Glossary

What it means: How you split your money between different assets (example: 60% BTC, 40% cash).

What it means: Combining multiple separate measurements into one final reading.

How it’s done (conceptually): Each input is transformed into a comparable format, then combined using a fixed method (often weighting + averaging).

Example: If you have 10 different “market condition” inputs, aggregation is the step that turns those 10 numbers into one final indicator value.

Aggregation is usually done to reduce reliance on any single input that might be misleading on its own.

What it means: Any crypto asset that isn’t Bitcoin.

Beginner reality: Many altcoins are more volatile than BTC. They often outperform during strong bull phases, and they often drop harder in risk-off periods.

Practical implication: If you’re new, treat alt exposure carefully. High volatility is not only “upside”; it’s also deep drawdowns.

What it means: A data event that is unusual compared to normal behavior (for example, a one-day spike caused by a one-off event).

Why it matters: If you treat anomalies as “normal,” your indicator may overreact.

Example: One abnormal exchange event causes a sudden spike in a metric. An anomaly-aware system tries not to let that single event dominate the reading.

What it means: A reading that is allowed to appear on the dashboard only after review.

Why it matters: It aims to prevent accidental publishing of incorrect data or incomplete updates.

What it means:

• Ask: the lowest price someone is willing to sell for (what you pay when you buy instantly).
• Bid: the highest price someone is willing to buy for (what you receive when you sell instantly).
• Spread: the difference between ask and bid.

Why it matters: The spread is a “hidden cost” that hits you when you buy and then sell.

Example: If bid is 100 and ask is 101, the spread is 1. If you buy and immediately sell, you lose that gap (plus fees).

What it means: Making decisions based on stories, headlines, influencers, or emotions rather than a consistent rule set.

How it shows up in practice:

• Buying because “everyone is talking about it”
• Selling because of fear after a sharp drop

What “reducing bias” means here: Using the same decision rules even when emotions are high.

What it means: Buy an asset and hold it for long periods without actively trading.

What beginners underestimate: The emotional part. Even strong long-term assets can drop 50–80% in crypto.

How to use it safely: If you choose buy-and-hold, you need a risk level where you can tolerate major drawdowns without panic selling.

What it means: Something you compare performance against (commonly buy-and-hold BTC).

Why it matters: You can make money and still underperform your benchmark.

Example: Strategy returns +40% while BTC returns +70%. You still profited, but you didn’t beat BTC.

What it means: The overall “weather” of the market—not a single day’s move.

How to think about it: Even if an asset rallies today, the broader environment might still be weak over the next weeks/months.

What it means:

• Bull market: sustained upward cycle
• Bear market: sustained downward cycle

Beginner note: Crypto cycles often include violent counter-moves (bear market rallies, bull market corrections). That’s why clear rules help.

What it means: A price “summary” for a time period: Open, High, Low, Close.

How to think about it: It’s one package of information that says where price started, how far it moved, and where it ended.

Why close matters: Many strategies rely on the daily close to reduce noise and avoid reacting to temporary intraday spikes.

What it means: Protecting what you already have (avoiding large losses).

Why it matters in crypto: Big drawdowns can take a long time to recover from, even if the asset is strong long-term.

Practical mindset: “I want to stay in the game” beats “I want to win big this month.” in the long term.

What it means: Price moves up and down without a clear direction.

Why it matters: Sideways periods can trigger false entries and exits if you react too quickly to small moves.

What it means: Too much of your portfolio depends on one asset or one idea.

Example: If 90% of your portfolio is in one altcoin, a single event can dominate your results.

What it means: Many different measurements are pointing in the same direction.

How to interpret it correctly:

• High consensus = stronger alignment
• Why it can still “stall”: Markets can become overextended or enter sideways conditions even when inputs align strongly.

What it means: How similarly two assets move.

Why it matters: If everything is correlated, holding many assets may not reduce risk much.

Example: Many altcoins drop at the same time as BTC in risk-off events, the only difference is that they usually drop much harder.

What it means: When most of the crypto market tends to move with Bitcoin.

Why it matters: If the market is usually correlated to BTC, BTC can serve as the “reference asset” for broader conditions.

What “decouple” means: When some assets move differently from BTC (often late-cycle behavior).

What it means: Who controls the assets.

