There's been little to do during the current 24-hour market cycle seeing as how the conclusions I reached after conducting an analysis (or evaluation) of yesterday’s consistently profitable periods of trading gave me numbers indicating that up to this point, today's market conditions are such as to advise against entering any positions or making any trades. Perhaps this is because everyone is waiting (for the time being) until they can get a peek at the Federal Funds Rate and/or see the Federal Open Market Committee's projections and/or its statement a couple of hours from now. But in any event, I decided to use the downtime to determine how long I can sustain winning streaks if using my updated forecast models to trade the horribly structured (in my opinion) NADEX binary option contracts. My aim is to focus exclusively on trade setups guided solely by mathematical odds and statistical probability. If I were a mathematician, I might want to try isolating purely probabilistic models using Bayesian approaches, perhaps, or even Monte Carlo simulations, in order to evaluate trade setups without reliance on other inputs—but unfortunately, a mathematician I am not! Initial results inform me that even with the extra "wiggle room" offered by in-the-money binary option contracts, trading under less than optimal market conditions remains ill advised! Began the day with $105,696.70 Initial contracts: USDJPY > 144.72 USDCAD > 1.3639 $105,821.70 = +$125 profit Next hour: Buying both AUDUSD and USDCAD These pairs were contrarian to one another—USDCAD was the wrong choice! $105, 591.70 = -$230 loss
Hey, I just noticed that these updated models hint at the 90-minute price range being a very useful measure, even under poor trading conditions. I therefore plotted them on a 15-minute chart, which in turn suggested that using the 1½-hour price range in conjunction with the half-day and full-day ranges might constitute a configuration that could very well be successfully used for entering high-probability longer-range profitable positions.
Indeed, it appears that moving the 90-minute measure to the center of my approach has empowered me to recognize the “foolproof” forecast model I wished to have at my disposal before increasing my position size from 0.01 or 0.02 lots to 1.0 lots, with every trade made after its adoption (the last eight) closing in the black. By employing it from the get-go come Friday (tomorrow is a holiday in the USA) I should be able to realize much greater returns by capturing bigger movements earlier in the day. So then, similar to how Jim Simons' Medallion Fund uses quantitative, data-driven strategies to capitalized on subtle, short-term market inefficiencies, Numerical Price Prediction's (NPP's) approach to day trading foreign currency pairs relies on data-driven pattern recognition to integrate the predictive power of repetitive price movements into a disciplined technical analysis methodology—leveraging ongoing real-time data and up-to-the-minute forecast models to interpret short-term price action in view of replicating price structures. The system's exact methodology can be conceptualized in the manner suggested by Nick McDonald of Trade With Precision—as a recipe that combines specific technical tools and confirming signals which align across multiple timeframes at a given moment, thus increasing the likelihood of successful outcomes by stacking the odds in the trader's favor, just as following a tried and true cake recipe ensures one prepares a well-baked delicious desert. Elements such as market structure, levels of support and resistance and typical price ranges are quantified to help identify optimal entry and exit points, ensuring trades align with mathematically justifiable choices stemming from objective, odds-based decisions. It is a robust system that balances rigorous precision with disciplined risk management to optimize trade outcomes. This approach employs: (A) principles akin to flight dynamics, applying physics-like rules to predict asset price movements, along with (B) cycle theory and (C) assumptions compatible with Edgar Peters’ fractal market hypothesis to detect subtle, recurring signals while grounding decisions in key technical levels reflecting past behavior. By combining a predictive edge with a focus on statistically validated trade setups, NPP aims to achieve consistent profitability through relatively rapid, high-probability trades while minimizing exposure to market noise and emotional biases.
I touched on how aspects of the quantitative approach developed by Jim Simons’ Medallion Mund and the recipe-like strategies of Trade With Precision’s Nick McDonald are reflected in the methodology used by Numerical Price Prediction—not to mention how elements of flight dynamics, cycle theory and Edgar Peters’ Fractal market hypothesis also come into play. However, I neglected to touch on the similarities between NPP’s viewpoint and that of Gareth Soloway, chief strategist at Verified Investing—a perspective he developed over 25 years which emphasizes a disciplined, probability-based approach to trading that leverages key technical levels and statistical odds to enhance profitability. So then, like Soloway, I too focus on key levels for decision making along with a proprietary methodology that combines odds-based price analysis, pattern recognition and critical timing to pinpoint historically proven, high-probability trade setups.