Here are several brokers those are chosen by large fund managers to execute their mechanical trading systems.
Trade Center
Rich Futures
Attain Capital
Wisdom Financial
Striker
Keener Capital
Angus Jackson
RJO Futures
Seems like no MT4 brokers used by large firms (not yet ?) 
Here is a compilation of several brokers providing Metatrader interface. This is taken from Bob’s posting on the Metatrader’s yahoogroups.
*********************
From: Bob [mailto:grumpyone@...]
Sent: Tuesday, November 22, 2005 6:16 PM
To: MetaTrader_Experts_and_Indicators@yahoogroups.com
Subject: Re: [MT_E and I] Experts Prohibited
I have not checked all these links out to be sure they go somewhere. But it should give you a good starting point of MT4 Brokers
Bob
Found this at samuel’s multiply blog entry. 
And remember, past performance is not necessarily indicative of future results. 
Another excerpt from Paul’s blog:
If you are going to trade the news make sure you completely realize what (if any) cause and effect relationships actually exist between news events and price moves, and what the timing of them is. For example, significant news announcements for stocks usually cause increases in volatility, liquidity, and volume, but not necessarily in a predictable direction – that depends on the differences between actual and anticipated news.
For this reason it is better to base a trading method simply on anticipation of higher volatility rather than attempting to accurately predict the future direction. In this way you can still profit even when it turns out that the long-term reliability of your perceived cause-effect relationship actually turns out to be no better than random.
This is from the pmking’s blog entry:
Some things in trading just aren’t possible. Maybe a car analogy will help. Imagine for a moment you are designing a car and it has to have the following characteristics:
So it’s a fast sports car at the high end of performance. Now you have a couple more required characteristics:
If you know anything about physics and conservation of energy you will quickly realize that these 4 characteristics would be virtually impossible to embody into one vehicle (with current technology). You have 2 main choices – compromise on some of the requirements, or design 3 cars (a sports car, an SUV, and a compact).
What has this got to do with trading? Well a lot of the time people are trying to design the ‘Holy Grail’ system that has the following characteristics:
Just like the car design where some of the characteristics have an inverse relationship (e.g. top speed to fuel economy) trading systems exhibit similar behavior. High win%, for example, is usually inversely proportional to both trade frequency and average size of winners compared to losers.
When you are attempting to design a trading system it is important that you make sure you don’t have an ‘impossible specification’ for what you want to achieve because you don’t clearly understand the relationships between the various system components and characteristics. Otherwise the only thing you’ll achieve is frustration.
Finding a robust short term trading system is not impossible ? Well, maybe. But sure it is a hard task. Given these 3 reasons below, research on a robust ST TS is very appealing:
1. Math
Higher frequency of trades enables increasing positions size faster in a given period of time (compounding) during run-ups, but also enables decreasing positions size faster during drawdowns.
2. Source of profits
Long term trend-following / Turtle System captures profits from existence of trends (trends often connected with macro-economic cycles). As we all know, markets tend to move in trends but also experience long “choppy” periods, without any substantial move in one direction. Hence diversification is used to reduce negative impacts of non-trending periods in a single markets. Unfortunately, most liquid markets are highly correlated. As a result, these strategies performance depend on the magnitude of trends.
Short term trading captures profits from market inefficiencies, more precisely – from market’s over-reactions. If we’ll sum up all inefficiencies in the short-term level, they’ll add up to a greater amount than in the long-term level. Of course in order to play on short-term basis we must have low commissions and high liquidity – two things which have dramatically improved since ’90s or ’80s.
3. Predictability
Volatility in the coming short-term periods is more predictable than in the long-term periods. Try to estimate the average daily range for the next 5 days. Now try to predict the average yearly range for the next 5 years – error will be much bigger.
To add more on the research, here is some other resources to be read later:
Traderclub Forum
One member of the tradingblox forum, Mr. Cyphrograph (from Poland), brought this topic to the forum
Short term VS Long term trading.