• Exchange custody: the exchange holds the keys
• Self-custody: you control the keys

Beginner implication: Convenience vs control. Self-custody reduces exchange risk, but increases personal responsibility.

• Custody: Where the assets are held (exchange vs self-custody).
• Control: Who can move the assets (you vs an institution).
• Execution: The act of placing the trade (you decide and place orders).

What it means: A simplified label that translates a number into an action-oriented category.

Why it helps: It prevents users from “over-reading” small number changes.

Example: Instead of arguing whether +0.19 is “almost bullish,” a state system makes it clear when the threshold is truly crossed.

What it means: Different “families” of information used to build a reading.

• Technical measures: derived from price/volume behavior (trend structure, momentum measures, volatility structure, etc.).
• Market sentiment: how optimistic/pessimistic participants appear (often via positioning/behavior proxies).
• Global macro: broader financial conditions outside crypto (liquidity conditions, rates, risk appetite).
• On-chain behavior: signals derived from blockchain activity (how coins move, holding patterns, network usage proxies).

Why multiple categories matter: One category can be “wrong” or noisy in certain conditions, while the others keep the system grounded.

What it means: Invest a fixed amount on a fixed schedule, regardless of price.

Plain meaning:
Instead of buying all at one price, you buy across many different prices. Your “average buy price” becomes a blend of those purchases, instead of one risky entry point.

One-liner you can remember:
With DCA, you automatically buy more units when price is lower and fewer units when price is higher—so your average entry becomes a blended middle.

• It’s easier to stick to. A simple recurring plan helps you build a position gradually without constant monitoring.
• It can lower the chance of panic buying (FOMO) during spikes, because you already have a plan.

What it solves: The “when do I buy?” problem.

What it means:
A structured version of DCA where you only buy in historically favorable “value zones,” and you do not buy at all when conditions are historically overextended (overheated zones). The goal is to deploy capital only when the risk/reward is statistically favorable.

How it differs from DCA:

• DCA: same amount each time, no matter what
• Tactical DCA: you buy only when predefined conditions show a high-value zone; you do not buy when conditions are overheated/overextended

Why Tactical DCA is far superior (in practice):
Regular DCA treats every price the same.
But markets don’t behave like that—there are periods where price is statistically stretched cheap (better long-term risk/reward) and periods where price is stretched expensive (worse long-term risk/reward).

Tactical DCA is superior because it:

• 1) Deploys capital only when the odds are better
  - You buy only when conditions are historically favorable, instead of spreading capital across both good and bad conditions.
• 2) Avoids feeding overheated markets completely
  - Regular DCA keeps buying even when price is extremely extended.
  - Tactical DCA does not buy at all during those conditions, which often improves your average entry and avoids regret buys.
• 3) Builds discipline where most people fail
  - Most people do the opposite emotionally: they buy after big pumps and stop buying after big drops.
  - Tactical DCA forces the opposite behavior: buying only in value zones and refusing to buy in overheated zones.

How to do it (practical example):
If conditions are “value,” buy $150 (or any amount your plan defines)
If conditions are overheated/overextended, buy $0

Key principle:
You must have a system with conditions which show clear high value versus low value zones.
Without that, Tactical DCA becomes guessing—which defeats the entire point.

What it means: A rule-based shift from “watching/partial exposure” to “entering” based on a threshold.

It’s about removing guesswork: “should I, shouldn’t I” debates and defining the moment your plan says “now we act.”

What it means: The drop from a peak portfolio value to a later low.

Why it matters: Most people quit during drawdowns, not because the plan is “wrong,” but because the pain is bigger than expected.

What it means:

• Entry: when you buy/add
• Exit: when you sell

Beginner issue: Many people plan entries but don’t plan exits, which leads to panic decisions later.

Practical tip: Decide in advance what conditions would make you reduce or step aside. (+0.2 entry, - 0.2 exit).

What it means: How well a signal performs when acted on at the intended time.

Why delays can reduce it: If the system is designed to be acted on soon after release, waiting can mean you enter after the best risk/reward window has passed.

Simple example: If a signal flips at the daily close and you wait days or sometimes even hours, the market may already have moved significantly, changing the risk profile.

What it means: Your portfolio value over time.

Why it matters:
Two strategies can end with the same return, but one can be far harder to follow due to deeper drawdowns or a rougher path.

