Investopedia defines Algorithmic trading (also called automated trading, black-box trading, or algo trading) as a computer program that follows a defined set of instructions (an algorithm) to place a trade.
Algo trading, a domain previously exclusive to savvy proprietary and institutional traders, is now growing rapidly among retail traders in India. This rapid growth has been enabled by brokers providing API services to their customers who can then trade automatically without manual intervention. Further, free backtesting and code-free execution services provided by AlgoTest, have immensely helped retail traders and put them on an equal footing with these institutions. Traders can backtest their strategies for free on this platform, and deploy them LIVE in the market without any knowledge of coding.
The COVID pandemic too completely changed the market with greater participation of retailer traders. The number of Demat accounts rose from 40 Crores in March 2020 to 90 Crores by March 2022 representing a 125% growth in 2 years! This entry of new traders and influencers led to the popularizing of many positional and intraday options strategies like the now famous and fairly simple 920 Straddle, Weekly Iron Condor, and monthly calendar spreads, among others.
The development cycle of a Strategy in AlgoTest
How is any strategy developed? Algo trading strategies follow a cycle from hypothesis, to backtesting, to paper trade, and finally to live execution. Once a strategy is deployed live, a trader must keep track of live results vs backtest results, and course correct whenever necessary. Let us take a close look at all these steps:
- Hypothesis: In this step, traders come up with an idea they believe would yield a suitable ROI and also meet their risk appetite. This can be as simple as selling an ATM Bank Nifty CE and PE (Straddle) at 9:20 am every morning with a leg-wise Stop Loss at 30% of the premium sold (The famous #920straddle strategy).
- Backtest: Traders must Backtest this hypothesis with the available historical data to see how well has this strategy done in the past. This is an iterative process wherein many changes are made to the original strategy before arriving at one that matches their profit expectation and risk appetite.
- Paper Trading: Once a strategy has been selected, traders would like to paper trade the strategy for a few days/instances to see that the strategy is working as per expectations.
- Live Trading: Now we are ready to deploy and go live with the strategy in the market.
- Analysis: This step is very important for traders to see if the strategy is working as per the backtest results.
The 60% ROI Strategy
Now let us build out a simple strategy that we can deploy on Zerodha. The following are the parameters of the strategy:
- Instrument: BANKNIFTY
- Entry: 9:30 AM
- Strike: ATM
- Order: Sell CE and PE
- Trail SL to Breakeven – All Legs: If any leg’s SL is hit, trail the SL of all other legs to their respective entry prices.
- CE Stop Loss: 15%
- PE Stop Loss: 15%
- Overall MTM Stop Loss: Rs 2000
Here are the backtest results:
Analysis of this Strategy
This strategy is ideal for a trending day; hence it has a low individual leg SL of 15%. It will give a very good profit on days when the market is in a trend.
Deployed Capital: Rs 1.8 L
Overall Profit: Rs 6 L
Yearly Profit (Data for 5.5 years): Rs 1.09 L
ROI: 60% Per Annum
The win% of this strategy is 40% which is low since the market is not trending on most days.
Max Drawdown: According to Investopedia, the definition of Max Drawdown is, “A maximum drawdown (MDD) is the maximum observed loss from a peak to a trough of a portfolio before a new peak is attained. Maximum drawdown is an indicator of downside risk over a specified period.”
The Max drawdown for this strategy is Rs 12,830 over the last 5 and half years. This is barely 7% (approx) of the deployed capital of Rs 1.80 L. Most portfolios of long-term investors suffered a drawdown of 40-50% during the Covid fall. Hence, with respect to the downside risk, this strategy has done better than many long-term portfolios!
Return/MaxDD: This ratio gives the number of times the Max Drawdown is covered by the yearly return/profit. This strategy has a Return/MaxDD of 8.47 which means that the yearly profit generated from this strategy covers the Max Drawdown by more than 8 times! Use this as a risk-adjusted heuristic. Usually, the higher this number, the more attractive the strategy.
Observing the monthly Pnl table shows that the strategy has not had a single loss making month in more than 3 years including the March 2020 Covid Crash.
How to Deploy?
Shared below is a YouTube link on how a trader can use AlgoTest to create and backtest this particular strategy and easily deploy it to paper. Another link is shared that helps in setting up the broker (Zerodha) and deploying the algo to live. No Coding Experience is required by someone to build, test and deploy an algo. Also shared is a playlist of YouTube videos helping new traders develop new strategies and backtest them on AlgoTest.
Link 1: https://bit.ly/3OQ4YvN
Link 2: https://bit.ly/3vwVmz7
Link 3: https://bit.ly/3vuz01f
Link 4: https://bit.ly/3oyEwMk
Who can Benefit from AlgoTest?
All traders have benefitted from this free backtest service and code-free deployment. But for part-time traders with jobs, algo trading has been a boon. The system takes the trades without them having to manually input the trades and constantly monitor the markets. Full-time traders now have enough time to work and develop new strategies while the system trades for them.
In conclusion, AlgoTest is trying to give retailers the tools to compete with big institutional traders with huge resources. Their offered tools, be it the free backtester or the code-free algo trading system have helped traders develop and deploy new strategies in the market with little effort.