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causal20sc7700 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: However, since the U.S. has ratcheted up oil production and reduced its reliance on imports, shocks are less impactful to the United States.
Answer: | noise | However, since the U.S. has ratcheted up oil production and reduced its reliance on imports, shocks are less impactful to the United States. | [
"noise",
"causal"
] | 0 |
causal20sc7701 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Combining some of the more pressing issues in the market for September, which is seasonally a weak month for equities, we can't help but to marvel at the unwind of some of the more popular trades.
Answer: | noise | Combining some of the more pressing issues in the market for September, which is seasonally a weak month for equities, we can't help but to marvel at the unwind of some of the more popular trades. | [
"noise",
"causal"
] | 0 |
causal20sc7702 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Short oil, long bonds, long momentum and short value had been all the rage in 2019. In September, the reverse is in force and having been stimulated by sector rotation and a sell-off in the bond market.
Answer: | noise | Short oil, long bonds, long momentum and short value had been all the rage in 2019. In September, the reverse is in force and having been stimulated by sector rotation and a sell-off in the bond market. | [
"noise",
"causal"
] | 0 |
causal20sc7703 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: When will the unwind of these overcrowded trades come to an end remains to be seen, but here is what J.P. Morgan's quant team reminds investors about and with some nostalgia (Volmageddon). JPM's head quant analyst Marko Kolanovic also denotes that even with the recent crude oil spike and unwinding of the short energy positions, investors really need not worry.
Answer: | noise | When will the unwind of these overcrowded trades come to an end remains to be seen, but here is what J.P. Morgan's quant team reminds investors about and with some nostalgia (Volmageddon). JPM's head quant analyst Marko Kolanovic also denotes that even with the recent crude oil spike and unwinding of the short energy positions, investors really need not worry. | [
"noise",
"causal"
] | 0 |
causal20sc7704 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Figure 1 below implies that we could start expecting a negative impact from Oil on the S&P 500 in an $80-$85 range for WTI. This is still far away from the current level of $60. The last two times the market has experienced a momentum breakdown this severe, it preceded or coincided with an economic recession (see below).
Answer: | noise | Figure 1 below implies that we could start expecting a negative impact from Oil on the S&P 500 in an $80-$85 range for WTI. This is still far away from the current level of $60. The last two times the market has experienced a momentum breakdown this severe, it preceded or coincided with an economic recession (see below). | [
"noise",
"causal"
] | 0 |
causal20sc7705 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: He believes the recent breakdown in momentum signals the end of Goldilocks at best, and a recession at worst… but that both outcomes suggest the big winners this year are likely to come under further pressure. If the porridge is too cold, he believes the secular growth part of the long momentum strategy is more at risk than the defensives.
Answer: | noise | He believes the recent breakdown in momentum signals the end of Goldilocks at best, and a recession at worst… but that both outcomes suggest the big winners this year are likely to come under further pressure. If the porridge is too cold, he believes the secular growth part of the long momentum strategy is more at risk than the defensives. | [
"noise",
"causal"
] | 0 |
causal20sc7706 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: He doesn't believe momentum weakness will lead to a healthy or smooth rotation from growth to value because such a rotation will create too much portfolio destruction for most active managers and force a de-grossing of risk.
Answer: | noise | He doesn't believe momentum weakness will lead to a healthy or smooth rotation from growth to value because such a rotation will create too much portfolio destruction for most active managers and force a de-grossing of risk. | [
"noise",
"causal"
] | 0 |
causal20sc7707 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Moving beyond Monday's crude oil headlines and speculations, investors will now focus on the economic data of the week and the FOMC 2-day meeting that kicks-off Tuesday.
Answer: | noise | Moving beyond Monday's crude oil headlines and speculations, investors will now focus on the economic data of the week and the FOMC 2-day meeting that kicks-off Tuesday. | [
"noise",
"causal"
] | 0 |
causal20sc7708 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The event will end with a likely 25 bps rate cut on Wednesday and the subsequent press conference that follows the announcement. The risk to the market is not likely the rate cut itself, but rather the forward looking statements, dot plot and number of detractors. Two members opposed the last rate cut, and even more could oppose this one, based on certain of the economic data that has been delivered since the July FOMC meeting.
Answer: | noise | The event will end with a likely 25 bps rate cut on Wednesday and the subsequent press conference that follows the announcement. The risk to the market is not likely the rate cut itself, but rather the forward looking statements, dot plot and number of detractors. Two members opposed the last rate cut, and even more could oppose this one, based on certain of the economic data that has been delivered since the July FOMC meeting. | [
"noise",
"causal"
] | 0 |
causal20sc7709 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Some strategists haves said the more dissents, the more it would add to increased market volatility, since the Fed outlook becomes much more uncertain if Fed officials are not more uniformly supporting policy actions.
Answer: | noise | Some strategists haves said the more dissents, the more it would add to increased market volatility, since the Fed outlook becomes much more uncertain if Fed officials are not more uniformly supporting policy actions. | [
"noise",
"causal"
] | 0 |
causal20sc7710 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The dot plot is where most market participants will head once the statement's are released.
Answer: | noise | The dot plot is where most market participants will head once the statement's are released. | [
"noise",
"causal"
] | 0 |
causal20sc7711 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: If the dot plot doesn't project more easing, the task might fall to Fed chairman Jerome Powell to leave the door open for another cut when he talks to reporters.
