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52 Minute Risk Management Masterclass from a $100,000,000 Trader — Transcript

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0:00Risk management is one of the most
0:02important skills, yet it is one of the
0:04most complex and sometimes even
0:06counterintuitive parts of trading. Do we
0:08always need to have a hard stop on our
0:10trades? Shocker, no. Should we ever
0:12violate our risk rules? Also shocker,
0:15maybe sometimes. Is it okay to risk
0:17blowing up your whole account? Well,
0:19actually, I'd argue there are situations
0:22where it is. Is undercapitalizing on big
0:24opportunities a sign of poor risk
0:26management? 100% [music]
0:28and I'm going to explain why to all of
0:29this. This video is my attempt at making
0:32the ultimate comprehensive guide to risk
0:34management in trading. The fundamental
0:36truth of trading is that you cannot have
0:38reward without risk. Or as the normies
0:40would call it, no pain, no gain. Risk is
0:43inherent in everything we do.
0:45Ultimately, risk management is not about
0:47eliminating risk. That is impossible in
0:49markets. It is about intelligently
0:51controlling exposure to help us achieve
0:54our goals. My definition of risk
0:56management is a set of processes and
0:58rules that allow you to maximize the
1:00odds of achieving your stated goals
1:02while minimizing the odds of
1:03encountering unacceptable outcomes. Risk
1:06management in trading isn't just about
1:08stop losses and risk rules. True risk
1:10management is much broader. It includes
1:12managing position sizing, but also the
1:14emotional and psychological side of
1:16trading, as well as the money management
1:18rules we follow. At its core, risk
1:20management is about balancing
1:22aggression, taking enough risk to
1:24meaningfully capitalize on
1:25opportunities, along with defense, or
1:27ensuring the avoidance of unacceptable
1:29outcomes. In many ways, one of the
1:31biggest themes of this entire
1:33presentation is that risk management is
1:35not about maximizing safety. It is about
1:38maximizing long-term expected value
1:40while avoiding those outcomes that are
1:41unacceptable. Before we can discuss how
1:44to manage risk though, we first need to
1:46answer a more important and fundamental
1:48question. What exactly are we trying to
1:52avoid? That question is part of what
1:54makes risk management so complicated and
1:56subjective. Risk management will always
1:58fundamentally be unique to the
2:00individual. One of the biggest mistakes
2:02in trading discourse is pretending there
2:04is one universally correct risk model
2:06that everyone should follow. No trader,
2:09no firm, and no hedge fund has the same
2:11financial situation, emotional
2:13tolerance, obligations, or goals. The
2:16correct amount of risk depends entirely
2:19on context. For a pension fund, a
2:21university endowment, or a retired
2:23elderly person, a 20% drawdown may be
2:26completely unacceptable because the
2:28primary objective is preservation of
2:30capital and consistency. The utility of
2:33additional upside is low relative to the
2:35devastation a large loss could create.
2:38Meanwhile, another trader may rationally
2:41be willing to risk a 100% of an account
2:44because they are undercapitalized, can
2:46easily replenish the funds, and are
2:48optimizing for asymmetric upside. As
2:50individuals, we all have completely
2:52different utility functions for
2:55incrementally more money. This is why
2:57internet debates about the correct
2:58amount of risk are often useless. Most
3:01people arguing about risk are
3:02unknowingly optimizing for entirely
3:05different objectives. Losing 50K means
3:08radically different things to different
3:09people. To one person, it's just an
3:11inconvenience. To another, it may
3:13represent financial ruin, instability
3:15for their family, or years of savings
3:17erased. Risk management, therefore, is
3:20never purely mathematical. It is
3:22financial, psychological, situational,
3:25and lifestyle dependent all at once. The
3:28ultimate point of risk management is to
3:30avoid risk of ruin, but ultimately, each
3:33individual needs to define that for
3:35themselves. For some, that might mean
3:37blowing up their whole account. For
3:38others, that might even mean a 20%
3:41drawdown. If you are a trader at a hedge
3:43fund that needs to produce returns every
3:45year, ruin could even be defined as
3:47underperforming the market for
3:48consecutive years. Now, here is one
3:50warning as you take the first step and
3:52seek to define that. Studies have shown
3:55that most people greatly overestimate
3:57how much risk they think they can
3:59stomach. Or as the great risk
4:01philosopher, Mike Tyson, would say,
4:03"Everyone has a plan until they get
4:05punched in the mouth." Until you have
4:07actually weathered through multiple
4:08drawdowns, you have no idea how you are
4:11going to react when you are hit in the
4:13face. For that reason alone, most people
4:15would benefit from being far more
4:17conservative than they think at first
4:19blush. It sounds really easy and macho
4:21to think that you could weather a 50%
4:23drawdown. But if your risk rules allow
4:25you to get there, experiencing it is a
4:28whole different thing. You might be in a
4:30multi-day or multi-week or even
4:32multi-month slump. Your confidence might
4:35be shattered and your psychology shaken.
4:37How well will your actual
4:38decision-making be and how severely
4:41impacted will your normal life,
4:42psychology, and emotions be if you reach
4:45that point? Trust me, as someone who has
4:47taken some big losses and some big
4:49drawdowns, so much of developing as a
4:51trader is about minimizing those periods
4:54while maximizing time spent in positive
4:57feedback loops where you are making
4:58continuous progress and feeling
5:00motivated. This is where the concept of
5:02risk of ruin becomes so important. A
5:04drawdown does not need to wipe out your
5:06account to fundamentally damage your
5:08ability to perform. A loss large enough
5:10to destroy your confidence, impair your
5:12decision-making, and strain important
5:14relationships, or create chronic stress
5:16can be almost as damaging as a financial
5:19blowup itself. The first goal of trading
5:21is not getting rich. It is survival.
5:23Most traders never even make it to the
5:25point where skill can compound because
5:27they blow themselves up first. Trading
5:29is one of the few professions where a
5:30single catastrophic mistake can erase
5:33years of progress. The market only has
5:35to kill you once. What makes drawdowns
5:37so dangerous is that recovery math
5:39becomes exponentially harder the deeper
5:42the loss gets. A 50% drawdown requires a
5:46100% return just to get back to break
5:49even. An 80% loss requires a 400% gain,
5:53and a 90% loss requires 900%.
5:56Most people intellectually understand
5:58this, but very few emotionally respect
6:01how devastating those large losses
6:02really are. This is also why leverage
6:05destroys so many traders. Leverage
6:06magnifies not only returns, but the
6:09probability of ruin. Most traders
6:11drastically underestimate drawdown risk
6:13because during good periods compounding
6:16feels magical. But compounding works
6:17both ways. Just as gains can snowball
6:20upward, losses can spiral downward with
6:22equal force. The problem is that once
6:25losses get too large, mathematics starts
6:27working against you in an awfully brutal
6:30fashion. Many of these ideas are
6:31reflected in concepts like the Kelly
6:33criterion, which is essentially attempts
6:35to determine the mathematically optimal
6:37amount of capital to risk based on edge
6:40and probability. We will get deeper into
6:42that formula later, but the key takeaway
6:44is not the formula itself, but the
6:46principle underneath it. Overbetting can
6:48kill you. Even if you have a real
6:50advantage, sizing too aggressively
6:52introduces such large volatility and
6:54drawdown risk that the odds of eventual
6:57ruin skyrocket. Ironically, many traders
6:59blow up at near peak confidence, not
7:02peak fear. After large winning streaks,
7:03people begin extrapolating recent
7:05success indefinitely into the future.
