Market Depth

#Definition

Market depth measures the volume of buy and sell orders waiting at various price levels in a market's order book. Deep markets can absorb large trades with minimal price movement; shallow markets see significant price swings from relatively small orders.

In prediction markets, depth determines how much you can trade before your own orders start working against you. A market with strong depth on both sides provides reliable price signals, while a thin market's quoted probability may not survive even modest trading activity.

#Why It Matters in Prediction Markets

Market depth directly affects both trading costs and signal reliability.

For traders, depth determines execution quality. In a deep market, a $10,000 position might move the price by 0.5%. In a shallow market, the same order could push prices 10% or more, turning a profitable trade into a losing one through slippage.

For forecasters, depth indicates how seriously to take a market's probability estimate. A price of 70% backed by $500,000 in orders represents stronger collective conviction than the same price with only$ 5,000 supporting it.

For market efficiency, depth enables informed traders to correct mispricings. If correcting an obvious error requires accepting 5% slippage, the error persists longer than it should.

#How It Works

#Visualizing Depth

Market depth appears as layers of orders at progressively worse prices:

ASK SIDE (Sell Orders)
$0.65 → 5,000 shares
$0.63 → 3,000 shares
$0.61 → 2,000 shares
$0.60 → 500 shares    ← Best Ask

─────────────────────

$0.58 → 1,000 shares  ← Best Bid
$0.57 → 4,000 shares
$0.55 → 6,000 shares
$0.53 → 8,000 shares
BID SIDE (Buy Orders)

#Visualizing Market Depth

Note: The "Valley" in the middle is the spread. The "Walls" on either side represent depth.

#Depth Asymmetry

Markets often show uneven depth. In the example above:

Ask side depth: 10,500 shares within $0.05 of best ask
Bid side depth: 19,000 shares within $0.05 of best bid

This asymmetry suggests selling pressure would encounter more resistance than buying pressure. Large sell orders would push prices down faster than equivalent buy orders would push prices up.

#Calculating Price Impact

To estimate execution price for a large order, walk through the order book:

Example: Buying 4,000 shares

Step 1: Buy 500 @ $0.60 = $300
Step 2: Buy 2,000 @ $0.61 = $1,220
Step 3: Buy 1,500 @ $0.63 = $945
─────────────────────────────────
Total: 4,000 shares for $2,465
Average price: $0.616
Slippage: $0.016 per share (2.7%)

If you had expected to buy at the displayed price of $0.60, the actual cost is 2.7% higher.

#Price Impact Visual

#Python: Calculating Market Depth

A script to quantify how "thick" the order book is.

def calculate_depth_score(bids, asks, mid_price, range_pct=0.02):
    """
    Sum of order volume within 'range_pct' of the mid_price.
    """
    lower_bound = mid_price * (1 - range_pct)
    upper_bound = mid_price * (1 + range_pct)
    
    bid_depth = sum([vol for price, vol in bids if price >= lower_bound])
    ask_depth = sum([vol for price, vol in asks if price <= upper_bound])
    
    return {
        "bid_depth_value": bid_depth,
        "ask_depth_value": ask_depth,
        "total_depth": bid_depth + ask_depth,
        "imbalance": bid_depth / (ask_depth + 1) # Avoid div/0
    }

# Example Data
bids = [(0.58, 1000), (0.57, 4000), (0.55, 6000)]
asks = [(0.60, 500), (0.61, 2000), (0.63, 3000)]

# Calculate 5% depth
score = calculate_depth_score(bids, asks, 0.59, 0.05)
print(f"Total Depth (±5%): ${score['total_depth']}")
print(f"Bid/Ask Imbalance: {score['imbalance']:.2f}x") 
# Imbalance > 1.0 means stronger buy support

#Depth Score Formula

Some platforms calculate a depth score:

Depth Score = Total order value within X% of mid-price

For example, depth within 2% of the $0.59 mid-price:

Bids from $0.578 to$ 0.59: ~$580 value
Asks from $0.59 to$ 0.602: ~$300 value
Total 2% depth: $880

Higher scores indicate more liquid, tradeable markets.

