So with a few months of research, I’ve been through some of the pain of coming out good strategies be it short term speculative, trend trade, mean reversion, spreads, or just plain time based trading strategies.

These are just some products that are currently on my system:

• US markets Top 10 Volume (so the spreads are 1 cent away, with high volatility/beta though)
• US markets?Top 10 Volatility (must satisfy good spreads)
• Futures markets (Global Index, commodities)
• Correlated US Stocks

Some findings base on my systems:

• Good spreads and volume helped reduce slippages costs, based on Market orders
• Volatility means more trading signals, but does not necessarily means profits
• Futures can be traded like stocks with the same systems, but some trading basics got to be identified and applied.
• eg. Nikkei 225 Futures lacked the “Point” by point spread, instead they are traded with a 5 points per tick, making it hard for Alpha due to the spread.
• On the contrast, the Hang Seng Index futures are great way to trade, because of the tick value.
• Markets are definitely correlated. Systems are up on 20 hours a day, from 8:00am GMT +8 Asian time, to 5:00pm EST US Time.
• By running systems to handle the risk from Hang Seng to Nikkei, and over to Nasdaq and the S&P500 futures, including WTI Crude from Europe to US times, you can see some correlation when one market moves, so is the other, and how the algorithms act upon these information, intra day.
• On the opening bell from 9:30am – 10:00am EST, and on good days (prices are short squeezed onto the Long or Short side), returns can run up to $300-$500, and before 10:00am, it can capture quite a good day’s worth of profits. But so are the risks, when there’s only 10% of the time with such opportunity, and 90% probably losing up to $100-$200. This will be refined and optimized.
• Some of the Algorithm cannot detect what is a random price action and what is an ‘actionable’ trade. So some results are therefore random and something only the system can only manage, but cannot act upon by forecasting or prediction.
• Fortunately, some US Stocks can produce consistent results, even after trading a >5000 shares a day for many many days. o:-)
• For a typical day when all systems are used and all products are added, trades can run up to 500-1000 trades a day, and over a value of USD 2 Million worth of shares traded.
• Adding all up, however the Equity curve are still negative, and points in an inverted 45 degrees, with only about 25-30% of winning ratio and Average/Trade at a negative value

Ahh, some of these stuff are pretty good for record keeping, knowing what works and what not. Thinking back on the days where I had made a few hundreds on an intraday, it spook me to realize how much risk Im actually putting on to produce that kind of returns, that is always inconsistent. Now that the programming of these systems comes at a snap of my fingers, it’s quite easy to “optimize” and fine tune the results.

In my current phase, optimizing the systems for speed and efficiency is a top priority. Tweaking and playing around with the numbers so the magic happens; frequency of signals/trade goes down (reduces brokerage fees) while Profits goes up (cutting useless stuff away).

Also, I have introduce a new strat using pure mean reversion and short trend systems (to counter the mean reverts), and just this system alone is able to produce quite a good run.

So… 3 objectives to meet in 3-6 months time:

1. Trading of more products eg. Futures & Equities, essentially a system able to manage in excess of at least USD 1 Million
2. Average profit per trade > 50 cents, or the Win/Loss ratio > 40% for consistency of at least 100,000 trades over 3 months.
3. Sharpe ratio > 3

Cool, what a post. Next, I’ll be updating my fund performance on my asset allocation base strategies and how they are doing over the past 2 months… (glancing over Municipals Bonds, it was a good bet and a good add to my portfolios since the S&P downgrade in August 2011 =:)