7:07Risk feels lower precisely when it's
7:09often the highest. That's when our
7:11position sizes expand, our discipline
7:13weakens, and traders begin believing
7:15they are safer than they really are.
7:17That combination of leverage,
7:18confidence, and complacency is what
7:20wipes out many otherwise talented
7:22traders. Once you've decided though what
7:24your unacceptable outcomes are, that's
7:26the first step, and then you can then
7:28start to set risk rules around them. One
7:30of the most important things to
7:32understand about risk management is that
7:34it is inherently iterative. No trader
7:37sits down on day one and magically
7:39constructs the the framework. Risk
7:41management is refined over time through
7:43experience, mistakes, observation, and
7:46adaptation. Some lessons come from
7:48paying your own tuition. You're taking
7:49losses, you're violating our rules, and
7:51you run into risks that you weren't even
7:53yet aware existed. But, the truly
7:55intelligent traders also learn from the
7:57mistakes of others so that they do not
8:00need to personally experience every
8:01catastrophic outcome themselves. Every
8:04major blowup in market history contains
8:06lessons. Every trader who imploded from
8:08leverage, emotional decision-making,
8:10concentration risk, ego, or complacency,
8:12they leave behind warnings for those
8:14willing to study them. Over time, good
8:16risk management becomes less about
8:18theory and more about pattern
8:19recognition. You begin identifying which
8:22situations historically lead to
8:23disaster, both in yourself and in
8:25others, and then you slowly build rules
8:27and safeguards around those
8:29vulnerabilities. In many ways, risk
8:31management is a process of continually
8:33discovering where you are fragile, and
8:35then systematically reinforcing those
8:37weaknesses before they become fatal. To
8:39use the phrase of Nassim Taleb, the best
8:42traders are anti-fragile. Their losses
8:44don't ruin them, and in fact, their
8:46losses make them stronger because they
8:48learn from them and adapt. This is one
8:50reason I believe that studying both
8:52successful traders and failed traders is
8:54so valuable. The market is constantly
8:56showing us examples of risks we have not
8:58yet considered. We can either learn
9:00those lessons cheaply through
9:01observation or expensively through
9:03experience. Now that we've established
9:05what risk management actually is, why
9:07it's personal, and what outcomes are
9:09trying to avoid, and why risk management
9:11is a constantly evolving process, let's
9:13start building the actual framework
9:15itself. I break risk management into two
9:17categories: offensive risk management
9:20and defensive risk management. We're
9:21going to start with defensive. The most
9:23common defensive tool in the toolkit for
9:25traders is setting hard loss limits and
9:28guardrails around the outcomes that are
9:30unacceptable to us. The best traders and
9:32institutions build systems and rules
9:35that reduce the probability of
9:36catastrophic mistakes occurring in the
9:38first place. If it is good enough for
9:40Jane Street or Citadel or Point72, why
9:43do you think it should not be utilized
9:44by you as well? Essential to these
9:46guardrails for the retail trader is
9:48setting hard daily and weekly drawdown
9:51limits. At a certain point, losses begin
9:53affecting psychology, objectivity, and
9:56your decision quality. A trader who's
9:58deeply frustrated, tilted, or revenge
10:00trading is no longer operating with the
10:02same expected value as they normally
10:04would. Because of this, many traders
10:05create predefined rules around maximum
10:08daily loss, maximum weekly drawdown, or
10:10mandatory cooling off periods after
10:13large losses. The purpose is not just
10:15about protecting capital. It's
10:17protecting decision-making quality
10:19during periods where emotions begin
10:21compounding risk. Professional
10:23frameworks also create rules around
10:25position sizing and aggregate exposure.
10:27This includes maximum position caps,
10:29maximum percentage of account exposure
10:31per trade, and limits on how much total
10:33capital can be concentrated traded one
10:35theme, sector, or correlated group of
10:37positions. A proper framework therefore
10:40sets rules not just around individual
10:42position size, but also around total
10:44exposure to different risks like
10:45overnight risk or event risk. A truly
10:47professional framework also includes
10:49rules around mental and physical state.
10:51This is an area retail traders often
10:53completely ignore despite it being
10:55massively important. Many elite traders
10:57create filters around sleep, fatigue,
10:59illness, emotional stress, distraction,
11:02or psychological instability because
11:04they recognize their decision-making
11:05quality materially deteriorates under
11:08those conditions. Some traders, like
11:10myself, reduce size or avoid trading
11:13altogether after poor sleep. The core
11:15principle is recognizing that risk is
11:17not purely market-based. This is why
11:19institutional firms and prop firms often
11:21implement layers of controls far beyond
11:23simple stop losses. Some firms have
11:25automatic lockouts after certain
11:27drawdowns, others enforce strict
11:29concentration limits, exposure caps,
11:31overnight restrictions, or mandatory
11:33risk reviews. These systems exist
11:35because even highly skilled traders are
11:36still human beings vulnerable to
11:38emotion, overconfidence, fatigue, and
11:41poor judgment under stress. Again, if
11:43some of the best institutional trading
11:45firms in the world are using these
11:46practices, why as a lone retail trader
11:49are you not doing everything in your
11:50power to emulate that environment? The
11:52goal of these risk rules is not simply
11:54to define how much you can lose, but to
11:56determine exactly what actions you will
11:58take if and when those limits are
12:00reached. The more objective and
12:01rule-based the framework is, the easier
12:03it becomes to follow. Here are two basic
12:06examples of what these rules might look
12:07like. For example, an intraday trader
12:10might have a daily loss limit of $2,500,
12:12a weekly loss limit of $7,500, and a
12:15monthly loss limit of 15 grand. Their
12:17rules could state that if they lose
12:19$1,500 in a day, they must immediately
12:21cut all position sizes by 50%. If they
12:24reach their $2,500 daily loss limit,
12:26they must close all positions and stop
12:28trading for the remainder of the day.
12:30And if they reach their weekly loss
12:31limit, they must trade at half size for
12:33the following week while reviewing their
12:34trades and identifying mistakes. If they
12:37reach their monthly loss limit, they
12:38must stop trading entirely for several
12:40days, conduct a thorough review of their
12:42performance, and return with minimum
12:44size until they demonstrate consistency
12:46again. Because this trader specializes
12:48in intraday trading, they may also have
12:50a rule that no positions can be held
12:52overnight under any circumstances. A
12:54swing trader may use a different
12:56framework because overnight exposure is
12:58a core part of their strategy. For
12:59example, they might allow 5% drawdown
13:02from their portfolio high before taking
13:04defensive action, and a 10% drawdown
13:06before entering a full risk reduction
13:08mode. Their rules could state that if
13:10the portfolio declines by 5%, all
13:12positions must immediately be reduced by
13:1450%. If the drawdown reaches 10%, they
13:16must exit all non-core positions, move
13:19primarily to cash, and spend time
13:20reassessing market conditions before
13:23putting significant risk back on. Swing
13:25traders may also have overnight exposure
13:27rules stating that no single position
13:29can exceed 20% of the portfolio and that
13:31total overnight exposure cannot exceed
13:33100% of account equity. If either limit
13:36is breached, positions must be reduced
13:38before the market closes. They may also
13:40require themselves to cut overnight
13:41exposure by half ahead of major events
13:44such as earnings, FOMC meetings, or
13:46elections. Notice that these frameworks
13:47are built around specific if-then rules.
