As self-taught experts, we’ve effectively earned our “PhD” in robotic trading through sheer dedication, each of us surpassing the customary 10,000 hours associated with a traditional PhD candidate’s commitment to their field. And we’ve had to be self taught, what with university programs for traders being rather thin on the ground. So what did we learn?
- Consistency: A dependable trading system should exhibit consistent performance, favoring a pattern of steady, smaller gains over the occasional windfall. The system should likewise aim to minimize drawdowns, the peak-to-trough decline in capital, as excessive drawdowns can be challenging to recover from.
- Deterministic: a system that isn’t deterministic is worthless, Test, calibrate, re-test, know your limits well enough to tell when a particular loss or win is in or outside of the normal. If you testing shows you can safely suffer eight losses in a row, for instance, then keep your hands off the tiller. If not, go flat on all of your positions and then return to square one.
- Compounding: Albert Einstein said it best: “Compound interest is the eighth wonder of the world. He who understands it, earns it; he who doesn’t, pays it.”
- Risk Management: Never trade without robust risk management mechanisms in place, including stop-loss orders, position sizing rules, risk-reward ratios, news-awareness, volatility benchmarking, embargoes, and heuristics to protect capital and limit losses.
- Continuous Monitoring and Optimization: Every trading systems will require periodic adjustments to remain effective, so traders should closely monitor their results, correlate those results against predetermined norms and then, if necessary, adjust.
- No Ad-Hoc Action: Always trust your modelling; never (ever!) take any sort of ad-hoc action, even in the face of significant loss. Do not change a single setting by hand (unless your modeling tells you to do so!) and never ever go-flat unless your trading falls outside of pre-tested norms.
- Always Diversify: As a rule, you should never trade a single asset on its own. Diversification can reduce ultimate gains, but your first and last consideration in trading should be capital preservation. Nobel laureate Harry Markowitz famously said “Diversification is the only free lunch in investing.”
- Money Management: Effective money management in trading is the art of safeguarding capital while optimizing position sizes across the portfolio to ensure long-term sustainability and profitability. In a more practical sense, this comes down to hedging a number of different systems together and then adjusting the capital allocated to each based upon your modelling results.
- Viability Testing: Assessing the viability of a trading system involves a multifaceted approach, including quantitative methods like the Sharpe ratio and Monte Carlo simulations. The Sharpe ratio gauges a system’s risk-adjusted returns, helping traders understand the efficiency of their strategies. Monte Carlo simulations, on the other hand, stress-test trading systems by running multiple scenarios, providing insights into potential outcomes under varying market conditions. Additionally, back-testing, historical performance analysis, and real-time trading results analysis play pivotal roles in evaluating a system’s consistency and adaptability. A holistic assessment, combining these quantitative methods with qualitative factors like strategy transparency and risk management, is key to determining the overall viability and robustness of a trading system.
- Calibration: The system should perform well in live-trading conditions, accounting for slippage, latency, and other market factors that can impact execution. Moreover, live trading must be periodically benchmarked against simulated trading, to detect (and ultimately respond to) drift.
- Record Keeping: Comparing and contrasting trading systems is key; at the transactional, criteria and results level. When evaluating potential systems we look at dozens of reports and charts to decide upon system viability.
- Adaptability: A good trading system should be adaptable to different market conditions. It should have the flexibility to (automatically) adjust strategies or parameters when market dynamics change.
- Realistic Expectations: A trading system should set realistic expectations for returns, avoiding promises of “get-rich-quick” schemes. Be (extremely!) skeptical of any claim (including ours!)
I could go on and on and on, but my essential point is rather simple: if you want to stand a chance at making consistent money with forex then you’ll need to embark on a PhD program of your own, find a vendor who can give you a leg up, or not trade forex.
To help with you decision, you might look at our results, read-up on the partners, make your peace with the fact that we make no claims (aside from the fact that it’s possible to lose money trading forex), do some independent research, maybe even chat with sales. Then, if it still makes sense to you, click on that “Get Started” button and you’ll be off and running in no-time.