# Tag Info

10

An interesting starting point is The Cost of Latency by Moallemi and Saglam. After setting up a simple order execution problem --- in which a trader must chose between a market order and a limit order and guarantee execution over a fixed interval $[0,T]$, they proceed to derive a (complex) close form solution for the optimal strategy and evaluate the impact ...

7

Ha, interesting, so many responses with "negative" expectations. There are plenty of people that have successfully gone down this road and are producing pretty nice returns, so obviously it is possible. A trader with a smaller capital has better chances of producing good ROC with very reasonable risk parameters, simply because he's would not be constrained ...

6

As a starting point to my answer, I would say that reading a book is not sufficient to start doing automated trading on your own as chrisaycock suggests in his comment. I would answer your questions in 3 different ways. First, building your "AI bot" which I would rather call a systematic algorithm not only requires programming skills, it also means having ...

4

So those are cumulative pnl figures and you are interested in the percent changes in pnl from one data point to the next? Don't use log returns, simply generate the percent changes through r(t)/r(t-1)-1. 4.3922/5.2735-1 = -16.71% (in your example time series I made the assumption that the time series is in ascending order. Given your description of the ...

3

For me, I would calculate daily returns for such a series by backing out the daily PnL and dividing by some volatility number. lets define your cumsum as "c_pnl": daily_pnl = c_pnl - [0; c_pnl(1:length(c_pnl-1)] max_draw = max(cummax(c_pnl) - c_pnl) pct_returns = daily_pnl / max_draw # in terms of drawdown Don't you have capital already in the ...

3

There are: Bloomberg: TOMS, SSEOMS, AIM, EMSX TT Trading Systems (X-Trader, mostly for futures, spreads,...) Orc Group: Orc (often used for listed options) And uncountable others, really depends on which product you look to trade. But please note that you asked specifically about automated trading and to be honest, most shops code up their own order ...

2

I can share my own experience working with the Deltix product suite. As a research and development platform it's very feature rich with support for every back-testing mode there is (BBO, Trade, Midprice, Bar, Level 2 Order Book) and advanced optimization modes (walk-forward, genetic, mean-variance, portfolio optimization, etc). I have built components and ...

1

Don't try to capture LIVE tick data using a WebApp. I'm not saying it can't be done, I'm just saying you would get zero benefits and you would have to work way harder to make it functional. Web servers are designed with a premise, serve the user the requested data as fast as possible and free that resource up. You would have to fight the server logic (as ...

1

I think the simplest way to achieve what you're looking for is through regression coefficient hypothesis testing. Perform linear regression on returns (y-axis) vs. dates (x-axis) over the desired time frames (do it once for 5 months, once for dataset w/15 months worth of data, and once for 60 months worth of data). As a result of regression, you will get ...

1

You might want to take a look at the Waters Technology buy side technology awards, especially for execution management systems (EMS). Most hedge funds want to use multiple counterparties so they would want a broker-neutral trading system. As far as I'm aware, the most popular platforms are Portware and Flextrade.

1

The OpenGamma platform (www.opengamma.com) is probably the most comprehensive trading and risk analytics offer in the open source world. It supports the interest rate, forex and equity products you mentioned. It contains also a strong quantitative finance library.

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