Important crypto context (why equity curves matter even more in crypto):
Crypto equity curves are rarely a smooth, steady line upward.
Most of the time, crypto moves through long periods where “nothing happens” (sideways, choppy, slow grind), and then a large share of the total returns often shows up in a much shorter time window (sharp trending phases).

What this causes:

• Returns become “skewed” in time: a small window can generate a huge portion of the multi-month or multi-year gains.
• If you miss those windows, your long-term results can look dramatically worse—even if you were “in the market” for most of the year.
• Those quiet periods are where most people lose discipline (they get bored, doubt the plan, chase random trades, or stop following their rules right before the move).

Why this makes having good systems in place even more important:
A good system is designed to keep you positioned correctly through the boring phases and ready for the windows where the real returns tend to occur.
It reduces the chance you step aside at the wrong time, get chopped up by noise, or only re-enter after the move has already happened.

Example:
If most of a year’s gains come from a 6–10 week strong uptrend, then being correctly positioned during that window can matter more than what you do during the other 40+ weeks. That’s why the “shape” of the equity curve—and whether your approach reliably catches those key windows—matters as much as the final return.

What it means: A platform where you buy/sell crypto.

Beginner best practice: Use exchanges for buying/selling. Consider withdrawing long-term holdings to self-custody.

What it means: Costs charged when you trade or withdraw.

Why beginners should care: Small fees repeated often become meaningful.

Practical example: If you trade frequently, fees + spread + slippage quietly compound.

What it means: Buying because price is rapidly rising and you feel you’re “missing it.”

What it means: A signal that triggers, but the market does not follow through into a sustained move.

Why it’s normal in systematic approaches: Indicators react to probabilities, with uncertainty always present. Some signals will fail—especially in choppy periods.

How users handle it in practice: By following the same rules every time, rather than trying to “guess which one is real.”

What it means: Multiple data inputs point in the same direction.

What it means: Deploying the portion of capital you decided is meant to be “in the market,” rather than sitting in cash/stable assets.

Practical example: If your plan is “I invest 100% when conditions are supportive,” that is full allocation.

Important nuance: Full allocation does not mean “maximum leverage” or “maximum risk.” It just means “the plan says we’re in.”

What it means:

• Reading: the current value
• Threshold: a predefined level where interpretation changes

Why thresholds matter: They reduce subjective interpretation and decision drift.

What it means: Transaction fees on a blockchain network.

Practical impact: Fees vary by network and congestion. Always check fees before sending.

What it means: A data input that reflects broader financial conditions that can affect crypto.

Beginner-friendly way to think about it: Crypto doesn’t live in a bubble. Interest rates, liquidity, and risk appetite can influence demand for risk assets.

How it shows up: Sometimes crypto moves strongly when liquidity is easy, and struggles when liquidity tightens.

What it means: A device designed to store private keys offline.

Why it’s considered safer: It reduces exposure to malware and online attacks.

What it means: Inputs chosen because they are:

• measurable,
• consistent over time,
• harder to manipulate,
• and meaningfully related to market behavior.

What it’s trying to avoid: Building a system from random metrics that look good in one period but fail later.

What it means: Making portfolio choices because of news intensity rather than a plan.

Why it’s dangerous: Headlines peak at emotional moments—tops and bottoms are often emotionally loud.

What it means:

• Hot wallet: connected to internet (more convenient, higher risk)
• Cold wallet: offline (less convenient, lower risk)

Practical approach: Keep small amounts hot, long-term holdings cold.

• Buy on a reputable exchange.
• Enable strong 2FA (authenticator app is commonly preferred over SMS).
• Withdraw long-term holdings to a wallet you control.
• Store your seed phrase offline (never as a photo, note app, or cloud file).
• Test a small withdrawal first before moving larger amounts.

What it means: A computed value that summarizes market conditions according to a defined method.

Beginner note: It’s a tool for consistency. It does not remove risk.

What it means: The reading is scaled so negative values reflect one side of conditions and positive values reflect the other side.

How to interpret safely:

• The sign (negative/positive) suggests direction/condition
• The magnitude (how far from zero) suggests strength of agreement

Common mistake: Treating the number like a price target. It is a condition reading.

What it means:
Risk that is built into the asset class itself — even if you do everything “right.” It cannot be removed, but it can be minimized and controlled with better tools, or better discipline. You can manage it (position sizing, exit rules), not eliminate it.

