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Index Arbitrage
Index arbitrage is a subset of statistical arbitrage focusing on index components. An index (such as S&P 500) is made up of several components (in the case of the S&P 500, 500 large US stocks picked by S&P to represent the US market), and the value of the index is typically computed as a linear function of the component prices, where the details of the computation (such as the weights of the linear function) are determined in accordance with the index methodology. The idea of index arbitrage is to exploit discrepancies between the market price of a product that tracks the index (such as a Stock market index future or Exchange-traded fund) and the market prices of the underlying index components, which are typically stocks. For example, an arbitrageur could take the current prices of traded stocks, calculate a synthetic index value using the relevant index methodology, and then apply an interest rate and dividend adjustment to calculate the "fair value" of the stock market index f ...
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Statistical Arbitrage
In finance, statistical arbitrage (often abbreviated as ''Stat Arb'' or ''StatArb'') is a class of short-term financial trading strategies that employ mean reversion models involving broadly diversified portfolios of securities (hundreds to thousands) held for short periods of time (generally seconds to days). These strategies are supported by substantial mathematical, computational, and trading platforms. Trading strategy Broadly speaking, StatArb is actually any strategy that is bottom-up, beta-neutral in approach and uses statistical/econometric techniques in order to provide signals for execution. Signals are often generated through a contrarian mean reversion principle but can also be designed using such factors as lead/lag effects, corporate activity, short-term momentum, etc. This is usually referred to as a multi-factor approach to StatArb. Because of the large number of stocks involved, the high portfolio turnover and the fairly small size of the effects one is trying to ...
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S&P 500
The Standard and Poor's 500, or simply the S&P 500, is a stock market index tracking the stock performance of 500 large companies listed on stock exchanges in the United States. It is one of the most commonly followed equity indices. As of December 31, 2020, more than $5.4 trillion was invested in assets tied to the performance of the index. The S&P 500 index is a free-float weighted/capitalization-weighted index. As of August 31, 2022, the nine largest companies on the list of S&P 500 companies accounted for 27.8% of the market capitalization of the index and were, in order of highest to lowest weighting: Apple, Microsoft, Alphabet (including both class A & C shares), Amazon.com, Tesla, Berkshire Hathaway, UnitedHealth Group, Johnson & Johnson and ExxonMobil. The components that have increased their dividends in 25 consecutive years are known as the S&P 500 Dividend Aristocrats. The index is one of the factors in computation of the Conference Board Leading Economic Index ...
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Stock Market Index Future
In finance, a stock market index future is a cash-settled futures contract on the value of a particular stock market index. The turnover for the global market in exchange-traded equity index futures is notionally valued, for 2008, by the Bank for International Settlements at US$130 trillion. Uses Stock index futures are used for hedging, trading, and investments. Index futures are also used as leading indicators to determine market sentiment. Hedging using stock index futures could involve hedging against a portfolio of shares or equity index options. Trading using stock index futures could involve, for instance, volatility trading (The greater the volatility, the greater the likelihood of profit taking – usually taking relatively small but regular profits). Investing via the use of stock index futures could involve exposure to a market or sector without having to actually purchase shares directly. There are cases of equity hedging with index futures. One case is where a portf ...
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Exchange-traded Fund
An exchange-traded fund (ETF) is a type of investment fund and exchange-traded product, i.e. they are traded on stock exchanges. ETFs are similar in many ways to mutual funds, except that ETFs are bought and sold from other owners throughout the day on stock exchanges whereas mutual funds are bought and sold from the issuer based on their price at day's end. An ETF holds assets such as stocks, bonds, currencies, futures contracts, and/or commodities such as gold bars, and generally operates with an arbitrage mechanism designed to keep it trading close to its net asset value, although deviations can occasionally occur. Most ETFs are index funds: that is, they hold the same securities in the same proportions as a certain stock market index or bond market index. The most popular ETFs in the U.S. replicate the S&P 500, the total market index, the NASDAQ-100 index, the price of gold, the "growth" stocks in the Russell 1000 Index, or the index of the largest technology companies. ...
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Basis Risk
Basis risk in finance is the risk associated with imperfect hedging due to the variables or characteristics that affect the difference between the futures contract and the underlying "cash" position. It arises because of the difference between the price of the asset to be hedged and the price of the asset serving as the hedge before expiration, namely b = S - F. Barring idiosyncratic influence by the other aspects to be enumerated just below, by the time of expiration this simple difference will be eliminated by arbitrage. The other aspects that give rise to basis risk include a) Quality - arising when the hedge in place has a different grade which is not perfectly correlated with the basis; b) Timing - arising due to mismatch between the expiration date of the hedge asset and the actual selling date of the underlying asset; c) Location/Transportation Costs - arising due to the difference in the location of the asset being hedged and the asset serving as the hedge, and which typ ...