13:50If a certain loss threshold is reached,
13:52a predefined action automatically
13:54follows. This removes discretion during
13:56periods of stress and protects traders
13:58from emotional decision-making. It
14:00ensures that a temporary setback does
14:02not become a career-threatening
14:03drawdown. Note that even the different
14:05needs of a purely intraday trader versus
14:07a swing trader highlights just how
14:09customized a risk process needs to be.
14:11Before we move on, I want to introduce
14:13one concept that has become increasingly
14:15important in my own trading. Having a
14:17hierarchy of risk rules. Not all risk
14:20rules are equally important. Some rules
14:22are flexible, others are not, and under
14:25standing the difference can be critical.
14:26Part of what makes the topic of risk
14:28management so complex is that the
14:29dynamic nature of markets requires
14:32traders to have a lot of flexibility in
14:34their rules. Part of our advantage as a
14:36discretionary trader over systematic
14:38traders is that we can respond quicker
14:41and more effectively to situations that
14:43might not have been seen before. That is
14:45why I think an optimal risk management
14:47system has a hierarchy of risk rules
14:49with some being far more flexible than
14:51others and some rules being truly
14:53unbreakable if you want to protect
14:55yourself from ruin. On that lower
14:57hierarchy of risk rules, there are
14:59absolutely times in a trade where I
15:01might move my stop or not have a stop or
15:03there might even be days where I
15:05increase my risk beyond my predefined
15:07risk limit. A certain level of
15:09flexibility is needed to adapt and
15:11maximally capitalize. But there are
15:13other rules that I am dramatically less
15:15flexible on. These are the rules
15:17designed to prevent the unacceptable
15:18outcomes. These are the account survival
15:20rules around maximum drawdowns and
15:22avoiding catastrophic losses. In other
15:25words, I'm comfortable being flexible
15:27where mistakes are recoverable if it
15:29allows me to better capitalize on
15:30discretionary situations. What I don't
15:33want is that flexibility bleeding into
15:35the bigger picture rules that protect me
15:37from myself. I am not comfortable being
15:39flexible where mistakes can be
15:41existential. The goal of risk management
15:43should not be to eliminate discretion.
15:45The goal is to make sure discretion
15:47never becomes catastrophic. With that
15:49higher-level understanding of risk
15:51rules, let's now dig down to our
15:53day-to-day risk management tools. Up to
15:55this point, we've largely been
15:56discussing risk management at the
15:58account and framework level. We've
15:59talked about defining unacceptable
16:01outcomes, understanding risk of ruin,
16:03and creating larger picture rules that
16:05protect us from ourselves. But
16:07eventually, every trader arrives at the
16:09trade level. And once we get to the
16:10trade level, one of the most common risk
16:12management tools is the stop-loss. A
16:14stop-loss is the trigger that will lead
16:16you to exit your position and lock in
16:18your loss. As you might imagine,
16:20stop-losses are one of the most
16:21universal topics in all of trading. Most
16:23traders utilize them on every trade they
16:25take. In fact, one of the most famous
16:27risk management quotes on stop-losses
16:29comes from Bruce Kovner in Market
16:31Wizards. "Whenever I enter a position, I
16:33have a predetermined stop. I know where
16:36I'm getting out before I get in. It's
16:37the only way I can sleep." One of the
16:39most important distinctions in trading
16:41risk management is a difference between
16:43a mental stop-loss and a hard stop-loss.
16:45A hard stop-loss is an actual order
16:47entered into the market that will
16:49automatically exit your position once
16:51price reaches a predefined level. A
16:53mental stop-loss, on the other hand, is
16:55discretionary. You're telling yourself
16:56that you intend to get out at a certain
16:58price, but no actual order exists in the
17:01market. The execution relies entirely on
17:03your discipline, emotional control,
17:06reaction speed, and ability to process
17:08information in real time. Neither is
17:10inherently correct in every situation.
17:12Hard stops provide certainty and
17:14protection against hesitation, emotional
17:16paralysis, or catastrophic tail events.
17:19They are especially valuable for newer
17:21traders, highly emotional traders, or
17:23situations where one cannot actively
17:25monitor positions. However, hard stops
17:28can also expose you to temporary
17:29dislocations and situations where you
17:31are mechanically removed from an
17:33otherwise valid trade. Mental stops
17:35offer flexibility. They allow
17:37experienced traders to interpret the
17:38context, tape, liquidity, and news flow
17:41before exiting. Sometimes a level
17:43briefly trades through and immediately
17:45reclaims. Sometimes the manner in which
17:47a level breaks matters more than the
17:49level itself. A trader using mental
17:51stops may avoid unnecessary exits and
17:53improve overall expectancy. The problem
17:55is that mental stops require extremely
17:58high levels of discipline because the
17:59human brain is exceptionally good at
18:02rationalizing losses once money's on the
18:04line. Many traders claim to use mental
18:06stops when in reality they simply do not
18:08have stops. Regardless of whether the
18:10stop is mental or hard, the critical
18:12concept is that every professional trade
18:14should generally have a predefined point
18:16where the trade thesis is invalidated.
18:18Without that point, you cannot truly
18:20quantify your risk. And if you cannot
18:22quantify risk, you cannot properly
18:24calculate expected value. Expected value
18:26in trading is essentially the
18:27mathematical expectation of a trade over
18:30many repetitions. What makes stop losses
18:32so important is that your loss when
18:33wrong is often the one variable you can
18:36know with relatively high confidence
18:38before entering the trade. Your
18:39potential reward is almost always an
18:42estimate. Your win rate is often an
18:44estimate. But if you define your stop
18:46properly, you can usually know very
18:48closely what you stand to lose if the
18:49setup fails. That is huge because it
18:51allows position sizing to become more
18:54objective. If you know your stop is $1
18:56away, and you're willing to risk $500,
18:59then your size becomes straightforward.
19:01You need 500 shares. If your stop
19:03suddenly widens to $5, your position
19:05size must shrink accordingly. You only
19:07need 100 shares. The stop is what
19:09converts abstract trade ideas into
19:11measurable risk. In many ways, this is
19:14why technical analysis and expected
19:16value are so deeply connected. Charts
19:18are not just random drawings. Good
19:20technical setups help define logical
19:22invalidation points, and those points
19:24are, from a theoretical perspective,
19:26where your expected value goes negative.
19:28As traders, we never ever want to have
19:31any exposure when expected value is
19:33negative. If you don't understand that,
19:35make sure you check out this video I
19:36made on the subject. I'd be remiss if I
19:38didn't mention one other type of stop
19:40some traders use, a time stop. A time
19:42stop is a risk management rule where you
19:44exit a trade not because price hit your
19:46stop loss, but because the trade has not
19:48worked within the expected amount of
19:49time. In other words, if this setup is
19:52valid, it should start working by X
19:54amount of time. If it doesn't, I'm out.
