Onyx Financial is a provider of financial market technologies focusing on creating robust solutions using the latest quantitative methods and technologies.

Algorithmic Trading
Onyx Financial's trading platform interfaces with a number of brokers and provides real time automated trading. New models and algorithms can easily be added and ensembled to stay up to date with market conditions and risk profiles. Failover connectivity or VPS hosting may be enabled to ensure seamless access to the market.

The platform back-tests models against a wide variety trading objectives and walk-forward scenarios. Onyx Financial has an extensive library of financial data spanning the past 60 years in the equity and FX markets and 10 years in the commodities markets. Many of Onyx’s models have been back-tested on over 100,000 bars of historical data.

One of Onyx Financial’s key focuses is on keeping the number of features and parameters in a model small to ensure that the model is robust and not over-fitted to aged market conditions. Models also usually combine different time frames and the ensembling of principles from the fields of Pattern Recognition, Intermarket-Relationships and Digital Signal Processing (DSP).

Onyx Financial is not currently trading fixed income, credit or volatility based instruments however this is currently under investigation.

Pattern Recognition and Machine Learning
One of Onyx Financial’s key strengths of is its innovative use of genetic and machine learning computational techniques to gain the maximum returns from market inefficiencies.

In Onyx Financial’s arsenal of pattern recognition models include –

Support Vector Machines (SVMs)
Gaussian Process Regressions (GPRs)
K-Nearest Neighbours (KNNs)
Artificial Neural Networks (ANNs)

Most of these systems are able to provide a Bayesian measure of confidence allowing trading to only occur on those patterns with the highest confidence.

Many patterns in financial time series occur over wildly different time frames. Onyx Financial implements models which draw heavily from the field of Speech Recognition including Isolated Word Recognition (IWR) to dynamic warp market data feeds to correct for dilation in the time or volatility domains. This also gives the algorithms a tendency to be adaptive to market conditions.

Onyx Financial employs genetic algorithms to solve the problem of parameter optimisation. However, using a reduced number of parameters or robust sets of parameters which perform well over a wide variety of market conditions is favoured to trying to find the absolute optimal solution. Additionally non-parametric models which map feature vectors to higher dimensions are favoured as they require minimal optimisation and are hence more stable.

Model inputs are measured for effectiveness and carefully chosen using a number of proprietary metrics. The distribution of these inputs is usually examined and mapped to a uniform probability distribution to increase the model’s ease of learning. Furthermore, the number of features is frequently reduced using the Karhunen–Loève Transform (KLT) or Singular Value Decomposition (SVD). This ensures that the principal components of market behaviour are identified and isolated before modelling.

Onyx Financial frequently ensembles many models into a single trading algorithm. This ensures that the maximal amount of inefficiency is extracted from the historic time series.

Shannon Entropy, Mutual Information, Hidden Markov Models (HMMs), Maximum Entropy Spectral Analysis (MESA) and Singular Spectrum Analysis (SSA) models are currently under investigation.

Volatility Modelling
Onyx Financial has a wide variety of techniques for volatility approximation and forecasting. At the most simple are the EWMA and GARCH models which we use for scaling of time series data and in our risk management methodology.

In the field of derivatives trading, accurate forecasting of volatility is crucial. Onyx Financial is able to use its machine learning models to create high fidelity models which simplify the measurement and prediction of volatility and hence yield accurate derivative pricing. This may be employed for volatility arbitrage, VIX trading, or pricing of derivatives on both buy and sell sides of OTC transactions.

Onyx Financial is able to provide a number of derivative pricing models based on Finite Difference Method (FDM) based on either explicit or implicit calculations.

Risk Management
Risk Management is the most commonly overlooked component of systematic trading. Onyx Financial solves this challenge by combining a number of simple yet robust strategies.

Firstly, Onyx Financial is able to deliver experience in Monte Carlo methods for both Market and Credit Risk Management. Of particular interest are the use of Antithetic and Low Discrepancy Numbers.

However for the purpose of risk management on real time trading, a volatility adjusted bootstrap of historic portfolio values can yield a highly robust measure of the expected draw-down with a given level of confidence. This avoids the need for excessive calibration or approximation of correlations. In other words this uses the co-dependency structure of the historical data to model portfolio behaviour while avoiding the need and hence dangers inherent in calibration. Historical changes in portfolio value are corrected for volatility before bootstrapping. The success of this method is reliant on having a reasonable approximation of the current volatility.

Onyx Financial is able to combine many trading strategies optimally to minimise portfolio drawdown. This is tempered with an understanding that in extreme events the co-dependency of markets is likely to be very different to normal day-to-day trading. In other words, in a distressed market, most instruments’ behaviour tends to approach perfect correlation.

Using Onyx Financial’s systems a new trade is not taken unless it satisfies risk management criteria.

Technologies
Onyx Financial is able to provide extensive experience in software development. Our custom solutions are architected and built to fit business needs. These predominately focus on robust, fast, usable and extensible systems. Our development technologies of choice are –

Microsoft Visual C# 2010
Microsoft Visual C++ 2010
Microsoft SQL Server 2008 R2
Mathworks MATLAB
Microsoft Excel 2010 (VBA)

Web technologies such as ASP.Net 4.0 are also available on request.

Where appropriate we have the option of performing highly vectorised calculations on the CPU using Intel’s Maths Kernel Library (MKL) library.

We are currently investigating hardware-dedicated GPU processing for even faster calculations.

About Us
Onyx Financial is available for either consultancy and/or software development. Please contact for further information.