Greek Trend Trader

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There are four cardinal rules which should be part of every traders strategy – Trade with the trend, Cut losses short, Let profits run, and Managing risk.

With GTT now create your own strategies using simple and easy to use strategy/logic designing language, Define your entry and exit parameters using technical as well as quantitative parameters. Backtest your strategy’s financial & statistical result aided by superlative charting tool with latest technical indicators and studies. Test strategies on intraday as well as historical data starting from 2006 till date.

  • Auto execution based on built strategies
  • Multiple strategy execution.
  • Customizable strategies.
  • Backtest strategy results.
  • Strategy Trade pointers on Chart for easy analysis
  • Charting tool with 100’s of technical indicators and studies
  • Multiple Charts windows
  • Live Strategy Scanner
  • Co-location option

Brokers urge traders to adopt Algo Trading

Objective of the move is to use automation to maximise trading profits.

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‘Completely automate your strategy with only a few clicks’; ‘Maximise trading profits by using approved execution strategy’, ‘Customise your strategy with custom target and stop-loss, bullish or bearish signals without any programming knowledge’.

These are some of the benefits of algo (algorithm-based) trading highlighted by Ludhiana-based broker MasterTrust on its website. MasterTrust is not the only one goading retail traders to adopt algo-based strategies to trade. A slew of other top domestic brokers such as Edelweiss Financial Services, Sharekhan, IIFL, Prabhudas Lilladher and Reliance Securities have started selling the concept to traders.

The objective remains the same: use automation to maximise trading profits. The broker too benefits by getting an additional fee from the traders — as high as Rs 15,000 to Rs 30,000 per month per strategy — to use the facility. “These strategies help traders tap opportunities in a milli-second, which is practically impossible through human intervention. Besides, algos can provide an additional source of revenue to brokers since customers are willing to pay a fee for using the facility,” said B Gopkumar, chief executive of Reliance Securities. He said Reliance Securities currently have three or four standard algo strategies in place and might do a mass rollout to its clients in the next month or so.

The simplest algo strategies could involve buying a stock when it rises above the 200-day moving average, or selling a particular stock when it moves into overbought territory. There are many other sophisticated strategies such as pair trading and scalping. Scalping, for instance, involves making profits on small price changes. Traders who implement this strategy will place anywhere from 10 to a couple of hundred trades in a single day to capture small price moves.

“At Edelweiss, we are addressing the needs of professional traders and high net worth individuals who have large trading teams,” said Harish Sharma, business head — brokerage and wealth management, Edelweiss Broking, adding they were looking to expand the suite of algo products in the coming months.

Algo trades use advanced mathematical models for effecting transactions and can pump thousands of orders in a second. There are multi-client and single-client algos. The former are automated strategies targeted at multiple clients and based on a preset system of rules developed by brokers or algo vendors. Single-client algos are customised according to the needs of a particular client. Popular algo vendors in the market include Omnesys, Symphony Fintech, and Greeksoft Technologies.

Brokers cite several benefits of employing algo-based strategies. It takes away the emotions from decision making, enabling traders to honour stop-losses and other targets. It also helps clients size their trades more effectively and ensure they don’t become over-leveraged in the market.  Some experts, however, believe algo-based strategies are not suited to individuals because of the complexity and the risks involved.

“Retail traders may not be in a position to understand some of these strategies and burn their fingers,” said a broker, on condition of anonymity.

While algo trades provide liquidity as more orders are placed, they can distort prices if wrong programmes are allowed to run unchecked. However, this is mostly a problem only in cases of large orders executed by institutional clients.

As a precautionary step, stock exchanges currently audit all algos to back test them and assess their risk parameters, and might take 25-40 days to before greenlighting a particular strategy.

Interestingly, in September last year, the Association of National Exchanges Members of India (Anmi), a body of stockbrokers, had written to the regulator, suggesting ways to minimise risks arising out of algo trades. At present, about 20 per cent of the turnover on the exchanges comes through the algo route.