19:56A normal stop answers, "How much price
19:58pain am I willing to take?" Whereas a
20:00time stop answers, "How long am I
20:02willing to wait for the thesis to prove
20:04itself?" The reason why time stops
20:05matter is that many good trades should
20:07have a certain pace, particularly in
20:09breaking breaking news trades. My thesis
20:11is that the news is a huge deal. If the
20:13market isn't catching on within minutes,
20:15I'll often exit rather than wait for my
20:17stop. Similarly, one of my most
20:19important trading heuristics is that
20:21your best trades work immediately. If a
20:23trade isn't working at all, over time I
20:25do start to reduce size or just cut it.
20:27So, in a small subset of trades, I do
20:29use time stops. So, does that mean you
20:32always need to use a stop? Well,
20:34actually no. Even this is personal.
20:36Fundamental value investors like Warren
20:38Buffett and even famous traders like
20:40Market Wizard Chris Camillo do not use
20:42price stops. Instead, their stop is if
20:45their thesis is disproved rather than a
20:47certain dollar loss amount. Before I
20:48move on to position sizing, though, it's
20:50important to recognize that stop losses
20:52are not perfect. In practice, markets
20:54can have price gaps, halts, breaking
20:56news, and misfills. Sometimes we find
20:59ourselves in situations where the market
21:00is already moved dramatically beyond our
21:02intended risk level. That raises an
21:04important question. George Coyle,
21:06co-author of the recent Market Wizards
21:08book that I was featured in, asked me
21:09this. What do you do if price blows way
21:11past your stop? The reality of trading
21:13is that this can occur for any
21:15assortment of reasons. So, what does one
21:17do? I think most people would assume my
21:19answer is that you get out, no questions
21:21asked. However, that would be wrong.
21:23There are times where you are caught
21:25offsides. But, closing out the trade at
21:27a certain price might genuinely feel
21:29crazy and actually have immense negative
21:32expected value. In an optimal world,
21:34expected value should drive every
21:36trading decision we make. So, if we gap
21:38way down and massively overshoot my
21:40stop, but I would actually be buying the
21:42stock if I were flat, why would I
21:44automatically want to sell? The one
21:46disclaimer to this is if it violates a
21:48larger overarching risk rule, meaning
21:50the trade going further against you
21:52would create a loss that you simply are
21:53not willing to take. In practical terms,
21:55assuming that is not the current
21:57situation, I try my best to imagine I am
21:59completely flat the position and then
22:01objectively handicap the expected value
22:03from that point forward. If I genuinely
22:05believe the expected value is hugely
22:07positive, I may continue holding
22:09position or even increase my size.
22:11However, I will establish a new hard
22:13stop based on the amount of additional
22:15risk I'm willing to tolerate. In other
22:17words, the original stop may have
22:18failed, but that does not mean risk
22:20management disappears. This is one of
22:22the reasons why I spent so much time
22:24earlier discussing larger account level
22:26risk rules and the hierarchy. In my
22:27mind, there's a huge difference between
22:29violating a trade level rule and
22:31violating an account level rule. I may
22:33be flexible on trade management if
22:34expected value justifies it, but I am
22:37far less flexible when it comes to rules
22:39designed to protect my psychology, my
22:41capital, and my long-term survival.
22:43That's the beauty though of this topic.
22:45In practice, these situations are
22:46personal and complex. Risk management is
22:48rarely as simple as blindly following a
22:50checklist. If we can't always rely on
22:52stop-losses, that poses another
22:54question. What other tools or concepts
22:56can we utilize to keep ourselves safe?
22:58The next one I want to present is
22:59position sizing. A stop-loss helps
23:01define risk. Position sizing determines
23:04whether that risk is survivable. If
23:06you're properly sized, gaps, halts, and
23:08unexpected adverse events are usually
23:10survivable. If you're improperly sized,
23:12even the best stop-loss in the world may
23:15not save you. As important as
23:16stop-losses are, I would argue that
23:18position sizing is actually the more
23:20powerful risk management tool. In fact,
23:22those successful traders and investors
23:23like Buffett and Chris Camillo that
23:25don't even use traditional stop-losses,
23:27they use position sizing. This is
23:29because position sizing determines how
23:31much damage a mistake can do before it
23:32ever occurs. Position sizing is one of
23:34the single most important risk
23:36management tools in trading because no
23:37matter how skilled you are, no matter
23:39how good your setup is, no matter how
23:41much research you have done, you are
23:43never eliminating risk. Markets are full
23:45of risks that exist beyond your stop.
23:47You're always exposed to variables you
23:49cannot fully control. Halt risk, gap
23:51risk, and more. It's important to note,
23:52these are not black swan events. These
23:55are normal market realities. Traders
23:57often think catastrophic outcomes only
23:59happen once every decade. But, severe
24:01slippage, violent gaps, and halted names
24:03happen far more frequently than most
24:05inexperienced participants realize,
24:07which is precisely why position sizing
24:09matters so much. Position sizing is what
24:11determines whether an unexpected event
24:13becomes survivable or career-ending. A
24:16trader who's oversized can be correct on
24:18their thesis and still blow up because
24:19the path the market took was too violent
24:22for their account to withstand.
24:23Meanwhile, a properly sized trader can
24:25survive adverse outcomes, even the black
24:27swans, long enough for their edge to
24:30play out over hundreds or thousands of
24:32trades. Almost any position can be made
24:34safer by making it smaller. Likewise,
24:36almost any position can be made
24:38dangerous by making it large enough. One
24:40general rule regarding position sizing
24:42is that as traders, we need to be far
24:43more conservative when sizing our shorts
24:45versus our longs. Let me explain. One of
24:48the realities of long-only trading is
24:50that even if a trader does not use a
24:51hard price stop, they can still
24:53theoretically quantify maximum risk in
24:55an extremely conservative way. Why?
24:57Because this stock can only go to zero.
24:59If you buy $10,000 worth of a stock,
25:01your worst possible outcome is losing
25:03that $10,000. That may still be
25:05catastrophic depending on account size,
25:07but importantly, the downside is finite
25:10and mathematically knowable. In other
25:11words, even without a predefined stop
25:13loss, a long only trader can always size
25:16positions under the assumption that the
25:18stock could completely collapse. That
25:20possibility is precisely why long only
25:22exposure, while dangerous, is still
25:25fundamentally more controllable from a
25:27tail risk perspective than short
25:28selling. Short selling completely
25:30changes this equation. When you short a
25:32stock, your gains are capped at 100%,
25:34but your losses are theoretically
25:36infinite because the stock can continue
25:38rising indefinitely. Many inexperienced
25:40traders hear that phrase and dismiss it
25:42as some abstract textbook concept. It is
25:44not abstract at all. Markets have
25:46repeatedly demonstrated that upside
25:48dislocations can become so violent that
25:51price totally breaks from reality and
25:53can blow your account in a blink. This
25:55becomes especially dangerous shorting
25:57micro caps where liquidity is thin and
25:59reflexive squeezes can feed on
26:01themselves. We have seen names like the
26:03ticker ZJYL gap hundreds of percent
26:05higher in shockingly short periods of
26:07time. These were not just funny charts
26:09on social media. These events blew up
26:11traders, bankrupted accounts, and
26:13severely crippled even some highly
26:14experienced traders. I personally know a
26:16handful of traders whose careers and
26:18financial lives were materially damaged
26:21by moves like these. And importantly,
26:23this danger is not isolated to obscure
26:25penny stocks. Even larger market cap
26:27companies can become extraordinarily
26:29dangerous on the short side. Avis Budget
26:31Group became one of the most recent
26:33examples of a modern squeeze where
26:35momentum, limited float dynamics, and
26:37forced covering created a near vertical
26:39move. More broadly, any company has some
26:41news that could catapult the stock
26:43multiples higher where any company can
26:45theoretically receive a buyout offer at
26:47a huge premium to its prevailing market
26:49value. A stock trading at $5 can
26:51suddenly open at 15, 30, or even higher
26:54with absolutely no opportunity to exit
26:56beforehand. This is why shorting is
26:58always magnitudes more dangerous and
27:00complex than simply being long stock.
