Quants & HFT

Situation

The interaction between Technology and Economics in Financial Markets has revolutionized the process of Trading Strategies in Financial Institutions. Decisions that used to take hours in the past are now made within seconds. In our days, we can use analytical Algorithmic Systems that compute large amounts of data and mitigate risk in real time to achieve optimal execution strategies through unique configurations.

The tools needed to participate in such Electronic Trading environments consist of a computer and software linked to a trading platform. Efficiency in Execution depends on the computer and software characteristics as well as on the algorithms implemented for targeted trading objectives.

Although there are various algorithms in the market, none can be adjusted to the different levels of risk investors are willing to take. A Quant & HFT Desk is responsible for the Research and Development of such models that would satisfy any client’s investment needs, i.e. investment returns higher than interest rate or stock exchange performance.

Complications

The Finance Institutional Industry is currently under reconstruction, and firms are setting up more sophisticated systems that provide more sophisticated analysis, strategies and techniques via Quantitative Analysis, Quantitative Strategies, Algorithmic Trading, High Frequency Trading, Black Boxes and Grey Boxes, etc. in order to compete in the market.

On this particular subject there is not a lot of literature covering algorithm development and implementation and the existing research cannot always justify the results. This is why Techno's Quant desk does not limit itself by solely analysing data but also by providing end products (Algorithms) that can be tested, modified and produce tangible results.

The process of Algorithmic Trading combines a variety of fields such as:

• Human Behaviour (i.e. what drives people desire to buy or sell)
• Computer Science and Artificial Intelligence (i.e. how can we integrate intelligence in a computer systems, how can systems learn and re-adjust)
• Mathematics (i.e. how functions can be adjusted in order to justify right decisions, as well as quantitative approaches to future financial behaviour and probabilistic approaches to trading actions).  

Therefore the main complication remains to incorporate all of the above into trading frameworks in order to create specific Algorithms for optimal Trading depending on risk-reward ratios. 

Solutions

Techno Innovations' Quant Desk focuses on producing Algorithmic Trading Systems (i.e. computerized systems) by implementing deferent risk metrics (i.e. Risk Management) with the aid of signals (i.e. Optimal trading Points) in order to achieve Optimal Trading Strategies.

It researches the various conditions of a trade and distinguishes what characterizes a trade as optimal, and how price and volume affect the market equilibrium state.

Further, it researches into risk assessment, i.e. quantitative grouping of data, statistical interpretation, ratios, comparative variables, behavioural finance, etc. in order to understand how to manage risk and learn from a number of available options.

It also investigates Algorithmic limitations and advantages of the computing decision process.

Taking all the above into account, Techno's Quant Desk is able to create custom Algorithms depending on the risk and return clients are willing to take (i.e. higher risk investments should account to higher expected returns).

Finally, once set up and tuned on the necessary variables, any Quantitative Trading Algorithm should be able to work on its own, with Human Monitoring, and identify and distinguish what makes a right and a wrong decision, making sure that Optimal Execution will occur.