Which fintech application is most likely to be used for executing large orders by dividing them across exchanges?
Explanation
Algorithms can optimize execution to minimize market impact.
Other questions
Which of the following best defines 'Fintech'?
Data generated by business processes such as bank records and retail scanner data is best described as which type of alternative data?
Which of the following characteristics of Big Data refers to the speed at which data is communicated?
If a dataset has a size of 5,000 terabytes, this is equivalent to:
Real-time stock market price feeds are characterized as having:
Which of the following is considered an unstructured form of data?
In the context of data science processing methods, 'Curation' refers to:
Which visualization technique is most appropriate for illustrating the frequency that specific words appear in a text sample?
Computer systems that are programmed to simulate human cognition are best described as:
In Machine Learning, what is the primary function of the training dataset?
Which type of machine learning involves input and output data that are labelled?
A machine learning model that treats noise as true parameters and identifies spurious patterns is said to exhibit:
The analysis of unstructured data in text or voice forms, such as evaluating regulatory filings, is best described as:
Which fintech application uses computers to interpret human language, specifically for tasks like speech recognition and language translation?
Which trading strategy specifically identifies and takes advantage of intraday securities mispricings using computers?
Robo-advisory services typically offer portfolios with which of the following characteristics?
What is the primary advantage of robo-advisors for customers?
A potential disadvantage of robo-advisors during crisis periods is:
In a distributed ledger, what mechanism is required to validate new entries?
Which element links blocks sequentially in a blockchain?
Computers on a blockchain network that solve cryptographic problems to validate transactions are called:
Which type of distributed ledger network allows all participants to view all transactions and has no central authority?
In a permissioned network, which of the following is most likely true?
Which of the following describes an Initial Coin Offering (ICO)?
What is a potential benefit of using distributed ledger technology for post-trade clearing and settlement?
Electronic contracts programmed to self-execute based on agreed terms are known as:
Tokenization refers to:
Underfitting in a machine learning model means the model:
Which of the following is a challenge associated with machine learning results being a 'black box'?
Deep learning is a technique that typically uses:
The 'Internet of Things' refers to:
A firm has accumulated 2,000 terabytes of data. This amount is equivalent to:
Data that are communicated periodically or with a lag are said to have:
In the context of machine learning, 'unsupervised learning' means:
Using ML to evaluate large volumes of research reports to detect subtle changes in sentiment is an example of:
Cryptocurrencies typically reside on which type of network?
A potential benefit of giving regulators permission to view a distributed ledger is:
Mining on a blockchain requires vast resources of computing power and electricity primarily to:
Robo-advisory services are most likely to appeal to which type of investor?
Which data processing method involves assuring data quality by adjusting for bad or missing data?
Which of the following is considered a 'traditional' source of data?
An algorithm given inputs of source data with no assumptions about their probability distributions is characteristic of:
Which of the following describes the relationship between 'volume' and 'variety' in Big Data?
Which dataset is used to refine relationship models in machine learning?
What is a significant drawback of Distributed Ledger Technology regarding trade cancellations?
Investors in Initial Coin Offerings (ICOs) should be aware that:
Which of the following is a risk analysis technique that can be enhanced by Big Data and Machine Learning?
A key challenge in using Big Data is:
Which technology could potentially replace paper real estate deeds at government offices?