White Paper
Project History & Objective.
The EPIC software development team set out nine years ago to develop a sophisticated software architecture for the trade of originally crude oil futures and over time moved on to various other market instruments of trade such as Equity Market Indices, Stocks, Commodities and Crypto.
The objective: to provide a stable yet high performance auto trading software product achieving an increasingly higher ROI over time as the algorithm processes market data, structure of trade action and order-flow.
The software has undergone a number of updates over the years, the most recent updates have provided for a stable trading entity that continues to excel in terms of ROI.
Current Deployment and Use.
EPIC is now used by a diverse number of trading entities, for example at the trading team at Compound Trading Group and Associated Trading Platforms (for live trading alerts), AutoTrader Platforms, Copy Trading Auto Trade, Private Accredited Investor Client Account Trade Executions and our five deployed Crypto Tokenization projects.
Over time the architecture of the software has been perfected and as of late 2024 is considered “core” architectually complete and only maintenance and small incremental refined updates are expected in future.
Near Term Plans.
The EPIC Development Team is now in process of deploying EPIC Machine Learning Trade Software to a Private Equity Platform for the purpose of securing a quantifiable data-set in early 2025 to be used as a real world data set for deploying EPIC Software to further Private Equity Market Organizations & Funds and various Professional Trading Groups. We are also targeting late 2025 or early 2026 as a time to enter the publicly traded markets pending private equity deployment.
2025 is the year EPIC Machine Learning Software is deployed through-out global markets via Private Equity Fund and Professional Trading Groups.
Performance (ROI) and Stability.
In terms of performance, EPIC is now deployed to 27 different instruments of trade on various trade platforms and exchanges, with many different account sizes.
The team of five computer scientists running the operation are housed in a secure facility with 27 servers (each running one instrument of trade) and various other network equipment that bring the total upstart development costs (including overhead) in at just under 9M USD as of late 2024.
Annual returns range between 30% ROI – 300% with the average return being just over 90% ROI per annum. There are few real world trade scenarios in which EPIC is returning below 30% and few over 300% per year. The returns are expected to escalate (performance of the software) at a pace of about 10-30% escalation per year as it becomes more refined over time. Currently, in general a 70-90% per year ROI is the base line expectation for onboarding account consideration.
It is important to note that the specific instrument of trade, size of the account and when in the cycle of trade an account is onboarded to the software will affect the ROI determined at various reporting intervals. For example, an account onboarded mid cycle of trade sequence can see varied results until the onboarded account has run a full duration of trade sequence (which can at times be a few months or more depending on the market conditions and instrument of trade).
The primary game-changer in development was the EPIC IDENT™ Order Flow component of the code and more recently the Intra-Day High Frequency code that relies heavily on IDENT™.
In short, there are three primary protocols of code in the software;
- Swing Trading (average sequence duration is 11 weeks and has been as short as 1 week and as long as 16 weeks).
- Intra-Day High Frequency (average sequence duration is considerably less than 24 hours but can also be described at times as intra-week lasting up to 3 or 4 days).
- EPIC IDENT™ Order Flow (extremely high frequency for positioning alongside significant machine “entities” that have presented themselves in the intra-day order flow).
The software has proven to be very stable while consistently providing considerable returns.
To our knowledge, as information can be found publicly – the EPIC Machine Trading Software is quite literally best in class in the world.
What Does Best in Class Returns Look Like?
Jim Simon’s achieved an astounding average annual return of 66% from 1988 to 2018, before management fees. Contrast this with: Peter Lynch 29%, Warren Buffet 21%, George Soros 20%, and Charlie Munger 20% with the average annual return on the Standard and Poor’s index of 10%.
From Google AI:
“Jim Simons, a legendary investor and mathematician, achieved an average annual return of 66% for his Medallion Fund over 40 years. This return rate is considered unrivaled in the investment world.
Here are some other details about Jim Simons’ returns:
Net returns: Simons’ average annual net return was 39.2% after fees.
Fees: Simons’ fund charged a 5% fixed fee and a 44% performance fee after 2002.
Comparison to the S&P 500: In 2008, the Medallion Fund made 82% net of fees, while the S&P 500 lost 37%.
Comparison to Warren Buffett: While Simons is considered by some to be one of the most successful investors in history, his investment strategy was very different from Warren Buffett’s.
Simons was known as the “quant king” for his pioneering use of quantitative analysis in investing. He founded Renaissance Technologies in 1988, convinced that he could predict market movements with the same certainty as mathematical equations.”
References:
https://www.voronoiapp.com/markets/Jim-Simons-Medallion-Fund-vs-SP-500-Returns-1558
The main takeaway, EPIC Machine Learning Software is outperforming the best in the world, and it is doing that with superior stability (drawdown relative to return).
EPIC Software Highlights.
- Lightning Fast Decisions. EPIC trading software executes trades through utilizing over 9300 weighted decisions instantly. The instructions provided within the architecture are growing daily. A human trader cannot make decisions as quickly, cannot process the data required for most intelligent trading probabilities and cannot execute trades as precisely.
