2. BUY AND SELL RULES
From my experience, the simpler the buying and selling rules, and the more
complex the ranking system, the more reliable is the system from a out of
sample performance perspective. That’s why this model relies basically on one
thing: the ranking system. By keeping things simple we just avoid overoptimization and curve fitting.
The model goes to cash when the market conditions are weak, its market timed
with VIX and technical indicators.

3. THE RANKING
SYSTEM
The ranking system for this model is composed of 120+ nodes looking at a
great varieties of factors, fundamentals and technicals. Profitability, cashflows, valuation, growth, earnings estimates as well as moving
averages, volumes etc…
A picture is worth one thousand words. This image talks by itself.
It also performs wonderful for all 20, 50, 100 stocks as we will see later.

5. 1% FIXED SLIPPAGE WITH NEXT DAY
AVERAGE HIGH LOW

6. 10 STOCKS EVENID = 1

7. 10 STOCKS EVENID = 0

8. EXCLUDING TOP 10
PERFORMERS

9. LETS TRADE WITH A
PORTFOLIO OF 20 STOCKS

10. LETS TRADE WITH A
PORTFOLIO OF 50 STOCKS

11. LETS TRADE WITH A
PORTFOLIO OF 100 STOCKS

12. LET’S CHANGE THE
UNIVERSE TO SP500

13. LET’S CHANGE THE
UNIVERSE TO SP400

14. LET’S CHANGE THE
UNIVERSE TO SP600

15. WITHOUT MARKET TIMING

16. LETS TURN OFF ALL BUYING AND SELLING RULES
AND LET’S SET LIQUIDATION EVERY 2 WEEKS

17. LET’S INCREASE TURNOVER -> MAX
TURONVER = 1,422.01%

18. LET’S DECREASE TURNOVER
TO 781.08%

19. NOW WE ARE GOING TO RUN A BACKTEST WITH SEVERELY DEGRADED FACTORS:
FIRST WE REMOVE THE WEIGHTS OF EVERY NODE AND SUB-NODE IN THE RANKING SYSTEM.
ON THE UNIVERSE, WE ADD 20% TO EVERY FACTOR, NAMELY LIQUIDITY AND MINIMUM STOCK
PRICE.
FOR EACH BUY AND SELL RULE THAT DEPENDS ON A THRESHOLD (MARKET TIMING, RANKING
SIGNALS ETC..) WE WILL ADD 20% (FIRST IMAGE) AND REMOVE 20% (SECOND IMAGE) ON EACH
THRESHOLD.
WE RUN THE SIMULATION WITH (HIGH+LOW)/2 AS THE TRANSACTION PRICE AND VARIABLE
SLIPPAGE.

20. DEGRADED WITHOUT
MARKET TIMING

21. CONCLUSIONS
Once a strategy is created two things must be done:
Verify that the performance is not the result of mere chance.
Get some clue as to whether this strategy will continue to outperform in the future.
This is where all these tests become useful.
Reviewing them, I draw several conclusions:
It is very unlikely the performance is the result of chance. The model kept
outperforming the market even as we radically altered its parameters.
Drawdowns down to 55% have to be expected in case of a generalized market decline.
This strategy did provide an edge on the market for the last 14 years. We can
reasonably expect it will continue to do so in the future.
These curves are a better representation of the model going forward, since they are the
result of sub-optimal parameters.
Remember, nobody can be certain about the future so trade only with money you can
afford to lose.
Happy trading !

22. Disclaimers
Simulation results must be interpreted in light of differences
between simulated performance and actual trading, differences
between subscriber performance and live out-of-sample model
performance, and the fact that past performance is no guarantee
of future results. (See Subscriber Terms.)
Please note I am not a registered adviser. I am not offering
personal advice regarding the suitability of a particular investment.
If you are unsure as to the suitability of a particular investment for
your own circumstances please contact a registered financial
adviser for advice.