Hello everyone. I guess I’m 3rd member from Poland on this forum, together with TK and steady_jake. We had some hot discussion on a polish futures message board, and now I want to continue it at “Trader’s Roundtable” as I believe it is more suitable for that kind of discussion. Here’s the hypothesis: Short term trading can reach the level of robustness (or performance), which can not be achieved by long term methods or long term trend-following systems or – let’s be straight – Original Turtle System. The question I want to ask you is: can we verify the above hypothesis using historical results (hypothetical from backtesing or actual trading figures)? IMHO, Yes we can do it. Since our abilities to predict future are weak, what else do we have beside history? Well-known method used for predicting possible outcomes, namely Monte Carlo Simulation is based on historical figures also.
I want to present a little research I’ve done on this subject. Let’s compare actual trading performance. Turtles vs Active Traders battle. We take 3 famous Turtles on one side (B. Dunn, J.W. Henry, W. Eckhardt) and 3 quants who employ short-term trading methods on the other (T. Crabel, Denali, C-View Limited). Let’s take 2 ratios for measuring robustness / risk-adjusted return / performance quality (name it like you want):
1. Compounded Annual Return / Worst Drawdown (CAR/WDD, monthly basis) – before management and incentive fees,
2. Annualized Sharpe.
Turtles camp:
DUNN Capital Management-DUNN WMA (Nov 84 – Sep 03)
CAR/WDD 0.52, Sharpe 0.64
John W Henry & Company-Financial and Metals (Oct 84 – Aug 03)
CAR/WDD 0.91, Sharpe 0.83
Eckhardt Trading Standard (Jan 87 – Sep 03)
CAR/WDD 1.38, Sharpe 0.75
Active Traders camp:
Crabel Cap. Mgmt-Diversified 1XL (Jan 92 – Sep 03)
CAR/WDD 3.77, Sharpe 1.38
Denali Asset Management-Ascent (May 99 – Sep 03)
CAR/WDD 10.26, Sharpe 2.75
C-View Limited 3XL (Oct 96 – Aug 03)
CAR/WDD 5.62, Sharpe 1.66
Source: www.iasg.com
Disclaimer: I’m not connected with any managers mentioned above.
Well, numbers speak for themselves 
As you may suspect, figures for short term systems backtested and optimized against the past data are much, much better – especially, when you set worst drawdown figure to around 40% by position size management rules.
Turtles camp has one advantage over active traders: they have longer track records. However, I don’t want to wait 15 years in order to have comparable periods. That is the zillion dollar question: will these excellent CAR/WDD & Sharpe figures sustain in the future?
Where are the grounds for differences between short and long term trading performance? IMO, they’re located in 3 main areas:
1. Math
Higher frequency of trades enables increasing positions size faster in a given period of time (compounding) during run-ups, but also enables decreasing positions size faster during drawdowns.
2. Source of profits
Long term trend-following / Turtle System captures profits from existence of trends (trends often connected with macro-economic cycles). As we all know, markets tend to move in trends but also experience long “choppy” periods, without any substantial move in one direction. Hence diversification is used to reduce negative impacts of non-trending periods in a single markets. Unfortunately, most liquid markets are highly correlated. As a result, these strategies performance depend on the magnitude of trends.
Short term trading captures profits from market inefficiencies, more precisely – from market’s over-reactions. If we’ll sum up all inefficiencies in the short-term level, they’ll add up to a greater amount than in the long-term level. Of course in order to play on short-term basis we must have low commissions and high liquidity – two things which have dramatically improved since ’90s or ’80s.
3. Predictability
Volatility in the coming short-term periods is more predictable than in the long-term periods. Try to estimate the average daily range for the next 5 days. Now try to predict the average yearly range for the next 5 years – error will be much bigger.
We are now working on several systems. They are counter trend typed system and swing trading system.
As those previous systems, the development are conducted on MT4 platform, partnering with Balidev’s engineers.
Be it a passionate young Nick Leeson, or a family man Rusnak of Allied Irish Bank, they are all human. And human are all the same. Human has emotions. Human has creativity. Let alone the creativity be used when developing a system. And the emotion be the motivator for developing a better system. But when trading a live account, let the system run itself with 0% emotion and creativity. That is why great successful traders use 100% mechanical trading systems.
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