|
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 expectation 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 s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Wilmott (magazine)
''Wilmott Magazine'' is a mathematical finance and risk management magazine, combining technical articles with humor pieces. Each copy of ''Wilmott'' is 11 inches square, runs about 100 pages, and is printed on glossy paper. The magazine has the highest subscription price of any magazine. ''Esquire''. 16 July 2007. Retrieved 4 March 2017. Content and contributors ''Wilmott'' has a section with technical articles on , but includes quantitative financial comic strips, and lighter articles. ''Wilmott'' magazine's regular contributors include[...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Random Walk
In mathematics, a random walk, sometimes known as a drunkard's walk, is a stochastic process that describes a path that consists of a succession of random steps on some Space (mathematics), mathematical space. An elementary example of a random walk is the random walk on the integer number line \mathbb Z which starts at 0, and at each step moves +1 or −1 with equal probability. Other examples include the path traced by a molecule as it travels in a liquid or a gas (see Brownian motion), the search path of a foraging animal, or the price of a fluctuating random walk hypothesis, stock and the financial status of a gambler. Random walks have applications to engineering and many scientific fields including ecology, psychology, computer science, physics, chemistry, biology, economics, and sociology. The term ''random walk'' was first introduced by Karl Pearson in 1905. Realizations of random walks can be obtained by Monte Carlo Simulation, Monte Carlo simulation. Lattice random ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Trend Following
Trend following or trend trading is a trading strategy according to which one should buy an asset when its price trend goes up, and sell when its trend goes down, expecting price movements to continue. There are a number of different techniques, calculations and time-frames that may be used to determine the general direction of the market to generate a trade signal, including the current market price calculation, moving averages and channel breakouts. Traders who employ this strategy do not aim to forecast or predict specific price levels; they simply jump on the trend and ride it. Due to the different techniques and time frames employed by trend followers to identify trends, trend followers as a group are not always strongly correlated to one another. Trend following is used by commodity trading advisors (CTAs) as the predominant strategy of technical traders. Research done by Galen Burghardt has shown that between 2000-2009 there was a very high correlation (.97) between tr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ornstein–Uhlenbeck Process
In mathematics, the Ornstein–Uhlenbeck process is a stochastic process with applications in financial mathematics and the physical sciences. Its original application in physics was as a model for the velocity of a massive Brownian particle under the influence of friction. It is named after Leonard Ornstein and George Eugene Uhlenbeck. The Ornstein–Uhlenbeck process is a stationary Gauss–Markov process, which means that it is a Gaussian process, a Markov process, and is temporally homogeneous. In fact, it is the only nontrivial process that satisfies these three conditions, up to allowing linear transformations of the space and time variables. Over time, the process tends to drift towards its mean function: such a process is called ''mean-reverting''. The process can be considered to be a modification of the random walk in continuous time, or Wiener process, in which the properties of the process have been changed so that there is a tendency of the walk to move back ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pairs Trade
A pairs trade or pair trading is a market neutral trading strategy enabling traders to profit from virtually any market conditions: uptrend, downtrend, or sideways movement. This strategy is categorized as a statistical arbitrage and convergence trading strategy. Pair trading was pioneered by Gerry Bamberger and later led by Nunzio Tartaglia's quantitative group at Morgan Stanley in the 1980s. The strategy monitors performance of two historically correlated securities. When the correlation between the two securities temporarily weakens, i.e. one stock moves up while the other moves down, the pairs trade would be to short the outperforming stock and to long the underperforming one, betting that the "spread" between the two would eventually converge. The divergence within a pair can be caused by temporary supply/demand changes, large buy/sell orders for one security, reaction for important news about one of the companies, and so on. Pairs trading strategy demands good position s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cointegration
In econometrics, cointegration is a statistical property describing a long-term, stable relationship between two or more time series variables, even if those variables themselves are individually non-stationary (i.e., they have trends). This means that despite their individual fluctuations, the variables move together in the long run, anchored by an underlying equilibrium relationship. More formally, if several time series are individually integrated of order ''d'' (meaning they require ''d'' differences to become stationary) but a linear combination of them is integrated of a lower order, then those time series are said to be cointegrated. That is, if (''X'',''Y'',''Z'') are each integrated of order ''d'', and there exist coefficients ''a'',''b'',''c'' such that is integrated of order less than d, then ''X'', ''Y'', and ''Z'' are cointegrated. Cointegration is a crucial concept in time series analysis, particularly when dealing with variables that exhibit trends, such as ma ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Convergence Trade