27:02Longs have capped downside and unlimited
27:04upside. Shorts have capped upside and
27:07theoretically unlimited downside. That
27:09asymmetry fundamentally changes how risk
27:11management frameworks must be built. As
27:14traders scale larger over time, this
27:16becomes even more important. Small tail
27:18risks that are survivable at lower size
27:20can become existential threats when
27:22leverage and larger sizing are
27:23introduced. Many traders appear highly
27:25successful for years while quietly
27:27carrying enormous hidden tail exposure
27:30until one abnormal event permanently
27:32wiped out a massive percent of their
27:34capital. This is why the best risk
27:36managers obsess over survival. They
27:38understand that trading is not merely
27:40about returns. It's about ensuring that
27:42no single event and no single position
27:44can permanently remove you from the
27:45game. There is one more defensive tool I
27:47want to emphasize. I'd say it really
27:49might be the most powerful tool for the
27:51retail trader. Most traders think of
27:52risk management purely through the lens
27:54of stop losses, position sizing, or
27:56portfolio exposure. But wiring out
27:58profits might be one of the most
28:00overlooked forms of risk management for
28:02retail traders. The trader graveyard is
28:04full of tens of thousands of people who
28:06found initial success in markets, became
28:08overconfident, and never wired out funds
28:11to diversify away from just their
28:13trading risk. Money inside a trading
28:15account is psychologically different
28:16from money outside of it. A common
28:18phrase in trading is that unrealized
28:20profits don't count until you close the
28:22position. A corollary of that should be
28:24that profits don't count until you've
28:26either been paid out on them if you're
28:27at a prop firm, or wired that money out
28:29of the account, because it is still at
28:31risk, especially for retail traders. One
28:33bad day or one bad trade can wipe out
28:36years of progress. That's why wiring out
28:37profits can be such an important tool.
28:39Once capital leaves the trading account
28:41and is moved into passive investments or
28:43cash, that money is no longer directly
28:45exposed to your trading decisions. In
28:47many ways, wiring out profits creates a
28:49psychological firewall between your
28:51speculative self and your long-term
28:53financial future. Another benefit of
28:55wiring money out is that it is one of
28:56the few things that truly protects
28:58against black swan events. I mentioned
29:00position sizing earlier as one
29:02protection, but the truth is that any
29:04money in a trading account is
29:05theoretically at risk. By definition,
29:07you cannot fully eliminate black swan
29:09risk, but position sizing, wiring out
29:12profits, and being especially careful
29:13when shorting are among the best
29:15defenses available. Many successful
29:17traders, like my friend Alex Temes, who
29:19I interviewed in this video, have openly
29:21discussed how wiring out profits
29:22regularly has been one of the best
29:24decisions they ever made. Beyond the
29:26obvious financial protection, it creates
29:28enormous psychological stability. There
29:30is tremendous peace of mind in knowing
29:32that regardless of what happens
29:33tomorrow, a meaningful portion of your
29:35gains have already been permanently
29:36secured, your quality of life will not
29:38be impaired. That psychological
29:40stability is often underestimated by
29:42beginner traders. Traders who know they
29:45protected wealth outside the market
29:46often trade calmer, clearer, and more
29:48rationally. Ironically, having less
29:51capital in the account can sometimes
29:52improve decision-making because the
29:54trader is no longer subconsciously
29:56defending an ever-growing pile of
29:58unrealized financial gains and their
30:00identity. There's no universally correct
30:02framework for when traders should wire
30:03out profits because risk tolerance and
30:05account size, financial goals all
30:07differ. What do these wiring out rules
30:09look like in practice? Here are a few
30:11ideas. Withdraw all capital above a
30:13predetermined account size, withdraw 25%
30:16of profits at the end of every month, or
30:18withdraw 50% of any profits made above a
30:21new all-time high in account equity. And
30:23with those tools having been discussed,
30:24now we get to the fun part, the
30:26offensive side of risk management. Up
30:28until this point, we've largely been
30:29discussing defensive risk management,
30:31how we limit losses and protect our
30:33accounts from catastrophic outcomes.
30:35Those are all incredibly important
30:37questions, but they only represent half
30:39of risk management. The other half is
30:41maximizing our best opportunities. One
30:43of the biggest misconceptions in trading
30:45is that good risk management means
30:46always being conservative. In reality,
30:49that could not be further from the
30:50truth. Good risk management is not about
30:52minimizing risk at all costs. It's about
30:55allocating risk intelligently. Many
30:57struggling traders unknowingly play
30:59permanent defense. They become so
31:01focused on avoiding losses that they
31:03never properly capitalize on their
31:05biggest edges. They size everything
31:07similarly, hesitate in high conviction
31:09moments, and treat mediocre setups and
31:12elite setups almost identically. But, if
31:14your edge is real, that approach is
31:16mathematically flawed. As Mike
31:18Bellafiore of SMB Capital has emphasized
31:21for years to his traders, your job is
31:23not merely to avoid losses. Your job is
31:26to risk aggressively within your risk
31:28frameworks when your very best A+
31:30opportunities appear. Trading is not a
31:33game where equal risk should be
31:35allocated equally across all situations.
31:37The best traders understand that markets
31:40are highly asymmetrical. Most
31:42opportunities are mediocre. A small
31:44percentage are exceptional. And it is
31:46those exceptional situations that often
31:48drive the majority of long-term
31:50performance. Many of the traders with
31:52the best equity curves are not the
31:54traders who constantly play small.
31:56They're the traders who stay disciplined
31:58and controlled during average
31:59conditions, but become highly aggressive
32:01when high expected value opportunities
32:03emerge. They understand when conditions
32:06are unusually favorable and are willing
32:08to press hard when the probabilities
32:10shift in their favor. Poker offers an
32:13excellent analogy for this concept.
32:15Imagine you are an elite poker player
32:17who is always excessively conservative
32:20regardless of hand quality. Even when
32:21dealt pocket aces, statistically one of
32:24the strongest starting hands possible,
32:26you refuse to size up or press your
32:28advantage. Over time, despite playing
32:30safe, you will almost certainly lose
32:32because you are failing to maximize your
32:34expected value during your highest best
32:37situations. Professional poker players
32:39understand that survival alone is not
32:41enough. They must aggressively
32:43capitalize when probabilities are
32:45strongly in their favor because those
32:47moments disproportionately determine
32:49long-term profitability and trading is
32:51no different. If a trader risks the same
32:54amount on mediocre setups as they do on
32:56elite setups, they are failing to
32:58properly align capital allocation with
33:00expected value. In many ways, one of the
33:02defining characteristics of elite
33:04traders is not simply their ability to
33:06avoid bad situations, but their ability
33:09to recognize when conditions are
33:10extraordinarily favorable and
33:12meaningfully increase their exposure. Of
33:14course, this must always be within a
33:16robust risk management framework.