Answer: | noise | If the dot plot doesn't project more easing, the task might fall to Fed chairman Jerome Powell to leave the door open for another cut when he talks to reporters. | [
"noise",
"causal"
] | 0 |
causal20sc7712 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The market desires that the Fed remains carefully watching not just the U.S. economic data, but the global economic data, which continues to weaken. Additionally, the market desires that the Fed expresses it's willingness to ease further, should the data deteriorate further in the coming months.
Answer: | noise | The market desires that the Fed remains carefully watching not just the U.S. economic data, but the global economic data, which continues to weaken. Additionally, the market desires that the Fed expresses it's willingness to ease further, should the data deteriorate further in the coming months. | [
"noise",
"causal"
] | 0 |
causal20sc7713 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Investors have reduced their expectations for future rate cuts to include just one more in 2019, December.
Answer: | noise | Investors have reduced their expectations for future rate cuts to include just one more in 2019, December. | [
"noise",
"causal"
] | 0 |
causal20sc7714 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Nonetheless, the Fed will need to at least express its willingness to act with more accommodation should the economic situation demand it. At present, we believe that the Fed, led by Chairman Jerome Powell, has ample room to navigate the upcoming rate announcement and press conference, especially after the geopolitical event this weekend.
Answer: | noise | Nonetheless, the Fed will need to at least express its willingness to act with more accommodation should the economic situation demand it. At present, we believe that the Fed, led by Chairman Jerome Powell, has ample room to navigate the upcoming rate announcement and press conference, especially after the geopolitical event this weekend. | [
"noise",
"causal"
] | 0 |
causal20sc7715 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The 3 main risks to the Fed's outlook and global activity are as follows: Global economic slowdown Trade policy uncertainty Low inflation Pushing the Fed aside, if not at least for the day… there will certainly be enough time to worry about the Fed come Wednesday. The economic data has been coming in stronger than expected of late.
Answer: | noise | The 3 main risks to the Fed's outlook and global activity are as follows: Global economic slowdown Trade policy uncertainty Low inflation Pushing the Fed aside, if not at least for the day… there will certainly be enough time to worry about the Fed come Wednesday. The economic data has been coming in stronger than expected of late. | [
"noise",
"causal"
] | 0 |
causal20sc7716 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: This has pushed the Citi Economic Surprise Index higher of late.
Answer: | noise | This has pushed the Citi Economic Surprise Index higher of late. | [
"noise",
"causal"
] | 0 |
causal20sc7717 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The index had spent most of the year in negative territory before a stretch of positive service sector, jobless claims, retail sales and consumer spending data. The notable manufacturing decline doesn't portend as negative for the U.S. economy as it does for other industrialized nations.
Answer: | noise | The index had spent most of the year in negative territory before a stretch of positive service sector, jobless claims, retail sales and consumer spending data. The notable manufacturing decline doesn't portend as negative for the U.S. economy as it does for other industrialized nations. | [
"noise",
"causal"
] | 0 |
causal20sc7718 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The U.S. economy has been less reliant on manufacturing since the 1970s.
Answer: | noise | The U.S. economy has been less reliant on manufacturing since the 1970s. | [
"noise",
"causal"
] | 0 |
causal20sc7719 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The service sector has grown to become the greatest part of the U.S. economy, setting itself apart from the Eurozone and China.
Answer: | noise | The service sector has grown to become the greatest part of the U.S. economy, setting itself apart from the Eurozone and China. | [
"noise",
"causal"
] | 0 |
causal20sc7720 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The contraction in ISM manufacturing data previously witnessed in 2015 wasn't significant enough to drive a recession in the United States. Given the relatively small weight of manufacturing in the U.S. economy, it must decline substantially to drive a recession.
Answer: | noise | The contraction in ISM manufacturing data previously witnessed in 2015 wasn't significant enough to drive a recession in the United States. Given the relatively small weight of manufacturing in the U.S. economy, it must decline substantially to drive a recession. | [
"noise",
"causal"
] | 0 |
causal20sc7721 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Current conditions appear similar to the 2015 contraction but above levels typically experienced going into recession.
Answer: | noise | Current conditions appear similar to the 2015 contraction but above levels typically experienced going into recession. | [
"noise",
"causal"
] | 0 |
causal20sc7722 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: With some of the focus on manufacturing data this week, the latest regional data is expected to weaken and has. The Empire State business conditions index fell 2.8 points to 2 in September, the New York Fed said Monday. Economists had expected little change and a reading of 4.9, according to a survey by Econoday.
Answer: | noise | With some of the focus on manufacturing data this week, the latest regional data is expected to weaken and has. The Empire State business conditions index fell 2.8 points to 2 in September, the New York Fed said Monday. Economists had expected little change and a reading of 4.9, according to a survey by Econoday. | [
"noise",
"causal"
] | 0 |
causal20sc7723 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The index of present General Business conditions only fell slightly and expectations for the next six months were notably weaker, falling from 25.7 down to 13.7. While both of these indices are well off their highs from the last year or two, they also aren't at levels that, at this point, would be considered dangerous for the economy.
Answer: | noise | The index of present General Business conditions only fell slightly and expectations for the next six months were notably weaker, falling from 25.7 down to 13.7. While both of these indices are well off their highs from the last year or two, they also aren't at levels that, at this point, would be considered dangerous for the economy. | [
"noise",
"causal"
] | 0 |
causal20sc7724 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: One notable aspect of the Empire State survey was the large drops in expectations for Capital Expenditures and Technology Spending.