Source – Business Standard (May 30, 2016)

Rising interest of online trading amongst the young investors

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With easy availability of gadgets, use of superior technology, rising internet speed and access to analyst information, there is steep rise of over 76% of online trading among the young investors in the last couple of years as a primary source of additional income.

According to the survey, more and more youngsters are adapting this quick, efficient and hassle free option of stock trading. Around 60 to 75% rise in trading since the inception of online trading account India, especially amongst the youth investors. Be it a mom to the business professional anyone can be a part of this multi-billion stock market of India and trade anytime, anywhere and anyhow through Online Trading.

In its countrywide survey conducted by the Associated Chambers of Commerce and Industry of India (ASSOCHAM) under the aegis of its Social Development Foundation, reveals that the online share trade industry is growing by 160% year-on-year, the value of all trades executed through the internet has grown more than ten times in two years.

Major metropolitan cities in which respondents were interviewed include Delhi-NCR, Mumbai, Ahmadabad, Cochin, Bangalore, Hyderabad, Kolkata, Indore, Patna, Pune, Chandigarh and Dehradun and it was observed that there has been a steep rise in the use of online share trading with the upcoming technology platform for continuous trading. ASSOCHAM used random data to choose investors representing various age groups, occupation, gender, marital status and annual income range.

According to the findings of the survey, online share trading has become a major fascination by large number of young energetic and intelligent population mostly professionals or unprofessional and employed or unemployed.

Stock trading is the new age thrive, every youngsters are looking toward to improve the income levels. Online trading is the most profitable business, which just requires knowledge of the trading concept, said majority of the respondents.

The survey further reveals that young generation is very analytical, quick and responsive to the every changing market scenario, adds the survey.

With an online trading account India, you can access your mutual funds, stocks, IPOs, equities and much more avoiding the need for multiple brokers, multiple bank accounts and multiple folios. There is also no need to call an agent and one of the biggest benefits of online investment is the complete privacy, adds the 78% of the respondents.

The knowledge of basic trading concepts is enough to get youngsters started. Analyst feeds are also abundantly available online and that helps make trading easier. It is interesting to note that a majority of young investors prefer the futures and options or F&O segment to the spot market, adds the survey.

Online trading account India is considered as a key instrument to improve earnings amongst the youth who are smart, cautious and pick an easy go medium, as it does not require any complicated procedures to carry out trades. Men and women both trade online almost neck to neck in their race to earn high gains with less pain.

Private sector employees who wish to secure their future financial resources form biggest percentage of those trading online. Self employed professionals and public sector employees also form a large chunk of those trading online with most young investors focusing upon the market derivates, permutation and combinations, stats and graphs to extract handful returns from the markets, highlights the survey.

The lagging brokerages are now forced to improve their operational costs and age old lagging trade practices in order to be successful. One of the main obstacles to further development of online trading is telecom infrastructure, which is forcing most online retail brokerages to offer telephone trading as a backup, said Mr. Rawat.

Majority of the respondents doing internet trading belong to the age group of 18 to 23 years followed 24 to 29 years. Similarly, people belong to 30 to 35 age groups. Whereas, 8% people are each from the age group of 36 to 41 years and above 42 years age. Out of 2,500 respondents, 69 % are male and 31% are females.

Nearly, 32% of the people are doing job in private organizations and only 16% are having their own business. Whereas, 20% people are government employees and only 12% are professionals. Over 56% people are unmarried and 44% are married in the collected sample, adds the survey.

In the poll 36% people have an annual income range of 0 to 4 Lakhs. And 32% people have income between 5 to 8 Lakhs. Similarly, 16 % and 8% people have an income range of about 9 to 12 Lakhs and 13 to 15 Lakhs respectively, highlights the survey.

In the survey, it is found that majority of young investors (64%) like to trade in futures and options (F&O) and it shows there is a need to create awareness among investors regarding profitability of investment in futures and options, adds the survey.