33:18Aggression without discipline is
33:20recklessness. The goal is not blind
33:23gambling or emotional oversized trading.
33:25The goal is calculated aggression backed
33:28by experience, preparation, statistical
33:30understanding, and defined downside.
33:33This is also why many traders struggle
33:35when they become overly traumatized by
33:37losses. They become so psychologically
33:39focused on defense that they lose the
33:41willingness to properly attack
33:43opportunity. But trading is not a sport
33:45where you can win purely by avoiding
33:47mistakes. At some point, you must score.
33:50The question then becomes, how much more
33:52should you risk when the opportunity is
33:54exceptional? That brings us to one of
33:56the most famous concepts in all of risk
33:58management, the Kelly criterion. If good
34:00risk management means taking full
34:02advantage of our best opportunities,
34:04then a natural question emerges. How
34:06much more should we actually risk?
34:08Shouldn't there be some mathematical
34:10formula that tells us exactly how much
34:12to bet? Many traders have asked this
34:13exact question and unsurprisingly, many
34:16quants have tried to answer it. One of
34:18the most famous quantitative position
34:20sizing models is this Kelly criterion,
34:22which attempts to calculate the
34:23mathematically optimal amount of capital
34:26to allocate to a trade based on an
34:28expected value. In theory, this sounds
34:30appealing. If you have a larger edge,
34:31you should risk more. If you have a
34:33smaller edge, you should risk less.
34:34Conceptually, I strongly agree with
34:36that. In fact, much of my own philosophy
34:38around risk management is built around
34:40the idea that larger edges deserve
34:42larger bets. The problem is that these
34:44formulas often break down in practice.
34:46First, they require estimating inputs
34:48such as win rates, payoff ratios, and
34:50expected value with the level of
34:52precision that most traders simply do
34:54not possess. Markets are constantly
34:56changing, and even small errors in these
34:57assumptions can lead to dramatically
35:00different sizing recommendations. More
35:02importantly, these formulas are rarely
35:04personalized to the individual trader. A
35:06position size that may be mathematically
35:08optimal for one person may be
35:10psychologically intolerable for another.
35:12Risk management is ultimately personal.
35:15Factors such as financial circumstances,
35:17your resilience and experience level,
35:19and your trading objectives all matter.
35:21A formula cannot adequately account for
35:23these differences. This highlights a
35:25broader challenge with many quantitative
35:27risk models. They often optimize for
35:29theoretical returns rather than actual
35:32real-world execution. A risk model is
35:34only useful if you can consistently
35:36follow it. And in practice though, this
35:38sizing creates drawdowns that cause
35:40fear, hesitation, and second-guessing,
35:42which leads to deviations from the plan.
35:44Then the formula has failed regardless
35:46of what the math says. This is one of
35:48the biggest reasons why I don't use any
35:50quantitative risk formulas in my own
35:52trading. While I appreciate the concepts
35:54behind them, I believe risk management
35:56is too personal and markets are too
35:58dynamic to be reduced to a single
36:00equation. Ultimately, I care far more
36:02about finding a sizing framework that I
36:04can actually execute consistently than
36:06one that is theoretically optimal on
36:08paper. A formula that works in a
36:10spreadsheet but breaks down in real life
36:12isn't particularly useful. Instead,
36:14position sizing should reflect both the
36:16opportunity and the individual taking
36:18the risk. And while I don't use formal
36:20quantitative risk formulas, I am a huge
36:22believer in something closely related,
36:24dynamic bet sizing, which is a topic I
36:26made especially popular for retail
36:28traders through Twitter. And this
36:30concept is that larger edges deserve
36:31larger bets. And I fully explain it in
36:34this video. In fact, one of the biggest
36:35mistakes traders make is treating every
36:37opportunity as though it deserves the
36:39same amount of risk. Markets don't work
36:41that way. Some opportunities have little
36:43edge, others have massive edge. And so
36:45if expected value varies across
36:46opportunities, then your position sizing
36:48should vary as well. One of the ways I
36:50personally implement this is through my
36:51daily report card process. Every day I
36:53evaluate the opportunity set in front of
36:56me and assign an overall risk level for
36:57the day. On slower days, I may be
36:59trading very small. On normal days, I
37:01may be trading my baseline size. And on
37:03highly opportunistic days, however, I
37:05may be risking dramatically more. In
37:08some situations, I might be risking 10
37:10times more than I would on a slow day.
37:12And in rare situations, I might even be
37:14risking 100 times more. Now, as you've
37:16probably gotten the feel of already,
37:18risk management is not always some
37:19perfect thing in practice. What happens
37:21when it's a slow day and out of nowhere
37:24something crazy happens? That's why
37:26practical risk management for traders
37:28often involves being flexible. My risk
37:30management has always involved a ton of
37:32subjectivity in real time and
37:34adaptability while also sticking to
37:36those bigger picture hard rules on
37:38losses and drawdowns. If opportunity
37:40suddenly explodes, I want the
37:42flexibility to increase risk. If
37:44conditions deteriorate, I want the
37:46flexibility to decrease risk. In other
37:48words, I don't mind using flexibility in
37:51intraday long as I'm not
37:54violating those bigger picture rules.
37:56This distinction is so important and
37:58it's something we'll revisit repeatedly
38:00throughout this video. Some risk
38:01management rules should be highly
38:02flexible, others should be almost
38:04completely rigid. And that brings us to
38:06another critical component of risk
38:07management, recognizing when the
38:09environment itself is changed. One of
38:11the most important and difficult skills
38:13traders must develop is recognizing when
38:14the environment calls for offense versus
38:16defense. Markets are not static.
38:18Conditions constantly evolve. There are
38:21periods where opportunity is abundant,
38:23volatility and moves are clean, and the
38:25liquidity is favorable to really sizing
38:27up. There are other periods where
38:28conditions are choppy, uh the moves are
38:31random and slow, and it's just simply
38:33incompatible with your trading strategy.
38:35Great risk management requires
38:37understanding that difference. Many
38:39traders make the mistake of trying to
38:40force offense in defensive environments.