Answer: | noise | One notable aspect of the Empire State survey was the large drops in expectations for Capital Expenditures and Technology Spending. | [
"noise",
"causal"
] | 0 |
causal20sc7725 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The index that tracks plans for Technology spending fell 10.9 points from 17.4 down to 6.5 in what was the largest monthly drop since May 2016.
Answer: | noise | The index that tracks plans for Technology spending fell 10.9 points from 17.4 down to 6.5 in what was the largest monthly drop since May 2016. | [
"noise",
"causal"
] | 0 |
causal20sc7726 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Plans for Capital Expenditures were even worse as that index fell 18.6 points from 23.2 down to 4.6.
Answer: | noise | Plans for Capital Expenditures were even worse as that index fell 18.6 points from 23.2 down to 4.6. | [
"noise",
"causal"
] | 0 |
causal20sc7727 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: For that index, it was the third-largest decline in the report's history dating back to 2001 and the largest monthly decline since May 2016. Here again, though, while these declines are pretty steep, they aren't at levels that in the past have been considered recessionary.
Answer: | noise | For that index, it was the third-largest decline in the report's history dating back to 2001 and the largest monthly decline since May 2016. Here again, though, while these declines are pretty steep, they aren't at levels that in the past have been considered recessionary. | [
"noise",
"causal"
] | 0 |
causal20sc7728 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: And today's economic data releases aren't terribly meaningful historically, as investors look forward and toward tomorrow's FOMC meeting. As noted earlier, the service sector aimed at servicing consumers has remained healthy in the face of weakening manufacturing output. The consumer has been benefitting from wage gains and a robust labor market.
Answer: | noise | And today's economic data releases aren't terribly meaningful historically, as investors look forward and toward tomorrow's FOMC meeting. As noted earlier, the service sector aimed at servicing consumers has remained healthy in the face of weakening manufacturing output. The consumer has been benefitting from wage gains and a robust labor market. | [
"noise",
"causal"
] | 0 |
causal20sc7729 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Household financial obligations remain at some 45+ year lows when juxtaposed with disposable income levels.
Answer: | noise | Household financial obligations remain at some 45+ year lows when juxtaposed with disposable income levels. | [
"noise",
"causal"
] | 0 |
causal20sc7730 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: August monthly retail sales confirmed for investors that despite all the talks of a recession and waning consumer sentiment surveys, the consumer remained in spend-mode. We might have expected this from the recent update from the Personal Income and Expenditures (PCE) data that pointed in a significant decline in the Personal Savings Rate, the first significant decline of 2019. What may be proving of greater importance in the consumer spending equation in 2019 than in years past is the acceleration in wage growth amongst the low-wage bracket.
Answer: | noise | August monthly retail sales confirmed for investors that despite all the talks of a recession and waning consumer sentiment surveys, the consumer remained in spend-mode. We might have expected this from the recent update from the Personal Income and Expenditures (PCE) data that pointed in a significant decline in the Personal Savings Rate, the first significant decline of 2019. What may be proving of greater importance in the consumer spending equation in 2019 than in years past is the acceleration in wage growth amongst the low-wage bracket. | [
"noise",
"causal"
] | 0 |
causal20sc7731 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: As we can see from the BLS Nonfarm Payroll data chart below, low wage earners have experienced the most significant pick-up in wages in years and when compared to peer wage tiers. When we consider the drop in the Personal Savings rate since mid 2019, we are forced to recognize that low-wage earners are not typically savers. With this in mind, it is no wonder the Personal Savings rate has dropped as low-wage growth has accelerated to the upside and has found retail sales also accelerating since mid-year.
Answer: | noise | As we can see from the BLS Nonfarm Payroll data chart below, low wage earners have experienced the most significant pick-up in wages in years and when compared to peer wage tiers. When we consider the drop in the Personal Savings rate since mid 2019, we are forced to recognize that low-wage earners are not typically savers. With this in mind, it is no wonder the Personal Savings rate has dropped as low-wage growth has accelerated to the upside and has found retail sales also accelerating since mid-year. | [
"noise",
"causal"
] | 0 |
causal20sc7732 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Despite economic uncertainty, households increased their spending at a 4.7% annual rate in the second quarter, the strongest pace in four and a half years. WSJ's Gunjan Banerji looks at why the consumer is powering forward, and whether it could be enough to prop up the economy, in this latest video analysis of the consumer. Gunjan outlines that despite several headwinds, the consumer has outperformed fears of an economic slowdown.
Answer: | causal | Despite economic uncertainty, households increased their spending at a 4.7% annual rate in the second quarter, the strongest pace in four and a half years. WSJ's Gunjan Banerji looks at why the consumer is powering forward, and whether it could be enough to prop up the economy, in this latest video analysis of the consumer. Gunjan outlines that despite several headwinds, the consumer has outperformed fears of an economic slowdown. | [
"noise",
"causal"
] | 1 |
causal20sc7733 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: And to accompany or coincide with Gunjan's analysis of the consumer and wage growth benefits adding to consumer spending, holiday sales are expected to show YoY growth once again.
