![Automated trading Strategies
As per the new architecture is capable of scaling too many
strategies out of which we apply 2 of them .
• Simple Moving Average (SMA)
• The simple moving average is the simplest type of moving
average.
• It is arguably the most popular technical analysis tool used
by traders.
• A simple (or arithmetic) moving average is an arithmetic
moving average calculated by adding the elements in a time
series and dividing this total by the number of time periods.
• [SMA = (Sum of data points in the moving average
period)/(Total number of periods)]
Algo Trading Short Title 13/23](https://image.slidesharecdn.com/beamerkeynotelookingstyle1-171127070600/85/Algo-trading-Minor-Project-strategy-EMA-with-Ipython-13-320.jpg)
![Algorithm
• Step 7:- Slicing dataframe.
• Step 8:- converting dataframe to csv file.
• Step 9:- calculation SMA[ n/n].
• Step 10:- calculation
EMA[(alpha*prev.close)+(1-alpha*prev.ema)
where alpha=( 2/1-n).
• Step 11:- Cal. EMA for 5,8 and 13 days.
• Step 12:- Convert all csv data to dataframe.
Algo Trading Short Title 16/23](https://image.slidesharecdn.com/beamerkeynotelookingstyle1-171127070600/85/Algo-trading-Minor-Project-strategy-EMA-with-Ipython-16-320.jpg)
![Algorithm
• Step 13:- Plotting graph through dataframe.
• Step 14:- By using euclidean formula, distance between
two lines[dist((x, y), (a, b)) = (x − a)2 + (y − b)2]
• Step 15:- Cal.risk line= [dist((x, y), (a, b)) - [dist((x1, y1),
(a1, b1))
• Step 16:- If risk line == 0, check if (x,y) >(x1,y1) generate
’BUY’ signal else ’SELL’.
Algo Trading Short Title 17/23](https://image.slidesharecdn.com/beamerkeynotelookingstyle1-171127070600/85/Algo-trading-Minor-Project-strategy-EMA-with-Ipython-17-320.jpg)
Algo trading(Minor Project) strategy EMA with Ipython
- 1. ALGORITHMIC TRADING Minor Project Deb Prakash Ganguly 1401227154 Guided by (ASST PROF.NAMITA BAJPAI) 27,NOVEMBER,2017 C.V RAMAN COLLEGE OF ENGINEERING . Algo Trading Short Title 1/23
- 2. CONTENTS • INTRODUCTION • OBJECTIVE • SOFTWARE REQUIRED • ARCHITECTURE • STRATEGIES • ALGORITHIM • OUTPUT GRAPH • LIMITATIONS • CONCLUSION • FUTURE ENHANCEMENT • REFERENCES Algo Trading Short Title 2/23
- 3. INTRODUCTION • It is the process of using set of rules or any mathematical model to generate profits at a high speed frequency that is impossible for a human trader • It is simply a way to minimize the cost, market impact and risk in execution of an order.It is widely used by investment banks and hedge funds. Algo Trading Short Title 3/23
- 4. OBJECTIVE • To predict stock prices through lagger indicator. • Investor will evaluate strategies from a rigorous scientific perspective to prevent financial crises . • It will help in portfolio management to make a prediction individual stocks. • Trades will be instantly, to avoid significant price changes Reduced transaction costs or brokerage charge. • Reduced possibility of mistakes by human traders based on psychological factors. Algo Trading Short Title 4/23
- 5. SOFTWARE REQUIRED • Automated trading can be done by c, c++, java script, ipython, etc.out of which we are using interactive python(Ipython) • Most of the quant traders prefer Python algorithmic trading as it helps them build their own execution mechanisms . • Python can be used to develop some great treading platform where using c or c++ is a time consuming job . • It has packages like Pandas, NumPy, PyAlgoTrade, MatPlotLib which support google finance, csv files.Are free of cost. Algo Trading Short Title 5/23
- 6. Interactive python IPython provides a rich architecture for interactive computing with: • A powerful interactive shell. • A kernel for Jupyter. • Flexible, amendable interpreters to load into your own projects. Algo Trading Short Title 6/23
- 7. ARCHITECTURE • The entire automated trading system can now be broken down into 3 parts : • The exchange(s) the external world • The server • Market Data receiver • Store market data • Store orders generated by the user • Application • Take inputs from the user including the trading decisions • Interface for viewing the information including the data and orders • An order manager sending orders to the exchange Algo Trading Short Title 7/23
- 8. Traditional Architecture Algo Trading Short Title 8/23
- 9. NEW ARCHITECTURE • The traditional architecture could not scale up to the needs and demands of Automated trading with Direct market access (DMA). • The latency between origin of the event to the order generation went beyond the dimension of human control . • Order management also needs to be more robust and capable of handling many more orders per second. Algo Trading Short Title 9/23