Convergence trade is a trading strategy consisting of two positions: buying one asset forward—i.e., for delivery in future (going ''long'' the asset)—and selling a similar asset forward (going '' short'' the asset) for a higher price, in the expectation that by the time the assets must be delivered, the prices will have become closer to equal (will have converged), and thus one profits by the amount of convergence. Convergence trades are often referred to as arbitrage, though in careful use arbitrage only refers to trading in ''the same'' or ''identical'' assets or cash flows, rather than in ''similar'' assets. Examples On the run/off the run On-the-run bonds (the most recently issued) generally trade at a premium over otherwise similar bonds, because they are more liquid—there is a liquidity premium. Once a newer bond is issued, this liquidity premium will generally decrease or disappear. For example, the 30-year US treasury bond generally trades at a premium relati ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Autocorrelation
Autocorrelation, sometimes known as serial correlation in the discrete time case, measures the correlation of a signal with a delayed copy of itself. Essentially, it quantifies the similarity between observations of a random variable at different points in time. The analysis of autocorrelation is a mathematical tool for identifying repeating patterns or hidden periodicities within a signal obscured by noise. Autocorrelation is widely used in signal processing, time domain and time series analysis to understand the behavior of data over time. Different fields of study define autocorrelation differently, and not all of these definitions are equivalent. In some fields, the term is used interchangeably with autocovariance. Various time series models incorporate autocorrelation, such as unit root processes, trend-stationary processes, autoregressive processes, and moving average processes. Autocorrelation of stochastic processes In statistics, the autocorrelation of a real ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Standard Deviation
In statistics, the standard deviation is a measure of the amount of variation of the values of a variable about its Expected value, mean. A low standard Deviation (statistics), deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range. The standard deviation is commonly used in the determination of what constitutes an outlier and what does not. Standard deviation may be abbreviated SD or std dev, and is most commonly represented in mathematical texts and equations by the lowercase Greek alphabet, Greek letter Sigma, σ (sigma), for the population standard deviation, or the Latin script, Latin letter ''s'', for the sample standard deviation. The standard deviation of a random variable, Sample (statistics), sample, statistical population, data set, or probability distribution is the square root of its variance. (For a finite population, v ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Review Of Quantitative Finance And Accounting
A review is an evaluation of a publication, product, service, or company or a critical take on current affairs in literature, politics or culture. In addition to a critical evaluation, the review's author may assign the work a rating to indicate its relative merit. Reviews can apply to a movie, video game, musical composition, book; a piece of hardware like a car, home appliance, or computer; or software such as business software, sales software; or an event or performance, such as a live music concert, play, musical theater show, dance show or art exhibition. Online review platforms also aim to provide a space where buyers can share authentic experiences—positive or negative—and businesses can use this feedback to improve their services. In the cultural sphere, ''The New York Review of Books'', for instance, is a collection of essays on literature, culture, and current affairs. In academia User review A user review refers to a review written by a user or consumer of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Time Series
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 ''f ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Jeremy Siegel
Jeremy James Siegel (born November 14, 1945) is an American economist who is the Russell E. Palmer Professor Emeritus of Finance at the Wharton School of the University of Pennsylvania. He appears regularly on networks including CNN, CNBC and NPR, and writes regular columns for Kiplinger's Personal Finance and Yahoo! Finance. Siegel's paradox is named after him. Early life and education Siegel was born into a Jewish family in Chicago, Illinois, and graduated from Highland Park High School. He majored in mathematics and economics as an undergraduate at Columbia University, graduating in 1967 with a Bachelor of Arts (B.A.), ''summa cum laude'', with membership in Phi Beta Kappa. He obtained a Ph.D. in economics from the Massachusetts Institute of Technology (MIT) in 1971. As a graduate student he studied under Nobel Prize winners Paul Samuelson and Robert Solow. Career Academics He taught at the University of Chicago for four years before moving to the Wharton School of th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
