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High Frequency Data
High frequency data refers to time-series data collected at an extremely fine scale. As a result of advanced computational power in recent decades, high frequency data can be accurately collected at an efficient rate for analysis.Ruey S. Tsay (2000) Editor's Introduction to Panel Discussion on Analysis of High-Frequency Data, ''Journal of Business & Economic Statistics'', 18:2, 139-139, Largely used in financial analysis and in high frequency trading, high frequency data provides intraday observations that can be used to understand market behaviors, dynamics, and micro-structures.Andersen, T. G. (2000). Some reflections on analysis of high-frequency data. ''Journal of Business & Economic Statistics'', 18(2), 146-153. High frequency data collections were originally formulated by massing tick-by-tick market data, by which each single 'event' (transaction, quote, price movement, etc.) is characterized by a 'tick', or one logical unit of information. Due to the large amounts of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Time-series Data
In mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average. A time series is very frequently plotted via a run chart (which is a temporal line chart). Time series are used in statistics, signal processing, pattern recognition, econometrics, mathematical finance, weather forecasting, earthquake prediction, electroencephalography, control engineering, astronomy, communications engineering, and largely in any domain of applied science and engineering which involves temporal measurements. Time series ''analysis'' comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series ''forecasting ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Equi-distant
A point is said to be equidistant from a set of objects if the distances between that point and each object in the set are equal. In two-dimensional Euclidean geometry, the locus of points equidistant from two given (different) points is their perpendicular bisector. In three dimensions, the locus of points equidistant from two given points is a plane, and generalising further, in n-dimensional space the locus of points equidistant from two points in ''n''-space is an (''n''−1)-space. For a triangle the circumcentre is a point equidistant from each of the three vertices. Every non-degenerate triangle has such a point. This result can be generalised to cyclic polygons: the circumcentre is equidistant from each of the vertices. Likewise, the incentre of a triangle or any other tangential polygon is equidistant from the points of tangency of the polygon's sides with the circle. Every point on a perpendicular bisector of the side of a triangle or other polygon is equidist ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bias Of An Estimator
In statistics, the bias of an estimator (or bias function) is the difference between this estimator's expected value and the true value of the parameter being estimated. An estimator or decision rule with zero bias is called ''unbiased''. In statistics, "bias" is an property of an estimator. Bias is a distinct concept from consistency: consistent estimators converge in probability to the true value of the parameter, but may be biased or unbiased; see bias versus consistency for more. All else being equal, an unbiased estimator is preferable to a biased estimator, although in practice, biased estimators (with generally small bias) are frequently used. When a biased estimator is used, bounds of the bias are calculated. A biased estimator may be used for various reasons: because an unbiased estimator does not exist without further assumptions about a population; because an estimator is difficult to compute (as in unbiased estimation of standard deviation); because a biased esti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Autoregressive Model
In statistics, econometrics and signal processing, an autoregressive (AR) model is a representation of a type of random process; as such, it is used to describe certain time-varying processes in nature, economics, etc. The autoregressive model specifies that the output variable depends linearly on its own previous values and on a stochastic term (an imperfectly predictable term); thus the model is in the form of a stochastic difference equation (or recurrence relation which should not be confused with differential equation). Together with the moving-average (MA) model, it is a special case and key component of the more general autoregressive–moving-average (ARMA) and autoregressive integrated moving average (ARIMA) models of time series, which have a more complicated stochastic structure; it is also a special case of the vector autoregressive model (VAR), which consists of a system of more than one interlocking stochastic difference equation in more than one evolving random vari ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mean Reversion (finance)
Mean reversion is a financial term for the assumption that an asset's price will tend to converge to the average price over time. Using mean reversion as a timing strategy involves both the identification of the trading range for a security and the computation of the average price using quantitative methods. Mean reversion is a phenomenon that can be exhibited in a host of financial time-series data, from price data, earnings data, and book value. When the current market price is less than the average past price, the security is considered attractive for purchase, with the expectation that the price will rise. When the current market price is above the average past price, the market price is expected to fall. In other words, deviations from the average price are expected to revert to the average. This knowledge serves as the cornerstone of multiple trading strategies. Stock reporting services commonly offer moving averages for periods such as 50 and 100 days. While reporting ser ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Half-life