The emerging scenario makes it necessary for the broking companies to identify investor’s perception of level service quality, which strongly influences the investor’s behavioral intentions. This would facilitate the process of categorizing, determining and measuring, controlling and thereby improving the investor inclination/interest in online trading.

With brokerage firms tries to find level of satisfaction of investors with broking firms by extending several incentives and concessional service charges to attract the investors.

The survey was able to target corporate employees from 18 broad sectors, with maximum share contributed by employees from IT/ITes sector (17 per cent).

After IT/ITeS sector, contribution of the survey respondents from financial services is 11 per cent. It includes employees engaged in banking sector, stock brokerage house, insurance sector, financial consultancy and chartered accountants.

Employees working in engineering and telecom sector contributed 9 per cent and 8 per cent respectively in the questionnaire. Nearly 6 per cent of the employees belonged from market research/KPO and media background each. Management, FMCG and Infrastructure sector employees share is 5 per cent each, in the total survey.

Respondents from power and real estate sector contributed 4 per cent each. Employees from education and food& beverages sector provided a share of 3 per cent each. Advertising, manufacturing and textiles employees offered a share of 2 per cent each in the survey results.

Algorithmic trading in India: Current State, Challenges and Future

Algorithmic trading in India

We posed the following question in-front of our experts in financial markets:

How do you think the Algorithmic trading is performing in India? And how you foresee it vis-a-vis the algorithmic trading in US?  The challenges facing the algorithmic trading in India, and its future?

But before we come to our question, here is a brief about Algorithmic trading and High frequency trading (HFT):

Algorithmic trading is the use of algorithms to generate orders based on certain conditions. In last 3 yrs, algorithmic trading has gained prominence in Indian Markets.

High frequency trading involves the use of these algorithms in placing orders in real time in stock exchange and utilising market inefficiencies for one’s benefit. Mostly arbitrage opportunities help HFT traders make small profits and since the volumes are high, even small profits help these HFT traders make huge gain!

Now, coming back to our question, in our view:

  • Algo trading in India is still in nascent stage. US and UK markets are way ahead of Indian markets.
  • The sentiment of Indian brokers/dealers towards high frequency/ algorithmic trading needs to change. They find it difficult to adapt to the new technology and do not want to give up their traditional way of trading.
  • All the exchanges require the algorithms to get an approval after which a broker can execute those algorithms. Among the Indian exchanges, getting approval from MCX is toughest and from BSE is easiest.

And now, let’s see what our experts have to say:

“Expect high sophisticated ALGO development, but likely focused on a relatively small number of liquid stocks. LIQUIDITY will define success of the effort. Regulatory issues could mushroom”

 “The key is to approach each market separate and tune the algorithms to specifically perform for that market.”

They further state that the approach to Indian market would consist of:

  1. Identifying the universe of stocks that drives the market and study over all the Indian market
  2. Speak to experienced “old school” traders and extract valuable information
  3. Create specific market rules which will drive the algorithms on the macro scale
  4. Build tailor made algorithms per each stock for the frequently traded stocks
  5. Build in local anti gaming techniques

It is evident that through algorithmic trading, investors will be able to customize algorithms and automate their trading strategies to serve best their objectives. This will allow them to access liquidity at an optimal price, alongside being able to reducing market impact and signaling risk.

But the move to introduce algo trading in Indian stock markets is being faced with many questions like the increasing volatility and the cost of its setting being a deterrent. But the shift to algorithmic trading will surely be better for the broader market, if not a few.

Algo trading turnover at a historic high on popularity

Algo trading turnover at a historic high

With increasing volatility in the equity markets and stiffening competition among brokerages, more and more institutions are adopting technology to use algorithmic and high frequency trading (HFT) to stay in the race.

According to stock exchange data, algorithmic trading accounted for 14.94% and 20.78% of total cash market turnover on BSE and NSE, respectively, in February 2013.

According to BSE, the share of algo trading has never been so high before.

While NSE declined to share the historical data related to the share of algo trading, information on BSE website clearly shows that algos have gained immense popularity in the recent months. For instance, algo accounted for less than 10% of the total turnover in December last year and stayed in the range of 5-8% for most part of 2012.