Crypto example (true inherent risk):
You buy and hold Bitcoin with strong security, no leverage, and you never leave funds on a risky platform. Even then, Bitcoin can still drop 50–80% during a broad crypto bear market because crypto is structurally volatile and demand/liquidity can vanish quickly. That drawdown risk is inherent to the asset class.

How it’s different from other risk "types":

• Exchange hacks / frozen withdrawals = counterparty risk (you can reduce it with self-custody or better venue choice).
• Overleveraging / liquidations = execution/strategy risk (you can avoid by not using leverage).
• Market-wide deep drawdowns in BTC/crypto = inherent risk (you can’t remove it; you can only control exposure and rules).

What it means: Using different types of measurements so the indicator isn’t overly dependent on one “view” of the market.

Why it matters: If all inputs are basically the same thing, you get false confidence.

What it means: Identity verification required by many exchanges.

Why it exists: Compliance and anti-fraud.

What it means: The secret "keys", or passphrases that controls your crypto.

Beginner rule: If someone gets your private key or seed phrase, they can take your funds.

Always keep them stored away offline.

What it means: Using multiple signals together so one signal defines the “environment” and another refines timing or allocation.

Beginner-friendly explanation: One signal answers “should I be involved at all?” Another answers “how should I structure exposure while I’m involved?”

Why users do it: It can reduce emotional decision-making and create clearer boundaries.

What it means: How easily you can trade without moving the price.

Why it matters: Low liquidity increases slippage and makes trading more expensive.

• Market order: buys/sells immediately at current prices
• Limit order: sets your price; fills only if market reaches it

Beginner approach: Market orders are simple, but sometimes a bit more expensive (fees); limit orders can reduce slippage in some conditions and are usually cheaper (fees), but doesn't always trigger.

What it means:
Market structure is the way price movement is organized over time. It describes whether a market is generally moving upward, moving downward, moving sideways in a range, or transitioning between those states. A common way to describe this organization is by looking at sequences of swing highs and swing lows (turning points) over time.

Beginner version: Recognizing whether the market is trending, stalling, or breaking down.

How quant systems use market structure:
Quant systems typically do not “eyeball” highs/lows. They operationalize structure with rules so it can be measured consistently, for example:

• defining what counts as a swing high/low (turning point) using a fixed lookback rule,
• checking whether swing highs/lows are rising, falling, or mixed,
• confirming whether price is spending more time making progress in one direction (trend) or returning to the same zone (range).

The output is usually a simple classification like “uptrend / downtrend / range” used to guide exposure and risk rules.

Key beginner takeaway:
Market structure is the market’s “shape” over time: uptrend, downtrend, range, or transition. Investors use it to stay aligned with conditions instead of reacting to short-term noise.

What it means: After extreme movement, price often drifts back toward a more typical range (the mean).

Why it matters: Many “value zone” ideas rely on this tendency.

Important nuance: Mean reversion can take longer than people expect, and it doesn’t happen reliably on a short schedule.

What it means: A timeframe typically measured in weeks to months.

Why it matters: Many users get confused and expect immediate results. Medium-term tools are not designed for daily flipping.

What it means: Strength continuing in the same direction.

What it means: Conditions are not strongly supportive or strongly bearish based on the indicator’s inputs.

How users typically treat it: Reduce urgency. Stay prepared. Avoid forcing trades.

What it means: Adjusting data so values across different time periods can be compared fairly.

Common tool: Z-score.

What it means: Short-term movement that looks meaningful but is mostly random.

Beginner trap: Overreacting to noise leads to frequent unnecessary decisions.

What it means: Rules that do not change based on mood, opinions, or “feelings about the market.”

What it looks like in practice: The same input + same method produces the same output—no interpretation needed.

What it means: A metric comparing “good outcomes” to “bad outcomes” relative to a threshold.

You choose a threshold (also called a target or minimum acceptable return) such as 0%, a risk-free rate, or any return level you care about. Omega then compares:

• Gains above the threshold (how much returns exceed the target), to
• Losses below the threshold (how much returns fall short of the target),

using the full return distribution rather than only the average and volatility.

How to interpret Omega

• Ω > 1: more probability-weighted gains above the threshold than losses below it (better).
• Ω = 1: “balanced” around that threshold (gains and losses are similar in weight).
• Ω < 1: losses below the threshold outweigh gains above it (worse).