#Examples

#Example 1: Major Election Market

A presidential election market shows:

$2 million in bids within 2% of best bid
$1.8 million in asks within 2% of best ask
Spread: 0.5 cents

A trader can place $50,000 orders with less than 0.3% slippage. The depth supports institutional-size positions and suggests the probability reflects substantial capital commitment.

#Example 2: Niche Policy Market

A market on obscure regulatory action shows:

$3,000 in bids within 5% of best bid
$2,500 in asks within 5% of best ask
Spread: 8 cents

Even a $500 order might move prices by 3-5%. The displayed probability is fragile; a single motivated trader could shift it dramatically.

#Example 3: Pre-Event Depth Collapse

An economic data market one hour before release:

Normal depth: $100,000 on each side
Current depth: $5,000 on each side

Market makers have pulled orders anticipating volatility. Traders placing last-minute bets face much worse execution than usual.

#Example 4: Asymmetric Depth Signal

A market shows 75% probability with:

$200,000 in bid-side depth
$50,000 in ask-side depth

The imbalance suggests strong buying interest meets limited selling interest. This could indicate informed money accumulating Yes positions, or simply that current holders are reluctant to sell.

#Risks and Common Mistakes

Trusting displayed prices at size

The price shown represents what's available for small trades. Traders who size positions based on visible prices, then execute market orders, often pay significantly more than expected.

Ignoring depth when evaluating probabilities

A "high probability" event at 92% means little if total depth is $200. Anyone could have moved that market with pocket change. Weight probability signals by the capital supporting them.

Missing depth deterioration

Depth can vanish quickly before major events, during unusual volatility, or when market makers experience technical issues. Orders that would have executed cleanly yesterday might fail catastrophically today.

Confusing depth with volume

Volume measures historical trading activity; depth measures current available liquidity. A market with high past volume might have low current depth if participants have exited or are waiting on the sidelines.

Front-running visible depth

Large visible orders can be pulled before execution or may be "iceberg" orders showing only a fraction of true size. Don't assume displayed depth will remain available when you need it.

#Practical Tips for Traders

Check depth before sizing positions: Your order should be small relative to available depth at your target price range to avoid excessive slippage
Use depth charts: Visual representations show order concentration at different price levels, revealing support and resistance zones
Split large orders: Rather than executing all at once, break orders into smaller pieces and execute over time as depth replenishes
Set slippage limits: Most platforms allow maximum slippage settings that cancel orders exceeding your tolerance
Monitor depth changes: Sudden depth withdrawal often precedes volatility or indicates informed traders repositioning
Compare depth across platforms: The same underlying event may have better depth on one platform than another
Factor depth into expected value calculations: If capturing an edge requires significant slippage, the edge may not be worth pursuing

#FAQ

#How is market depth different from liquidity?

Market depth is one component of liquidity. Depth specifically refers to order book size at various price levels: how much is available to trade. Liquidity is broader, encompassing depth plus factors like trading frequency, speed of order replenishment, and overall ease of execution. A market can have good depth but poor liquidity if orders rarely get filled.

#What causes market depth to change?

Depth fluctuates based on market maker activity, trader positioning, approaching events, and overall market conditions. Before major announcements, market makers often reduce depth to limit their exposure to sudden price moves. After resolution, depth typically returns as uncertainty resolves.

#Does an AMM-based market have market depth?

Yes, but it works differently. In AMM systems, depth is determined by the liquidity pool size and the bonding curve formula rather than discrete orders. Larger pools create deeper markets. The "depth" is continuous rather than stepped, but the same principle applies: larger trades move prices more.

#How much depth is "enough" for my trade size?