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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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Complex Event Processing
Event processing is a method of tracking and analyzing (processing) streams of information (data) about things that happen (events), and deriving a conclusion from them. Complex event processing, or CEP, consists of a set of concepts and techniques developed in the early 1990s for processing real-time events and extracting information from event streams as they arrive. The goal of complex event processing is to identify meaningful events (such as opportunities or threats) in real-time situations and respond to them as quickly as possible. These events may be happening across the various layers of an organization as sales leads, orders or customer service calls. Or, they may be news items, text messages, social media posts, stock market feeds, traffic reports, weather reports, or other kinds of data. An event may also be defined as a "change of state," when a measurement exceeds a predefined threshold of time, temperature, or other value. Analysts have suggested that CEP will give ...
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Dark Pool
In finance, a dark pool (also black pool) is a private forum (alternative trading system or ATS) for trading securities, derivatives, and other financial instruments."The New Financial Industry"
(March 30, 2014). 65 ''Alabama Law Review'' 567 (2014); Temple University Legal Studies Research Paper No. 2014-11; via SSRN.
Liquidity on these markets is called dark pool liquidity. The bulk of dark pool trades represent large trades by s that are offered away from public ex ...
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Electronic Trading
In finance, an electronic trading platform also known as an online trading platform, is a computer software program that can be used to place orders for financial products over a network with a financial intermediary. Various financial products can be traded by the trading platform, over a communication network with a financial intermediary or directly between the participants or members of the trading platform. This includes products such as stocks, bonds, currencies, commodities, derivatives and others, with a financial intermediary, such as brokers, market makers, Investment banks or stock exchanges. Such platforms allow electronic trading to be carried out by users from any location and are in contrast to traditional floor trading using open outcry and telephone based trading. Sometimes the term trading platform is also used in reference to the trading software alone. Electronic trading platforms typically stream live market prices on which users can trade and may prov ...
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Implementation Shortfall
In financial markets, implementation shortfall is the difference between the decision price and the final execution price (including commissions, taxes, etc.) for a trade. This is also known as the " slippage". Agency trading is largely concerned with minimizing implementation shortfall and finding liquidity. Decision price The decision price is the price of the stock that prompted the decision to buy or sell. The most common decision price is the close price or the arrival price. If we split the decision to buy a stock from the actual trading of the stock, as is often the case with fund managers (decision makers) and brokers (trade executors), you can see why both are used. From the fund manager's point of view, his decision to trade is often based on the closing price of the day's trading (along with the entire history of the stock and other signals/indicators). When he decides to buy a particular stock the next day, it is because he believes that the price will go up from tha ...
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Investment Strategy
In finance, an investment strategy is a set of rules, behaviors or procedures, designed to guide an investor's selection of an investment portfolio. Individuals have different profit objectives, and their individual skills make different tactics and strategies appropriate. Some choices involve a tradeoff between risk and return. Most investors fall somewhere in between, accepting some risk for the expectation of higher returns. Investors frequently pick investments to hedge themselves against inflation. During periods of high inflation investments such as shares tend to perform less well in real terms. Time horizon of investments. Investments such as shares should be invested into with the time frame of a minimum of 5 years in mind. It is recommended in finance a minimum of 6 months to 12 months expenses in a rainy-day current account, giving instant access before investing in riskier investments than an instant access account. It is also recommended no more than 90% of your money i ...
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Quantitative Trading
Mathematical finance, also known as quantitative finance and financial mathematics, is a field of applied mathematics, concerned with mathematical modeling of financial markets. In general, there exist two separate branches of finance that require advanced quantitative techniques: derivatives pricing on the one hand, and risk and portfolio management on the other. Mathematical finance overlaps heavily with the fields of computational finance and financial engineering. The latter focuses on applications and modeling, often by help of stochastic asset models, while the former focuses, in addition to analysis, on building tools of implementation for the models. Also related is quantitative investing, which relies on statistical and numerical models (and lately machine learning) as opposed to traditional fundamental analysis when managing portfolios. French mathematician Louis Bachelier's doctoral thesis, defended in 1900, is considered the first scholarly work on mathematical finan ...
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