Algo trading refers to the use of computer programs to execute trades in the stock, commodity or other financial markets. These programs execute trades as and when the pre-defined parameters related to price, timing, quantity are triggered. Complex trading strategies can also be implemented using algos.

Market experts say that technology — by way of algo-based trading and HFT — continues to play a big role in changing the brokerage industry as it helps in executing orders in fraction of a second with utmost efficiency, accuracy and without human intervention.

“Technology is playing a huge role. It might replace human beings one day, although not completely. If the same task could done with the help of a machine in more efficient and time saving manner, why would you not invest in it?”

Market experts said that these software have advanced in such a way that one can do derivatives rollover by a click of a button. “Earlier a dealer had to sit in front of the screen and manually feed the order. It was time-consuming and a costly affair”.

“Proprietary desk of international brokerages the world over wanted DMA into Indian equities so that they could punch their orders using algos without the need of a broker in India…While the concerns raised by the market regulator are appreciated, I do not think the regulator can take a step back.”

The RBI had highlighted the risks attached to algorithmic trading in its June 2012 Financial Stability Report. The report stated that several instances of extreme volatility and disruptions were witnessed in Indian stock markets that could be directly and indirectly attributed to the increased use of algorithmic trading.

Why We Shouldn’t Ban Algorithmic Trading ?

Why We Shouldn’t Ban Algorithmic Trading

On Friday, 20th April 2012, two mysterious events occurred on the National Stock Exchange (NSE). In the morning, Infosys futures crashed over 20% and quickly recovered back to the original level. In the afternoon, just before 2:30pm, Nifty futures crashed 6.7% from the 5,350 level back down to 5,000, and then nearly instantly recovered back to 5200. Both crashes were blamed on algorithmic trading.

Program trading has been blamed for “flash crashes” for nearly 25 years. In October 1987, US markets took a nose dive on a single day and for years, the blame game went on with the primary suspect being program trades. This is understandable. Since a computer can trade with much faster speed than a human, it can set off a spiralling price change by continuously buying or selling with no real control. Why then, should we even allow algorithmic trading?

Program trading can provide for great trading opportunities with less human error. Much of the arbitrage that used to happen in Indian markets was manual. To bridge any potential difference in prices between the NSE and BSE (the two largest stock exchanges in India), arbitrageurs would use two computers, manually entering a buy order on one and a sell order on another. The speed of the operator was his biggest skill, so the dealing room would resound with a cacophony of keyboards when an opportunity arose. The problem? A human can only look at so many opportunities, so many price differences remain. A slight error on that keyboard (F2 instead of F1) can result in a large loss. The operators cost money in terms of computers, real estate and benefits. You could eliminate much of these by using a computer to do exactly the same thing.

Program trading can curtail broker front-running and impact costs. Often, when a fund would have to take large positions, their brokers would put their own buy orders earlier, so that the large purchase from the fund would give them a great profit. In India, much of the volume is made up of the top 100 stocks. After that, stocks trade less than 20 cr. a day. For a mutual fund to buy about 25 cr. ($5 million) in a lesser known stock, its size will immediately drive up the price and a broker is quite likely to front-run their purchase. Using an algorithm instead will allow the purchaser to spread their purchase over several days and several brokers, hunting for volume slowly over time.

Algorithms can also provide liquidity where there isn’t otherwise any. For you to purchase a stock, there needs to be a seller in place. Many stocks don’t have the kind of interest from either investors or traders. Of the near-1,500 stocks traded on the NSE, more than 1,000 trade less than 50 lakh (Rs. 5 million) a day. The spread between the buy and sell prices on the exchange may be too wide; a typical market maker provides the liquidity that allows you to buy or sell at a reasonable cost. Market making operations used to be manual earlier; they are now run through algorithms.

