I spent the vast majority of my career working in the high-tech industry as a professional engineer, marketer and business manager. From a young age I was fascinated with the vision of working hard, earning more than you spend and investing the difference in high-quality investments that yield a sizeable return. By age 30 I sampled investment offerings from the most reputable and most highly regarded companies in the US asset management industry. Charles Schwab, Vanguard, TD Ameritrade, eTrade, Interactive brokers, eToro, FxPro, Skilling and ICmarkets are companies where I still maintain accounts. The promise of the investment Industry makes logical sense - I work hard in my job and they work hard to put my capital at work to obtain a steady growth while minimising risk. I get my work amplified by the work of others and I benefit by being prudent enough to save and invest – rather than simply consume.
My first reality vs expectations shock came in 2001 during the dot com collapse. Three years into my multinational a career I had amassed considerable sum in my retirement account. I watched in horror as those savings dropped by 50% in the span of a few months. I couldn’t understand how a professionally managed diversified portfolio could drop by that much. Was this an unprecedented event? As an immature investor I closed all my positions to protect half my capital. I started investigating the history of the asset management industry to understand how unprecedented my circumstance was. I discovered that often asset management professionals often at best replicated index performance and that they used investments from many sectors and geographies to minimise risk, often at the expense of growth performance. The result was most often underperformance relative to the S&P 500 long term while getting little protection in major market downturns. Yiannis, these events are rare events - I told myself - surely, they only happen every 30 years or so? Then in 2008, merely 7 years later the Lehman collapse happened - wiping even more from my portfolio. 12 years later during the COVID pandemic there was a -30% short-term crash followed by explosive growth thereafter. I guess not every thirty years. In fact counting market downturns of greater than 20% - I count 5 for the S&P 500 – 2 of which were greater than 50%.
S&P 500 Futures Weekly Chart Showing 5 >20% Market Crashes since 2000
Being someone who believes in personal responsibility - I came to the conclusion that had I held to a buy and hold mindset - all my personal investing challenges would have been solved. This is largely true - buy and hold in most cases - since 1929 would have worked out great. Being a bit of a perfectionist though I wanted to understand how buy and hold would have fared through the 1929 crash. During the Great Depression the markets lost a total of 90% in value over the span of 3 years. This left me with a bad taste in the mouth. Even the holy S&P 500, fully diversified and in all its glory is vulnerable to a 1929-like event. Very vulnerable it seems - so vulnerable that you can be left with 10% of your original wealth, potentially amassed over a lifetime. Whether you believe a 1929-like event can happen again is down to personal belief and most of our beliefs are shaped by our experiences. As I watched my father lose everything in 1974, during the short Cyprus war and then have half his life savings confiscated in the 2013 bank crisis in Cyprus - my beliefs tend to not put all the faith in the systems that govern us.
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A technologist at heart, with a history in measurement, data, analysis and cause & effect process - I wondered if technology could help. Can signal processing, analysis, statistics and the modern world of machine-learning help us build better investment offerings? When I first started delving into automated trading and the underlying research on different quantitative techniques - I landed on the story of Jim Simmons, the mathematician who founded Rennaissance Technologies. I read how Jim built an empire that beat all the financial asset managers at the game of investing. He was able to get a higher return for a lower risk over decades. This gave me encouragement to keep digging. I found a lot of resonance with the research from John Ehlers, who wrote many books on signal processing in financial markets. John did a great job sharing his work with the community. I tried to convince John to work with me, but he very gracefully explained to me that he is fully retired and not looking to change that. Then I was fortunate for a period to get exposed to and work with Dr. Anthony Constantinides from Imperial College in the UK - founder of the Financial Signal Processing laboratory there and this once again encouraged me that the journey would be difficult but with an end in sight. I am also convinced that this road must be travelled as it holds promise to offer something extremely beneficial for the world of investing.
John Ehler’s book Cycle Analytics for Traders
Dr. Anthony Constantinides Presentation on Financial Signal Processing Principles
The next and most important part of our journey was getting reunited with Dr. Panagiotis Charalambous - a friend of a friend and someone who had developed an entire acoustic modelling software package - including all the acoustic models and the solver engine encompassed within. I found out that Panagiotis had been working for years for Spotware, the cTrader company (a leading retail trading platform) - that he would help users develop algorithms for automated trading and that he was very open to a collaboration as it fit right in line with his expertise. We agreed with Panagiotis that we would do a very informal test on some of the ideas and decide whether to proceed based on the findings. Three years ago, Panagiotis did the test and told me that the results are promising. He added that in his day to day work he sees many results and many ideas that when implemented and back-tested back 10 years don’t work out. I had already founded Aieden Technologies through which I was invoicing my consulting clients - Panagiotis partnered with me and off we went.
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Spotware and the cTrader platform were clearly an ideal choice for us at this stage in our journey. cTrader is a robust, extremely well engineered platform - has support through C# for automated trading - advanced genetic algorithms for optimisation of parameters, backtesting and most importantly a native copy trading eCosystem. I became a believer in copy-trading eCosystems as a way for deploying our trading technology to traders in the most efficient way possible. As we never take ANY custody of client funds, and we don’t recommend the choice of strategies that an investor pursues – copy-trading allows the technologists to do technology and the regulated brokers in the eCosystem to do their work in providing regulated investments. While copy-trading is only currently available on retail brokerage eCosystems - we believe the end user benefit is so large that eventually large institutional brokers such as Interactive Brokers will be forced to participate. Collective2, is a 3rd party startup that offers copy-trading to US investors – using directed trading with Interactive Brokers – paving the way for copy-trading to obtain legitimacy, even in the United States. Already some new brokers in the United States like Alpaca … have extensive capabilities for directed trading through APIs - paving the way for copy trading eCosystems.
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We spent the last three years with Panagiotis, researching, developing, testing different technical analysis techniques, statistical techniques and our own signal processing. We had many failures, but each one yielded a new component of learning that had to be learned through hard work and failure. 14 months ago, we deployed our most promising EURUSD Grid Algo to start building a track record as a proof-of-concept. This demo account has run 24/7 on the cTrader Copy eCosystem and as of the date of writing this article has generated 67% growth in that timeframe against a worst case risk of -37% (which is still a bit too high for our liking). Obviously, an investor can make choices on the funds allocated to this strategy as part of their portfolio so that they can manage the reward/risk equation to their preferences. Many algos on cTrader Copy promise 1000s of percentage gains by using extreme leverage but they have a different philosophy to ours and most of them simply fail and restart (i.e. just like financial asset managers have done but worse because their longevity is six months). We want a long term differentiated return compared to traditional products for the self-managed investor and our end goal (in the next 12 to 18 months) would be to deploy 20 to 50 strategies so that a self-directed investor can invest in a portfolio that consists of a variety of assets and strategy types.
Asset History of Aieden EUR/USD Grid Running on cTrader Copy
Part of our commitment is to ‘eat our own dog food’ as they say. My commitment is to redirect my own investment capital towards our own copy trading strategies so that I experience the exact same experience with my own capital as those that utilise our strategy through regulated brokers. Every time we release a strategy - more of my capital will be deployed towards this end. What better market research can you have than that?
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This is the story of our journey and its authentic cause we lived it and because we are real people with real names and public personas - I hope you find it interesting, and I hope you join us.
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