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Professional Report
Ronald L. Johnson
Investment Consultant
1424 Seagull Dr. Ste.107 Phone 727-771-7020Palm Harbor, FL 34685 Fax 727-771-0980
Day TradingDay Trading
An Analysis of Public Day Trading at a Retail DayTrading Firm
The Purpose of The Analyses
Numerous market studies have concluded that accurate market timing is not possible, even for professionalmoney managers. Day trading is the ultimate test of market timing in that the trade is opened and closed withinthe same day.The emergence of the Internet and the availability of almost instantaneous real-time market data haveincreasing numbers of public investors interested in trading on a short-term or intraday basis. Retail brokeragefirms concentrating on this speculative activity frequently claim that a high percentage of their retail publicclients are profitable.The purpose of this analysis was to analyze a statistically significant sample of public day trading experiencesin order to determine whether public retail customers really have been successful day traders, and to identifyand quantify the risks that public investors face as day or short-term traders.
How The Analysis Was Conducted
Step 1.
The Project Group on Day Trading randomly chose thirty (30) short-term trading accounts for analysisfrom a retail day trading firm:Thirty accounts were analyzed in order to provide a representative sample of public short-term tradingactivity. The accounts were chosen without knowing either the distribution of short-term trades within theaccount or the profitability of the trading conducted.
Step 2.
A matched trading analysis, commission-to-equity analysis, and turnover analysis was conducted foreach account by STZ Analytical Services.A matched trading analysis matches opening trades with closing trades and was required to identify theprofitability and duration of all trades in each account. A typical matched trading analysis conducted forthis report is shown at Exhibit A-1.Commission-to-equity and turnover analyses were conducted for each account to quantify the degree ofactivity and the costs associated with that activity in each account. Typical turnover and
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commission-to-equity analyses conducted for this report are shown at Exhibit A-2.
Step 3.
This analysis addresses all of the trading as well as the day trading conducted in each account. Tradingstatistics were calculated and evaluated based on the matched trading results of Step 2. The typical set-upanalyses conducted for this report is shown at Exhibit A-3.The analysis established important selected trading statistics for each account (shown at the top of ExhibitA-3). The individual account statistics were calculated on the basis of matched trading record shown below theheading QTY, DAYS HELD, P/L . (Exhibit A-3 includes only the first 26 trades, sorted by Days Held forillustration).Account A7, for example, had four day trades (0), three two day trades (2), two three (3) day trades, etc. Themajority of the accounts traded 1,000 share lots.Most of the selected statistics are well known to professional traders and trading system developers andare used to evaluate trading and trading systems. The individual account statistics were used to evaluatethe performance of each account and pinpoint areas where other analysis was required.
Speculative Trading Analyses
There are two main issues in any speculative trading account:Will the account consistently make money?Will the account lose all of its capital?These issues are interrelated and concern the probability that the trading will be successful, the effectiveness ofthe trading in controlling losses and letting profits run, and the percentage of capital risked on each trade. Allare important.
Because an account has a net profit at any point in time does not necessarily mean it is a successful way to trade
.
For example, it is quite possible that an account is temporarily profitable yet is trading in amanner that yields a high probability the account will lose all of its funds in the near future. Selected statisticsfocus on the underlying causes of performance or non-performance.Accounts traded in a manner that produces a high payoff ratio, high reward/risk ratio, and a high percentage ofprofitable trades (without overtrading) will consistently produce large profits and a low risk of ruin. The analysesconcentrated on quantifying this underlying capability.Important trading statistics:
Average Trade
.
The average trade is an important measure of any trader or tradingsystem. It is generally the first figure considered in evaluating trading effectiveness.
It is an estimate of the expected return for each trade
. In general, the larger the value of theaverage trade, the better.While the average trade statistic will be less in day trading than in longer term trading, most traderswouldn’t consider a day trading system that makes less than an average trade of $200, or less than $400on a longer term basis.
Stock day traders face both market and stock specific risk.
The day trader doesn’t know if a stocktakeover is going to occur and cause an immediate large loss in his or her short position or if a majormarket decline will result in a large loss in the trader’s long position.
1.
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The largest day trading loss in this study was $12,800. It takes 64 trades at an average trade of $200 pertrade to recover from such a loss. The largest 1,000 share loss was $81,522.
2) Payoff Ratio.
The ratio of the average winning trade to the average losing trade. The larger thisratio is, the better. It is difficult to be a successful trader with a payoff ratio under 1. The sign ofan effective trader is the ability to let his or her profits run and cut his or her losses short.
3) Probability of Success.
Probability is calculated by determining the percentage of profitabletrades. It is an estimate of whether the next trade will be successful. If the probability of successis low, the payoff ratio must be high. In other words, if you have more losing trades than winningtrades, the average winning trades must be large enough to more than offset the average losingtrades or you’ll eventually lose all capital.
4) Reward/Risk Ratio.
(Also known as the Profit Factor) The ratio is calculated by dividing thegross profits by the gross losses. Most traders want at least $2 of reward for every $1 risked.