Answer: | noise | And to accompany or coincide with Gunjan's analysis of the consumer and wage growth benefits adding to consumer spending, holiday sales are expected to show YoY growth once again. | [
"noise",
"causal"
] | 0 |
causal20sc7734 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Holiday retail sales for 2019 are forecast to increase 4.5% to 5%, exceeding $1.1 trillion, according to an annual survey by Deloitte.
Answer: | noise | Holiday retail sales for 2019 are forecast to increase 4.5% to 5%, exceeding $1.1 trillion, according to an annual survey by Deloitte. | [
"noise",
"causal"
] | 0 |
causal20sc7735 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: That would be better than the Census Bureau data of sales growth of 3.1% on sales of $1.09 trillion from last November to January. I think this will be a surprise for our clients, said Rod Sides, vice chairman of Deloitte's retail and distribution practice in the U.S. I think most [retailers] would expect a slightly lower increase.
Answer: | noise | That would be better than the Census Bureau data of sales growth of 3.1% on sales of $1.09 trillion from last November to January. I think this will be a surprise for our clients, said Rod Sides, vice chairman of Deloitte's retail and distribution practice in the U.S. I think most [retailers] would expect a slightly lower increase. | [
"noise",
"causal"
] | 0 |
causal20sc7736 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: … This is probably bigger than those expectations.
Answer: | noise | … This is probably bigger than those expectations. | [
"noise",
"causal"
] | 0 |
causal20sc7737 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Sides denotes some key positive factors that will push holiday sales higher in 2019: 2019 holiday season laps a season last year during which the U.S. government shut down and the stock market saw major declines last December.
Answer: | noise | Sides denotes some key positive factors that will push holiday sales higher in 2019: 2019 holiday season laps a season last year during which the U.S. government shut down and the stock market saw major declines last December. | [
"noise",
"causal"
] | 0 |
causal20sc7738 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: We're [coming] off a much lower base.
Answer: | noise | We're [coming] off a much lower base. | [
"noise",
"causal"
] | 0 |
causal20sc7739 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: … But we don't expect [those things] to happen this holiday season.
Answer: | noise | … But we don't expect [those things] to happen this holiday season. | [
"noise",
"causal"
] | 0 |
causal20sc7740 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The U.S. labor market remains strong.
Answer: | noise | The U.S. labor market remains strong. | [
"noise",
"causal"
] | 0 |
causal20sc7741 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Unemployment rates still near record lows.
Answer: | noise | Unemployment rates still near record lows. | [
"noise",
"causal"
] | 0 |
causal20sc7742 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Consumer confidence elevated. A separate forecast by global consulting firm AlixPartners is calling for holiday sales growth of 4.4% to 5.3 percent.
Answer: | noise | Consumer confidence elevated. A separate forecast by global consulting firm AlixPartners is calling for holiday sales growth of 4.4% to 5.3 percent. | [
"noise",
"causal"
] | 0 |
causal20sc7743 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: But AlixPartners says there's still unprecedented uncertainty as the season approaches.
Answer: | noise | But AlixPartners says there's still unprecedented uncertainty as the season approaches. | [
"noise",
"causal"
] | 0 |
causal20sc7744 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: While our forecast is bullish, we are nevertheless advising clients to be nimble, said Joel Bines, a managing director for AlixPartners. These are uncharted waters, and the best course to set is one that includes a strong cost control and flawless execution. As the economy muddles through the Q3 period, which will come to an end this month, we also anniversary the annual recession call from the infamous pseudo-economist David Rosenberg.
Answer: | noise | While our forecast is bullish, we are nevertheless advising clients to be nimble, said Joel Bines, a managing director for AlixPartners. These are uncharted waters, and the best course to set is one that includes a strong cost control and flawless execution. As the economy muddles through the Q3 period, which will come to an end this month, we also anniversary the annual recession call from the infamous pseudo-economist David Rosenberg. | [
"noise",
"causal"
] | 0 |
causal20sc7745 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: It was in June of 2018 that Rosenberg made his previous recession forecast.
Answer: | noise | It was in June of 2018 that Rosenberg made his previous recession forecast. | [
"noise",
"causal"
] | 0 |
causal20sc7746 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: While we can recognize the growth slowdown in 2019 and from tough comparisons, fueled by tax reform legislation and now refuted by a year-long trade war, Finom Group doesn't see the necessary components for an imminent recession.
Answer: | noise | While we can recognize the growth slowdown in 2019 and from tough comparisons, fueled by tax reform legislation and now refuted by a year-long trade war, Finom Group doesn't see the necessary components for an imminent recession. | [
"noise",
"causal"
] | 0 |
causal20sc7747 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Equity futures and crude oil are setting up for a negative open for trading on Wall Street Tuesday, but noted market bull Tony Dwyer of Canaccord Genuity suggests investors should get aggressive with their equity exposure near-term.
Answer: | noise | Equity futures and crude oil are setting up for a negative open for trading on Wall Street Tuesday, but noted market bull Tony Dwyer of Canaccord Genuity suggests investors should get aggressive with their equity exposure near-term. | [
"noise",
"causal"
] | 0 |
causal20sc7748 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: On CNBC's Fast Money, Monday evening, Dwyer laid out his case that history suggests a continuation of the market move higher into 2020. Sentiment got bearish enough with 10-year yield low enough 2011-2012: Fears of Greece to be knocked out of Euro and Euro to break up.
