Slow & Steady, Algo trading takes up decent share on Dalal Street

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Algorithmic trading, a gift of technological advancement to the stock market, is catching up fast with Indian traders and investors.

Markets regulator Sebi recently strengthened the framework for algorithmic trading, making its acceptance more widespread and inconspicuous.

To keep up with changing times, it has become essential for professional traders and arbitrageurs to ramp up speed of execution using contemporary technology tools. And algorithmic trading has come handy.

Algorithmic trading first entered stock markets in mid-1980s, and today it constitutes nearly 70 per cent of total trading volumes in developed markets.

Algorithms are a set of instructions that perform various operations in the market based on the inputs given. Market watchers say the use for algo trading is likely to grow rapidly, as people learn more about financial models, technical indicators and complex, multi-leg option strategies. In many US companies, programmed algos generate technical trades.

In Indian market, many traders use algo signals, which have a set of pre-defined rules, for trading along with their back-tested data base.

“Algorithmic trading can be used regardless of trading strategy. They are used for research and analysis as well as trade execution. One of the early usages of algorithms in stock trading was to help better and faster execution of large orders to reduce their adverse impact on prices, which was the case when such trades used to be executed manually,” says Nitesh Khandelwal, Co-Founder & CEO, QuantInsti.

“It has now become popular with professional traders to enhance profitability of various strategies regardless of market movement, a technique also called alpha of the strategy,” Khandelwal said.

Chandan Taparia, Technical & Derivatives analyst at Motialal Oswal Financial Services, said algo is a platform or a process of using program to follow a defined set of instructions for placing trades to generate profits at a frequency, as such trades are difficult to manage manually. A person can set defined rules based on price, quantity, timing, volumes and any other mathematical model.”

Taparia said the scope for algo trading is huge in India, because of its feasibility, speed and its ability to mitigate human error in execution.

Algorithmic trading can potentially help traders execute orders faster, expand strategy portfolios by using more advanced quantitative tools and remove human emotions that often affect the performance of trading strategies.

“Because of these reasons, algorithmic and quantitative trading strategies are getting more popular, as it can increase the likelihood of success with the backing of the statistical rigor,” Khandelwal said.

Sebi allowed algorithmic trading in India in April 2008 by opening up direct market access to the institutions. Since then, it has grown rapidly across the various asset classes.

“Today, close to 50 per cent of the overall exchange volumes in the F&O segment happen through algorithms. Even in the cash market, the share has grown to more than 30 per cent,” he said.

Algorithmic trading has much higher shares in developed markets, specifically in the US, where more than 70 per cent of overall exchange volumes comes through this route. A part of it can be attributed to the fact that algorithmic trading has existed in the US market for many decades now.

While many people often confuse algorithmic trading with HFT, which is only a specific case or subset of algo trading. One can use algo trading techniques even for fundamental investing with longer investment horizons.

Globally, algo trading is more popular among institutions and professional traders than the individual and retail traders for execution of trades.

The skill and technology needed for algo trading is complex and expensive. Hedge funds, option traders, strategists, pro traders, arbitragers, jobbers, scalper are major users of algo trading.

The key skill needed to succeed in this domain is an understanding of statistics and programming besides, of course, knowledge of the financial markets.

The success rate of algo trade depends on the logic or parameters set in the rule of algo. It’s not a default system, it’s only a platform where people can code their logics as per their understanding and according to a back-tested data base, said Taparia of MOFSL.

In terms of adoption, the Indian market has already crossed the halfway mark of the US and European market levels in last decade. Lower cost of technology, cheaper access to computing power and availability of skilled resources are likely to help fast-track this transition, Khandelwal said.

The future of algo trading adoption will also depend on how the regulations and government policies shape up.

Sebi has been quite prudent with the regulations in this domain. Sebi guidelines on algo trading have also played a positive role in helping its adoption.

From the regulation point of view, the first experiences with the technology have been encouraging. The Indian market has not seen many flash crashes compared with what similar instances in the developed markets.

There are also reports that Sebi might come up with guidelines for use of algo trading by retail traders, which shall help further understanding and acceptance of the domain at a larger scale.

“Algo trading can be beneficial for small-time investors, as it increases liquidity in the market and thereby simplifies the entry and exit process. Increasing depth of algo trading would be good for capital markets as it will remove price inefficiencies in traded securities,” says Ajay Kejriwal, President, Choice Broking.

Source – Economic Times.

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EMA with Supertrend As Source

Supertrend is a trend following indicator which can be used to identify upward or downward
trends.

BUY{
SET ST = SUPERTREND(7,3,SIMPLE);
SET MA = EMA(ST,9);
MA > ST AND MA <= (ST * 1.005) AND CLOSE > MA;}

SELL{
SET ST = SUPERTREND(7,3,SIMPLE);
SET MA = EMA(ST,9);
MA < ST AND ST <= (MA * 1.005) AND CLOSE < MA;}

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Relative Momentum Index (RMI) With WMA.

The Relative Momentum Index (RMI) is a variation of the Relative Strength Index (RSI). While the RMI counts up and down days from today’s close relative to the close n-days ago while the RSI counts days up and down from close to previous close.

