C Reddit Mentions | ChartExchange

>"Income drawdown" is the established name of taking money from a pension
Fair enough, but in trading, "drawdown" ordinarily refers to a decline in equity from a prior peak. My reading was reasonable apart from your clarification.
>Your goal should be able to perform meaningful business
Definitely. But a business objective is not the same as a valid performance test. I never said traders shouldn't be interested in success. I disputed your *definition* of success as earning a specified number of dollars within an arbitrary month.
Trading returns are variable. No matter how profitable a strategy is it will have losing months. Even if your goal is to cut trades as soon as you reach a specified small dollar amount for the month, you have no assurance that the first trade won't put you down, nor do you have any assurance that the second won't put you down further, or the third. A trader relying on any kind of trading income, whether bills or entertainment subscriptions, needs an expense reserve separate from trading capital. Bills are paid from the reserve; profitable periods replenish it. Success is measured by long-term returns, not monthly performance.
>think of that as more of a grading scale. An A is all three in this case, A B is two, a C is one, and a F is zero.
This grades short-term outcomes, not trading quality.
Suppose two traders take twenty 1:1 trades. Trader A follows a tested 55% strategy perfectly but happens to lose eleven trades. Trader B trades a negative-expectancy strategy, sizes recklessly, and gets lucky. Your system can give A an F and B an A.
With twenty 1:1 trades and a 55% overall win rate, the probability of finishing at breakeven or worse is about 41%, before costs. A 45% strategy still has about a 25% chance of finishing positive. A small sample size hardly tests anything.
>This is a great way to do so without relying on noisy metrics.
If you're actually a trader you know monthly dollar profit *is* a noisy metric. There's no disputing that.
Monthly dollar profit also means nothing without accounting for capital, risk, trade count, drawdown, etc. Expectancy and execution data over a *large* sample size is what separates skill from variance, not whether Hulu got paid.
>If it were a matter of you going to the gym...
Physical training produces a relatively direct relationship between controlled behavior and physical adaptation. Trading combines controlled decisions with highly variable outcomes. So the analogy fails.
A competent trader tracks controllable inputs and longer-term trends, not whether one arbitrary weigh-in earns an A. Profit matters, but *short-term* profit is not evidence of skill, or longevity. Thus, success in trading is properly a measurement of *decision quality* over the long-term, not individual outcomes.
>Confidence simply comes from practice in humans and the test result is the proof that the confidence makes sense.
This seems backwards. It sounds like you're saying confidence comes first, then you test to see if the confidence is warranted. Practice should only build confidence when the test measures the relevant skill. Short-term P&L does not reliably do that. In a high-variance activity, an outcome may be only weakly connected to the quality of the decision. A trader executing a positive-expectancy setup can lose. A gambler overleveraging and violating every rule can win big. Your grading system and $ monthly goals would have favorable variance teaching beginners to feel confident about bad decisions.
>move from Fs every three months to Fs once a year or even less
Again, fewer losing months does not necessarily mean better trading. Your metrics of success do not reflect a realistic understanding of variance.
Strategy A makes +3R in six months and loses -1R in six months. That's +12R overall, but with six "F"s.
Strategy B makes +0.5R in eleven months and loses -10R once. That's -4.5R overall, with only one "F".
You're rewarding smoothness while ignoring magnitude and tail risk. A reduction in losing months tells us little without more information. It could reflect improvement, or it could reflect ordinary variance or changes in market regime.
>going long when you should go long, even if your entry is crap... was the right play
Textbook outcome bias. Poor entry, irrational stop, and unjustified target do not become sound decisions just because the trade wins.
"Going long when you should go long" also begs the question. How is "should" determined? If it means price rose, that's hindsight. If it means the long had greater conditional expectancy based on information available at entry, that must be determined across *many* comparable trades.
You're right that market regimes matter. But regime identification and strategy selection must be assessed across a sufficient sample, not judged by whether the next trade happened to win.
>the first step is to know which strategy to take off the shelf to begin with
Based on what criteria, tested over what sample size?
>The expectancy doesn't change based on who is using it.
I never said it did. What are you talking about?
I said trade-management rules affect the return distribution. That's not "bad statistics." That's basic math. I took your comment about making $20 while "gunning for $300" to mean that the practical usefulness of $20 could influence you to exit early. If that's what you meant, then my criticism squarely addresses this. Changing an exit rule can change win rate and/or average win size. Therefore, it can change expectancy.
Kelly is equally sensitive to those inputs. Change the estimated probability or payoff ratio and the Kelly-optimal fraction changes.

document.getElementById("qqCSPc").onerror = function(){this.style.display='none';}; .dark-mode .fGQh67{ color: white; background-color: #333333; border: 2px solid white; }.light-mode .fGQh67{ color: #333333; background-color: white; border: 2px solid #333333; }CCitigroup Inc.stock NYSE

C
Citigroup Inc.
stock NYSE