Trading – Event-driven Trading: Everything you Need to Know

Enrich the conversation Stay focused and on track. Learn cryptocurrency trading What is bitcoin What is ethereum What are blockchain forks What are the risks? It may therefore take some time before it appears on our website. Since then has rallied From Wikipedia, the free encyclopedia. Forgot your user name or password?

An event driven strategy is an investment strategy that seeks to generate value by taking advantage of stock mispricing that results from corporate events.

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Typically, a third party point-and-click tool will severely limit freedom to test with custom signals and odd portfolios, while at the other end of the spectrum a custom-coded diy solution will require tens or more hours to implement with high chances of ending up with cluttered and unreadable code. Zipline is widely known and is the engine behind Quantopian PyAlgotrade seems to be actively developed and well-documented pybacktest is a light-weight vector-based framework with that might be interesting because of its simplicity and performance.

First one for the evaluation is Zipline. My first impression of Zipline and Quantopian is a positive one. Zipline is backed by a team of developers and is tested in production, so quality bugs should be great. There is good documentation on the site and an example notebook on github. To get a hang of it, I downloaded the exampe notebook and started playing with it.

To my disappointment I quickly run into trouble at the first example Simplest Zipline Algorithm: The dataset has only days, but running this example just took forever. Here is what I measured: This kind of performance would be prohibitive for any kind of scan or optimization. Another problem would arise when working with larger datasets like intraday data or multiple securities, which can easily contain hundreds of thousands of samples.

Unfortunately, I will have to drop Zipline from the list of useable backtesters as it does not meet my requirement 4 by a fat margin. In the following post I will be looking at PyAlgotrade.

On top of that, out-of-sample testing is on a 15 days period! Robert, I agree with your comments fully. The major problem with twitter prediction is the lack of a long, real trading track record. But I guess in a tulip mania, everything is possible. Do you know of any available applications that incorporate Twitter or other real-time search tools?

Anon, I am not aware of open-source news search applications, but as I mentioned in my post, Ravenpack, Sensobeat, Recorded Future are 3 of the vendors in this field. I trade news based strategies for a living, but take an entirely different approach. Rather than try to beat everyone to the punch I enter trades on the opening cross of the first session following the news report.

It's archaic from a quantitative standpoint, but it requires nothing more than Excel, a little VB programming and Yahoo Finance. It's also very reliable from an implementation standpoint, i.

PEAD is one such strategy. But the returns became too erratic, and perhaps the time horizon to exit became too short, for me to continue. Good to hear it is still working for you! Ernie, When were your entry points relative to the earnings announcement? I have found the day immediately following the announcement needs to be treated separately from subsequent time periods. What type of exit criteria did you use? Analyses I have run using tick data have shown that entering on open and exiting anytime after 3: PDA may also communicate with exchange computer system via a conventional wireless hub As used herein, a PDA includes mobile telephones and other wireless devices that communicate with a network via radio waves.

Computer device is shown connected directly to the Internet The connection may be via a modem, DSL line, satellite dish or any other device for connecting a computer device to the Internet.

One or more market makers may maintain a market by providing bid and offer prices for a derivative or security to exchange computer system Exchange computer system may also exchange information with other trade engines, such as trade engine One skilled in the art will appreciate that numerous additional computers and systems may be coupled to exchange computer system Such computers and systems may include clearing, regulatory and fee systems.

Coupling can be direct as described or any other method described herein. The operations of computer devices and systems shown in FIG. For example, computer device may include computer-executable instructions for receiving order information from a user and transmitting that order information to exchange computer system In another example, computer device may include computer-executable instructions for receiving market data from exchange computer system and displaying that information to a user.

Of course, numerous additional servers, computers, handheld devices, personal digital assistants, telephones and other devices may also be connected to exchange computer system Moreover, one skilled in the art will appreciate that the topology shown in FIG.

Price calculation module may include a memory module and a processor Price calculation module may be located at an exchange, such as at exchange computer system shown in FIG. Memory module may be implemented with one or more physical or magnetic memory devices, such as a disk drive, magnetic memory, optical disk or other device used to store computer-executable instructions. In one embodiment, memory module is implemented with a random access memory RAM of processor Memory module includes a model used to value event driven option contracts.

The model may be a Merton jump diffusion based model that includes assumptions Assumptions may include geometric motion of the price of an underlying financial instrument and a finite number of events, such as one event. An exemplary model is described in detail below. The total variance over time t, conditioned on discrete number n of jumps is a sum of diffusion variance and event driven jumps n variance. The Merton European call model is a pricing option value G with strike K as a sum of the Black-Scholes B-S option values g n weighted with probabilities w n of randomly timed jumps n generated in economic events m from a poisson distribution.

Underlying price and strikes must be positive to fit geometric process assumption. In accordance with an embodiment of the invention, the Merton jump diffusion model is extended to value or price event driven option contracts with jumps timed deterministically rather than randomly and underlying and strike prices limited to a positive range to fit geometric process assumption. We first reduce an underlying event driven Poisson process to a binomial one.

Reducing total variance to events driven variance only by setting diffusion variance to 0 in event driven auction markets. The Merton jump diffusion model is adapted with a Black-Scholes model with the number of jumps n serving as approximation for the time to expiration t. In accordance with an embodiment of the invention, the Merton jump diffusion model is modified with a Bachelier based arithmetic motion model. The Merton European call jump diffusion model assumes geometric underlying process and computes option value as a composite sum of Black-Scholes option prices g n with volatility based on both diffusion and event driven jumps.

The Bachelier model assumes arithmetic motion in the underlying instrument process driven by diffusion. The generic Merton jump diffusion model is modified to price scheduled event driven option contracts with deterministically timed jumps and a Bachelier based approach to underlying arithmetic motion. In presence of event driven jumps, underlying arithmetic motion approximation dS has both diffusion and jump components and can be described as.

Next, the geometric process in the Merton jump diffusion model is replaced with an arithmetic Bachelier based process. To model event based option contracts with jumps generated in underlying economic events, we reduce the Poisson process to a binomial process.

Because of the underlying motion arithmetic assumption, underlying price and strikes are not limited to a positive range and could be positive, zero or negative as in trade deficit or non-farm payroll statistics related contracts in auction markets.

Each Greek estimates the risk for one variable: So Greeks accounting for event driven jumps may be determined as follows:. Then, similar to options composite Greeks may be produced as weighted sums of Greek values conditioned on jumps generated with jump probability rate p. Greeks jump rate parameter can be tuned up against Black-Scholes model determined Greeks and improve risk analysis when Black-Scholes model determined Greeks i. Gamma are overestimated at near expiration time.

Various embodiments of the invention may also utilize a modified Bachelier model to price 1 put and 2 put and call event based options. Binary cash-or-nothing options with Q fixed payoff may be modeled as follows. Then Binary cash-or-nothing Price is a discounted expected value of receiving payout Q. The method shown in FIG. In step event driven option contract parameters are received. As shown in FIG.

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Find out how to construct a trading strategy based around market events. Aug 25,  · Event Driven Trading System - News Trader - Free Program Trading Systems. Event-Driven Trading Strategies Event driven strategies are defined as “special situations” investing. The strategy is designed to extract profits by significant pending corporate or market news events.