TP ICAP has just issued a trading update on its results for the third quarter. The company is reporting that its revenues were higher by 3 percent year-on-year at £420 million ($548 million). The first nine months of the year have so far yielded revenues of £1.35 billion ($1.76 billion). The figure is higher by 9 percent when compared to the first nine months of 2016.
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TP ICAP is showing remarkable resilience amid challenging market conditions. The revenues are 1 percent higher when compared to last year. Income from the Energy & Commodities business was lower by 1 percent, while Data & Analytics
Analytics
Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability.
Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability.
Read this Term grew by 6 percent.
Revenue Per Broker Increases
TP ICAP has highlighted that its Institutional Services business saw strong growth during the period. The company’s revenue per broker has increased, marking improved efficiency of the company’s workforce.
Despite a relatively solid performance when compared to many industry peers, it issued a conservative outlook for the fourth quarter of the year. Challenging trading conditions have been cited as the main risk while the base in the fourth quarter of last year was marked by Volatility
Volatility
In finance, volatility refers to the amount of change in the rate of a financial instrument, such as commodities, currencies, stocks, over a given time period. Essentially, volatility describes the nature of an instrument’s fluctuation; a highly volatile security equates to large fluctuations in price, and a low volatile security equates to timid fluctuations in price. Volatility is an important statistical indicator used by financial traders to assist them in developing trading systems. Traders can be successful in both low and high volatile environments, but the strategies employed are often different depending upon volatility. Why Too Much Volatility is a ProblemIn the FX space, lower volatile currency pairs offer less surprises, and are suited to position traders.High volatile pairs are attractive for many day traders, due to quick and strong movements, offering the potential for higher profits, although the risk associated with such volatile pairs are many. Overall, a look at previous volatility tells us how likely price will fluctuate in the future, although it has nothing to do with direction.All a trader can gather from this is the understanding that the probability of a volatile pair to increase or decrease an X amount in a Y period of time, is more than the probability of a non-volatile pair. Another important factor is, volatility can and does change over time, and there can be periods when even highly volatile instruments show signs of flatness, with price not really making headway in either direction. Too little volatility is just as problematic for markets as too much, we uncertainty in excess can create panic and problems of liquidity. This was evident during Black Swan events or other crisis that have historically roiled currency and equity markets.
In finance, volatility refers to the amount of change in the rate of a financial instrument, such as commodities, currencies, stocks, over a given time period. Essentially, volatility describes the nature of an instrument’s fluctuation; a highly volatile security equates to large fluctuations in price, and a low volatile security equates to timid fluctuations in price. Volatility is an important statistical indicator used by financial traders to assist them in developing trading systems. Traders can be successful in both low and high volatile environments, but the strategies employed are often different depending upon volatility. Why Too Much Volatility is a ProblemIn the FX space, lower volatile currency pairs offer less surprises, and are suited to position traders.High volatile pairs are attractive for many day traders, due to quick and strong movements, offering the potential for higher profits, although the risk associated with such volatile pairs are many. Overall, a look at previous volatility tells us how likely price will fluctuate in the future, although it has nothing to do with direction.All a trader can gather from this is the understanding that the probability of a volatile pair to increase or decrease an X amount in a Y period of time, is more than the probability of a non-volatile pair. Another important factor is, volatility can and does change over time, and there can be periods when even highly volatile instruments show signs of flatness, with price not really making headway in either direction. Too little volatility is just as problematic for markets as too much, we uncertainty in excess can create panic and problems of liquidity. This was evident during Black Swan events or other crisis that have historically roiled currency and equity markets.
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Commenting on the interim results, the CEO of TP ICAP, John Phizackerley, said: “Despite mixed market conditions our revenue growth to date demonstrates the value of our diversified portfolio. Looking ahead we expect comparatively subdued market conditions for the fourth quarter of 2017 although we are well-placed to benefit from any interest rate rises in the US and Europe.”
“Our top priority has been delivering the integration of TP ICAP and we continue to make good progress. Integration is on track and in line with the guidance we gave at the half year. We have also made significant one-off and long-term investments in areas such as MiFID II, broker surveillance systems, Cybersecurity, Belfast and our Institutional Services division.”
Looking for a New CFO
In addition to the financials, the company announced top executive changes. Andrew Baddeley, the Chief Financial Officer of TP ICAP, has stepped down from the company’s board. He will remain with the company until the end of the year to ensure a smooth transition. Deputy CFO Robin Stewart will take on the role on an interim basis.
“Andrew Baddeley has overseen the finance function at an intense period of change and growth for the group. He was responsible for putting in place the integration process for ICAP and Tullett Prebon, which is now well underway, and on track. Andrew has done this while helping us deliver a good financial performance in challenging market conditions. We are sad to see him go,” Phizackerley said.
