Cash to Future Arbitrage

5 min read

Arbitrage between cash and derivatives (futures) is more prevalent now. This EPAT project will help you understand and learn how you can build-up a module on Cash future Arbitrage. This, in turn, would help you bet on cash future spread to maximize intraday profits.

This article is the final project submitted by the authors as a part of their coursework in the Executive Programme in Algorithmic Trading (EPAT®) at QuantInsti®. Do check our Projects page and have a look at what our students are building.

About the Author

Chandrashekhar Satoskar is an arbitrage trader at Religare Securities Ltd. He holds bachelors in Commerce from Mumbai University and has completed his Master’s in Business Administration (M.B.A.) from Vinayaka Mission's Research Foundation. He is currently working as a Bullion, Equity & Derivative Trader in Westbury Tradecom Limited.

Project Motivation

As an EPAT alumni, I am very much interested in building-up a module on Cash future Arbitrage which will help the traders or jobbers to bet on cash future spread just like intraday spread betting to maximize intraday profits. For backtesting the above strategy, I am taking the help of Excel for the same.


There are two types of arbitrage:

  • Whenever Futures price is greater than the Spot price, it is known as "Contango" or called as futures trading @ Premium
  • Whenever Futures price is less than (discount) Spot price it is known as “Backwardation” or called as futures trading @ Discount.

There are also two types of arbitrageurs:

  • One set is more like day traders or jobbers, playing on spreads between cash and futures and capturing jobbing differences wherever possible.
  • The other set is more like medium-term investors, who are interested in a fixed income stream for a medium-term without taking any credit risk or underlying view.

Data Mining

We can get data from many API or interactive brokers. For data mining, I am using ZERODHA PI software which gives per minute data which helps to collect data for backtesting the module.

Data Analysis

Following are the steps for data analysis:

1. First, get rates of SPOT and FUTURE as per time frame -Here I am using 1 min. time frame

2. Calculate the difference between future and spot known as SPREAD.

3. Calculate the Bollinger band of the spread which we get to identify upper and lower limits of spread and also will get mean for the same.

4. Calculate CCI (Commodity Channel Index) of spread to identify trends of spread

5. Calculate MACD (Moving Average Conversion Diversion) of CCI which will help to identify spread conversion diversion signal from MACD

6. After the above calculation time to generate a signal for the strategy,

  • Whenever Spread is greater than or equal to Upper Bollinger band and the value of MACD is less than MACD signal value then will Buy Spot and Sell Future i.e. Fresh Up.
  • Whenever Spread is less than or equal to Lower Bollinger band and the value of MACD is greater than MACD signal value then will Buy Future and Sell Spot i.e. Unwind.
  • If the above conditions do not match, then we will keep the cell blank.

7. Calculate BPS (basis Points): BPS = Spread / Price*100

8. Now we will define the status column to identify what is the current status of the trade i.e. Fresh UP or Unwind:

  • We will take one trade at a time - this means if one trade going on ignores all trading signals till FA END (Take P&L from Fresh UP) or UN END (Take P&L from Unwind) come.
  • We will not take a new unwind signal after 3.15 pm because in the Indian market carrying short selling is not allowed
  • If the previous status is BLANK (NO Trade) then keep cell as blank
  • If the previous status is FRESH UP and Spread is Less than or equal to Lower Bollinger band and the value of MACD is greater than MACD signal value then FA END (will take P&L from Fresh UP).
  • If the previous status is Unwind and Spread is greater than or equal to Upper Bollinger band and the value of MACD is less than MACD signal value then UN END (will take P&L from Unwind).

9. After we know the status of trade time to execute the trade quantities as per given fund size, I took 1 cr of fund for backtesting the above strategy.

So we use this formula:

If the current status is FRESH UP or UNWIND then ROUNDDOWN (TotalFund/Price)/Lot Size of Particular stock * Lot Size

10. Now we define the buy price or sell price so we take from Spot price or future price

  • If the current status is Fresh up then will take spot price as a buy price and sell price as a future price
  • If the current status is Unwind then will take future price as a buy price and sell price as a spot price)

11. Now define Buy value and Sell value so the formula is,

  • Buy Value = Price * Lot Size
  • Sell Value = Price * Lot Size

12. Calculate Gross profit: It is the difference between Fresh UP Spread and FA END Spread or Unwind Spread and Un END spread

13. Calculate Net Profit: Net Profit = Gross profit – Trading Expenses

14. Calculate return NP in BPs: Return NP = Net Profit / Total fund*100

15. Calculate Strategy results such as:

  • Positive results,
  • Negative results,
  • Positive trades,
  • Negative trades,
  • Average returns.


  • Forecast Fresh UP or Unwind Signal on an intraday basis
  • Drawback: Short selling is not allowed
  • Buyer and Seller must have a Unique ID to enter a trade in any particular stock if the same trade will square off automatically and will be released into Trading Expenses.

Key Findings

  • To develop intraday trading for jobbers and traders and generate returns with using of big funds
  • Trade whenever Spread touches upper or lower Bollinger band with MACD or crossed over MACD signal line
  • Don’t initiate the trade after 3.15 pm because there are low chances to earn good returns
  • If you properly follow the above steps there are chances to earn a good amount of money in intraday
  • Whenever taking the new trade look into Nifty/Banknifty SPOT and Future premium/discount which would be your additional tool to trade.
  • Try to search the stocks with upcoming results, Corporate actions, Budget’s month, RBI policy etc. which will create more trading opportunity with a chance to earn an additional alpha.


The above trading strategy is a low-risk strategy that seeks to generate additional alpha in intraday trading using the

  • Bollinger band,
  • Commodity Channel Index, and
  • MACD.

Different time frame applies for different stocks so select the right time frame to right stocks while backtesting and trading.

Above strategy, overall performance ratio will be around 70% but do backtest as per your end. Trading is tough, I hope this strategy helps all traders to trade from my experience no trading strategy lasts forever, I find myself reinventing my trading styles and try to develop new strategies.

Good Luck and Happy Trading!

If you want to learn various aspects of Algorithmic trading then check out the Executive Programme in Algorithmic Trading (EPAT). The course covers training modules like Statistics & Econometrics, Financial Computing & Technology, and Algorithmic & Quantitative Trading. EPAT equips you with the required skill sets to build a promising career in algorithmic trading.

Disclaimer: The information in this project is true and complete to the best of our Student’s knowledge. All recommendations are made without guarantee on the part of the student or QuantInsti®. The student and QuantInsti® disclaim any liability in connection with the use of this information. All content provided in this project is for informational purposes only and we do not guarantee that by using the guidance you will derive a certain profit.