Correspondingly, high frequency trading (HFT) generally refers to a strategy which holds assets intraday. Low frequency trading (LFT) generally refers to any strategy which holds assets longer than a trading day. A momentum strategy attempts to exploit both investor psychology and big fund structure by "hitching a ride" on a market trend, which can gather momentum in one direction, and follow the trend until it reverses.Īnother hugely important aspect of quantitative trading is the frequency of the trading strategy. A mean-reverting strategy is one that attempts to exploit the fact that a long-term mean on a "price series" (such as the spread between two correlated assets) exists and that short term deviations from this mean will eventually revert. Many of the strategies you will look at will fall into the categories of mean-reversion and trend-following/momentum. arXiv Quantitative Finance - /archive/q-fin.Here is a small list of places to begin looking for strategy ideas: In fact, one of the best ways to create your own unique strategies is to find similar methods and then carry out your own optimisation procedure. These optimisations are the key to turning a relatively mediocre strategy into a highly profitable one. The reason lies in the fact that they will not often discuss the exact parameters and tuning methods that they have carried out. You might question why individuals and firms are keen to discuss their profitable strategies, especially when they know that others "crowding the trade" may stop the strategy from working in the long term. Trade journals will outline some of the strategies employed by funds. Quantitative finance blogs will discuss strategies in detail. Academics regularly publish theoretical trading results (albeit mostly gross of transaction costs). You will need to factor in your own capital requirements if running the strategy as a "retail" trader and how any transaction costs will affect the strategy.Ĭontrary to popular belief it is actually quite straightforward to find profitable strategies through various public sources. This research process encompasses finding a strategy, seeing whether the strategy fits into a portfolio of other strategies you may be running, obtaining any data necessary to test the strategy and trying to optimise the strategy for higher returns and/or lower risk. Strategy IdentificationĪll quantitative trading processes begin with an initial period of research. Quant trading how to#We'll begin by taking a look at how to identify a trading strategy. Risk Management - Optimal capital allocation, "bet size"/Kelly criterion and trading psychology.Execution System - Linking to a brokerage, automating the trading and minimising transaction costs.Strategy Backtesting - Obtaining data, analysing strategy performance and removing biases.Strategy Identification - Finding a strategy, exploiting an edge and deciding on trading frequency.Thus being familiar with C/C++ will be of paramount importance.Ī quantitative trading system consists of four major components: However as the trading frequency of the strategy increases, the technological aspects become much more relevant. Not only that but it requires extensive programming expertise, at the very least in a language such as MATLAB, R or Python. It can take a significant amount of time to gain the necessary knowledge to pass an interview or construct your own trading strategies. Quantitative trading is an extremely sophisticated area of quant finance. The second will be individuals who wish to try and set up their own "retail" algorithmic trading business. The first will be individuals trying to obtain a job at a fund as a quantitative trader. This post will hopefully serve two audiences. In this article I'm going to introduce you to some of the basic concepts which accompany an end-to-end quantitative trading system.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |