How the story began
The story began 15 years ago when a group of developers founded a small IT company and started to work on the introduction of quantitative methods of investment research based on the experience of scientists in the field of theoretical physics, applied mathematics and programming in the financial markets. Today Quant Infinity is an international group of IT-companies focused on developing software for quantitative trading on international financial markets. It has over 15 years of experience in product development for financial companies, 8 years of which were spent successfully developing and installing automated trading systems. Investment hedge funds, trust companies, banks, and family offices implement Quant Infinity solutions for managing either their own funds or for providing asset management services to clients under their own brand (White Label). Quant Infinity services are already used by financial companies in Europe and Asia.
What is Quantitative Investing, and how does it work?
Quantitative investing emerged in the United States in the 1970s. Edward Thorpe, an American professor of mathematics at MIT (Massachusetts Institute of Technology), is considered to be the founder of this trend. In his research on the movement of quotes on the stock exchange, he concluded that it is possible to predict changes in asset prices with the help of the probability theory, predictive analytics and the law of large numbers.
Thorpe used his developments in his first quantitative investment fund, founded in late 1969. Over the next 18 years, he turned $1.4 million into $273 million. His Princeton Newport Partners (1969-1988, with an average income of 19.1% per year) and Ridgeline (1994-2002, with an average income of 21%, with a volatility of 7%) were beyond the reach of traditional managers of that time.
In the 1970s, for investors accustomed to investing in traditional instruments on financial advisers’ guidance, Thorpe’s method appeared to be like predicting the future. However, over two decades, many hedge funds, major banks, and other financial companies in the US actively began to apply this method. Citadel, QIM, TwoSigma are the most well-known companies among them. The method has been utilized as well by some investment departments at the largest US banks like JPMorgan, Citigroup, Goldman Sachs, Wells Fargo, and others.
Quantitative funds today
By the end of the first quarter of 2019, the total assets under the management of hedge funds reached USD 3.0113 trillion. According to Global Hedge Fund Industry Outlook 2019, the largest funds which use quantitative methods of investing demonstrated significant growth over the period 2013-2018. The volume of assets under the management of these funds is more than USD 1 trillion.
Hedge Fund Industry AUM, $ Billions (Source: BarclayHedge)
Predictive analysis, probability theory, Big Data, and Artificial Intelligence used for analysis and prediction in quantitative funds. The best of these funds present impressive results on a long horizon. For example, the average annual return of Renaissance Technologies by Jim Simons (the founder of the most successful hedge fund according to Forbes) for the last 30 years was 40% per annum. Even the total average return of all quantitative funds exceeds traditional hedge funds´ return. Between 2012-2017, the average return of quantitative funds was 5.1% per year, while the average return of “traditional” hedge funds was 4.3% per year.
How to profit from this
The Quant Infinity solution is an international algorithmic trading strategy developed in 2011 which is being constantly improved by a team of mathematicians. Since the beginning the strategy has been continuously developed. The results, which are regularly confirmed by an international audit company are above 35% p.a. in average. For risk-averse investors, the volatility of the strategy can easily be down-scaled, thus still offering pure alpha creation. The strategy has always been among the top 10 international rankings of Barclay Hedge and EurekaHedge in terms of return on par with the largest international funds.
The strategy currently encompassed more than 7´000 bots which are all being run and monitored automatically. The quality of each individual bot is essentially determined by its return per risk and is conventionally measured via the Sharpe ratio. Mathematically, the Sharpe ratio is defined as the ratio of the annualized mean return to the annualized standard deviation of returns. The higher the Sharpe ratio, the smoother the track record of the individual bot. It is directly linked to the probability of generating a positive return over a given horizon of time. Over the last 4 years, the Sharpe ratio of the Quant Infinity strategy is 1.27. As a benchmark, over the last 4 years the Sharpe ratio of the S&P 500 Index is 0.72. Under these circumstances the probability to achieve a positive result over the next 2 years is 92.9% for the Quant Infinity strategy and only 83.5% for the S&P500 Index.*
* The Sharpe ratio of the strategy was calculated using Composite track record since 01.07.2015. The Sharp Ratio of S&P500 Index was calculated using open sources since 01.07.2015.
Ways of cooperation
White label fund/proprietary trading
You as a regulated investment company (e.g. a fund) can offer the Quant Infinity-Strategy to your own clients either as a stand-alone version or integrated with different strategies to increase your diversification.
You own the product and you set up the parameters which are right for your market and your clients at your own discretion. The total amount of assets under management in the strategy shall however not be less than USD/EUR 5 M for a proper functioning of it.
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Phone: +357 25262186
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