indirectly from use of or reliance on the content of this website(s). Under no circumstances does this information represent an advice or recommendation to buy, sell or hold any security.