Finally, large orders (greater than a few crores in value) are usually blocked by stock exchanges, assuming there has been a fat finger trade or a mistaken entry. Yet, large deals must take place when they must — if an investor decides to exit a large holding in a stock, they might use an algorithm to send in orders in allowable chunks.

Algorithmic trading, however, comes with its own set of problems. A rogue program can place orders continuously and take the entire system down. During Mahurat Trading in October 2011, such a program created a ruckus in the BSE, so much that the exchange canceled all trades made on that day to avoid a payment crisis.

Even if an algorithm splits large orders into parts that stock exchanges let through, the input itself may be faulty (an extra zero for instance) which means the algorithm does exactly what the order limit was designed to restrict: the fat finger trade. This, they say, is what happened with the Infosys order on Friday, 20th April 2012.

With such large orders, stop-losses can get triggered, creating another spiral. Some traders place a protective stop (in simple terms: “Sell-If-The-Price-Falls-To-X”) way below market prices; such stops get taken out when such large orders come by and those investors that sell feel disappointed when the market rebounds immediately. But that will happen even with large “manual” orders; algo trading is only a convenient scapegoat.

That steep falls are only engineered by automated trading is also suspect. The market has “circuit” limits which shut down trading when the index moves over 10%. After the 2009 elections, when markets moved up 10% in a short while, algorithmic trading wasn’t blamed; neither was it when markets crashed 10% in October 2009. The feeling was that the moves were “justified” since there was news behind it (The election results and a Lehman bankruptcy impact respectively). Since there was no “reason” on Friday, computers must have been to blame.

This is just witch-hunting. Computers do exactly as they have been programmed to do, and there will be large errors if they aren’t monitored properly (as manual traders must be). The regulators and the exchange must investigate each such case, and indeed, it has turned out it was more the human input that caused the error. Every rogue trader or trading program must be found and punished. Surveillance needs to get much more sophisticated to detect misbehaving automated trades. Algorithms already use a different code when entering trades; a series of checks can be run whenever required to see if any rules were violated. Some of this cost needs to be borne by the algo-trading community, by fees like a per-transaction or per-order fee payable to SEBI.

But we can’t go around demanding bans on algorithmic trading just because of a flash crash. Knee jerk reactions like that will hurt legitimate players or put them at the mercy of their brokers, and that is plain wrong.

Algorithmic Trading- Is it the New Artificial Intelligence for Investors?

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Algorithmic Trading has come a long way, from reading the tick data days to being latest buzz on the trade markets. Has your firm captured the essence of this new artificial intelligence?

The black-box trading was a hush-hush scenario until a year ago, as only a few trading firms offered them to their clients.Nevertheless, today, you can receive a bevy of free algo trading. Therefore, when a firm announces the discovery of the next generation of trading platform, the financial services industry ears perk up. Here it is about interpreting newsflow the moment it is delivered from the horse’s mouth.

“A client depends on a sell-side firm to execute its order on its behalf according to certain benchmarks. But, when it comes to a strategy, the Algorithmic Trading system actually generates the orders. Some hedge funds do this.”

For level-one sell side firms, automated trading has become a crucial part of their existence. These firms employ algorithm trading as the basic strategy to gain momentum in the markets across the globe.

How does this artificial intelligence work? Algorithmic trading is standardized by Volume-weighted average price (VWAP) it divides the total value of trades by the total volume over a period. Interestingly, European-banking conglomerate UBS utilizes algo trading for its 40% clientele. Other giant corporations who are testing the unique capabilities of robo trading include JPMorgan Chase, Credit Suisse and Dresdner Kleinwort Wasserstein.

You think only brokerage firms and banking institutions are eagerly investigating the technology?

Dow Jones the financial news boffin is secretive about performing tests on the news-reading solution with several chief sell side firms. Meanwhile, Thomson Press corroborates- it is examining the concept with clients.

Despite the term “newsflow algorithm” akin to Algorithmic Trading, it is believed that the system will hold an immense value to the financial industry for order-generating strategies. The automated trading will consider newsflow amongst a wide array of information available for influence trading activities.

