Algo Trading Strategies

Trend Following

This trading strategy captures trends across multiple markets using various risk management methods. Trend followers trade in a variety of instruments like bond, indices, currencies, energy, agriculture etc in multiple markets. This helps in capturing the trends in an efficient way. These strategies use technical analysis, chart patterns and indicators to make investment decisions. Longer the time duration of trend, larger is the profit-making potential. Key components of trend following strategies are:

  • Identify a way when a trend has started
  • Decide your trading window time frame
  • Choose the markets to trade
  • Choose the risk that you can take per each trade
  • Decide the condition of your trading strategy
  • Decide a low risk entry point
  • Decide an initial stop loss to exit if you are wrong
  • Decide an exit rule if you are right or when trend changes.

Market Sentiment

Market Sentiments be it greed or fear are captured from various comments and posts in twitter and other social media platforms by extracting relevant information of the burning issues of that time with the help of natural language processing (NLP), computational linguistics etc. Market sentiments goes bullish in nature when there is an expectation that prices will move in upward direction. It becomes bearish when there is an expectation and fear that prices will move in the downward direction. Sentiment indicators such as US Prez election, Natural calamities, start of War between the countries, Rate cuts of Central Banks of US/India etc gives idea about future upward or downward direction of price movement of a security before it moves. There are also number of mathematical ways of categorizing sentiment indicators. Some of them are as follows:

  • Odd-lot shot sell ratio:
  • Put/call volume ratio:
  • Market Volatility Index: NASDAQ Composite Index(VXN), S&P 100 Index (VXO), CBOE Volatility Index(VIX)
  • Daily Sentiment Index US (DSI) & Daily Sentiment Index Europe (DSIE):
  • Arms Index(TRIN):
  • Speculative Sentiment Index(SSI):
News Based
 

News based Algo trading systems are designed in a way to connect to news wires such as Thomson Reuters and Dow Jones News wires and generate charts and reports to help traders in better investment decisions. These news wire analyse the news like trading in securities of the companies in the day when their quarterly financial results are declared, pending compliance and regulatory cases resolution expectation date trading etc.

Arbitrage
 

This is a way of making profit by taking advantages of price difference between 2 markets or price difference between different segments (Cash, Futures etc) of the same exchange. Also, due to misquote of prices, there is an opportunity for arbitrage get created and Algo Trading Strategies identifies such opportunities and make profits out of it before market price gets adjusted. To reduce risk of such price adjustments in both markets or to reduce the exposure to market risk, the buying in one market and selling in another must be done simultaneously.

Mean Reversion
 
 
Mean Reversion Trading is the concept which believe the high movement of prices on either side of the average mean will always come down to the mean over a time and traders tries to make profit from it by both selling and buying. Selling needs to be done when implied volatility is high and buying needs to be done when implied volatility is low using strategies. Selection of correct moving average price can get tricky. The most popular units of moving average used in trading is called Simple Moving Average. Simple Moving Average (SMA) is the average closing price of a stock over the last “n” period. Different SMA used are 5 SMA or a 5 day SMA, 10 SMA, 20 SMA, 50 SMA, 100 SMA, 200 SMA. Faster moving SMAs (10 SMA) will have more trading opportunities and less reward to risk ratio than slower moving SMAs (100 SMA). Various other types of moving averages are as below:
  • Triangular Moving Average (TMA)
  • Exponential Moving Average (EMA)
  • Weighted Moving Average (WMA)
  • Adaptive Moving Average(AMA)
  • Typical Price Moving Average (TPMA)
Trade Execution
 
 
These types of strategies are focused on large quantity of order executions. These orders when executed at one go without considering the liquidity in market runs the risk of negative payoff. To avoid this situation, large quantity of orders is split into sets of smaller ones based on available liquidity. Some of the popular Execution Algos are TWAP and VWAP, POV
 
Time Weighted Average Price (TWAP): – It is defined as the average price of a security over a specific period. TWAP Algos split large quantity of orders and send them in smaller quantity at a specific interval of time to market. TWAP is first calculated by the Open, High, Low and Closing Prices and calculating averages of those averages as time progresses. TWAP does not consider the fact that the trading volume is high at the beginning and at the end of the day. To tap profit from such intraday market behaviour VWAP is used
 
Volume Weighted Average Price (VWAP):VWAP algorithm places the orders in the market in line with the intraday volume trend. This algorithm is designed on the historical data and orders are split on the average weighted volume. Executions can be impacted whenever there is deviation from historical data on any given day. For such deviation, to minimize the impact POV is used.
 
Percentage of Volume (POV): – It is designed to minimize the market impact by placing orders in a constant predefined % of trading volume over a period. It dynamically adjusts to % market participation rate as a function of real time market conditions such as continuously updated volume forecast received in market data feed unlike VWAP which was dependent on historical data. Setting higher POV will produce greater market impact and less price fluctuation risk and smaller POV will delay the execution and increase the price risk