BUY{
SET RM = RMI(CLOSE,50,9);
SET MA = WMA(RM,50);
CROSSOVER(RM,MA) AND RM < 20;}

LONGEXIT{
SET RM = RMI(CLOSE,50,9);
SET MA = WMA(RM,50);
CROSSOVER(MA,RM) AND RM > 60;}

SELL{
SET RM = RMI(CLOSE,50,9);
SET MA = WMA(RM,50);
CROSSOVER(MA,RM) AND RM > 60;}

SHORTEXIT{
SET RM = RMI(CLOSE,50,9);
SET MA = WMA(RM,50);
CROSSOVER(RM,MA) AND RM < 20;}

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Swing Index (SI)

The Swing Index (Wilder) is a popular indicator that shows comparative price strength within a single security by comparing the current open, high, low, and close prices with previous prices.

BUY{
SET TP1 = TP();
SET MA = WMA(TP1,50);
SET SI1 = SI(2);
SET MA1 = EMA(SI1,21);
CROSSOVER(TP1,MA) AND REF(MA1,1) < 0.01 AND REF(CLOSE,1) > REF(OPEN,1);}

LONGEXIT{
SET TP1 = TP();
SET MA = WMA(TP1,50);
SET SI1 = SI(2);
SET MA1 = EMA(SI1,21);
CROSSOVER(MA,TP1) AND REF(MA1,1) > 0.01 AND REF(CLOSE,1) > REF(OPEN,1);}

SELL{
SET TP1 = TP();
SET MA = WMA(TP1,50);
SET SI1 = SI(2);
SET MA1 = EMA(SI1,21);
CROSSOVER(MA,TP1) AND REF(MA1,1) > 0.01 AND REF(CLOSE,1) > REF(OPEN,1);}

SHORTEXIT{
SET TP1 = TP();
SET MA = WMA(TP1,50);
SET SI1 = SI(2);
SET MA1 = EMA(SI1,21);
CROSSOVER(TP1,MA) AND REF(MA1,1) < 0.01 AND REF(CLOSE,1) > REF(OPEN,1);}

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MACD WITH WMA

This trading system is based on MACD,WMA and CCI indicators.

BUY{
SET MCD = MACD(8,12,9,SIMPLE);
SET W13 = WMA(CLOSE,13);
SET W27 = WMA(CLOSE,27);
SET C1 = CCI(14,SIMPLE);
CROSSOVER(W13,W27) AND MCD > 0.01 AND C1 > 0.01;}

SELL{
SET MCD = MACD(8,12,9,SIMPLE);
SET W13 = WMA(CLOSE,13);
SET W27 = WMA(CLOSE,27);
SET C1 = CCI(14,SIMPLE);
CROSSOVER(W27,W13) AND MCD < 0.01 AND C1 < 0.01;}

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Bollinger Bands Breakout and RSI Trading System

When the RSI is above 70, and when the Price drops above the Higher Bollinger Band.When the RSI is below 30, and when the Price drops below the Lower Bollinger Band.

BUY{
SET BT = BBT(CLOSE,20,2,SIMPLE);
SET RS = RSI(CLOSE,11);
RS > 70 AND CROSSOVER(CLOSE,BT);}

SELL{
SET BB = BBB(CLOSE,20,2,SIMPLE);
SET RS = RSI(CLOSE,11);
RS < 30 AND CROSSOVER(BB,CLOSE);} 

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Trade Volume Index (TVI)

The Trade Volume index shows whether a security is being accumulated or distributed.

BUY{
SET TV = TVI(CLOSE,0.25);
SET MA = SMA(TV,21);
CROSSOVER(TV,MA);}

SELL{
SET TV = TVI(CLOSE,0.25);
SET MA = SMA(TV,21);
CROSSOVER(MA,TV);}

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CANDLESTICK PATTERN CNTD.

BUY{
SET C1 = REF(CLOSE,1);
SET C2 = REF(CLOSE,2);
SET C3 = REF(CLOSE,3);
SET O1 = REF(OPEN,1);
SET O2 = REF(OPEN,2);
SET O3 = REF(OPEN,3);
O3 > C3 AND O2 > C2 AND O1 > C1 AND CLOSE > OPEN AND CLOSE > MAX(HIGH,4);}

LONGEXIT{
CLOSE > REF(CLOSE,1) * 1.022;}

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CANDLESTICK PATTERN CNTD.

BUY{
SET PC3 = REF(CLOSE,3);
SET PC2 = REF(CLOSE,2);
SET PC1 = REF(CLOSE,1);
SET PO3 = REF(OPEN,3);
SET PO2 = REF(OPEN,2);
SET PO1 = REF(OPEN,1);
PC3 < PO3 AND PC2 > PO2 AND PC1 > PO1 AND PC1 > PO3;}

SELL{
SET PC3 = REF(CLOSE,3);
SET PC2 = REF(CLOSE,2);
SET PC1 = REF(CLOSE,1);
SET PO3 = REF(OPEN,3);
SET PO2 = REF(OPEN,2);
SET PO1 = REF(OPEN,1);
PC3 > PO3 AND PC2 < PO2 AND PC1 < PO1 AND PC1 < PO3;}

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Parabolic Stop and Reversal (Parabolic SAR)

Author Welles Wilder developed the Parabolic SAR. This indicator is always in the market (whenever a position is closed, an opposing position is taken). The Parabolic SAR indicator is most often used to set trailing price stops.

BUY{
SET PS = PSAR(0.2,0.02);
SET MA = EMA(PS,21);
SET MA2 = SMA(CLOSE,50);
CROSSOVER(MA,PS) AND CLOSE < MA2;}

LONGEXIT{
SET PS = PSAR(0.2,0.02);
SET MA = EMA(PS,21);
SET MA2 = SMA(CLOSE,50);
CROSSOVER(PS,MA) AND CLOSE > MA2;} 

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