robustness presentation

FROM LAB TO HOME

Frank’s Models

BUY AND SELL RULESFrom 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 over-optimization and curve fitting.

The model goes to cash when the market conditions are weak, its market timed with VIX and technical indicators.

THE RANKING SYSTEM

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.

The ranking system for this model is composed of 120+ nodes looking at a great varieties of factors, fundamentals and technicals. Profitability, cash-flows, valuation, growth, earnings estimates as well as moving averages, volumes etc…

ROBUSTNESS TESTS

1% FIXED SLIPPAGE WITH NEXT DAY AVERAGE HIGH LOW

10 STOCKS EVENID = 1

10 STOCKS EVENID = 0

EXCLUDING TOP 10 PERFORMERS

LETS TRADE WITH A PORTFOLIO OF 20 STOCKS

LETS TRADE WITH A PORTFOLIO OF 50 STOCKS

LETS TRADE WITH A PORTFOLIO OF 100 STOCKS

LET’S CHANGE THE UNIVERSE TO SP500

LET’S CHANGE THE UNIVERSE TO SP400

LET’S CHANGE THE UNIVERSE TO SP600

WITHOUT MARKET TIMING

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

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

LET’S DECREASE TURNOVER TO 781.08%

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.

DEGRADED WITHOUT MARKET TIMING

CONCLUSIONSOnce 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 !

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.