Adapting Forex Strategies To Canadian Economic Trends

Adapting Forex Strategies To Canadian Economic Trends – In the last decade, algorithmic trading (AT) and high frequency trading (HFT), especially HFT, have taken over the trading world. During 2009-2010, more than 60% of US trading was attributed to HFT, although this percentage has declined in the past few years.

Here’s a look at the world of algorithmic and high-frequency trading: how they relate, their benefits and challenges, their main users, and their current and future status.

Adapting Forex Strategies To Canadian Economic Trends

Adapting Forex Strategies To Canadian Economic Trends

First, HFT is a subset of algorithmic trading, and HFT in turn includes Ultra HFT trading. Algorithms essentially act as intermediaries between buyers and sellers, with HFT and Ultra HFT being a way for traders to capitalize on infinitesimally small price discrepancies that can only exist for a tiny amount of time.

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Rules-based computer-aided algorithmic trading uses specialized programs that make automated trading decisions to enter orders. AT splits large orders and enters these split orders at different times and even manages trade orders after they are submitted.

Large orders, usually by pension funds or insurance companies, can have a serious impact on share price levels. AT’s aim is to reduce this price impact by breaking up large orders into many small orders, thereby offering traders some price advantage.

Algorithms also dynamically control the schedule for sending orders to the market. These algorithms read high-speed data sources in real-time, detect trade signals, identify appropriate price levels, and then place trade orders as soon as they identify a suitable opportunity. They can also detect arbitrage opportunities and can make trades based on trend tracking, news and even speculation.

High frequency trading is an extension of algorithmic trading. They manage small trade orders to be sent to the market at high speed, often in milliseconds or microseconds – a millisecond is a thousandth of a second and a microsecond is a thousandth of a millisecond.

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These orders are driven by high-speed algorithms that replicate the role of a market maker. HFT algorithms usually involve two-sided order placement (buy-low and sell-high) in an attempt to profit from the bid-ask spread. HFT algorithms also try to “sense out” any pending large orders by sending several small orders and analyzing the patterns and time taken to execute the trade. If they sense an opportunity, the HFT algorithms will then try to take advantage of large backlogs by adjusting prices to fill them and make a profit.

Ultra HFT is also another specialized HFT stream. By paying an additional exchange fee, trading firms gain access to pending orders a fraction of a second before the rest of the market.

Using market conditions that cannot be detected by the human eye, HFT algorithms rely on finding profit potential in an ultra-short period of time. One example is arbitrage between futures and ETFs on the same underlying index.

Adapting Forex Strategies To Canadian Economic Trends

The following graphic shows what the HFT algorithms are trying to detect and profit from. These charts show the price movement of E-mini S&P 500 futures (ES) and SPDR S&P 500 (SPY) at different time frequencies.

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The deeper you zoom into the charts, the more price differences can be found between two securities that at first look perfectly correlated.

Please note that the axis for both tools is different. Price differences are significant even when they occur at the same horizontal levels.

So to the naked eye, what is perfectly synchronized appears to have considerable profit potential from the perspective of lightning-fast algorithms.

In the US markets, the SEC approved automated electronic exchanges in 1998. About a year later, HFT began, with trade execution times of a few seconds at the time. By 2010 this had been reduced to milliseconds – see Bank of England’s Andrew Haldane’s “Patience and Finance” speech – and today one hundredth of a microsecond is sufficient time for most trading decisions and HFT execution. Due to the ever-increasing computing power, it may be possible to achieve work at nanosecond and picosecond frequencies using HFT in the relatively near future.

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“represented more than 60% of all US stock volume,” which turned out to be a very high mark. By 2013, this percentage had dropped to around 50%. Bloomberg further noted that where in 2009 “high-frequency traders moved about 3.25 billion shares a day. In 2012, it was 1.6 billion a day” and “average profits fell from about a tenth of a penny per share to a twentieth of a penny”.

HFT trading ideally needs to have the lowest possible data latency (time delays) and the highest possible level of automation. Thus, participants prefer to trade in markets with a high level of automation and integration capabilities in their trading platforms. These include NASDAQ, NYSE, Direct Edge and BATS.

HFT is dominated by proprietary trading companies and includes a variety of securities, including stocks, derivatives, index funds and ETFs, currencies and fixed income instruments. A 2011 Deutsche Bank report found that of then-current HFT participants, proprietary trading firms comprised 48%, multi-service broker-dealer proprietary trading desks 46%, and hedge funds about 6%. Major names in this field include proprietary trading firms such as KWG Holdings (a merger between Getco and Knight Capital) and the trading departments of large institutional firms such as Citigroup ( C ), JP Morgan ( JPM ), and Goldman Sachs ( GS ).

Adapting Forex Strategies To Canadian Economic Trends

HFT is beneficial for traders, but does it help the market as a whole? Some of the overall market benefits cited by HFT proponents include:

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Opponents of HFT claim that algorithms can be programmed to send hundreds of fake orders and cancel them in the next second. Such “spoofing” momentarily creates a spurious surge in demand/supply leading to price anomalies that HFT traders can use to their advantage. In 2013, the SEC introduced the Market Information Data Analytics System (MIDAS), which examines data across various markets at a millisecond frequency to try to catch fraudulent activities such as “spoofing”.

The HFT market is also crowded and participants are trying to get ahead of their competitors by constantly improving algorithms and adding infrastructure. This “arms race” makes it increasingly difficult for traders to capitalize on price anomalies, even with the best computers and top-notch networks.

And the prospect of costly glitches also deters potential entrants. Some examples include the “Flash Crash” of May 6, 2010, where HFT-triggered sell orders led to an impulsive 600-point drop in the DJIA. Then there is the case of Knight Capital, then the king of HFT on the NYSE. On August 1, 2012, she installed new software and accidentally bought and sold $7 billion worth of NYSE stock at bargain prices. Knight was forced to liquidate its positions, costing it $440 million in one day and eroding 40% of the firm’s value. by another HFT firm, Getco, to form KCG Holdings, the merged entity is still struggling.

Thus, the major obstacles to HFT’s future growth include its declining profit potential, high operating costs, the prospect of stricter regulations, and the fact that there is no room for error as losses can quickly run into the millions.

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HFT as some growth potential overseas. Exchanges around the world are opening up to this concept and sometimes welcome HFT firms by offering all the necessary support. On the other hand, lawsuits have been filed against exchanges due to the alleged undue time advantage that HFT firms have. Despite growing opposition, France was the first country to introduce a special tax on HFTs in 2012, soon followed by Italy.

A study by US authorities assessed the impact of HFT on the rapid burst of volatility in the Treasury market on 15 October 2014. Although it found “that there is no single cause of turbulence”, the study did not rule out the potential for future risk from HFT, whether in terms of price, liquidity or volume impacts shops.

The growth of computer speed and the development of algorithms have created seemingly limitless possibilities in trading. But AT and HFT are classic examples of rapid developments that have outpaced regulatory regimes for years and allowed huge benefits for a relative handful of trading firms. While HFT may offer limited opportunities for traders in established markets such as the US in the future, some emerging markets could still be quite favorable for high-stakes HFT ventures.

Adapting Forex Strategies To Canadian Economic Trends

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