Volume and time are important factors considered by a simple algo trading. Conversely, complicated algorithms would allow several hundreds of real-time factors to arrive at a profitable investment decision. For instance, Credit Suisse swanks about an automated trading system that takes care of 3,000 data points every 10 seconds.

One-third of European and American stocks were driven by autopilot i.e., algorithms in 2006. In 2009, HFT firms accounted their 73% of US equity trading volume to the artificial intelligence.

NASDAQ, BATS and Direct Edge have gained a larger market share as compared to NYSE. Their success is attributed to algorithmic trading that enables them to reduce processing fees and commissions.

Thus, the development of automated trading has prompted a reduction in trade size and increased trade volume, leading to investment that is more profitable. And, profitable investments obtain a larger chunk of market share for automated brokerage and financial firms, as compared to old school of thought.

Algorithmic Trading Gaining Ground

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India is programmed to go the algorithmic trading way just like rest of the world since it helps to sidestep many ‘human errors’ that trip high volume traders adopting traditional trading methods.

The future of trading is in ‘programmed trading’ and India is heading the same way as other countries have been doing. Most of the day-traders lose money and it is estimated that 95 per cent of trading ended up in losses. While there is no assurance that by feeding the trading strategy into a computer, the success of it could be ensured, the chances of successful trading could go up. This is because many of the human weaknesses, like increasing the size of the order while smelling profit that would result in losses ultimately, will be eliminated and ‘that is the most important thing’.

No Human Emotion

The algorithmic trading is based on a programme written by an analyst or trader with parameters set earlier and it could be a jobbing programme or arbitrage trading etc. The advantage is that ‘human emotions will not play a part’ since the computer would execute the orders according to the programme.

It is a fully-automated process, no human intervention is needed and it is ‘away from sentiments’. The traders could do the trading in cash segments, F&O segment etc and the trading could be done in different scrips and there is the facility of putting stop loss too. The volume buying could be done at different price points giving the buyer the benefit of cost averaging and the buy/sell could be done in micro seconds. The high volatility the markets have been witnessing in the past six months has given greater opportunity for algorithmic trading.

While algorithmic trading facility is available in both NSE and BSE, because of the huge trading volume in NSE, more trades are taking place in that exchange. But one could buy in one exchange and sell in another. The algorithmic trading helped in improving liquidity and the traders could fix their own targets for buy or sell, which could be executed automatically.

Algorithmic trading is more suitable for trading in frontline stocks that had ample liquidity because when a sell order was generated, it should be executable. For HNIs, who have on hand a large volume of shares, they could set different price points for sale to average the selling price; and greater the market volatility, the greater is the opportunity in automated trading.

Algo Trading in India – Statistically Speaking !!!

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Algorithmic trading is all the rage in India right now, and across the market the view is unanimous: the only way is up. The question is how just fast it will grow.

By the start of 2012, Algo accounted for some 24 percent of cash equities turnover in India and about 30 percent of equity derivatives. According to figures from the Bombay Stock Exchange, by far the smaller of the two Indian exchanges that dominate equities trading, the share for equity derivatives has already jumped to 45 percent since then.

Algorithms and High frequency trading are the hottest topics in the market – algorithmic trading and HFT itself, and now the regulations around it. This is what the majority of players in the market are focused on today.

India has the building blocks in place for a ramp-up. Co-location has been available from both the Bombay Stock Exchange and its bigger competitor, the National Stock Exchange, for 18 months. Both exchanges, and market observers, say their trading platforms can handle HFT. Direct market access is available. Smart order routing between the two exchanges has also been operating since August 2010.

The Indian regulator, the Securities and Exchange Board of India (SEBI), produced guidelines for algorithmic trading in March which brokers, exchanges and market watchers hail as a sensible response. The new rules, they say, recognise that algorithmic trading is a natural development and are aimed at preventing problems but not blocking growth.

“All the dynamics point to an increase in automated and algo trading in the next few years,” Expect the cash equities and derivatives levels to raise around 50-55 percent within the next year or so.