Trading for a Living

[ra189663 10]

A year ago February, Stocks & Commodities had an article on using Value Line composite as the trigger to go long or short the Russel 2000. Back tested from the beginning of R 2000, he averaged something like a 20% return (he was using Martin Zweig's program). Best year was something like 50% return - worst year was about a -3%.

 

So, just using that as an average, one needs to keep in mind that to obtain that overall average a) the program has to work in the future, and b) no money was withdrawn (which may be the most critical point...).

 

Unless and until you have a track record of years (not months), you won't have any statistically relevant numbers to even decide from. Ask anyone who was making money hand over fist during a bull market and then ran headlong into a bear market with a program that wouldn't work then.

 

Add to that the need to pay taxes, even if you are reinvesting everything... and you won't be getting a 20% return.

 

But assuming you have a track record that has validity - meaning you have had good and bad markets you have survived - first before anything you pay your taxes. Then the second rule is you take out what you need (not what you want- what actual needs are), and you reinvest the rest.

 

Don't want to reinvest anything? Ever heard of inflation? Draw down? Enough said.

 

Keep in mind that you may have profits coming in hand over fist at the beginning of the year, and at the end of the year without drawing down anything, and not putting anything away for taxes, you can have less than you started with. Possibly significantly less.

[Tradewinds 12]

Unless and until you have a track record of years (not months), you won't have any statistically relevant numbers to even decide from.

 

The statistical relevance depends upon the confidence level and margin of error needed to make a profit. And that in turn depends upon the sample size, and the sample size depends upon the number of trades that a system generates. It a system generates 200 trades a day, then it doesn't take years for enough data to do a statistical analysis. If the system generates 25 trades a year, then it will take years.

[SIUYA 11]

The statistical relevance depends upon the confidence level and margin of error needed to make a profit. And that in turn depends upon the sample size, and the sample size depends upon the number of trades that a system generates. It a system generates 200 trades a day, then it doesn't take years for enough data to do a statistical analysis. If the system generates 25 trades a year, then it will take years.

 

I actually think this is a common misconception depending on the strategy.

People could produce plenty of simple back tested results that look good over a period of time and they hit all the right statistical measures. It does not mean they will work over all types of markets. I would ideally like to see how well something performs in a market that does not suit the strategy. It is when things are doing badly that the mistakes creep in to make things worse.

Even short term day trading systems often work better in one set of markets, or instruments than others. So unless you are truly and accurately testing a trading system over a portfolio of instruments or over many types of markets, backtesting is just that, a theoretical bunch of assumptions that tests and possibly curve fits the data available.

 

Not that backtesting is not relevant, but just because it is statistically relevant does not make it real life relevant.

[Tradewinds 12]

Not that backtesting is not relevant, but just because it is statistically relevant does not make it real life relevant.

 

I totally agree. In fact, I would state that a statistically relevant backtest could become absolutely meaningless. The underlying rules of a strategy may have absolutely nothing to do with accurately valuing the underlying security. A backtest could be a reflection of nothing more than investor behavior over a certain period of time. Investor behavior could change. If investors were basically speculators for the last 20 years, and not accurately valuing securities, that could be a potential problem going forward. I'm not saying that is the case. I'm just pointing out the issue of how value is determined for securities, and IF it is flawed, then trouble is inevitable at some point.

[MightyMouse 12]

I actually think this is a common misconception depending on the strategy.

People could produce plenty of simple back tested results that look good over a period of time and they hit all the right statistical measures. It does not mean they will work over all types of markets. I would ideally like to see how well something performs in a market that does not suit the strategy. It is when things are doing badly that the mistakes creep in to make things worse.

Even short term day trading systems often work better in one set of markets, or instruments than others. So unless you are truly and accurately testing a trading system over a portfolio of instruments or over many types of markets, backtesting is just that, a theoretical bunch of assumptions that tests and possibly curve fits the data available.

 

Not that backtesting is not relevant, but just because it is statistically relevant does not make it real life relevant.

 

A lot of times back testing a strategy is very similar to looking at the pattern of rain drops and figuring out a path that you could have taken to get from your font door to the road without getting wet. You will find the pattern and be excited when you do. But, what are the chances that the exact wind, cloud, and obstacles (a bird or plane flying by) occur at the same time next time?

 

On the other hand, you can look at the sky and quickly detect if it is a lot of rain or a light drizzle and get to the road when you will only get minimally wet.

[TimRacette 11]

A lot of times back testing a strategy is very similar to looking at the pattern of rain drops and figuring out a path that you could have taken to get from your font door to the road without getting wet. You will find the pattern and be excited when you do. But, what are the chances that the exact wind, cloud, and obstacles (a bird or plane flying by) occur at the same time next time?

 

On the other hand, you can look at the sky and quickly detect if it is a lot of rain or a light drizzle and get to the road when you will only get minimally wet.

 

Haha, love that analogy MM, spot on. It's my opinion that focusing on the system is not the crucial factor. As much as having a statistical edge and trading system is necessary, the crucial points come from within us and our ability to detach ourselves from the money and trade completely objective. Not giving into the fear of losing money, or the fear of being wrong on this trade. Being able to follow a system to the T and set your impulse aside makes a great trader.

 

Spend less time on the system, more time on detaching yourself from the money.

[tradelab03 10]

Trading is often viewed as a high barrier-to-entry field, but this is simply not the case in today's market. Now, anyone with ambition and patience can trade, and do it for a living, even with little to no money

[aimhi 10]

We can not rely on trading for a living in start however it can help us in future to earn good ROI and pay off our bills. SO it is good to start it as a hobby while doing the primary jobs to avoid financial losses.

[AlexMillford 0]

On 11/1/2016 at 7:59 PM, aimhi said:

We can not rely on trading for a living in start however it can help us in future to earn good ROI and pay off our bills. SO it is good to start it as a hobby while doing the primary jobs to avoid financial losses.

Absolutely agree with you