Daytrading system

Can someone turn $100 000 into $1 million in 12 months trading?

My response assumes the question is straight forward.

First, the math.

The equity must be ten times greater at the end of twelve months.

Final equity = initial equity * (geometric gain per trade) ^ number of trades

f = i * (g ^ n)

f is final equity, i is initial equity, g is geometric gain per trade, n is number of trades.  For a trade with a gain of 2%, g is 1.02.

We can divide f by i, which lets us express the final equity relative to the initial equity.  Call it TWR — terminal wealth, relative (after Ralph Vince).  TWR for this problem is 10.  Then

TWR = g ^ n

If trades are made daily, using 252 trading days per year, n = 252

10 = g ^ 252

g must be 1.0092

which is a gain of 0.92 percent per trade.

That is, make about 1% per trade, each trade using the entire account equity, trading every one of the 252 trading days in a year.

If trades are made weekly, using 52 weeks per year, n = 52

10 = g ^ 52

g must be 1.0452

which is a gain of 4.5 percent per trade.

That is, make about 4.5% per trade, each trade using the entire account equity, trading once per week.

Second, the trading vehicle.

With perfect hindsight to both the stocks and the timing, we can find individual stocks, or other tradable issues, that could have been traded with the required results.  Unfortunately, we cannot make trades using yesterday’s newspaper.  So we need a technique to forecast the gain of something tradable from today to a few days into the future, where the percentage gained is adequate to meet the growth requirement.

I recommend something that is liquid, has enough variability to provide the gains needed, not so much variability that intra-trade drawdown and / or trade-to-trade drawdown will cause excessive loss, and relatively easy to model.  That list is quite short.  The best candidates are exchange traded funds (ETFs) listed on US markets, including EWJ, EWL, EWM, IVV, IWB, IXJ, IYH, MDY, VDC, VGT, VHT, VIG, VPU, VUG, XLI, XLP, XLU, and XLV.

At the end of the year, your positions will be about one million dollars. Assuming a share price of $100, each order will be for about 10,000 shares.  To ensure fills close to published prices without affecting the price by your own order, daily volume of the issue traded must be at least 100 times your volume — $100,000,000 per day.

While the issues listed have the desired characteristics of profit potential, risk, and ease of modeling desirable for many traders, the compound annual rate of return (CAR) available from trading them directly is ”only” about 50%.  That is more than adequate for most traders.  To meet your goal, you need a CAR of about 1000%.

Third, finding leverage.

Options are available for many issues, including many on the list above.  There are several techniques for trading options.  Those that rely on time decay will not serve our needs.  But those that rely on changes in price of the underlying issue will.  These are described as ”directional” positions.  They can be established in a wide variety of ways, either buying or selling either calls or puts.  To ease discussion, we will assume that the forecast for a rise in price of the underlying ETF will result in purchase of a single call (not a spread); and the forecast of a drop in price of the underlying will result in purchase of a single put.  These positions are ”debit” positions, where we pay for the option when we buy it and that payment amount limits our liability without limiting our profit.

The price change in an option is related to several things.  Most significantly they are: the price change in the underlying issue, the change in volatility of the underlying issue, the strike prince of the option (its execution price) relative to the price of the underlying, and the time to expiration of the option.

As a very rough rule of thumb, the price of an option that is purchased with between 10 and 40 days until expiration and within one strike of ”at the money” will change about 20 times as much as the price of the underlying.  This relationship provides several advantages to help your challenge.  Most significantly they are: limited and known risk at the time the position is established, beta (relative price change) of about 20, control of large position size using smaller amount of cash.

The list of tradable issues is trimmed to those that have very liquid options.  To control 10,000 shares, you will need 100 options.  Depending on the accuracy of your forecasts, you may not need to trade at this size, but it will help identify the best candidates — those that trade thousands of options daily.  None of the issues listed above have option trading volume that high.  Another approach is to ”model something easy and trade something profitable.”  Which is to suggest developing a trading model using one of the issues on the list, but take the trades in the options of other issues that are both closely correlated and have higher option volume.

Fourth, forecast the future.

So far, everything has been easy.  To complete the plan, you need an accurate forecast of the future.  Fortunately, forecasts for short look ahead periods are easiest.  The plan will be to — trade frequently, trade accurately, hold a short period of time.  Trade every day or every week.  Be at least 65% accurate.  Hold from one to three days.

Every trade is a trend following trade for the period it is being held.  No matter the reason for entering a long position, we want an upward trend while we hold that position.  The best entries for short term positions is based on identifying prices that are over extended, then taking positions that will benefit from the price returning toward the mean.

I am the author of several books describing techniques to accomplish all of the steps described in this posting.  A search of Amazon Book category for my name, Howard Bandy, will bring up four that are in print.  The ”Quantitative Technical Analysis” book is the latest.  The ”Mean Reversion Trading Systems” book describes several techniques for identifying good short term trades.  You can read large sections of these books using Amazon’s ”look inside” tool.

Fifth, there are no guarantees.

I have made several presentations about trading system development and trading management which have been recorded and posted to YouTube.  A Google search using my name and YouTube will produce links to several.

One of my presentations is entitled ”The Four Faces of Risk.”  It gives background and detailed instructions for estimating the risk associated with any set of trades.  Turning $100,000 into $1,000,000 in one year is possible but not easy.  Of a group of people, all of whom follow good practices of trading system development, some will succeed, some will make a profit but miss the target, others will lose money.  Whatever the outcome, it may not be their fault.  That is not to suggest the trader has no control and should bet everything on a few trades.  It is to warn that meeting the goal is difficult.

Thanks for listening,

Dr Howard Bandy

Blue Owl Press

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