Set of rules, instructions, conditions coded into a computer software to predict movement in financial capital market. Also referred as systematic trading, robotic trading. An Automated Trading Systems or Algorithm Trading Software monitor trends or swings based on technical indicators, fundamental information and statistical information. Such information are interpreted by software from live streaming of market data feed and historical data. Algorithm Trading Software are used by portfolio managers, hedge funds, prop trading desk and retail traders.
Key behind Algorithm Trading is elimination of human errors as these systems eliminates any human emotions and 100 % discipline approach. Design of Algorithm Trading Systems are very robust and can make decision in nano seconds. Automated Trading Systems or Algorithm Trading Software are capable to incorporate any custom conditions and complex rules.
At Tvisi Algo Systems, we offer cost effective coding and consultancy services in automated trading domain. Our team is highly proficient in developing and designing of advanced trading systems in Python, C#, JAVA, C++. We work hard to design trading systems according to our clients custom requirements.
We at Tvisi Institute of Algorithmic Trading (TIAT) look to offer courses for programmers and non programmers to train them into quantitative or algorithmic trading programmers. Our course structure includes widely used programming languages like Python, C#.NET, JAVA, MQL, AFL with SQL database (basic and advanced SQL queries, stored procedures).
Our course is designed for traders, programmers, non-programmers to set up their own automated trading desk. Students will learn about capital markets (stock markets, forex markets, commodities markets). Students will learn about different trading platforms API like Interactive Brokers, Sterling Traders, Amibroker, Metatrader 4, Nest Trading platform, Trading Technologies and more. (Know More)
Demand for Automated Trading is on rise with increased participation of institutional traders, increase in retail traders and investors in all major capital markets. Selection of broker, type of auto trading system, technology selection to design your custom trading systems are of vital importance.
We have expertise and experience in Automated Trading domain and have an efficient team of quantitative programmers who are capable of designing and developing trading systems utilizing advanced mathematical models. Our team has expert programmers with skills in Python, C#, JAVA, VB, C++ and also understands trading and investments terminologies.
Our approach for programming Automated Trading Systems is streamlined, we discuss with our clients on Skype or over telephonic calls, we document our client's requirement step by step to ensure our understanding is on same page with our clients.
We believe in 100% accuracy when it comes to Automated Trading. Our programmers ensures all special cases, wild market scenarios are captured and are thoroughly tested. We also assist our clients with setting up trading desk setup, configuration of robots with broker's API and other third party trading tools or third party data feed providers.
Strategy backtesing is an essential tool to check if your strategy makes money over a period of time. Backtesting simulates your strategy trades on historical data. Instead of testing strategy with real money which could take months or year with risk of loosing money, a trader can simulate his / her trading strategies on historical data in order to gauge its effectiveness and check backtesting report. Backtesting provides simulated results for your strategy which will closely overlap with live trading results.
We have a dedicated research team experienced with Python, C#, JAVA, C++, R, Matlab, Excel and other statistical tools. Our team can assist you with research, analysis, reporting and optimization of your trading strategy. We can also code custom backtesting software. Custom backtesting software can have parameters for optimization, dynamic portfolio creation, create your own strategy or strategies and simulate backtesting one or universe of stocks.
Also known as HFT - a trading platform that run on powerful computers to transact a large number of orders at very fast speeds. Use of complex algorithms, best execution techniques, avoiding slippages are key for successful HFT systems. A HFT strategy opens trades or positions for few seconds. Institutions doing high frequency trading borrow significant leverage, do not accumulate trades or positions overnight, typically liquidate their all positions by end of market. High frequency trading systems requires high cost infrastructure setup, co-location server facility near exchange, round trip communication between HFT system and exchange should be minimal through very fast leased line internet, fast live market data feed. We provide consultancy for setting up best high frequency trading (HFT) desk.
Algorithms for HFT rely heavily on processing speed, data feed quality, direct market access, minimal transaction cost, smart order routing capabilities, order management and risk management makes HFT system highly scalable.Types of HFT systems.
History and live data feed providers for forex, commodities, stocks from all major global exchanges. Accessibility to live and history data feed is provided by data feed vendors through python api, .NET api, JAVA api, C++ api and direct history data download to excel or .csv files. History data time frame can go minimum upto 5 secs OHLCV candles bars. Major live data feed providers provides live tick by tick quotes or snapshot of few milliseconds quotes data.
Our in-house product history data download software developed on Interactive Brokers api can download history data for forex, stocks, commodities, options, index, ET with different chart time frames. Click here : for IB History data download software. We can also code history download software on any data feed vendor.
Many data feed providers also provides real time interactive charts with backtesting and market scanning. Below is the list of major history and live data feed vendors.
Algorithm trading in India started in 2008, automated trading has brought many significant changes in Indian markets and trading community. In the US and other developed markets, High Frequency Trading and Algorithmic trading accounts almost 73%. According the recent reports, 15% increase in automated trades on BSE and almost 49% of trades happening on NSE are through automated platforms.
Securities & Exchange Board of India (SEBI), started allowing Direct Market Access (DMA) facility on April 03, 2008 which facilitates trading by institutional clients without manual intervention by brokers. DMA permits direct access of exchange trading system through broker's infrastructure with no manual intervention.Trading platforms for Indian stock market