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Alpha Generation Platform
An alpha generation platform is a technology used in algorithmic trading to develop quantitative financial models, or trading strategies, that generate consistent alpha, or absolute returns. The process of alpha generation refers to generating excess returns. Alpha generation platforms are tools used by hedge funds, banks, CTAs and other financial institutions to help develop and test quantitative trading strategies. Alpha generation platforms support quants in the creation of efficient and productive quantitative trading strategies. Traditionally, quants have used tools such as MATLAB, R, C++ and other computer programming languages to create complex trading strategies that help them perform high-frequency trading. However, as market data volumes increase and more traders create financial models that deal with multi-asset class data, news sentiment data and more, quants must spend a large amount of time programming models, debugging code, and integrating multiple market data sou ...
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Algorithmic Trading
Algorithmic trading is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. This type of trading attempts to leverage the speed and computational resources of computers relative to human traders. In the twenty-first century, algorithmic trading has been gaining traction with both retail and institutional traders. It is widely used by investment banks, pension funds, mutual funds, and hedge funds that may need to spread out the execution of a larger order or perform trades too fast for human traders to react to. A study in 2019 showed that around 92% of trading in the Forex market was performed by trading algorithms rather than humans. The term algorithmic trading is often used synonymously with automated trading system. These encompass a variety of trading strategies, some of which are based on formulas and results from mathematical finance, and often rely on specialized software. Examples o ...
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Alpha (finance)
Alpha is a measure of the active return on an investment, the performance of that investment compared with a suitable market index. An alpha of 1% means the investment's return on investment over a selected period of time was 1% better than the market during that same period; a negative alpha means the investment underperformed the market. Alpha, along with beta, is one of two key coefficients in the capital asset pricing model used in modern portfolio theory and is closely related to other important quantities such as standard deviation, R-squared and the Sharpe ratio. In modern financial markets, where index funds are widely available for purchase, alpha is commonly used to judge the performance of mutual funds and similar investments. As these funds include various fees normally expressed in percent terms, the fund has to maintain an alpha greater than its fees in order to provide positive gains compared with an index fund. Historically, the vast majority of traditional funds h ...
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Returns (economics)
Returns, in economics and political economy, are the distributions or payments awarded to the various suppliers of a good or service Wages Wages are the return to labor—the return to an individual's involvement (mental or physical) in the creation or realization of goods or services. Wages are realized by an individual supplier of labor even if the supplier is the self. A person gathering mushrooms in a national forest for the purpose of personal consumption is realizing wages in the form of mushrooms. A payer of wages is paying for a service performed by one or more individuals and sees wages as a cost. Rent In classical economics rent was the return to an "owner" of land. In later economic theory this term is expanded as economic rent to include other forms of unearned income typically realized from barriers to entry. Land ownership is considered to be a barrier to entry because land owners make no contribution to the production process. They simply prevent others from using t ...
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Quantitative Analysis (finance)
Quantitative analysis is the use of mathematical and statistical methods in finance and investment management. Those working in the field are quantitative analysts (quants). Quants tend to specialize in specific areas which may include derivative structuring or pricing, risk management, investment management and other related finance occupations. The occupation is similar to those in industrial mathematics in other industries. The process usually consists of searching vast databases for patterns, such as correlations among liquid assets or price-movement patterns (trend following or mean reversion). Although the original quantitative analysts were "sell side quants" from market maker firms, concerned with derivatives pricing and risk management, the meaning of the term has expanded over time to include those individuals involved in almost any application of mathematical finance, including the buy side. Applied quantitative analysis is commonly associated with quantitative investm ...
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MATLAB
MATLAB (an abbreviation of "MATrix LABoratory") is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks. MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages. Although MATLAB is intended primarily for numeric computing, an optional toolbox uses the MuPAD symbolic engine allowing access to symbolic computing abilities. An additional package, Simulink, adds graphical multi-domain simulation and model-based design for dynamic and embedded systems. As of 2020, MATLAB has more than 4 million users worldwide. They come from various backgrounds of engineering, science, and economics. History Origins MATLAB was invented by mathematician and computer programmer Cleve Moler. The idea for MATLAB was based on his 1960s PhD thesis. Moler became a math professor at the University of New Mexico and starte ...
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R (programming Language)
R is a programming language for statistical computing and graphics supported by the R Core Team and the R Foundation for Statistical Computing. Created by statisticians Ross Ihaka and Robert Gentleman, R is used among data miners, bioinformaticians and statisticians for data analysis and developing statistical software. Users have created packages to augment the functions of the R language. According to user surveys and studies of scholarly literature databases, R is one of the most commonly used programming languages used in data mining. R ranks 12th in the TIOBE index, a measure of programming language popularity, in which the language peaked in 8th place in August 2020. The official R software environment is an open-source free software environment within the GNU package, available under the GNU General Public License. It is written primarily in C, Fortran, and R itself (partially self-hosting). Precompiled executables are provided for various operating systems. R ...