38:43They feel pressure to produce daily P&L
38:45and maintain their consistency, or
38:46they're just emotionally trying to stay
38:48in the game. But, one of the harsh
38:49realities of trading is that there are
38:50periods where the best trade is no trade
38:53at all. Sometimes the highest expected
38:55value decision is simply sitting on your
38:57hands. This is especially true in slow
38:59markets or markets where your specific
39:01edge is absent. If you're an intraday
39:03momentum trader and nothing is moving
39:05cleanly, aggressively forcing trades may
39:07simply mean donating money through
39:09commissions and frustration and
39:10exhaustion. If all of a sudden your
39:12setup stop falling through, continuing
39:14to trade aggressively simply because
39:16you're accustomed to activity can be
39:18super destructive. Professional traders
39:20understand that preserving mental
39:22capital is just as important as
39:23preserving financial capital. In fact,
39:25sometimes the best form of risk
39:27management is shifting entirely from
39:28offense into research and development
39:30mode. Instead of forcing mediocre
39:32trades, traders can spend time reviewing
39:34tape, studying historical setups,
39:37refining their systems, and journaling
39:38their mistakes. You can even spend this
39:40time improving your watch lists, testing
39:42ideas, or just mentally resetting and
39:44taking a break. Those periods may not
39:46feel productive in the short term
39:48because no money's being made, but over
39:50the long run they're often critical to
39:51longevity and growth. This becomes even
39:54more important during slumps. One of the
39:55worst things traders can do during
39:57periods of poor performance is try to
39:59increase their trading activity in an
40:00attempt to immediately recover losses.
40:02When you lose confidence, so often
40:04traders begin overtrading. They search
40:07for certainty and a recovery that
40:08doesn't exist, and they start forcing
40:10setups. But, if the market environment
40:12is poor and the trader themselves is
40:14mentally compromised, that combination
40:16can just be so damaging. Sometimes
40:18defensive risk management means reducing
40:20size dramatically. Sometimes it means
40:22only taking A+ setups, and sometimes it
40:24means shortening your holding times. And
40:26sometimes it also means just not trading
40:28at all until conditions improve or your
40:30confidence is back. This is one reason
40:32many elite traders think in terms of
40:34market conditions rather than just the
40:36individual setup. They understand that
40:38edge expands and contracts over time.
40:40There are environments where pressing
40:41aggressively is appropriate because the
40:43market's rewarding that style. And there
40:45are environments where survival and
40:47patience matter way more than the
40:48short-term profits. The irony is that
40:51inactivity often feels psychologically
40:53harder than trading. Humans naturally
40:55want action, especially ambitious and
40:57competitive traders that are drawn to
40:58markets. But discipline is not merely
41:00the ability to execute trades.
41:02Discipline's also the ability to not
41:04trade when the conditions are
41:05unfavorable. Ultimately, strong risk
41:07management it's not about being
41:09permanently aggressive or permanently
41:11conservative. It's about adaptation. The
41:13best traders survive because they
41:14understand when to attack aggressively
41:17and when to preserve capital,
41:18confidence, and wait patiently for
41:20conditions to change. If this topic of
41:22bet sizing interests you, be sure to
41:24watch this long-form discussion I did
41:26with Kyle Williams. Now that we have
41:27discussed defensive risk management and
41:29offensive risk management, we now need
41:31to address the elephant in the room. Our
41:33psychology and how it affects our risk
41:35taking. Robust risk management systems
41:38are often designed just as much to
41:40protect traders from themselves as they
41:42are to protect us from the market.
41:43Markets are emotional environments that
41:45constantly trigger some of the strongest
41:47psychological biases humans possess. And
41:49the dangerous part is that these biases
41:51often become strongest precisely when
41:53risk is highest. Tilt is one of the
41:55clearest examples. After a frustrating
41:57loss or a missed opportunity, traders
42:00often enter emotionally compromised
42:02states where decision-making
42:03deteriorates. They begin forcing trades,
42:06revenge trading, and abandoning their
42:08process, prioritizing emotional relief
42:10over the expected value of their trades.
42:12The problem is that traders on tilt
42:14rarely realize they are tilted in real
42:16time. This is why professional risk
42:18systems often include daily loss limits,
42:20cool down periods, mandatory breaks, or
42:22reduced sizing after losses. The goal is
42:25not merely protecting the capital. It's
42:26protecting the trader from an emotional
42:28spiral. FOMO, or fear of missing out, is
42:31another major destroyer. Markets
42:33constantly create the illusion that
42:34massive opportunities are slipping away
42:36every minute. You end up chasing
42:38extended moves, you enter late, abandon
42:40your game plan. You size too
42:42aggressively because you can't
42:43emotionally tolerate watching others
42:45make money without you. Ironically, many
42:47of the worst losses that traders
42:49experience come not from their planned
42:51trades, but from emotionally reactive
42:52trades they were never supposed to take
42:54in the first place. Strong risk
42:56management frameworks recognize that
42:58protecting traders from impulsive trades
43:00is just as important as protecting them
43:02from bad analysis. Overconfidence may be
43:05even more dangerous because it often
43:06emerges during periods of success. After
43:09large winning streaks, traders begin
43:10unconsciously believing they're seeing
43:12the market more clearly. During this
43:14period, blowups often occur not after
43:16periods of struggle, but these periods
43:18of extraordinary success because success
43:20lowers psychological defenses. The
43:22trader stops fearing risk precisely when
43:25they should fear it most, which is why I
43:26dedicated this whole video to the
43:28subject. Anchoring is another incredibly
43:30destructive bias in trading. Traders
43:32anchor to prior account highs, their P&L
43:34levels, even just anchor to prior market
43:37prices. A trader who once had a $2
43:39million account may psychologically
43:40refuse to accept operating at $1.2
43:43million, even if objectively they are
43:44still wildly successful. This anchoring
43:47creates increasingly reckless behavior
43:49as traders attempt to get back to prior
43:51peaks. Similarly, we anchor to stock
43:53prices themselves. A stock that traded
43:55at 100 can feel cheap at $40 despite
43:58fundamentally changing conditions.
44:00Markets do not care where a stock used
44:02to trade. The comparison game has become
44:04dramatically worse in the social media
44:06era. Traders are constantly exposed to
44:07curated highlight reels of other traders
44:09making enormous gains, posting massive
44:12P&L screenshots, or catching perfect
44:14entries. This creates immense
44:15psychological pressure to force returns.
44:18Traders end up no longer trading their
44:20own account, their own risk tolerance,
44:21and their own edge. Instead, they begin
44:23subconsciously competing in a game they
44:25were never supposed to be playing. Risk
44:27management frameworks need to account
44:29for this because envy and insecurity can
44:31ruin you. Moving goalposts is another
44:33dangerous bias. Traders often believe
44:35that achieving a financial milestone
44:37will financially trade satisfaction or
44:39safety. "Oh, once I make my first 100K,
44:42then I'll reduce risk." But then it
44:43becomes 500K or a million, then 5
44:45million. The target always moves. As
44:47wealth increases, lifestyle creep and
44:49psychological normalization often
44:51increase alongside it. Traders who once
44:54would have protected life-changing money
44:55begin treating enormous sums casually
44:58because their perception adapts to their
45:00current reality. This is one reason many
45:02traders never meaningfully de-risk even
45:05after extraordinary success. Robust risk
45:07management systems exist because human
45:09beings are not naturally wired for this
45:12type of decision-making under
45:13uncertainty. Good risk systems create
45:15structures that protect you from periods
45:18where emotion, ego, and greed would
45:20otherwise distort your judgment. The
45:22best traders understand that risk
45:24management is not simply about
45:25protecting against bad markets. It is
45:27about protecting against the predictable
45:29psychological weaknesses that emerge
45:31when money and uncertainty collide.