Answer: | noise | On CNBC's Fast Money, Monday evening, Dwyer laid out his case that history suggests a continuation of the market move higher into 2020. Sentiment got bearish enough with 10-year yield low enough 2011-2012: Fears of Greece to be knocked out of Euro and Euro to break up. | [
"noise",
"causal"
] | 0 |
causal20sc7749 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Stock market bottomed that year at -19.6%.
Answer: | noise | Stock market bottomed that year at -19.6%. | [
"noise",
"causal"
] | 0 |
causal20sc7750 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Then S&P 500 rallied 22% and from their the market rallied another 38% until the 10 year rallied to over 3%. 10-year likely made a low. Will likely go back to 2.5% over time.
Answer: | noise | Then S&P 500 rallied 22% and from their the market rallied another 38% until the 10 year rallied to over 3%. 10-year likely made a low. Will likely go back to 2.5% over time. | [
"noise",
"causal"
] | 0 |
causal20sc7751 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: We've had 3 mini recession fears already, driven by global industrial output.
Answer: | noise | We've had 3 mini recession fears already, driven by global industrial output. | [
"noise",
"causal"
] | 0 |
causal20sc7752 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: ECB disappointed in their action last week, but their commentary on inflation is what drove rates in the market. They got ahead of the curve not by cutting but by their commentary.
Answer: | noise | ECB disappointed in their action last week, but their commentary on inflation is what drove rates in the market. They got ahead of the curve not by cutting but by their commentary. | [
"noise",
"causal"
] | 0 |
causal20sc7753 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The Fed Funds Rate gets the S&P 500 to breakout, assuming it is not the highest level rate, which it is presently.
Answer: | noise | The Fed Funds Rate gets the S&P 500 to breakout, assuming it is not the highest level rate, which it is presently. | [
"noise",
"causal"
] | 0 |
causal20sc7754 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Dwyer believes investors should be playing offense by getting into the cyclicals, financials, tech and consumer discretionary.
Answer: | noise | Dwyer believes investors should be playing offense by getting into the cyclicals, financials, tech and consumer discretionary. | [
"noise",
"causal"
] | 0 |
causal20sc7755 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Again, the caveat is that the Fed has to get ahead of the curve by lowering rates or convincing the market to lift the long-end of the curve. Rounding out today's daily market dispatch, Finom Group offers this Public Service Announcement of sorts: Beware of social media pundits masquerading as economists, certified market technicians and strategists.
Answer: | noise | Again, the caveat is that the Fed has to get ahead of the curve by lowering rates or convincing the market to lift the long-end of the curve. Rounding out today's daily market dispatch, Finom Group offers this Public Service Announcement of sorts: Beware of social media pundits masquerading as economists, certified market technicians and strategists. | [
"noise",
"causal"
] | 0 |
causal20sc7756 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: With all the headlines surrounding the spike in crude oil and gas prices to come over the weekend, Twitter participants were out and about with false and misleading narratives.
Answer: | noise | With all the headlines surrounding the spike in crude oil and gas prices to come over the weekend, Twitter participants were out and about with false and misleading narratives. | [
"noise",
"causal"
] | 0 |
causal20sc7757 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Here is one example of such a false narrative: With over 11,700 followers, this twitter account thought it was necessary to frighten investors and market participants into believing there was some kind of run on the gas pumps, given the likely event of rising gas prices from the oil field bombings. A quick analytical dive into the photograph revealed the photo first appeared in a 2012 article here (link). This was also recently pointed out by Nick Cola's, co-founder of DataTrek Research, who says the spike in oil is likely unsustainable.
Answer: | noise | Here is one example of such a false narrative: With over 11,700 followers, this twitter account thought it was necessary to frighten investors and market participants into believing there was some kind of run on the gas pumps, given the likely event of rising gas prices from the oil field bombings. A quick analytical dive into the photograph revealed the photo first appeared in a 2012 article here (link). This was also recently pointed out by Nick Cola's, co-founder of DataTrek Research, who says the spike in oil is likely unsustainable. | [
"noise",
"causal"
] | 0 |
causal20sc7758 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Even the $80 level might not mean a pronounced broader downturn for the economy.
Answer: | noise | Even the $80 level might not mean a pronounced broader downturn for the economy. | [
"noise",
"causal"
] | 0 |
causal20sc7759 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Colas points out that of the recessions the U.S. has seen dating back to the early 1980s, none has come without an oil spike of at least 90%.
Answer: | noise | Colas points out that of the recessions the U.S. has seen dating back to the early 1980s, none has come without an oil spike of at least 90%. | [
"noise",
"causal"
] | 0 |
causal20sc7760 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The Great Recession, for instance, saw a 96% move, while the dot-com bust featured a 141% surge and 1990′s was preceded by a 96% jump.
Answer: | noise | The Great Recession, for instance, saw a 96% move, while the dot-com bust featured a 141% surge and 1990′s was preceded by a 96% jump. | [
"noise",
"causal"
] | 0 |
causal20sc7761 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Seth Golden
Answer: | noise | Seth Golden | [
"noise",
"causal"
] | 0 |
causal20sc7762 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Singapore AVIVA dangled S$15.3 million as a sign-on bonus to Prudential Assurance Company Singapore's then top agency manager Peter Tan Shou Yi in 2016, Prudential said.
