How I Wrote a Technical Book on Precious Metals Economics: From Market Anomalies to Published Authority

The Power of Technical Book Authoring

Writing a technical book transformed my career more than any consulting gig ever could. Let me walk you through my journey – from spotting unusual market patterns to seeing my name on an O’Reilly cover. It started when I became obsessed with a strange phenomenon: Morgan silver dollars kept selling for $90 even as silver prices climbed to $30/oz. That disconnect between metal value and collectible pricing became the beating heart of my book.

Finding Your Book’s Compelling Angle

Catching Those “Wait, That Doesn’t Make Sense” Moments

My “aha moment” came at a coin show, watching dealers pay $90 for common-date Morgans (like the 1881-S MS-63) while silver’s spot price made their melt value $23.19. Why weren’t prices rising? This anomaly became my book’s foundation because:

• It blended hard numbers with human collector psychology
• The math revealed economic principles affecting everything from gold coins to vintage watches
• It solved actual problems for both investors and history buffs

Stress-Testing Your Idea

Before pitching publishers, I geeked out with data:

• Tracked PCGS price guides against actual eBay auctions for 36 months
• Built Python tools to calculate numismatic premiums (see the code snippet I still use)

import pandas as pd
import numpy as np

# My trusty premium calculator
def calculate_premium_deterioration(spot_prices, coin_prices):
returns = pd.DataFrame({
'spot_returns': spot_prices.pct_change(),
'coin_returns': coin_prices.pct_change()
})
return returns.corr()

Crafting Proposals That Get Yeses

Speaking Each Publisher’s Language

I customized pitches like this:

• O’Reilly: “Let’s make the silver-to-premium ratio your next Animal Guide”
• Manning: “Collectors need live MEAP updates as gold prices swing”
• Apress: “Here’s how to code numismatic beta calculations”

“The proposal that made me swipe right showed both market pain points and the author’s unique data access.”
– My O’Reilly editor at our first coffee meeting

What Made My Proposal Work

The winning submission included:

• A table comparing premium crashes across gold coins, vintage comics, and rare whiskey
• Chapter summaries with Python exercises for calculating collectible risk premiums
• Real CAC-graded coin examples showing premium erosion in bull markets

Structuring Your Technical Story

Mixing Theory With Real Math

The final table of contents balanced:

• Numismatic economics explained through coin dealer interviews
• Step-by-step tutorials for building valuation models in Python
• Case studies like the 1896 $20 Liberty DE 64CAC that refused to appreciate

Showing What Spreadsheets Can’t

These visuals made complex ideas stick:

• Animated charts showing spot price vs. collectible value divergences
• Scatterplots revealing when premiums flip from growth to decay
• Decision trees for spotting buy/sell signals in volatile markets

Surviving the Writing Grind

Keeping Technical Details Digestible

For the Morgan dollar analysis, I broke it down:

1. Melt value = 0.77344 oz × silver spot price
2. Premium compression tracked through dealer buy/sell spreads
3. Rare dates vs. common dates performance compared

# Actual calculation from Chapter 7
melt_value = 0.77344 * silver_spot
numismatic_premium = (coin_price - melt_value) / melt_value

When Markets Move Mid-Draft

Gold’s surge from $1,700 to $4,000 forced last-minute updates:

• Rewrote the Saint-Gaudens case study as premiums evaporated
• Added real-time $3 Princess gold coin demand shifts
• Documented proof Franklin halves selling at melt value

Growing Your Audience Early

Sharing Nuggets While Writing

Months before publication, I:

• Published numismatic beta findings on SSRN
• Shared Jupyter Notebook templates with historical coin data
• Ran “Is Your Collection Underperforming Bullion?” webinars

Platform-Specific Teasing

Different audiences got tailored content:

• GitHub: Coin price scraper tools for PCGS data
• Medium: “Why Your Rare Coins Didn’t Gain Value Last Year”
• YouTube: Building a coin valuation model in 20 minutes

Inside Technical Publishing Houses

O’Reilly’s Signature Style

Their process demanded:

• Exercises in every chapter (I created 47)
• Detailed diagrams explaining premium decay mechanics
• Downloadable datasets and code samples

Realistic Timeline Expectations

My schedule looked like:

Life After Publication

Converting Pages Into Opportunities

The book became:

• My backstage pass to hedge fund consulting gigs
• The foundation for premium-tracking SaaS tools
• Fuel for keynote talks at collector conventions

Breathing New Life Into Content

Successful repurposing included:

• Turning chapters into LinkedIn Learning courses
• Building interactive Streamlit calculators
• Hosting coin show workshops with live analysis

From Curious Observer To Published Expert

Spotting those Morgan dollar anomalies taught me technical book success comes down to:

1. Finding measurable mysteries others overlook
2. Creating reproducible analysis frameworks
3. Matching your passion with publisher missions
4. Cultivating readers before you type “Chapter 1”

Whether you’re analyzing silver premiums or semiconductor yields, the path remains: observe what doesn’t add up, document your detective work, and teach your findings. That strange market quirk you’ve noticed? It might be your book’s first chapter.

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