A common rule of thumb: your order should be less than 10% of total depth within 1-2% of the current price to avoid significant slippage. For a market with $100,000 in nearby depth, trades up to$ 10,000 should execute reasonably well. Larger orders require more patience or acceptance of worse prices.

#Can depth be manipulated or faked?

Yes. "Spoofing" involves placing large orders to create the appearance of depth, then canceling them before execution. This can mislead traders about true market conditions. Some platforms prohibit spoofing, but enforcement varies. Be cautious of depth that seems unusually large for a market's typical activity level.

#Definition

#Why It Matters in Prediction Markets

Market depth directly affects both trading costs and signal reliability.

For market efficiency, depth enables informed traders to correct mispricings. If correcting an obvious error requires accepting 5% slippage, the error persists longer than it should.

#How It Works

#Visualizing Depth

Market depth appears as layers of orders at progressively worse prices:

ASK SIDE (Sell Orders)
$0.65 → 5,000 shares
$0.63 → 3,000 shares
$0.61 → 2,000 shares
$0.60 → 500 shares    ← Best Ask

─────────────────────

$0.58 → 1,000 shares  ← Best Bid
$0.57 → 4,000 shares
$0.55 → 6,000 shares
$0.53 → 8,000 shares
BID SIDE (Buy Orders)

#Visualizing Market Depth

Note: The "Valley" in the middle is the spread. The "Walls" on either side represent depth.

#Depth Asymmetry

Markets often show uneven depth. In the example above:

Ask side depth: 10,500 shares within $0.05 of best ask
Bid side depth: 19,000 shares within $0.05 of best bid

This asymmetry suggests selling pressure would encounter more resistance than buying pressure. Large sell orders would push prices down faster than equivalent buy orders would push prices up.

#Calculating Price Impact

To estimate execution price for a large order, walk through the order book:

Example: Buying 4,000 shares

Step 1: Buy 500 @ $0.60 = $300
Step 2: Buy 2,000 @ $0.61 = $1,220
Step 3: Buy 1,500 @ $0.63 = $945
─────────────────────────────────
Total: 4,000 shares for $2,465
Average price: $0.616
Slippage: $0.016 per share (2.7%)

If you had expected to buy at the displayed price of $0.60, the actual cost is 2.7% higher.

#Price Impact Visual

#Python: Calculating Market Depth

A script to quantify how "thick" the order book is.

def calculate_depth_score(bids, asks, mid_price, range_pct=0.02):
    """
    Sum of order volume within 'range_pct' of the mid_price.
    """
    lower_bound = mid_price * (1 - range_pct)
    upper_bound = mid_price * (1 + range_pct)
    
    bid_depth = sum([vol for price, vol in bids if price >= lower_bound])
    ask_depth = sum([vol for price, vol in asks if price <= upper_bound])
    
    return {
        "bid_depth_value": bid_depth,
        "ask_depth_value": ask_depth,
        "total_depth": bid_depth + ask_depth,
        "imbalance": bid_depth / (ask_depth + 1) # Avoid div/0
    }

# Example Data
bids = [(0.58, 1000), (0.57, 4000), (0.55, 6000)]
asks = [(0.60, 500), (0.61, 2000), (0.63, 3000)]

# Calculate 5% depth
score = calculate_depth_score(bids, asks, 0.59, 0.05)
print(f"Total Depth (±5%): ${score['total_depth']}")
print(f"Bid/Ask Imbalance: {score['imbalance']:.2f}x") 
# Imbalance > 1.0 means stronger buy support

#Depth Score Formula

Some platforms calculate a depth score:

Depth Score = Total order value within X% of mid-price

For example, depth within 2% of the $0.59 mid-price:

Bids from $0.578 to$ 0.59: ~$580 value
Asks from $0.59 to$ 0.602: ~$300 value
Total 2% depth: $880

Higher scores indicate more liquid, tradeable markets.

