*Using Factotum*
Ultra Low Latency Financial Trading Suite for Arbitrage and High Frequency Trading
Factotum Overview
Factotum is a platform independent suite, which runs on all operating systems (Linux, Windows, Mac). It uses Java and C as the main programming languages, with no external library dependencies
Factotum Client (Fractal)
Traders interact with the system using Fractal for placing all portfolio orders and managing parameters. It is user friendly with extensive tracking and analysis features.
Risk Management System (RMS)
Factotum RMS, enables the admin to control and monitor all traders activities. RMS is compliant to the requirements of exchanges, and permits the admin to set limits at all levels (system, trader, and/or portfolio)
Factotum Core (Algo Engine)
The algo engine (CORE) is in C with no external dependencies. Has a very efficient order-book management, while receiving several hundred GB data in a day. The wire-to-wire latency of the core is around 1-microsecond.
Trading Strategies
Factotum offers a wide variety of multi-leg strategies for futures and options, having the option of placing IOC multi-leg Orders or Bidding in one leg and covering other legs within microseconds. Also provides a long range of custom strategies for professional trading, like, momentum, market-making, scalping, etc. HFT strategies, along with the benefit of low-latency.
Multi-Leg Strategies Any combination of 2 to 6 scripts in any ratio
Single click access to most of the popular strategies. User can also create custom strategies as he wishes.
Standard Arbitrage Strategies Pure Arbitrage, Semi-Arbitrage
Options Box-Spread, Conversion-Reversal, Calendar Spread, Butterfly, Straddle-Strangle, and many more.
Special & Custom Strategies Market making, HFT, Basket, Others
Special strategies can also be implemented at low level. This enables lightning fast order placement on exchange.Connectivity and Placement
Factotum
Core is put in a Linux server in exchange's co-location. It is responsible for receiving tick by tick data, executing algorithms, and placing the orders to the exchange matching engine. Core encompasses all data connectivity modules to communication with exchange servers.
RMS can be placed in exchange or member's data-center. RMS communicates to Core over a TCP connection. It is responsible for all required checks, risk management, monitoring, and centralized control.
Client Fractal can login directly to RMS with proper authentication. Traders can access client from their working place over secure channel. It uses TCP connection to connect to the RMS.
Exchange Co-location:
Large exchanges allow clients/members to place their servers very near to exchange's "ORDERS MATCHING ENGINE" for low latency. This part of the exchange's data center is called as Co-location or Co-lo in short.
XTS ALGO TRADER SIMPLIFIES ADVANCED ALGORITHMIC TRADING AND REDUCED TIME TO MARKET
XTS ALGO TRADER
Multi Leg Strategy
Master Scalping
Candle Breakout
Call Executor
Calendar Spread
Ratio Spread
Multi Leg Strategy
Multi Leg Strategy is designed for smart traders to trade with multiple scripts and get the desired spread. This strategy is capable to place order for 2 leg, 3 Leg and 4 Leg of Options and Futures strategies. This strategy can be used for executing Option strategies, Future-Future, Future –Option, Pair Trading and Rollover.
Master Scalping
In this strategy whenever price moves down side it will buy/accumulate and upside sell and vice versa. User can define Start point and entry difference & exit difference, so system keep on Buying defined quantity whenever price goes down and sell whenever price moves up automatically and try to accumulate profit.
Candle Breakout
In this strategy system captures the High & Low in given period of time of a candle and place the Buy order 1 tick above the High and Sell order 1 tick below the low of the candle. If any one side order get execute system immediately cancel other side order and place Profit Target and Stop Loss as defined by user.
Call Executor
XTS Algo Trader Call Executor is CSV/Excel based Execution strategy for traders who generate Entry/Exit or Buy/Sell levels through their own analytic or subscribe to signal providers for Buy/Sell decisions. Through this strategy user will simply provide the trigger levels in a .CSV file & the strategy will accordingly execute the signals automatically.
Calendar Spread
Calendar Spread strategy involves simultaneously buying and selling of future contracts of same symbol but with different expiry dates.
