Money Management for trader and investor

High Expectancy is enough for system selection in Trading?

I have seen many people think money management is a very simple topic and they keep it very short (1% risk per trade)is it money management? According to me if u do money management properly even monkey can make money in the stock market( i m not kidding).

most people fail in trading because they come up with small capital and the market offers them giant leverage. looking at some success stories or Youtube think they can win but its game of probability and risk management where they lack knowledge. I m very certain that among profitable trader very few know that some trading system can make more money than other trading systems but they still trade all their systems...lolz for the negligence of money management.

Everyone knows money management has 30% weight in trading then why so least considered?

let's consider some examples given below.

how do you select your system among 100 systems available on the internet?

or just having a positive expectancy is enough for you?

Below are 4 positive expectancy system which one you select and why?

Most people Think(even professional traders) 1% risk on each trade is money management. They can make money on this Money management technique but is it max optimized? The answer is BIG No. Each trading system has a different win ratio and RR(the risk-reward ratio). We just can't select the system on the basis of winning accuracy or RR ratio.

In the above example, system4 has the highest accuracy but lest RR ratio. So expectancy will solve our problem of system selection on the basis of accuracy and RR with a single ratio. so we can say the highest expectancy means the highest PNL making system. from the above table, we can confidently say that system2 makes the highest ROI (return over investment) compared to other systems. when rest parameters kept constant.

Is it expectancy of a system is all?

In the next blog, we will unleash this question in detail...till date keep reading and keep sharing.

Now The System4 makes more ROI (return on capital) than sytsem2. Ultimately ROI is the final dream of every trader and investor. so positive expectancy of system is not a holy grail of Trading system selection.

So the final output is we need highest expectancy system with highest Frequency which can generate highest Returns.

Algo/quant/HFT Trading:

Algorithmic trading drives 40% of the trading volumes in Indian equity markets and the percentage is on the rise everyday. In the west this % is somewhere around 70%-80%. One of the big reasons that algorithmic trading has become so popular is because of the advantages that it holds over trading manually. The advantages of algo trading are related to speed, accuracy, reduced costs, multiple trades simultaneously(High Frequency Trading).

The Benefits of Algo Trading

There are various advantages of algorithmic trading, which are discussed as under:

Speed

Algorithms are composed in advance so you can execute the guidelines consequently. The primary advantage of doing this is speed. The speed is fast to the point that it is hard to take note of, as an individual.

You can examine and execute various indicators at a quick speed that is hard to spot. This empowers trades to be analyzed and executed quicker and gives better chances.

Precision

Precision is essential in algorithmic exchanging. Much like any other business, precision is the key to getting better outcomes in stock trading too.

Utilizing computers in trading, you can diminish a few errors that may occur when you perform the same action manually. It encourages you to expel any mistakes prior to trading in the live market.

Cost Reduction

You would not be at the risk of losing your income. You don't need to invest a considerable time in checking business sectors as exchanging should be possible without your consistent supervision.

The time spent on observing the market is radically lessened and gives you the chance to take part in different activities.

Back-Testing Ability

Watchful back-testing enables traders to assess and tweak a trading idea. It enables them to decide the framework's expectancy – the normal sum that a broker can hope to win (or lose) per unit of risk.

Diversify Trades

Mechanized exchange of frameworks allows the client to exchange multiple accounts or use different techniques at one time. The computer can scan for trading openings over a scope of business sectors, produce orders, and monitor trades.

So if we have a look at the overall benefits of Algo trading, they can be summed up the following way:

· Trades are executed in most ideal costs.

· Quick and exact exchange order situation

· Exchanges time effectively and in a split of a second. This helps you maintain a strategic distance from huge price changes

· Algo-trading makes markets more liquid.

· Lower exchange costs due to the absence of human intervention

· Concurrent automated checks that keep an eye on numerous market situations

· A decreased threat of manual mistakes in setting trades

· High-frequency trading. This exchange strategy generates great profits by submitting a substantial number of requests at a quick speed, over different markets and various decision parameters, in the light of pre-customized guidelines.

Does It Hurt the Market?

One would think that because most trading leaves a computerized paper trail, it would be easy to look at the practices of high-frequency traders to provide a clear-cut answer to this question but that is not true. Because of the volume of data and the firms' desire to keep their trading activities secret, piecing together a normal trading day is quite difficult for regulators. Those who debate this issue often look at the "flash crash."

On May 6, 2010, the Dow Jones Industrial Average mysteriously plummeted 10% in minutes, and just as inexplicably, rebounded. Some large blue chip stocks briefly traded at one penny. On Oct. 1, 2010, the Securities and Exchange Commission (SEC) issued a report blaming one very large trade in the S&P e-mini future contracts, which set off a cascading effect among high-frequency traders. As one algo sold rapidly, it triggered another. As more sell stops hit, not only were high-frequency traders driving the market lower, everybody, all the way down to the smallest retail trader, was selling. The "flash crash" was a financial snowball effect.

This incident caused the SEC to adopt changes that included placing circuit breakers on products when they fall past a certain level in a short period. In the wake of the flash crash, many asked whether imposing tighter regulation on high-frequency traders made sense, especially since smaller, less visible flash crashes happen throughout the market with regularity.

FAQ

Manual trading is ending or less lucrative?

can we beat Algo trading?

Is there any way to beat Algo?

You can write your views @ Avinash_200033@yahoo.com

In the next blog, we will cover next money management Parameter...till date keep reading and keep sharing,

Stock Market Returns are Symmetric or Asymmetric ?

why every trader/investor try to minimize the draw-down?

why draw-down one of main parameter considered while system development?

how much draw down is acceptable?

As shown in above table if a trader looses 90% then to regain the same capital he has to make 900%(quiet impossible task in short term).

In trading losses are inevitable so keeping optimal risk management system in place 15-20% is draw-down is quiet normal which can be distributed over 60 trades and 3 months horizon period at lest .( sweet spot)

draw down % acceptably depends on systems expectancy ratio and the type of system you are using (momentum trading/ trend following/contra-trend etc).

eg: checkout below example where system makes profit but draw down are quiet large which affect the systems annual return and require large initial capital.