The FIX Index, short for the Financial Market Fluctuation Index, is a set of innovative and leading volatility indices that provide early warning signatures of imminent market volatility, growth, baselines, and market pulses in advance for sophisticated risk management. Stay ahead of the curve with our one-of-a-kind leading market indices. We offer low-risk high-return solutions with our cutting-edge data-driven strategies.
After a decade of research using a sophisticated multidisciplinary
approach that combines cutting-edge methods in physics, namely
quantum mechanics, statistical mechanics, complexity physics,
and network theory, with economics, we have developed a
huge set of innovative signals, which no other firm offers,
that provide early signatures of volatility
and growth in the financial markets.
Currently, we have 700+ distinct signals for major global indices such as S&P-500, NASDAQ, MSCI World Index, and so on distributed across the following main categories.
• FIX Volatility Index®
Provides signals of impending market volatility weeks to months in advance, helping us protect our long-term returns from sudden market drops.
• FIX Growth Index®
Equally crucial, it confirms the bottom of a correction and indicates an impending rally, presenting an opportunity to enter the market at lower prices.
• FIX Market Pulse®
Provides an epoch for phase transitions and the directionality of the momentum
• FIX Market Baseline®
It acts similarly to support and resistance levels but is derived from financial networks rather than traditional pivot levels.
• FIX Cyclic Index®
Meanwhile, the Cyclic Index identifies prevailing trends in the market influenced by various factors, including seasonality, economic cycles, and sector rotations.
Moreover, these signals are not derived from AI. The FIX indices are calculated using a novel methodology based on a purely mathematical formulation with a rigorously defined set of equations and codes.
The FIX Index is built on a robust mathematical framework rooted in complex systems, non-linear dynamics, network theory, quantum and statistical mechanics, such as Random Matrix Theory (RMT), Gaussian Orthogonal Ensembles (GOE), Power Law, and Spectral methods such as Detrended Fluctuctuation Analysis (DFA) combined with mathematical microscopes such as Fourier and Wavelet transforms.
No AI or machine learning is involved in the development of the indices, which helps us avoid issues such as overfitting, sample set limitations, gradient descent problems, and other criticisms associated with black-box approaches.
Although we do not use AI in the computation of volatility and generation of the signals, AI can be used later to refine the insights and enhance the predictive capabilities our the financial models. Such systems are called Physics Informed Neural Networks or PINNs.
Furthermore, it can be difficult to manually analyze the hundreds of signals that we provide from our quantitative and mathematical models. The first five signals can be read and analyzed by visual inspection, which provides a good estimate of the imminent volatility. However one can use the hundreds of supplementary signals by supplying them data to sophisticated machine learning and artificial intelligence algorithms to extract deeper insights from the extensive data giving a highly accurate estimate
As we use a network approach, we do provide estimates for the entire market and not individual companies.
Translating the signals derived from the financial system's dynamics allows us to gauge the volatility of major global markets, and several sectorial indices as well. Therefore, simple trading strategies with automated guidance from the FIX-based system can outperform the market.
The strategies involve simple rotations and rebalancing across major global indices and sectors without using leverage, derivatives, commodities, and assets with higher risks such as small and mid-cap companies, private equity, or cryptocurrency. To enhance the returns further we do provide bespoke strategies tailored to the risk-reward appetite of our institutional investors.
