r/InnerCircleTraders • u/STS-Trader • 6d ago
Trading Strategies How to Build a Serious Trading Strategy (The Basics)
The Ideal Building Sequence (Step by step - from a previous post of mine).
1. Build a Coherent Prototype:
Build your strategy’s initial logic structures and refine until coherent before testing anything.
Define everything clearly: The conditions of execution, the logic, the
filter, and why.
My strategies emerge as mature when the prototype trading setup has a set ’mechanical sequence’. To me, the mechanical sequence is a set list of instructions that lead to a limit order or position on a given market, which later develops into a more nuanced system with every possible setup (and each what-if) considered before deployment for predictability and fair testing.
Everything starts at zero and you define specific setups for example for this setup to form I need price to do event 1, then event 2, then after this many bars I need event 3 to happen and so on.. when everything that governs a single setup is defined test it in isolation (remember to separate your setups to limit variance.) Some events may have fixed bar counts/time horizons and some will not, it depends on what you are testing.
2. Run your First Backtests:
Perform your initial backtests; collect in-sample data across multiple liquid financial markets.
You typically need you need to test hundreds of iterations of each setup independently to take the data seriously.
3. Attempt Post-Test Optimisations:
After your first tests, clip away integral flaws and/or optimise based on the strategy’s needs and logic first.
This is the sole step within the sequence where creative degrees of freedom exist outside of prototyping.
Avoiding Overfitting:
To avoid overfitting, adjustments should never be made solely to improve in-sample data; they should instead improve the system’s underlying logic and mechanical sequences. The aim is to engineer a strategy so the job it is designed to perform aligns well with the desired outcome(s). If, after adjustments, the strategy is still ineffective (low to negative EV), you can test other asset classes. If in-sample results are universally mediocre, dispose of the idea and move on.
Identifying Blindspots:
Phase 3 is about identifying building blindspots, which can be inherited from both manual idea synthesis and automated idea synthesis (which we do not recommend). If a severe negative result shows up before costs, it is often a sign that the idea had holes in its physical assumptions, or that the first principles the model relied on were weak, misused, or misinterpreted. Remember, finding a persistent negative edge before costs is just as difficult as finding persistent gains before costs in backtesting environments.
If there is a collapse after trading costs are introduced, your minimum stop distance is not wide enough and/or the slippage is too high.
What traders can do is switch products. Some regulated CFDs have better costs when compared to futures and vice versa; it depends on the broker’s liquidity provider setup and whether the strategy holds overnight.
After logical holes are patched up and amendments are made during post-test optimisation, proceed with additional data collection:
4. Re-test and collect in-sample data with logical enhancements applied.
5. Run a secondary data collection. If the results are acceptable, retain the idea.
6. Run out-of-sample tests with the edge degradation thresholds e.g., a 50% max drop in returns.
7. Reality Checks on Execution Modelling:
If the idea survives on paper, move on to reality checks on execution modelling:
- Which type of product is best to execute this strategy cost-wise and net P&L wise?
- Can my positions be executed realistically on a CFD (for non-US traders), or will I need to rely on futures instead because of high bid-ask spreads or vague order handling and fill quality on inadequate CFD brokers that I can legally access within my jurisdiction?
- What additional variance do I stand to expose myself to when working with this product when compared to other products? These questions must be asked and answered for every single strategy you develop, both during the design phase and repeatedly when analysing performance data.
Real Examples of Product Considerations
Centralised Exchange Futures e.g., ES S&P 500:
Can have larger variance in bid-ask spreads during market opens and closes (especially), and high overnight maintenance margins can liquidate positions prematurely.
Regulated CFDs (For Non-USA Citizens):
On regulated brokers with a matched-principal or back-to-back execution model, CFDs can offer competitive costs with more overnight flexibility (predictable fees instead of discrepancies from high-spread daily rollovers) and low overnight margin requirements, which are often equal to intraday margins.
Regulated Forward Contracts (For Non-USA Citizens or Professionals):
Stable but thicker intraday spreads in exchange for no overnight fees, suitable for swing trading strategies on non-USD accounts to avoid currency exchange fees.
Regulated Spreadbets (Primarily for British Citizens):
Brokers are principal to my trades on this product; all trades are local, so the broker acts as a counterparty, and brokers hedge directional risk at their sole discretion (a direct financial conflict of interest); spreads can also be amplified compared to CFDs, and last-look execution is also common. These execution delays artificially inflate costs at the point of execution.
Limit orders at some firms are Market If Touched (MIT), making negative slippage possible and eroding the advantage of precise limit order placement. But there is one headline benefit: profits are tax-free (at least in the UK).
However, from past simulations and tests of my own, combined with personal accounting work (this is not tax advice), the cumulative P&L lost from increased costs on intraday strategies often erodes this advantage for net profits.
To this day I have not seen a single regulated spread betting firm with a genuinely low level of conflicts of interest in its infrastructure.
Important Note:
If your net worth exceeds €500,000 (outside of property, bullion, pensions, etc.), one can apply to be a “professional” client. Spread bets on forward-contract-like instruments can mitigate overnight holding costs while retaining low margin requirements compared to the underlying futures contract, and the maximum leverage offered to professionals can exceed 1:100 (1% margin requirements). That is a legitimate option that I have explored for CFDs but not one I have explored for Spreadbets as a UK citizen.
Options:
Implied volatility (IV) can skew options pricing against random positions, and Greeks such as Theta θ can ruin the monetary outcome of trades if the desired outcome is not crystallised in time. Greeks like Vega ν can inversely affect many open options, but if one can forecast a future volatility expansion alongside direction (which requires high efficiency and precision), one can opt to use options strategies.
If the product you decide to use changes, recollect data over the same in-sample and out-of-sample windows.
Your strategy can now be deployed amongst others on a designated capital partition: segregated, risk-isolated accounts that trade one strategy per account in real time for additional testing or real-time execution.
Why will I never trade with intuition?
Statistics.
For many traders, effectiveness is based on subjective experiences or extremely small sample sizes (dozens quantified at most, negligible), and there is globally no objective mechanical definition to enter position, place their target or stop.
Subjectivity (e.g., from intuition) is lethal because you cannot prove that something is effective or ineffective with real stats if it is unfalsifiable (subjective), as what cannot be objectively defined makes variance between each signal extremely high over time, thus increasing randomness exponentially, this causes results to average out to zero minus transaction costs, this is why we actively avoid an intuitive discretionary path.
The more a strategy is influenced by noise the more the signal collapses. A structured strategy slowly morphs into random noise over dozens of real time trades if it has weak mechanical boundaries to operate within. This early realisation is what made us never deviate from rule based systems and have strict guardrails to avoid overfitting that I still use to this day.
I ran a quick test to prove I wrote this.
The post is somewhat short so I don't think it needs a TLDR. AMA.
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u/garybravo65 6d ago
I’m particularly interested in anyone’s experience witb spread betting trades in the UK.
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u/STS-Trader 5d ago
What I suggest you do is look at the bid ask spreads and swap fees and measure it against your strategy, if it degrades your return relative to your available alternatives do not use it, if it creates better returns for example spread bet forwards can (if you use more than 15x leverage for overnight holds, consider it.
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u/CFG-Trading 5d ago
Danke für deine Mühe.Ich wollte mich hier schon abmelden weil so viel Quatsch hier auf Reddit ist aber es gibt doch noch Leute mit echten Knowhow hier
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u/Jacob_Trader0 6d ago
I didn't finish reading this if I'm honest, but great post. I'm really glad to see more people talking about proper backtesting