- Algorithmic Chart Models. The EPIC software code includes over 300 hundred proprietary algorithmic chart models and the catalogue is growing. The algorithmic models have been designed, tested and refined in real-world trade for over 9 years by a team of day traders, each with over 20 years of experience. The trading models represent all time-frames from 15 second to monthly time-frames of trade. The algorithmic models have been back-tested to sixty months historically.
- Conventional Charting. The software includes conventional charting structures on all time-frames, also back-tested sixty months.
- Common Trade Set-Ups. Included in the software are common trade set-ups that oil day traders implement.
- Order Flow. EPIC IDENT™ is data-driven order flow intelligence in real-time to achieve best outcomes. The software includes and executes to a proprietary order flow identification system that tracks behavior (specifically isolating other market machine liquidity) and weighs identified entities and historical trade patterns to its trade decisions (instructions). EPIC IDENT™ increases its intelligence as it gathers data intra-day specific to liquidity flow, historical patterns, time of day, volatility, various preferences, latency, rejects and more. The method is similar to back-testing charting. However, the process occurs in real-time. In short, the software is looking for “fingerprints” within market liquidity. We cannot back-test 60 months as with charting, but back-testing from date of software deployment has been achieved.
- Time Cycles. Time cycles are within all algorithmic and conventional trading model structures. Order flow also has identified time cycles and other time cycle events such as, for example, weekly reporting in oil markets (API, EIA and rig counts). Additionally there are time-of day market time cycles around the world. All of these different time-cycles are included in the software architecture.
- Hard-Pivot Architecture. The risk threshold – management system within the EPIC architecture has a hard pivot rule-set that has near ended substantial risk for accounts.
Combined, these advantages enable the EPIC Trading software to outperform conventional trading methods.
About Public Market Machine Learning Trade.
The world of public market trade is rapidly changing. It is estimated (depending on source) that over 80% of futures are not traded by humans and are now traded by machines.
Machine trade may be simple, bot style software, high-frequency software or more sophisticated architecture as with the EPIC class of machine learning algorithm.
Our team commenced the trading software development journey nine years ago with algorithmic chart modeling development. From day one we employed computer scientists to work with us on a daily basis to build software that would emulate our trading methods.
Over time the software started to win more trades than our traders and today we rely almost solely on the software to execute trades. We simply “tweak” the software at each trade sequence to improve performance.
Account Size: ROI and Draw-Down Volatility.
The smaller the account traded, the more difficult it is for the software to limit downside risk and provide optimal returns.
We have learned over time that the smaller the account traded size the more ROI instability and volatility and has more considerable associated risk. For example, with crude oil futures trade, a 600k account becomes a stable size and will rarely see ROI volatility and draw-down risk oustide expectations and a 900k account size or greater never encounters considerable ROI volatility. As noted above, the risk threshold – management system within the EPIC architecture now has a hard pivot rule-set that has near ended risk for larger accounts.
The software is designed to trade within a sequence of trade within structures or set-ups. As the market price changes, the software trading logic uses all the different data to update the decision tree utilizing the instruction rule-set.
You can imagine this as a dot plot process similar to the game “Go” – not exactly, but the concept helps to visualize how the software plots a sequence plan for trade.
The “ebb and flow” of regular market trade allows opportunity for the software to plot a plan of trade within a sequence. The larger the account, the more dots that can be plotted (trades can be “bite sized” entries within an “ebb and flow”).
To understand the trading methodology of the software in each “sequence” of trade requires a moderately in-depth conversation to review data with a member of our team.
In short, the software uses a positioning (swing trade) protocol for each sequence of trade and a high-frequency intra-day protocol via EPIC IDENT™ technology. On the positioning (swing trade) side of the architecture, this means that as price is rising the software is building a position short through-out the rally (and the opposite is true if the price is falling). However, the average cost is off-set by the high-frequency component of trade via EPIC IDENT™ technology so that when the trend reverses the software achieves considerable returns.
API / Deployment Architecture.
EPIC software is designed to be deployed remotely – accessing an account and executing trades. This provides the account holder with ultimate control. The account holder grants the software access and the software executes machine trades to the account. Architecture provides opportunity for decentralized platform integration.
Conclusion.
This paper outlines the opportunities that can be presented by the growing influence of machine trade on global financial markets.
Competitors within the machine trade industry are becoming more and more refined and successful – the best in class are assumed to be winning a larger portion of proceeds.
The most significant immediate challenge developers face in machine trade is building a product that will perform within a prescribed threshold of downside limiting stability while outperforming conventional trading methods.
Soon thereafter the challenge becomes competing against “like-kind” machine trade peers and being best in class.
It is our expectation that fewer and fewer competitors will achieve more of the proceeds (as a whole of trade in public markets) at an exponential rate, which does provide urgency to development and deployment.
The EPIC machine trading software achieves consistent, predictable and very adaptable architecture that provides exceptional best in class ROI.