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High-frequency Trading
High-frequency trading (HFT) is a type of algorithmic financial trading characterized by high speeds, high turnover rates, and high order-to-trade ratios that leverages high-frequency financial data and electronic trading tools. While there is no single definition of HFT, among its key attributes are highly sophisticated algorithms, co-location, and very short-term investment horizons. HFT can be viewed as a primary form of algorithmic trading in finance.Lin, Tom C. W. "The New Financial Industry" (March 30, 2014). 65 Alabama Law Review 567 (2014); Temple University Legal Studies Research Paper No. 2014-11; . Specifically, it is the use of sophisticated technological tools and computer algorithms to rapidly trade securities. HFT uses proprietary trading strategies carried out by computers to move in and out of positions in seconds or fractions of a second. In 2017, Aldridge and Krawciw estimated that in 2016 HFT on average initiated 10–40% of trading volume in equities, and 10†...
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News Analytics
In trading strategy, news analysis refers to the measurement of the various qualitative and quantitative attributes of textual (unstructured data) news stories. Some of these attributes are: sentiment, relevance, and novelty. Expressing news stories as numbers and metadata permits the manipulation of everyday information in a mathematical and statistical way. This data is often used in financial markets as part of a trading strategy or by businesses to judge market sentiment and make better business decisions. News analytics are usually derived through automated text analysis and applied to digital texts using elements from natural language processing and machine learning such as latent semantic analysis, support vector machines, "bag of words" among other techniques. Applications and strategies The application of sophisticated linguistic analysis to news and social media has grown from an area of research to mature product solutions since 2007. News analytics and news sentiment ...
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Capital Market
A capital market is a financial market in which long-term debt (over a year) or equity-backed securities are bought and sold, in contrast to a money market where short-term debt is bought and sold. Capital markets channel the wealth of savers to those who can put it to long-term productive use, such as companies or governments making long-term investments. Financial regulators like Securities and Exchange Board of India (SEBI), Bank of England (BoE) and the U.S. Securities and Exchange Commission (SEC) oversee capital markets to protect investors against fraud, among other duties. Transactions on capital markets are generally managed by entities within the financial sector or the treasury departments of governments and corporations, but some can be accessed directly by the public. As an example, in the United States, any American citizen with an internet connection can create an account with TreasuryDirect and use it to buy bonds in the primary market, though sales to individu ...
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Investment
Investment is the dedication of money to purchase of an asset to attain an increase in value over a period of time. Investment requires a sacrifice of some present asset, such as time, money, or effort. In finance, the purpose of investing is to generate a return from the invested asset. The return may consist of a gain (profit) or a loss realized from the sale of a property or an investment, unrealized capital appreciation (or depreciation), or investment income such as dividends, interest, or rental income, or a combination of capital gain and income. The return may also include currency gains or losses due to changes in the foreign currency exchange rates. Investors generally expect higher returns from riskier investments. When a low-risk investment is made, the return is also generally low. Similarly, high risk comes with a chance of high losses. Investors, particularly novices, are often advised to diversify their portfolio. Diversification has the statistical effec ...
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Collective Investment Scheme
An investment fund is a way of investing money alongside other investors in order to benefit from the inherent advantages of working as part of a group such as reducing the risks of the investment by a significant percentage. These advantages include an ability to: * hire professional investment managers, who may offer better returns and more adequate risk management; * benefit from economies of scale, i.e., lower transaction costs; * increase the asset diversification to reduce some unsystematic risk. It remains unclear whether professional active investment managers can reliably enhance risk adjusted returns by an amount that exceeds fees and expenses of investment management. Terminology varies with country but investment funds are often referred to as investment pools, collective investment vehicles, collective investment schemes, managed funds, or simply funds. The regulatory term is undertaking for collective investment in transferable securities, or short collective invest ...
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Andrew Lo
Andrew Wen-Chuan Lo () (born 1960) is the Charles E. and Susan T. Harris Professor of Finance at the MIT Sloan School of Management. Lo is the author of many academic articles in finance and financial economics. He founded AlphaSimplex Group in 1999 and served as chairman and chief investment strategist until 2018 when he transitioned to his current role as chairman emeritus and senior advisor. Career Lo is a professor of finance at the MIT Sloan School of Management, the director of MIT's Laboratory for Financial Engineering, a principal investigator at MIT's Computer Science and Artificial Intelligence Laboratory, an affiliated faculty of the MIT Department of Electrical Engineering and Computer Science, an external faculty member of the Santa Fe Institute, and a research associate of the National Bureau of Economic Research. He is the founder of AlphaSimplex Group,
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