#Examples

#Example 1: Major Election Market

A presidential election market shows:

$2 million in bids within 2% of best bid
$1.8 million in asks within 2% of best ask
Spread: 0.5 cents

A trader can place $50,000 orders with less than 0.3% slippage. The depth supports institutional-size positions and suggests the probability reflects substantial capital commitment.

#Example 2: Niche Policy Market

A market on obscure regulatory action shows:

$3,000 in bids within 5% of best bid
$2,500 in asks within 5% of best ask
Spread: 8 cents

Even a $500 order might move prices by 3-5%. The displayed probability is fragile; a single motivated trader could shift it dramatically.

#Example 3: Pre-Event Depth Collapse

An economic data market one hour before release:

Normal depth: $100,000 on each side
Current depth: $5,000 on each side

Market makers have pulled orders anticipating volatility. Traders placing last-minute bets face much worse execution than usual.

#Example 4: Asymmetric Depth Signal

A market shows 75% probability with:

$200,000 in bid-side depth
$50,000 in ask-side depth

The imbalance suggests strong buying interest meets limited selling interest. This could indicate informed money accumulating Yes positions, or simply that current holders are reluctant to sell.

#Risks and Common Mistakes

Trusting displayed prices at size

The price shown represents what's available for small trades. Traders who size positions based on visible prices, then execute market orders, often pay significantly more than expected.

Ignoring depth when evaluating probabilities

A "high probability" event at 92% means little if total depth is $200. Anyone could have moved that market with pocket change. Weight probability signals by the capital supporting them.

Missing depth deterioration

Confusing depth with volume

Front-running visible depth

Large visible orders can be pulled before execution or may be "iceberg" orders showing only a fraction of true size. Don't assume displayed depth will remain available when you need it.

#Practical Tips for Traders

Check depth before sizing positions: Your order should be small relative to available depth at your target price range to avoid excessive slippage
Use depth charts: Visual representations show order concentration at different price levels, revealing support and resistance zones
Split large orders: Rather than executing all at once, break orders into smaller pieces and execute over time as depth replenishes
Set slippage limits: Most platforms allow maximum slippage settings that cancel orders exceeding your tolerance
Monitor depth changes: Sudden depth withdrawal often precedes volatility or indicates informed traders repositioning
Compare depth across platforms: The same underlying event may have better depth on one platform than another
Factor depth into expected value calculations: If capturing an edge requires significant slippage, the edge may not be worth pursuing

#Definition

#Why It Matters in Prediction Markets

#How It Works

#Visualizing Depth

#Visualizing Market Depth

#Depth Asymmetry

#Calculating Price Impact

#Price Impact Visual

#Python: Calculating Market Depth

#Depth Score Formula

#Examples

#Example 1: Major Election Market

#Example 2: Niche Policy Market

#Example 3: Pre-Event Depth Collapse

#Example 4: Asymmetric Depth Signal

#Risks and Common Mistakes

#Practical Tips for Traders

#Related Terms

#FAQ

#How is market depth different from liquidity?

#What causes market depth to change?

#Does an AMM-based market have market depth?

#How much depth is "enough" for my trade size?

#Can depth be manipulated or faked?

On This Page

Related Terms

Market Depth

#Definition

#Why It Matters in Prediction Markets

#How It Works

#Visualizing Depth

#Visualizing Market Depth

#Depth Asymmetry

#Calculating Price Impact

#Price Impact Visual

#Python: Calculating Market Depth

#Depth Score Formula

#Examples

#Example 1: Major Election Market

#Example 2: Niche Policy Market

#Example 3: Pre-Event Depth Collapse

#Example 4: Asymmetric Depth Signal

#Risks and Common Mistakes

#Practical Tips for Traders

#Related Terms

#FAQ

#How is market depth different from liquidity?

#What causes market depth to change?

#Does an AMM-based market have market depth?

#How much depth is "enough" for my trade size?

#Can depth be manipulated or faked?

On This Page

Related Terms