Trading Platform – Algorithmic Trading Model

Trading was always a difficult profession; getting better returns is one of fund managers’ primary concerns. Although this may appear to be a simple smart profession, with the massive quantity of information streaming through to the financial markets in a single second, a fund manager (FM) is left unable to deal and do his work with high productivity and huge profits.

Multi-asset (cross-asset) class trading necessitates a significant amount of study and analysis, and profiting from this technique needs an FM actively working with the trader – Alpha is what it’s all about. Most hedge fund managers’ ultimate goal has been to locate liquidity and benefit on deals done with wider spreads and higher profits. However, with more regulation and openness in today’s financial markets, facilities now have to consider better ways to get the necessary alpha and, eventually, profit.

Any use of algorithmic trading has increased significantly during the last decade. There are several ways available to assist an FM in his or her pursuit of alpha. These vary depending on asset type, deal size, risk tolerance, and a variety of other criteria.

Introduction

Many hedge funds adhere to a single principle: make income when the moment is right and before everyone else realises it’s feasible. They aggressively trade on both sides of something like the order book, regardless of whether the market is rising or falling. The process of finding liquidity across all types of investments and locations may not be a reality today, but with the effect of technology and the alarming rise witnessed in the alternative trading arena, it may not be a far-fetched prospect in the future.

Purchasing has taken a blow, but savvy fund managers will use any downturn as a chance to apply algorithms that will recoup their lost funds in a short period.

Technology Adoption

FMs are looking for methods to strengthen their trading approach. By hiring PhDs and mathematicians to create complicated arbitrage models, they are some of the early users of technology to help in financial decision-making.

Computational, networking, and connection are becoming more affordable because of technological advancements, which are being paired with increasingly sophisticated solutions and services. FMs are pushing the bounds of what technologies can accomplish daily to locate liquidity.

What does it mean for the trader?

Apart from activating an algorithm, a trader is just not required to make any further decisions in algo trading. This would not imply that the algorithm would replace the operator; alternatively, that trader will collaborate with quantitative analysts to develop new algorithms and adjust existing ones. The use of a graphic panel to plan and control hundreds of distinct algorithms is the way ahead for increasing traders’ productive.

Tools for the job

Jonathan discusses how a trader might employ the wide range of algorithmic trading capabilities accessible to him to attain his aims in the same way that Batman fights crime. The goal is not to have a comprehensive collection of algo trading strategies under its belt, but rather to be creative in how the trader applies them to his benefits, such as lowering costs, increasing trading efficiency, and freeing up essential time to process complicated trades that require his training and ability.

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