5) Percentage of Capital Risked.
Overtrading or risking too much per trade is a certain way oflosing all your capital. Any trader, no matter how good, increases his or her risk of ruin byincreasing the capital placed at risk on each trade.
6) Risk of Ruin.
The probability that a trader will lose all of his or her trading capital. Risk of Ruinis the probability that a trader will realize a series of losing trades that consumes all of his or herremaining trading capital.
1
If a trader has a 50 percent chance of winning/losing on a trade, his or her average winning trades mustequal his or her average losing trades (Payoff Ratio of 1) or he or she will eventually lose all his or hercapital. As the probability of success decreases the Payoff Ratio must increase to avoid ruin.Risk of Ruin tables utilized to determine the Risk of Ruin calculations in this report are included in Exhibit B.The probability of Ruin (losing all capital) is displayed within the table as a number between 0.000 (0% chanceof ruin) and 1.000 (100% chance of ruin). The four tables shown illustrate the effect of four money managementstrategies on a given trading capability.This study will employ only Figure 4 of Exhibit B (10% of available capital at risk) since the accountscontinuously risked more than 10% of their capital. In addition, if an account has a 100% Risk of Ruin atthe 10% exposure level, it has at least that at all greater levels of exposure. Accordingly, all Risk of Ruincalculations will be taken or extrapolated from Figure 4 of Exhibit B.
Account Performance (All Trading)
This initial analysis covered all trading conducted in the thirty accounts (4,339 trades), over trading periods ofbetween 1-10 months. As expected, all of the accounts had extremely large turnovers and cost-to-equity ratiosas outlined at Exhibit C. The average account was open 4 months, had an average turnover of 278, and acost/equity ratio of 56%.The annualized cost/equity ratio measures the amount of profit required on average equity just to paytransaction costs and break even. Few traders can absorb transaction costs of 56% per annum and beprofitable on a consistent basis.The quantitative analyses results of account performance are reported at Exhibit D for all trading.Two individuals traded six of the trading accounts reported in Exhibit D. One individual traded A11 and A22. The
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Professional Report
other individual traded accounts A1, A5, A20 and A26. The accounts with the most trades (A22 and A20) wereretained and the other accounts removed to avoid skewing the analysis. The 26-account analysis, representing4,093 trades, is at Exhibit E reporting the Account Performance of all individual trades.A comparison of the cumulative statistics between Exhibit D and Exhibit E shows that all the findingsremain the same. In sum, removing the multiple account trading was statistically insignificant.
Losing Accounts
Eighteen (18) of the twenty-six accounts (70% of the accounts), lost money
.
More importantly, all 18 accounts were traded in a manner that realized a Risk of Ruin of 100%.
That is, 70% of the accounts wouldalmost certainly lose any and all funds put at risk in them.
Winning Accounts
Eight (8) of the twenty-six accounts, or 30% of the accounts, were profitable.Despite being profitable, three of the accounts A2, A24, and A29, were traded in a manner that realized a highpotential Risk of Ruin (A2 –74%, A24-24%, and A29-84%) and low average trades. More importantly, however,the performance of each of these accounts is highly dependent on just one trade.The largest winning trade is a significant number as it relates to the net and gross profit. Trading (or atrading system) has a serious problem if a major portion of the profits comes from just one trade. Therule of thumb is that no more than 25% of the net profits should come from the largest trade.For example, account A2’s largest winning trade was $7,649.58. The account made only $609.10 on 99 tradeswithout that one trade. One trade out of 100 made 93% of the profit. The largest winning trade in account A24was $39,003.48, representing 39% of the profit on one trade in 597. Removing the largest winning trade fromaccount A29 ($662) leaves the account with a loss. In like manner, the largest winning trade from Account A28($5,635.95) represents 31% of the profit on one trade in 285. In addition, 70% ($33,667.50) of account A13profits of $48,645.40 came from just one trade in 149 trades.
The largest winning trade sensitivity analysis shows the underlying weakness in these accounts.
Only three (3) accounts, (11.5%) of the 26 analyzed, (accounts A8, A10, and A30) evidenced the profitability,reward/risk ratios, and low probability of ruin required for successful speculative trading. Account A8 was thebest trader analyzed in this study (Account A8 held its positions for an average of 47 days with no day trades).
Conclusions (Short-term Trading)
If this analysis is representative of short-term public trading, the individual and cumulative results show thatmost public traders will lose money attempting to short-term trade.
In fact, this study shows that 70% of the public traders analyzed will not only lose, but almost certainly lose everything they invest.
Only three accounts of the 26 analyzed (11.5% of the sample) illustrated trading results and techniquessufficient to profit from short-term speculation.
In sum, based on these findings, the vast majority of retail public investors (88.5%) would be best advised to refrain from short-term speculative
trading.
Account Performance (Day Trading)
Twenty-five (25) of the initial 30 accounts analyzed made at least one-day trade. The initial day trading analysiscovering all day trading conducted in the 25 accounts (2,839 trades) is at Exhibit F.
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