Answer: | noise | Singapore AVIVA dangled S$15.3 million as a sign-on bonus to Prudential Assurance Company Singapore's then top agency manager Peter Tan Shou Yi in 2016, Prudential said. | [
"noise",
"causal"
] | 0 |
causal20sc7763 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: And Mr Tan's company, PTO Management and Consultancy (PTOMC), received S$24 million from Aviva's subsidiary, Aviva Financial Advisers (AFA), after he quit Prudential.
Answer: | noise | And Mr Tan's company, PTO Management and Consultancy (PTOMC), received S$24 million from Aviva's subsidiary, Aviva Financial Advisers (AFA), after he quit Prudential. | [
"noise",
"causal"
] | 0 |
causal20sc7764 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: This included the 54-year-old's sign-on bonus and recruitment bonuses for bringing in new agents, the High Court heard on Friday.
Answer: | noise | This included the 54-year-old's sign-on bonus and recruitment bonuses for bringing in new agents, the High Court heard on Friday. | [
"noise",
"causal"
] | 0 |
causal20sc7765 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: PTOMC is the company through which Mr Tan is providing services to AFA.
Answer: | noise | PTOMC is the company through which Mr Tan is providing services to AFA. | [
"noise",
"causal"
] | 0 |
causal20sc7766 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: sentifi.com Mr Tan and PTOMC are being sued by Prudential for allegedly soliciting 221 agents and 23 agency leaders under Mr Tan to defect en masse to AFA in mid-2016.
Answer: | noise | sentifi.com Mr Tan and PTOMC are being sued by Prudential for allegedly soliciting 221 agents and 23 agency leaders under Mr Tan to defect en masse to AFA in mid-2016. | [
"noise",
"causal"
] | 0 |
causal20sc7767 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Prudential alleges that Mr Tan breached his contractual and fiduciary duties when he carried out the poaching while still being with the insurer. The insurer, through lawyers from Rajah & Tann, is seeking up to S$2.5 billion in compensation from the two defendants.
Answer: | causal | Prudential alleges that Mr Tan breached his contractual and fiduciary duties when he carried out the poaching while still being with the insurer. The insurer, through lawyers from Rajah & Tann, is seeking up to S$2.5 billion in compensation from the two defendants. | [
"noise",
"causal"
] | 1 |
causal20sc7768 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Mr Tan, defended by Senior Counsel Thio Shen Yi, rejected any liability as he said he did not have any non-solicitation contractual obligation, is not a fiduciary of Prudential and did not engage in any alleged acts of solicitation.
Answer: | noise | Mr Tan, defended by Senior Counsel Thio Shen Yi, rejected any liability as he said he did not have any non-solicitation contractual obligation, is not a fiduciary of Prudential and did not engage in any alleged acts of solicitation. | [
"noise",
"causal"
] | 0 |
causal20sc7769 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: He denied the allegation on Friday under cross-examination by Prudential's lawyer Murali Pillai that his sign-on bonus of S$15.3 million was for him to bring 250 of his agents from Prudential to AFA.
Answer: | noise | He denied the allegation on Friday under cross-examination by Prudential's lawyer Murali Pillai that his sign-on bonus of S$15.3 million was for him to bring 250 of his agents from Prudential to AFA. | [
"noise",
"causal"
] | 0 |
causal20sc7770 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The remuneration was to make up for financial incentives that he had to forgo and 1.5 times of his lost income for leaving Prudential, said the defendant, who is legally trained.
Answer: | noise | The remuneration was to make up for financial incentives that he had to forgo and 1.5 times of his lost income for leaving Prudential, said the defendant, who is legally trained. | [
"noise",
"causal"
] | 0 |
causal20sc7771 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The court heard that originally, Mr Tan was to receive S$16 million in sign-on bonus, but this was reduced to S$13.8 million to exclude business allowances, before the quantum was finalised at S$15.3 million.
Answer: | noise | The court heard that originally, Mr Tan was to receive S$16 million in sign-on bonus, but this was reduced to S$13.8 million to exclude business allowances, before the quantum was finalised at S$15.3 million. | [
"noise",
"causal"
] | 0 |
causal20sc7772 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Clawback of the full amount would be effected if the agents did not meet 70 per cent of business targets in the first draft of the agreement in May 2016. This condition was changed to meeting 85 per cent of business targets for two consecutive years in the second draft agreement dated June 27, 2016. However, the second draft also included a provision for no clawback if Mr Tan agreed to be bound by a restraint clause prohibiting him from continuing to participate in the financial services sector.
Answer: | noise | Clawback of the full amount would be effected if the agents did not meet 70 per cent of business targets in the first draft of the agreement in May 2016. This condition was changed to meeting 85 per cent of business targets for two consecutive years in the second draft agreement dated June 27, 2016. However, the second draft also included a provision for no clawback if Mr Tan agreed to be bound by a restraint clause prohibiting him from continuing to participate in the financial services sector. | [
"noise",
"causal"
] | 0 |
causal20sc7773 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Prudential's Mr Pillai argued that the condition was changed because Mr Tan had - by June 27, 2016 - secured over 200 agents to go over to AFA. Mr Tan disagreed. When the hearing commenced in July, the court heard that Aviva had prepared a war chest of S$100 million to S$150 million to poach the agents.