Important: Omega depends on the chosen threshold, so comparisons are only meaningful when you use the same threshold across assets/strategies.

What it means: A period where conditions suggest that a certain type of exposure (often higher risk) has better odds than usual.

Important nuance: An opportunity window still carries risk. It means risk/reward may be more favorable than normal.

What it means: An extreme data point that is unusually far from typical values.

Why it matters: Outliers can distort averages and standard deviations, which can distort signals.

What it means: A method to reduce the influence of extreme abnormal points in calculations.

Beginner value: It helps signals be less sensitive to one-off spikes.

What it means: Conditions where the market has moved far from typical levels and tends to carry higher reversal risk.

Practical context: Overextended markets can continue upward for longer than people expect.

What it means: How much you gained or lost.

How it’s calculated (basic):
P&L = Current value − Cost basis (minus fees)

Example: Buy $1,000 BTC, value becomes $1,250 → P&L +$250 before fees.

What it means: How large your exposure is.

Why it matters: Being right with huge size can still be emotionally impossible if volatility hits.

Beginner approach: Start smaller, increase only when you’ve proven you can follow the plan.

What it means: Everything you hold (crypto + cash and anything else).

What it means: A reading designed to reflect likelihood or supportive conditions, rather than certainty.

How to interpret it correctly:
It guides decisions under uncertainty

Why it’s useful: Without probability framing, most people drift into emotional guessing.

What it means: A temporary drop during a broader uptrend.

Why it matters: Many investors panic-sell during pullbacks even though pullbacks can be normal in uptrends.

What it means: A repeatable decision process defined in advance.

Why it helps: It reduces emotional decision-making.

What it means: Price moves sideways within a band for a while (up and down, but no strong direction).

Why this creates more false signals: Many indicators are designed to capture trend continuation. In ranges, the market repeatedly starts and stops.

What it means: Comparing assets to see which is performing better over a defined period.

Example: If ETH is up 40% while BTC is up 20% over the same period, ETH has stronger relative strength in that window.

What it means: What your capital can buy after a move, instead of how much you have numerically.

Example: If you rotate into something that holds value better during downturns, you may be able to re-enter risk assets later with more purchasing power.

What it means: Updating your portfolio to match a new allocation split.

How it's commonly done:

• Check the latest allocation split.
• Calculate how much money each asset should represent based on your total portfolio value.
• Buy and sell so your holdings match the new split.

What it means: How willing market participants are to take risk.

Beginner-friendly framing: When risk appetite is high, smaller and riskier assets often get more demand. When it’s low, people move toward safety.

What it means: Period when capital shifts away from risky assets.

What it means: A predefined “defensive place” to rotate into when conditions worsen.

Why it exists: In stress periods, people make poor decisions. A risk-off anchor is a pre-decided answer to “where do I go when I exit risk?”

What it means: Comparing what you might gain to what you might lose from a decision.

Simple example: If your upside is potentially large but the downside is limited by rules, risk-reward is more favorable.

Key point: Favorable risk-reward can still lose money—it means the tradeoff is more reasonable.

What it means: The backup that can restore your wallet.

Best practice: Store offline. Never photograph or store digitally.

What it means: You judge performance across many signals over time.

Why it matters: Beginners often quit after one or two false signals. Systematic approaches assume some signals will fail.

What it means: You receive a worse price than expected due to low liquidity or fast movement.

Sortino ratio is a risk-adjusted performance metric

What it means: A performance metric that measures return relative to downside volatility (harmful volatility).

Why it’s useful in crypto: Crypto has upside spikes and heavy downside tails. Sortino focuses on the downside “damage.”

It is similar to the Sharpe ratio, but with one key difference:

• Sharpe treats all volatility as “risk” (both upside and downside).
• Sortino measures risk using only downside volatility — meaning it focuses on returns that fall below a chosen target return.

This matters because most investors don’t view upside volatility as harmful. Sortino is designed to penalize only the part of volatility that represents falling short of the target.

Why we prefer Sortino in crypto (vs Sharpe)

1) Crypto often has large upside moves (and large downside moves)
Crypto can be very volatile. If you use Sharpe, strong upside volatility increases standard deviation and can reduce the Sharpe ratio — even if that volatility came from gains.

