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ALGO -TRADING : Developing a Mechanical Trading System

A trading system is a set of rules that defines conditions required to initiate and exit a trade. Usually, most trading systems have many parts, such as entry, exit, risk control, and money management rules. The rules of a trading system can be implicit or explicit, simple or complex. If you’ve ever tried it, you know that developing a trading system is no easy task. But you may find that following a series of steps could help you reduce the learning curve.


MFCS teaches about designing, testing, and implementing trading systems for the futures and equities markets. It begins by developing trading systems and ends by defining a system for trading. We deal with development and testing as in how the system performed on past data. It also discusses basic rules, key issues, and many new systems & explores how the system might do in the future, with a focus on equity curves, risk control, and money management.


There are three key features when it comes to developing a trading system: entry and exit signals, a plan for the type of stop, and a money management strategy. The goals of a mechanical system trader are to pick a time frame (for example, hourly, daily, weekly), identify the trend status, and anticipate the direction of the future trend. The system trader must then trade the anticipated trend, control losses, and take profits.

Algorithmic Trading Strategies

Algo trading


Mechanical trading system can be defined as methods of generating trading signals and quantifying risk that are independent of an individual trader’s discretion. Although the advantages in utilizing a mechanical trading system are manifold, most market participants agree that their greatest benefit is the tempering of destructive trader “emotionalism” – which is considered to be the enemy of all successful market participants from the decision-making process.


Obviously mechanical trading systems can be developed based on any number of objective criteria including interest rate differentials, gross domestic product, or EPS. But there is a fundamental limitation in using such tools. These tools require an in-depth understanding of market, trading instruments, equity patterns and technical analytical tools. Although in-depth knowledge of underlying fundamentals is not a necessary requirement. In fact, lack of fundamental knowledge allows traders to apply their system as readily to equities, live cattle, foreign exchange, commodity markets etc. Avoiding discretionary and Using a nondiscretionary, mechanical system is not easy—otherwise, everyone would do it. There is a lot of work in corning up with a system, testing it, adjusting it, and trying it correctly and convincingly. The tendency for many people is to "wing it" and see if it works. That method leaves the trader nowhere.

Algorithmic Trading Course | Learn Algo Trading

Algo trading is a platform where trades are automated with the help of a software eliminating all sorts of human interventions. The algo trading system is installed with trading strategies based on which trades are executed. The major dilemma of whether to enter a trade or not is completely taken care of by Algorithmic trading.


Basic advantages of a trading system are as follows

  • Eliminates emotion

  • Eliminates need for constant decision making

  • Ensures consistency of approach

  • Risk control

  • Same approach can be applied to many markets

  • Approach can be tested for statistical reliability


Technical analysis is used to develop two different types of mechanical trading systems for trade execution. Price – driven systems and indicator driven system. A combination of both can also be used. Deep knowledge of these systems is required to build up lucrative strategies and then ultimately generate profit from them.

  • What and Why of Algorithmic Trading?

  • The Transformation from Manual to Algo Trading

  • Stages of Algorithmic Trading:

  •  Formulating the Trading Concept/Logic

  •  Filtering criteria to choose the scripts

  •  Verification of Logic (at High Level)

  • When did Algorithmic Trading start?

  • Frequencies of Trading: HFT, MFT, LFT 

  • Algo Trading Strategies

For a better understanding, look into the list of the most popular strategies and their explanations:

  • Market Making Strategies

  • Arbitrage Strategies

  • Statistical Strategies 

  • Momentum Strategies

  • Sentiment Based Trading Strategies

  • Machine Learning Trading Strategies


  • Scalper

  • Scaling

  • Advance Jobber

  • Trend Jobber

2 Leg Spread Strategies

  • Currency Spread

  • Calendar Spread

  • Mega Vs Mini

  • Roll Spread

  • Cash Future ARB

2 Leg Ratio Strategies

  • Pair Trading

  • Long Short Equity

  • Bank Nifty Vs Nifty

  • Long Short Commodity

3 Leg Strategies

  • Long Short Equity

  • Commodity Arbitrage

  • Triangular Currency ARB

Basket Trading

  • Nifty Basket

  • Scanners

  • Proprietary Strategies


  • What are the Rules and Regulations in India?

  • How to Learn Algorithmic Trading.

  • Back testing and Optimization.

  • Paper Trading aka Forward Testing or Simulation Trading, in the real environment.

  • The workflow of Algorithmic Trading.

  • Deployment in the real environment

  • How to build your own Algorithmic Trading Business?

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