- 10. • The infrastructure level of this module is superior compared to traditional system . Hence the engine which runs the logic of decision making,is known as the Complex Event Processing engine, or CEP . • The risk checks are performed now by a separate Risk Management System (RMS) within the Order Manager (OM), just before releasing an order. Algo Trading Short Title 10/23
- 11. Algo Trading Short Title 11/23
- 12. • The new architecture was capable of scaling to many strategies per server, the need to connect to multiple destinations from a single server emerged. • The order manager hosted several adapters to send orders to multiple destinations and receive data from multiple exchanges. • To avoid this hassle of adapter addition, standard protocols have been designed. The most prominent among them is the FIX (Financial Information Exchange) . Algo Trading Short Title 12/23
- 13. Automated trading Strategies As per the new architecture is capable of scaling too many strategies out of which we apply 2 of them . • Simple Moving Average (SMA) • The simple moving average is the simplest type of moving average. • It is arguably the most popular technical analysis tool used by traders. • A simple (or arithmetic) moving average is an arithmetic moving average calculated by adding the elements in a time series and dividing this total by the number of time periods. • [SMA = (Sum of data points in the moving average period)/(Total number of periods)] Algo Trading Short Title 13/23
- 14. • Exponential Moving Average (EMA or EWMA) • The simple moving averages are sometimes too simple and do not work well when there are spikes in the price of the security. Exponential moving averages give more weight to the most recent periods. This makes them more reliable than the SMA and a better representation of the recent performance of the security. • alpha = 0.1 to 0.3 [ EMA = (Closing price minus EMA of previous day/bar) x alpha) + EMA of previous day/bar Rewritten as: EMA = (Closing price) x alpha + (EMA of previous day/bar) x (1 minus multiplier) Algo Trading Short Title 14/23
- 15. Algorithm • Step 1:- Start • Step 2:- Import packages • Step 3:-Request for API • Step 4:-Retrive access token • Step 5:-Request trade segment in NSE or BSE • Step 6:-Request for history data for a particular script from NSE Algo Trading Short Title 15/23
- 16. Algorithm • Step 7:- Slicing dataframe. • Step 8:- converting dataframe to csv file. • Step 9:- calculation SMA[ n/n]. • Step 10:- calculation EMA[(alpha*prev.close)+(1-alpha*prev.ema) where alpha=( 2/1-n). • Step 11:- Cal. EMA for 5,8 and 13 days. • Step 12:- Convert all csv data to dataframe. Algo Trading Short Title 16/23
- 17. Algorithm • Step 13:- Plotting graph through dataframe. • Step 14:- By using euclidean formula, distance between two lines[dist((x, y), (a, b)) = (x − a)2 + (y − b)2] • Step 15:- Cal.risk line= [dist((x, y), (a, b)) - [dist((x1, y1), (a1, b1)) • Step 16:- If risk line == 0, check if (x,y) >(x1,y1) generate ’BUY’ signal else ’SELL’. Algo Trading Short Title 17/23
- 18. Output Graph Algo Trading Short Title 18/23
- 19. Analysis Algo Trading Short Title 19/23
- 20. Limitations • Algorithmic trading is not 100 percent accurate.We just predict future stock price basis upon past stock behaviour. • Algorithmic trading is not universal. one algorithm cannot be applied to every situation. • Investor has to check daily news or updates of individual script. • Due to this market goes to more volatility. Algo Trading Short Title 20/23
- 21. Conclusion Trading is extremely difficult for both full time and especially part time traders.The best road to gain profit is finding your own trading strategies.Once you got it, is your goals and objectives.No,trading strategies lasts forever and i find myself constantly reinventing my strategy.I learned all of these lessons,and many more from trade academy during my internship. Algo Trading Short Title 21/23
- 22. Future Enhancement In year of 2008 SEBI started allowing DMA.In the US and other developed markets HFT estimated 70 percentage of equity market share.In India is around 12 percentage. As technology is growing,financial technology is growing up same space. In recent years,the number of machine learning packages has increased in finance trading. some established funds like Medallion,Citadel,JPmorgan using artificial intelligence, and there performance is in peak level. Upcoming years algo trading with AI power will have a huge impact in Indian market. Algo Trading Short Title 22/23
- 23. References • Fundamental of dataframe by Yves Hilpisch,2016, p.137 • API connection website:https://github.com/upstox/upstox-python • Algo Trading architecture https://www.quantinsti.com/blog/trading-systems- architecture Algo Trading Short Title 23/23