Answer: | noise | Prudential's Mr Pillai argued that the condition was changed because Mr Tan had - by June 27, 2016 - secured over 200 agents to go over to AFA. Mr Tan disagreed. When the hearing commenced in July, the court heard that Aviva had prepared a war chest of S$100 million to S$150 million to poach the agents. | [
"noise",
"causal"
] | 0 |
causal20sc7774 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Mr Tan has completed his testimony. The trial continues on Sept 24.
Answer: | noise | Mr Tan has completed his testimony. The trial continues on Sept 24. | [
"noise",
"causal"
] | 0 |
causal20sc7775 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Tay Peck Gek
Answer: | noise | Tay Peck Gek | [
"noise",
"causal"
] | 0 |
causal20sc7776 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Search ISAs are tax-exempt savings accounts available to individuals. At Knox & Eames, we advise individuals on tax efficient investments in the Henley-on-Thames, Oxfordshire area.
Answer: | noise | Search ISAs are tax-exempt savings accounts available to individuals. At Knox & Eames, we advise individuals on tax efficient investments in the Henley-on-Thames, Oxfordshire area. | [
"noise",
"causal"
] | 0 |
causal20sc7777 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Some information about ISAs is given below.
Answer: | noise | Some information about ISAs is given below. | [
"noise",
"causal"
] | 0 |
causal20sc7778 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Successive governments, concerned at the relatively low level of savings in the UK economy have over the years introduced various means by which individuals can save through a tax-free environment. What is an ISA? ISAs are tax-exempt savings accounts available to individuals aged 18 or over who are resident and ordinarily resident in the UK.
Answer: | noise | Successive governments, concerned at the relatively low level of savings in the UK economy have over the years introduced various means by which individuals can save through a tax-free environment. What is an ISA? ISAs are tax-exempt savings accounts available to individuals aged 18 or over who are resident and ordinarily resident in the UK. | [
"noise",
"causal"
] | 0 |
causal20sc7779 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: ISAs are only available to individual investors and cannot be held jointly. ISAs are guaranteed to run for ten years although there is no minimum period for which the accounts must be held.
Answer: | noise | ISAs are only available to individual investors and cannot be held jointly. ISAs are guaranteed to run for ten years although there is no minimum period for which the accounts must be held. | [
"noise",
"causal"
] | 0 |
causal20sc7780 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Investment limits Investment choices Investors are allowed to invest in a cash ISA, an investment ISA, an Innovative Finance ISA, or a combination of the three subject to not exceeding the overall annual investment limit. Investors are able to transfer their investments from a stocks and shares ISA to a cash ISA (or vice versa).
Answer: | noise | Investment limits Investment choices Investors are allowed to invest in a cash ISA, an investment ISA, an Innovative Finance ISA, or a combination of the three subject to not exceeding the overall annual investment limit. Investors are able to transfer their investments from a stocks and shares ISA to a cash ISA (or vice versa). | [
"noise",
"causal"
] | 0 |
causal20sc7781 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: ISAs are allowed to invest in cash (including bank and building society accounts and designated National Savings), stocks and shares (including unit and investment trusts and government securities with at least five years to run) and life assurance.
Answer: | noise | ISAs are allowed to invest in cash (including bank and building society accounts and designated National Savings), stocks and shares (including unit and investment trusts and government securities with at least five years to run) and life assurance. | [
"noise",
"causal"
] | 0 |
causal20sc7782 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: A wide range of securities including certain retail bonds with less than five years before maturity, Core Capital Deferred Shares issued by building societies, listed bonds issued by Co-operative Societies and Community Benefit Societies and SME securities that are admitted to trading on a recognised stock exchange are eligible to be held in an ISA, Junior ISA or Child Trust Fund (CTF).
Answer: | noise | A wide range of securities including certain retail bonds with less than five years before maturity, Core Capital Deferred Shares issued by building societies, listed bonds issued by Co-operative Societies and Community Benefit Societies and SME securities that are admitted to trading on a recognised stock exchange are eligible to be held in an ISA, Junior ISA or Child Trust Fund (CTF). | [
"noise",
"causal"
] | 0 |
causal20sc7783 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The Innovative Finance ISA can be used for loans arranged via a peer-to-peer (P2P) platform. Peer-to-peer lending is a small but rapidly growing alternative source of finance for individuals and businesses.
Answer: | noise | The Innovative Finance ISA can be used for loans arranged via a peer-to-peer (P2P) platform. Peer-to-peer lending is a small but rapidly growing alternative source of finance for individuals and businesses. | [
"noise",
"causal"
] | 0 |
causal20sc7784 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The Innovative Finance ISA may also invest in debt securities offered via crowdfunding platforms.
Answer: | noise | The Innovative Finance ISA may also invest in debt securities offered via crowdfunding platforms. | [
"noise",
"causal"
] | 0 |
causal20sc7785 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Withdraw and replace monies ISA savers may be able to withdraw and replace money from their cash ISA without it counting towards their annual ISA subscription limit for that year where they hold a 'Flexible ISA'.
Answer: | noise | Withdraw and replace monies ISA savers may be able to withdraw and replace money from their cash ISA without it counting towards their annual ISA subscription limit for that year where they hold a 'Flexible ISA'. | [
"noise",
"causal"
] | 0 |
causal20sc7786 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Additional ISA allowance for spouses on death An additional ISA allowance is available for spouses or civil partners when an ISA saver dies.