TP ICAP has just issued a trading update on its results for the third quarter. The company is reporting that its revenues were higher by 3 percent year-on-year at £420 million ($548 million). The first nine months of the year have so far yielded revenues of £1.35 billion ($1.76 billion). The figure is higher by 9 percent when compared to the first nine months of 2016.
Register now to the London Summit 2017, Europe’s largest gathering of top-tier retail brokers and institutional FX investors
TP ICAP is showing remarkable resilience amid challenging market conditions. The revenues are 1 percent higher when compared to last year. Income from the Energy & Commodities business was lower by 1 percent, while Data & Analytics
Analytics
Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability.
Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability.
Read this Term grew by 6 percent.
Revenue Per Broker Increases
TP ICAP has highlighted that its Institutional Services business saw strong growth during the period. The company’s revenue per broker has increased, marking improved efficiency of the company’s workforce.
Despite a relatively solid performance when compared to many industry peers, it issued a conservative outlook for the fourth quarter of the year. Challenging trading conditions have been cited as the main risk while the base in the fourth quarter of last year was marked by Volatility
Volatility
In finance, volatility refers to the amount of change in the rate of a financial instrument, such as commodities, currencies, stocks, over a given time period. Essentially, volatility describes the nature of an instrument’s fluctuation; a highly volatile security equates to large fluctuations in price, and a low volatile security equates to timid fluctuations in price. Volatility is an important statistical indicator used by financial traders to assist them in developing trading systems. Traders can be successful in both low and high volatile environments, but the strategies employed are often different depending upon volatility. Why Too Much Volatility is a ProblemIn the FX space, lower volatile currency pairs offer less surprises, and are suited to position traders.High volatile pairs are attractive for many day traders, due to quick and strong movements, offering the potential for higher profits, although the risk associated with such volatile pairs are many. Overall, a look at previous volatility tells us how likely price will fluctuate in the future, although it has nothing to do with direction.All a trader can gather from this is the understanding that the probability of a volatile pair to increase or decrease an X amount in a Y period of time, is more than the probability of a non-volatile pair. Another important factor is, volatility can and does change over time, and there can be periods when even highly volatile instruments show signs of flatness, with price not really making headway in either direction. Too little volatility is just as problematic for markets as too much, we uncertainty in excess can create panic and problems of liquidity. This was evident during Black Swan events or other crisis that have historically roiled currency and equity markets.
In finance, volatility refers to the amount of change in the rate of a financial instrument, such as commodities, currencies, stocks, over a given time period. Essentially, volatility describes the nature of an instrument’s fluctuation; a highly volatile security equates to large fluctuations in price, and a low volatile security equates to timid fluctuations in price. Volatility is an important statistical indicator used by financial traders to assist them in developing trading systems. Traders can be successful in both low and high volatile environments, but the strategies employed are often different depending upon volatility. Why Too Much Volatility is a ProblemIn the FX space, lower volatile currency pairs offer less surprises, and are suited to position traders.High volatile pairs are attractive for many day traders, due to quick and strong movements, offering the potential for higher profits, although the risk associated with such volatile pairs are many. Overall, a look at previous volatility tells us how likely price will fluctuate in the future, although it has nothing to do with direction.All a trader can gather from this is the understanding that the probability of a volatile pair to increase or decrease an X amount in a Y period of time, is more than the probability of a non-volatile pair. Another important factor is, volatility can and does change over time, and there can be periods when even highly volatile instruments show signs of flatness, with price not really making headway in either direction. Too little volatility is just as problematic for markets as too much, we uncertainty in excess can create panic and problems of liquidity. This was evident during Black Swan events or other crisis that have historically roiled currency and equity markets.
Read this Term around the US presidential election.
Commenting on the interim results, the CEO of TP ICAP, John Phizackerley, said: “Despite mixed market conditions our revenue growth to date demonstrates the value of our diversified portfolio. Looking ahead we expect comparatively subdued market conditions for the fourth quarter of 2017 although we are well-placed to benefit from any interest rate rises in the US and Europe.”
“Our top priority has been delivering the integration of TP ICAP and we continue to make good progress. Integration is on track and in line with the guidance we gave at the half year. We have also made significant one-off and long-term investments in areas such as MiFID II, broker surveillance systems, Cybersecurity, Belfast and our Institutional Services division.”
Looking for a New CFO
In addition to the financials, the company announced top executive changes. Andrew Baddeley, the Chief Financial Officer of TP ICAP, has stepped down from the company’s board. He will remain with the company until the end of the year to ensure a smooth transition. Deputy CFO Robin Stewart will take on the role on an interim basis.
“Andrew Baddeley has overseen the finance function at an intense period of change and growth for the group. He was responsible for putting in place the integration process for ICAP and Tullett Prebon, which is now well underway, and on track. Andrew has done this while helping us deliver a good financial performance in challenging market conditions. We are sad to see him go,” Phizackerley said.
