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Quantitative Trading in India
Wednesday 20 March 2013
Introduction to Quantitative Trading
Algorithmic trading involves the use of electronic
platforms in order to enter trading orders with an algorithm that decides on
various aspects of the order like timing, price, and quantity of the order. In
many cases it also initiates the order without human intervention.
Pension funds, mutual funds, and other buy side (investor
driven) institutional traders make extensive use of algorithmic trading to
divide large trades into several smaller trades with an aim to manage market
impact, and risk. Sell side traders, like market makers and some hedge funds,
brings liquidity to the market, resulting in the automatic generation and
execution of orders.
"High-frequency trading" (HFT) is a special
class of algorithmic trading, where computers make detailed decisions with an
aim to initiate orders on the basis of information received electronically,
much faster than human traders can process the information they observe. As a
result, a dramatic change has occurred in the market microstructure, especially
in the context of how liquidity is provided.
Any investment strategy, like market making, inter-market
spreading, arbitrage, or pure speculation (including trend following) may use
algorithmic trading.
Some of the investment strategies that are followed in
today’s scenario are:
1.
Trend following
This investment strategy tries to take advantage of
long-term, medium-term, and short-term moves occurring in various markets.
Traders using this approach apply current market price calculation, moving
averages and channel breakouts for the purpose of determining the general
direction of the market and for generating trade signals.
2. Pair trading
This is a market neutral pairs trading and statistical arbitrage that enables
traders to profit from almost any market condition, whether it is uptrend,
downtrend, or sidewise movement.
3. Delta neutral strategies
This describes a related financial securities portfolio
where the value of the portfolio remains constant owing to small changes in the
value of the underlying security.
4. Arbitrage
Arbitrage is defined in different ways. An economist and
a finance person would define it as the practice of availing the benefit of a
price difference between two or more markets. This helps to strike a
combination of matching deals that can capitalize upon the imbalance. And the
resulting profit is the difference between the market prices. An academician
would define arbitrage as a transaction that at any probabilistic or temporal
state does not involve any negative cash flow but involves a positive cash flow
in at least one state. Simply said, it is the possibility of a risk-free profit
at zero cost.
5. Mean reversion
This is a mathematical methodology that is used for stock
investing. However, it can be applied to other processes as well. The idea
behind mean reversion is that both the high and low prices of a stock are
temporary and that the price of a stock price tends to have an average price
over time.
6. Scalping
This is another method of arbitraging small price gaps
that have been created by the bid-ask spread. Scalpers make an attempt to act
like traditional market makers or specialists. Making the spread implies buying
at the bid price and selling at the ask price, resulting in a gain on the
bid/ask difference.
7. Transaction cost reduction
Majority of strategies that are referred to as
algorithmic trading (as well as algorithmic liquidity seeking) fall into this
category. Here large orders are split up into several smaller orders, that are
entered into the market over time. This strategy is called
"iceberging".
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