Answer: | noise | Additional ISA allowance for spouses on death An additional ISA allowance is available for spouses or civil partners when an ISA saver dies. | [
"noise",
"causal"
] | 0 |
causal20sc7787 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The additional ISA allowance is equal to the value of a deceased person's accounts at the time of their death and is in addition to the normal ISA subscription limit.
Answer: | noise | The additional ISA allowance is equal to the value of a deceased person's accounts at the time of their death and is in addition to the normal ISA subscription limit. | [
"noise",
"causal"
] | 0 |
causal20sc7788 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: There are time limits within which the additional allowance has to be used.
Answer: | noise | There are time limits within which the additional allowance has to be used. | [
"noise",
"causal"
] | 0 |
causal20sc7789 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: In certain circumstances an individual can transfer to their own ISA non-cash assets such as stocks and shares previously held by their spouse. In most cases, it is envisaged that the additional allowance will be used to subscribe to an ISA offered by the same financial institution that provided the deceased person's ISA.
Answer: | noise | In certain circumstances an individual can transfer to their own ISA non-cash assets such as stocks and shares previously held by their spouse. In most cases, it is envisaged that the additional allowance will be used to subscribe to an ISA offered by the same financial institution that provided the deceased person's ISA. | [
"noise",
"causal"
] | 0 |
causal20sc7790 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: As the rules allow the transfer of stocks and shares directly into the new ISA, in many cases the effect will be that the investments are left intact and the spouse becomes the new owner of the deceased person's ISA.
Answer: | noise | As the rules allow the transfer of stocks and shares directly into the new ISA, in many cases the effect will be that the investments are left intact and the spouse becomes the new owner of the deceased person's ISA. | [
"noise",
"causal"
] | 0 |
causal20sc7791 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The tax advantaged treatment of ISAs continues whilst an individual's estate is in administration. Tax advantages The income from ISA investments is exempt from income tax.
Answer: | noise | The tax advantaged treatment of ISAs continues whilst an individual's estate is in administration. Tax advantages The income from ISA investments is exempt from income tax. | [
"noise",
"causal"
] | 0 |
causal20sc7792 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Any capital gains made on investments held in an ISA are exempt from capital gains tax.
Answer: | noise | Any capital gains made on investments held in an ISA are exempt from capital gains tax. | [
"noise",
"causal"
] | 0 |
causal20sc7793 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Uses of an ISA Many people use an ISA in the first instance, to save for a rainy day. Since they were first introduced people have used them to save for retirement, to complement their pension plans or to save for future repayment of their mortgage to give just a few examples.
Answer: | noise | Uses of an ISA Many people use an ISA in the first instance, to save for a rainy day. Since they were first introduced people have used them to save for retirement, to complement their pension plans or to save for future repayment of their mortgage to give just a few examples. | [
"noise",
"causal"
] | 0 |
causal20sc7794 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: We have known young people, wary of commitment to long-term saving start an ISA and when more certain of the future use it as a lump sum to start another financial plan.
Answer: | noise | We have known young people, wary of commitment to long-term saving start an ISA and when more certain of the future use it as a lump sum to start another financial plan. | [
"noise",
"causal"
] | 0 |
causal20sc7795 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Help to Buy ISA The Help to Buy ISA, which provides a tax-free savings account for first time buyers wishing to save for a home. The scheme will provide a government bonus to each person who has saved into a Help to Buy ISA at the point they use their savings to purchase their first home. For every £200 a first time buyer saves, the government will provide a £50 bonus up to a maximum bonus of £3,000 on £12,000 of savings.
Answer: | causal | Help to Buy ISA The Help to Buy ISA, which provides a tax-free savings account for first time buyers wishing to save for a home. The scheme will provide a government bonus to each person who has saved into a Help to Buy ISA at the point they use their savings to purchase their first home. For every £200 a first time buyer saves, the government will provide a £50 bonus up to a maximum bonus of £3,000 on £12,000 of savings. | [
"noise",
"causal"
] | 1 |
causal20sc7796 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Help to Buy ISAs are subject to eligibility rules and limits: An individual is only eligible for one account throughout the lifetime of the scheme and it is only available to first time buyers.
Answer: | noise | Help to Buy ISAs are subject to eligibility rules and limits: An individual is only eligible for one account throughout the lifetime of the scheme and it is only available to first time buyers. | [
"noise",
"causal"
] | 0 |
causal20sc7797 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Interest received on the account will be tax-free.
Answer: | noise | Interest received on the account will be tax-free. | [
"noise",
"causal"
] | 0 |
causal20sc7798 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Savings are limited to a monthly maximum of £200 with an opportunity to deposit an additional £1,000 when the account is first opened.
Answer: | causal | Savings are limited to a monthly maximum of £200 with an opportunity to deposit an additional £1,000 when the account is first opened. | [
"noise",
"causal"
] | 1 |
causal20sc7799 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The government will provide a 25% bonus on the total amount saved including interest, capped at a maximum of £3,000 which is tax-free. The bonus will be paid when the first home is purchased. The bonus can only be put towards a first home located in the UK with a purchase value of £450,000 or less in London and £250,000 or less in the rest of the UK.
Answer: | causal | The government will provide a 25% bonus on the total amount saved including interest, capped at a maximum of £3,000 which is tax-free. The bonus will be paid when the first home is purchased. The bonus can only be put towards a first home located in the UK with a purchase value of £450,000 or less in London and £250,000 or less in the rest of the UK. | [
"noise",
"causal"
] | 1 |