Half-life (symbol ) is the time required for a quantity (of substance) to reduce to half of its initial value. The term is commonly used in nuclear physics to describe how quickly unstable atoms undergo radioactive decay or how long stable atoms survive. The term is also used more generally to characterize any type of exponential (or, rarely, non-exponential) decay. For example, the medical sciences refer to the biological half-life of drugs and other chemicals in the human body. The converse of half-life (in exponential growth) is doubling time. The original term, ''half-life period'', dating to Ernest Rutherford's discovery of the principle in 1907, was shortened to ''half-life'' in the early 1950s. Rutherford applied the principle of a radioactive element's half-life in studies of age determination of rocks by measuring the decay period of radium to lead-206. Half-life is constant over the lifetime of an exponentially decaying quantity, and it is a characteristic u ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Climate Change
In common usage, climate change describes global warming—the ongoing increase in global average temperature—and its effects on Earth's climate system. Climate change in a broader sense also includes previous long-term changes to Earth's climate. The current rise in global average temperature is more rapid than previous changes, and is primarily caused by humans burning fossil fuels. Fossil fuel use, deforestation, and some agricultural and industrial practices increase greenhouse gases, notably carbon dioxide and methane. Greenhouse gases absorb some of the heat that the Earth radiates after it warms from sunlight. Larger amounts of these gases trap more heat in Earth's lower atmosphere, causing global warming. Due to climate change, deserts are expanding, while heat waves and wildfires are becoming more common. Increased warming in the Arctic has contributed to melting permafrost, glacial retreat and sea ice loss. Higher temperatures are also causin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Meteorology
Meteorology is a branch of the atmospheric sciences (which include atmospheric chemistry and physics) with a major focus on weather forecasting. The study of meteorology dates back millennia, though significant progress in meteorology did not begin until the 18th century. The 19th century saw modest progress in the field after weather observation networks were formed across broad regions. Prior attempts at prediction of weather depended on historical data. It was not until after the elucidation of the laws of physics, and more particularly in the latter half of the 20th century the development of the computer (allowing for the automated solution of a great many modelling equations) that significant breakthroughs in weather forecasting were achieved. An important branch of weather forecasting is marine weather forecasting as it relates to maritime and coastal safety, in which weather effects also include atmospheric interactions with large bodies of water. Meteorological ph ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Typographical Error
A typographical error (often shortened to typo), also called a misprint, is a mistake (such as a spelling mistake) made in the typing of printed (or electronic) material. Historically, this referred to mistakes in manual type-setting (typography). Technically, the term includes ''errors due to mechanical failure'' or slips of the hand or finger, but excludes ''errors of ignorance'', such as spelling errors, or changing and misuse of words such as "than" and "then". Before the arrival of printing, the "copyist's mistake" or "scribal error" was the equivalent for manuscripts. Most typos involve simple duplication, omission, transposition, or substitution of a small number of characters. "Fat Finger", or "Fat-Finger Syndrome" ( also used in financial sectors), a slang term, refers to an unwanted secondary action when typing. When one's finger is bigger than the touch zone, there can be inaccuracy in the fine motor movements and accidents may occur. This is common with touchscreens. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Human Error
Human error refers to something having been done that was "unintended consequences, not intended by the actor; not desired by a set of rules or an external observer; or that led the task or system outside its acceptable limits".Senders, J.W. and Moray, N.P. (1991) Human Error: Cause, Prediction, and Reduction'. Lawrence Erlbaum Associates, p.25. . Human error has been cited as a primary cause contributing factor in disasters and accidents in industries as diverse as nuclear power (e.g., the Three Mile Island accident), aviation (see pilot error), space exploration (e.g., the Space Shuttle Challenger disaster and Space Shuttle Columbia disaster), and medicine (see medical error). Prevention of human error is generally seen as a major contributor to Data integrity, reliability and safety of (complex) systems. Human error is one of the many contributing causes of risk events. Definition Human error refers to something having been done that was "not intended by the actor; not desired b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Cleansing
Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data. Data cleansing may be performed interactively with data wrangling tools, or as batch processing through scripting or a data quality firewall. After cleansing, a data set should be consistent with other similar data sets in the system. The inconsistencies detected or removed may have been originally caused by user entry errors, by corruption in transmission or storage, or by different data dictionary definitions of similar entities in different stores. Data cleaning differs from data validation in that validation almost invariably means data is rejected from the system at entry and is performed at the time of entry, rather than on batches of data. The actual pro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