45:33Anything that materially increases the
45:35probability of making poor decisions is
45:37ultimately a risk management issue. That
45:40is again why I utilize a daily report
45:42card to check in on myself and make sure
45:44my risk is adapting to my sleep and
45:46psychological situation as well as the
45:48market opportunity set. Once we
45:50understand all these concepts, we can
45:51finally start putting them together into
45:53a practical framework. At this point,
45:55we've covered a tremendous amount of
45:57ground. We've discussed stop losses,
45:59position sizing, drawdown, psychology,
46:01offensive and defensive risk management,
46:03and even when to adapt to changing
46:05market conditions. The natural question
46:07becomes, what does all of this actually
46:09look like in practice? So, let me walk
46:11you through a sample. Let's say I've
46:13done the reflections on my personal
46:14tolerances and current life situation.
46:16Blowing up an account is not an
46:18acceptable outcome for me. In fact, I've
46:20decided that I never want to lose more
46:21than 50% of my trading account. While I
46:23do want to be aggressive when there are
46:25good opportunities, I want to take as
46:27little existential risk as possible.
46:29From there, I'm now going to set daily
46:31and monthly loss limits. In 1 month, I
46:33don't want to lose more than 20% of my
46:34account. If I ever draw down more than
46:3620%, it means I must take an immediate
46:393-day break to cool off and study what
46:41has gone wrong. From there, I must
46:43reduce my trading size by 50%. If I lose
46:4510% more of my account, I must take a
46:481-week break. From a daily perspective,
46:50I never want to lose more than 10% of my
46:52account. Yes, that's pretty aggressive,
46:54but let's assume for this avatar that
46:55I'm a solid home run trader, and
46:57sometimes I'm okay swinging the bat
46:59hard. Additionally, I never want to have
47:00more than 50% of my account in any given
47:03trade, nor do I want 50% of my account
47:05exposed to any given theme. If it's a
47:07short position, I'll never have over 25%
47:10of my account in any given position, and
47:12I will never overnight a microcap stock
47:14that's more than 2% of my account. Other
47:16risk rules might include that I must
47:18complete a daily report card each
47:19morning before I start trading. If my
47:21subjective pre-market temperature check
47:23is a C, I will reduce my risk by 50%,
47:26and if my pre-market temp check is a D,
47:28I will reduce risk by 80%, and if it's
47:31an F, I'm not going to trade that day at
47:32all. I'm only going to do productive
47:34work or recover. I can then break down
47:36each of the stop losses for every
47:37strategy in my playbook. That way, I
47:39know exactly where my out is before I
47:41get in. At the end of each month, I will
47:43wire out 50% of my profits above my high
47:45water mark. Going through all these
47:47steps allows you to build a basic risk
47:49management foundation. To be clear, this
47:51is far from comprehensive, but it is a
47:53pretty solid start. As I said before,
47:55developing these rules will be an
47:57iterative process. Now, keep in mind
47:59that you never want risk management
48:00rules so complex that you can't follow
48:02them in real time. If you have a
48:03200-page rulebook with infinite window
48:05cases, you are never going to be able to
48:08apply that appropriately in the heat of
48:09the battle. There is a trade-off between
48:11having a robust system versus one that
48:13can account for literally every
48:15situation imaginable. You need to find
48:17the balance that works for you. The
48:18purpose of this example wasn't to give
48:20you the perfect framework. In fact, that
48:22would be impossible because, as we
48:23discussed throughout the video, risk
48:25management is personal. Your drawdown
48:26limits, position limits, sleep rules,
48:28and sizing may look completely different
48:30from mine. The point is not the exact
48:32numbers. The point is the process and
48:34the things to consider. You want to
48:35identify the outcomes that are
48:37unacceptable to you, build rules around
48:38those outcomes, and refine those rules
48:40through experience, and then continue
48:42adapting as both you and the market
48:44evolve. Which brings me to one of the
48:45most important points about risk
48:47management. If there's one thing I hope
48:48you take away from this video, it's that
48:50risk management is not about avoiding
48:52risk. Risk is unavoidable. This is true
48:54in trading and in life. The moment we
48:56decide to participate in markets, we are
48:57accepting uncertainty. We are accepting
48:59that losses will happen, drawdowns will
49:01happen, and we will make mistakes.
49:03Recently, it came out on social media
49:05that Chris Camillo had a 70% drawdown,
49:07and that Christian Kaelin Maggie had a
49:0950% drawdown. Many have asked my
49:11thoughts on those drawdowns. When I see
49:13something like this, it actually doesn't
49:15surprise me nor mean that much to me.
49:17For starters, there are traders that
49:18have had astronomical returns. They do
49:21that through aggressive bets and high
49:22risk tolerance. As an outsider, I don't
49:25know their risk rules, their goals, or
49:26their actions that brought them there.
49:28But, I do know that by definition, in
49:30order to win big, one must risk big as
49:33well. It's like when a trader asks me if
49:34leverage is good or bad. It's neither.
49:36It's just a magnifier once expected
49:38value. The only real question is whether
49:40it's being deployed in a way that, over
49:42the long run, is likely to serve the
49:43trader's goals. I also hope this video
49:46challenged the idea that risk management
49:47is purely defensive. Many traders think
49:50risk management is simply about avoiding
49:51losses, but some of the worst risk
49:53management I've ever seen comes from
49:54traders who never properly capitalize on
49:57their biggest opportunities. Trading is
49:59not a game where we win simply by
50:00avoiding mistakes. At some point we need
50:02to take risk. At the same time, one of
50:04the reasons risk management is so
50:06difficult is that it is never finished.
50:08Markets evolve and we evolve with it.
50:10Many of the best risk management rules I
50:12follow today came from mistakes that I
50:14made years ago. Others came from
50:15watching traders far smarter than me
50:17make mistakes of their own. Perhaps the
50:19most humbling realization of all of this
50:21is that some of the biggest losses in
50:22market history come from risks that
50:24people didn't even realize they were
50:26taking. It is often what you think you
50:28know, but don't actually understand that
50:30gets you into trouble. Ultimately, the
50:32purpose of risk management is longevity.
50:34The goal is not to maximize the outcome
50:36of a single trade, a single day, or even
50:39a single year. The goal is to survive
50:40long enough for skill, experience, and
50:42discipline, and your good decisions to
50:44compound over time. The best traders
50:46take losses, we all do. But the best
50:49traders also by definition, they're the
50:50traders who avoid the losses that take
50:52them out of the game entirely. If you
50:54can build a framework that protects you
50:55from catastrophe and allows you to adapt
50:57as conditions change, will give you
50:59confidence to press aggressively when
51:01exceptional opportunities emerge, you
51:03will be far ahead of the vast majority
51:05of market participants. Risk management
51:07isn't what prevents success in trading.
51:09Proper risk management is what makes
51:11long-term success possible in the first
51:13place. If you enjoyed this long-form
51:15solo deep dive, which I haven't done
51:16before, let me know in the comments and
51:18let me know what other topics you would
51:20like me to address. And this video, it
51:22actually took me an absurd amount of
51:24time to create. I asked you for what
51:26questions you wanted answered, and I
51:27incorporated all that feedback into the
51:29script. It took me dozens of hours. So,
51:32if you made it to the end, first of all,
51:33you are a serious trader and I respect
51:35that. Please return the favor and just
51:37do a subscribe or share this video on
51:39social. It took me so much time. Thank
51:42you for watching, and I'll see you in
51:43the next one.
51:52>> Mhm.

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