Sortino avoids penalizing upside volatility because it only measures deviations that fall below the target.

2) Sharpe treats “good volatility” and “bad volatility” the same
Sharpe uses total standard deviation, so it does not distinguish between:

• volatility from large gains, and
• volatility from losses or shortfalls

In markets with big swings (common in crypto), this can make Sharpe less aligned with how many investors define risk (downside outcomes).

3) Sortino focuses directly on downside outcomes
Sortino is built around downside deviation, which is specifically the behavior investors typically want to control:

• falling below the target return
• large negative outcomes (which are penalized more due to squaring)

So Sortino can be a more informative risk-adjusted metric when upside and downside volatility behave very differently.

Why we optimize for Sortino ratio

When we “optimize for Sortino,” we choose parameters that aim to increase:

(excess return above the target) ÷ (downside deviation)

In plain terms, that means we prefer approaches that:

• improve returns relative to the target, and/or
• reduce how often and how severely returns fall below the target

This optimization focus is specifically about improving the balance between reward and downside risk — not minimizing volatility in general.

What it means: Tokens designed to track (or are pegged to) a stable value (like USD).

Why exclusions matter in market cap data: Stablecoins can distort “risk appetite” readings because they behave differently than volatile assets.

What it means: A market move that typically plays out over weeks/months, where investors hold an asset over the medium term.

What it means:
A structured version of DCA where you only buy in historically favorable “value zones,” and you do not buy at all when conditions are historically overextended (overheated zones). The goal is to deploy capital only when the risk/reward is statistically favorable.

How it differs from DCA:

• DCA: same amount each time, no matter what
• Tactical DCA: you buy only when predefined conditions show a high-value zone; you do not buy when conditions are overheated/overextended

Why Tactical DCA is far superior (in practice):
Regular DCA treats every price the same.
But markets don’t behave like that—there are periods where price is statistically stretched cheap (better long-term risk/reward) and periods where price is stretched expensive (worse long-term risk/reward).

Tactical DCA is superior because it:

• 1) Deploys capital only when the odds are better
  - You buy only when conditions are historically favorable, instead of spreading capital across both good and bad conditions.
• 2) Avoids feeding overheated markets completely
  - Regular DCA keeps buying even when price is extremely extended.
  - Tactical DCA does not buy at all during those conditions, which often improves your average entry and avoids regret buys.
• 3) Builds discipline where most people fail
  - Most people do the opposite emotionally: they buy after big pumps and stop buying after big drops.
  - Tactical DCA forces the opposite behavior: buying only in value zones and refusing to buy in overheated zones.

How to do it (practical example):
If conditions are “value,” buy $150 (or any amount your plan defines)
If conditions are overheated/overextended, buy $0

Key principle:
You must have a system with conditions which show clear high value versus low value zones.
Without that, Tactical DCA becomes guessing—which defeats the entire point.

What it means: A predefined level that changes interpretation of a reading.

Why it matters: It removes ambiguity.

What it means: The period each candle represents (daily, weekly, etc.).

What it means: A phase where the market is shifting, but the data does not yet agree strongly on direction.

Practical implication: This is where many people get chopped up by over-trading.

What it means: A sustained directional move over time.

What it means: The individual metrics that feed into a final indicator.

Why users should care: Even if you don’t see the inputs, understanding that multiple things contribute helps you interpret “consensus” correctly.

What it means: A standardized reference time used globally.

Why it matters: It keeps daily readings consistent across time zones.

What it means: How much price moves up and down.

Practical implication: Higher volatility means bigger swings, which affects sizing and risk tolerance.

What it means: A range where conditions are statistically more favorable relative to history.

What it means: Tool that controls keys (software wallet or hardware wallet).

What it means: Risk that an exchange freezes withdrawals, is hacked, or fails.

What it means: Earning additional tokens by participating in a protocol or locking funds.

Beginner warning: Yield introduces risks (smart contract risk, custody risk, lockup risk).

What it means: A standardized way to show how far today’s value is from the historical average, measured in standard deviations.

Interpretation:

• Large negative Z: far below typical (often interpreted as “cheap” relative to history)
• Large positive Z: far above typical (often interpreted as “overheated” relative to history)

What it means: Buying more in defined favorable zones and less outside them, instead of guessing.