Ratio Spread
Ratio Spread is an options trading strategy that involves buying and selling options contracts to create a position with a specific risk and reward profile. The strategy is implemented using options of the same type (either all calls or all puts) on the same underlying security, but with different strike prices and in different quantities.
XTS Algo Trader Algorithmic Trading Strategies
Trading Strategies
High Frequency trading models
Low Latency Statistical Arbitrage
Market Making
Quant Based Algorithm
Market and Newsbased Event Strategy
Benchmark-Driven Based Algorithms
High Frequency trading models
- HFT scalping strategy employs a very short holding period position based on certain alpha predicting small price movement and exit based on profit target and stop loss. It includes exploiting various price gaps caused by bid/ask spreads and order flows.
- Quote based strategies to exploit short lived inefficiency in market i.e. Box spread, Conversion-Reversal, Butterfly Spread, Volatility spread, Cash and Carry Arbitrage in Futures etc
- Implied Volatility (IV) based Bidding. This Algorithm allows bidding on Option Instrument based on user defined Implied Volatility (IV) and hedges it in Equity/Future/Options
- Arbitrage opportunities across related instrument in different exchanges.
Low Latency Statistical Arbitrage
Mean Reversal strategy that identifies medium and long term opportunities used to exploit financial markets that are out of equilibrium and assumes prices will eventually adjust to and reflect the fair value with certain predictability. It mostly uses pair trading and uses the concept of equilibrium of oscillation of long and short positions and applies a set of rules to spot inefficiencies and produce return.
Profit situation arising from pricing inefficiencies between securities that is identified through mathematical and statistical modelling techniques.
Index arbitrage: Trading Index against a basket of its component stocks.
Market Making
- Market making refers broadly to trading strategies that seek to profit by providing liquidity to other traders while avoiding accumulating a large net position in a stock. In the simplest terms, a market maker helps facilitate the execution of a trade by providing a continuous bid-and-ask market for a futures or options contract to any interested party, hoping to make a profit by exploiting the difference between the two prices, known as the spread. Intuitively, a market maker wishes to buy and sell equal volumes of the instrument (or commodity), and thus rarely or never accumulate a large net position, and profit from the difference between the selling and buying prices. Market making often requires placing and cancelling lot of orders and BlitzTrader SmartOrder command enables quant developer to effectively place new, modify and cancel orders at desired price level.
Quant Based Algorithm
- Mechanical Trading Strategies: A lot of best traders use some kind of mechanical rules based on technical analysis in their trading strategies. The trader should follow these rules exactly without hesitation or emotions and rules utilising multiple technical indicators to help them to identify price trends and future trading opportunities. Technical analysis is a form of trading strategy that looks purely at historical price action to determine current and future price trends. Examples: Fibonacci analysis, trend, momentum, volatility and volume based strategies using indicators like SMA, MACD, RSI stochastic, Bollinger Band, ATR, Standard Deviation etc
Market and Newsbased Event Strategy
Several investment management companies have specialized in exploiting news driven trading strategies that would affect the future sock price. Event driven hedge funds need to be on constant alert on news and company press releases as any potential profits could be “arbitraged” away after a short period after the event has taken place. Many news agency providers also provides low latency machine readable news feed that can be directly used in XTS Algo Trader trading strategy to exploit sudden price movement.
Such corporate news events are for example mergers, restructuring, litigation or bankruptcy, product announcements, examples for market news are announcements of economic indicators (unemployment rate, PMIs, etc.) or interest rate changes.
Benchmark-Driven Based Algorithms
Benchmark-Driven strategies seek to minimize slippage relative to client chosen benchmark to improve execution performance while minimizing market impact cost. Algorithms will attempt to find the best available price in the market, which often depends on minimising market impact by concealing a large order as far as possible. Techniques to achieve that often involve slicing an order into many smaller chunks. Examples: VWAP, TWAP, POV etc.
The execution can focus multi-venue in order to cope with the fragmentation of modern financial market and the system is designed to trade on any available source of liquidity.
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