Money Management Systems

Introduction Technical signals are useful for entry, but technical understanding of risk is even more important. Remember the law of percentages and how difficult it is to recover from losses. Investing and trading are a matter of determining and controlling loss of capital. Entry is easy; best exit is difficult. Money management consists of a number of ways to measure and to protect from the risk of loss either in individual trades or in complete systems.

How many of your trades are losers? What’s the typical percentage loss on a losing trade? How many of your trades are winners? What’s the typical percentage gain on a winning trade?

Expected Return Let’s say you determine that 40 percent of the time a trade loses, and it loses 1 percent. Sixty percent of the time, the trade wins, and winning trades are up 1.5 percent. With these numbers, you can calculate your per-trade expected return, like this:.40 × – ×.015 = – =.005 On average, then, you would expect to earn a half a percent on every trade you make.

How to calculate the probability of ruin Trader’s advantage trades win 60 percent of the time and lose 40 percent of the time. In that case, the trader’s advantage would be: 60% – 40% = 20% C is the number of trades in an account.

Valuing volatility Expected return gives you an idea of how much you can get from a trade on average, but it doesn’t tell you how much that return might vary from trade to trade The wider the range of returns that a strategy has, the more volatile it is. There are several ways to measure volatility. One common one is standard deviation.

In the derivatives markets, volatility is measured by a group of numbers Delta is a ratio that tells you how much the option or future changes in price when the underlying security or market index changes in price. Delta changes over time. Gamma is the rate of change on delta. That’s because a derivative’s delta will be higher when it is close to the expiration date, for example, then when the expiration date is further away. Vega is the amount that the derivative would change in price if the underlying security became 1 percent more volatile. Theta is the amount that a derivative’s price declines as it gets closer to the day of expiration.

Considering opportunity costs Opportunity cost is the value you give up because you choose to do something else. In trading, each dollar you commit to one trade is a dollar that you cannot commit to another trade. Thus, each dollar you trade carries some opportunity cost, and good traders seek to minimize this cost.

The underlying idea is that you should never place all of your money in a single trade, but rather put in an amount that is appropriate given the level of volatility. Otherwise, you risk losing everything too soon.

Money Management Styles Fixed fractional Gann Kelly Criterion Martingale Monte Carlo simulation Optimal F

Fixed fractional Fixed fractional trading assumes that you want to limit each trade to a set portion of your total account, often between 2 and 10 percent. Within that range, you’d trade a larger percentage of money in less risky trades and at the smaller end of the scale for more risky trades. Example- This means that if you have decided to limit each trade to 10 percent of your account, if you have a $20,000 account, and if the risk of loss is –$3,500, your trade should be:

Fixed ratio The fixed ratio money management system is used in trading options and futures. It was developed by a trader named Ryan Jones, who wrote a book about it. In order to find the optimal number of options or futures contracts to trade, N: N is the number of contracts or shares of stock that you should trade, P is your accumulated profit to date, and the triangle, delta, is the dollar amount that you would need before you could trade a second contract or another lot of stock.

Gann William Gann developed a complicated system for identifying securities trades. Part of that was a list of rules for managing money, and many traders follow that if nothing else. The primary rule is: Divide your money into ten equal parts, and never place more than one 10-percent portion on a single trade. That helps control your risk, whether or not you use Gann.

Kelly Criterion emerged from statistical work done at Bell Laboratories in the 1950s. The goal was to figure out the best ways to manage signal-noise issues in long-distance telephone communications. Very quickly, the mathematicians who worked on it saw that there were applications to gambling, and in no time, the formula took off.

Cont’ Kelly Criterion To calculate the ideal percentage of your portfolio to put at risk, you need to know what percentage of your trades are expected to win as well as the return from a winning trade and the ratio performance of winning trades to losing trades. Kelly % = W – [(1 – W) / R] W is the percentage of winning trades, and R is the ratio of the average gain of the winning trades relative to the average loss of the losing trades.

Example for Kelly ratio a system that loses 40 percent of the time with a loss of 1 percent and that wins 60 percent of the time with a gain of 1.5 percent. Kelly formula percentage to trade is:.60 – [(1-.60)/(.015/.01)]= 33.3 % - Interpretation : As long as you limit your trades to no more than 33% of your capital, you should never run out of money. Many traders use a “half-Kelly” strategy!!?

Martingale The martingale style of money management is common with serious casino gamblers, and many traders apply it as well. It’s designed to improve the amount of money you can earn in a game that has even odds. Most casino odds favor the house. Day trading, on the other hand, is a zero sum game, especially in the options and futures markets. This means that for every winner, there is a loser, so the odds of any one trade being successful Day trading, on the other hand, is a zero sum game, especially in the options and futures markets. This means that for every winner, there is a loser, so the odds of any one trade being successful are even. The martingale system is designed to work in any market where the odds are even or in your favor.

Martingale Under the martingale strategy, you start with a set amount per trade, say $2,000. If your trade succeeds, you trade another $2,000. If your trade loses, you double your next order (after you close or limit the first trade) so that you can win back your loss. (You may have heard gamblers talk about doubling down? Well, this is what they are doing.)

Martingale Under the martingale system, you will always come out ahead as long as you have an infinite amount of money to trade. The problem is that you can run out of money before you have a trade that works. The market, on the other hand, has almost infinite resources because of the huge volume of participants coming and going all over the world. That means that you have an enormous disadvantage. As long as you have a disadvantage, thoughtful money management is critical.

Monte Carlo simulation If you have the programming expertise or buy the right software, you can run what’s called a Monte Carlo simulation. In this, you enter in your risk and return parameters and your account value, let the program run, and it returns the optimal trade size. The system is not perfect — it is only a model that can’t incorporate every market situation that you’ll face and it has the fractional trade problem that the other systems do. But it has one big advantage: - It can incorporate random changes in the markets in ways that simpler money management models cannot.

Optimal F The Optimal F system of money management was devised by Ralph Vince. The idea is that you determine the ideal fraction of your money to allocate per trade based on past performance. This is the maximum percentage to invest any capital account in the trading system. If your Optimal F is 18 percent, then each trade should be 18 percent of your account — no more, no less.

Calculation of Optimal f The optimal f percentage = (percentage of wins x (profit factor +1) - 1) / profit factor Where: Percentage of wins is the percentage of winning trades Profit factor is the ratio of total gains over total losses Example: Optimal f = (.097 x ( ) - 1) / = 1.46% F is a factor based on the basis of historical data, and the risk is the biggest percentage loss that you experienced in the past.

Example : Optimal F Using these numbers and the current price, you can find the contracts or shares you need to buy. If your account has $25,000, your biggest loss was 40 percent, your F is determined to be 30 percent, and you’re looking at a stock trading at $25 per share, then you should buy 750 shares.

Notes on Optimal F Some traders only use Optimal F in certain market conditions, in part because the history changes each time a trade is made, and that history doesn’t always lead to usable numbers.