# Imperial Analytics
> Institutional-grade AI trading journal for futures traders running NinjaTrader.
> Imperial Analytics computes P&L server-side with per-instrument commission rates for major prop firms, and runs an AI agent pipeline on every trade to surface behavioral, statistical, and execution patterns above declared sample-size minima. Live broker sync is active for NinjaTrader and Tradovate, with prop-firm routes included.

## Core pages
- [Home](https://www.imperialanalytics.ai/): Product overview, the AI insight pipeline, and how the journal works.
- [Pricing](https://www.imperialanalytics.ai/pricing): $30/month plan and feature breakdown.
- [Features](https://www.imperialanalytics.ai/features): The dashboard, trade history, and AI insights surfaces.
- [Partners](https://www.imperialanalytics.ai/partners): Featured partners — NinjaTrader as recommended desktop execution; more partners on the horizon.
- [About](https://www.imperialanalytics.ai/about): Why Imperial Analytics exists and who it's for.
- [Contact](https://www.imperialanalytics.ai/contact): Support and product feedback.
- [Resources](https://www.imperialanalytics.ai/resources): Trader-facing reference (charting, prop firms, brokers, execution tools).
- [Glossary](https://www.imperialanalytics.ai/glossary): Plain-English definitions of profit factor, expectancy, R-multiple, trailing drawdown, FIFO, VWAP, and the behavioral patterns most journals never quantify.

## Legal
- [Terms](https://www.imperialanalytics.ai/terms): Subscription, billing, acceptable use, and AI insights terms.
- [Privacy](https://www.imperialanalytics.ai/privacy): Data collection, processing, and your export/deletion rights.

## Blog (newest first)
- [Moving Averages: How SMA and EMA Differ in Responsiveness](https://www.imperialanalytics.ai/blog/moving-averages-sma-and-ema): A simple moving average treats every bar equally. An exponential moving average weights recent bars more. See how that math changes signal timing and lag.
- [What Slippage Is and How It Differs From Commission](https://www.imperialanalytics.ai/blog/what-is-slippage-vs-commission): Slippage is the gap between expected fill and realized fill. Commission is a fixed per-trade charge. See how each is measured and why they show up separately.
- [What Overtrading Actually Is and How to Measure It](https://www.imperialanalytics.ai/blog/what-is-overtrading-in-futures): Overtrading is taking more trades than the strategy supports. See how to define it in numbers, separate it from a busy market day, and measure the cost.
- [What Overfitting Is and How It Inflates Strategy Results](https://www.imperialanalytics.ai/blog/what-is-overfitting-in-trading): Overfitting is when a strategy fits historical noise instead of a real edge. See how to spot it in backtests and journal data before live capital pays for it.
- [What Is Edge Decay and How It Shows Up in a Journal](https://www.imperialanalytics.ai/blog/what-is-edge-decay-in-trading): Edge decay is when a trading strategy's advantage erodes over time. See how it shows up in journal metrics before P&L, and how to tell it from variance.
- [Evaluation Accounts and Funded Accounts: The Difference](https://www.imperialanalytics.ai/blog/evaluation-account-and-funded-account): An evaluation account is a paid test of trading rules. A funded account pays out a share of profits. See how each works and the rules that govern both.
- [RSI Explained: What It Measures and What It Misses](https://www.imperialanalytics.ai/blog/what-is-rsi-and-its-limitations): RSI is a momentum oscillator that turns recent average gains and losses into a 0-100 reading. See what it measures, how it is calculated, and where it breaks.
- [Loss Aversion in Trading: How It Shows Up in Your Exits](https://www.imperialanalytics.ai/blog/loss-aversion-in-futures-trading): Loss aversion is the asymmetric pain of losses relative to wins. Learn how it warps a futures trader's exits and how to detect the pattern in your trade log.
- [What Is a Tick in Futures Trading? Tick Size and Tick Value](https://www.imperialanalytics.ai/blog/what-is-a-tick-in-futures-trading): A tick is the smallest legal price increment a futures contract can move. Learn how tick size and tick value differ, with worked CME contract examples.
- [What Is Expectancy in Trading and How to Calculate It](https://www.imperialanalytics.ai/blog/what-is-expectancy-in-futures-trading): Expectancy is the average dollar gain per trade across your trade log. Learn how to calculate expectancy from your own history and what the number means.
- [What to Review After a Max Loss Day](https://www.imperialanalytics.ai/blog/what-to-review-after-a-max-loss-day): A max loss day is a process signal, not a verdict. Here is what a futures trader reviews next: rules followed, position sizing, drawdown, and readiness.
- [Cutting Winners Short: How to Put a Dollar Figure on the Trades That Got Away](https://www.imperialanalytics.ai/blog/cutting-winners-short-the-dollar-cost-of-trades-that-got-away): Cutting winners short has a cost you can compute. Use Maximum Favorable Excursion against your realized exits to put a dollar figure on the money you left on the table.
- [FOMO Entries: How to Spot Them in Your Data and What They Cost](https://www.imperialanalytics.ai/blog/fomo-entries-the-real-cost-and-how-to-spot-them): FOMO entries don't follow a loss — they follow a missed move. Here's how to define them objectively, tag them in your journal, and quantify the damage.
- [The Hidden Math of Prop Firm Consistency Rules](https://www.imperialanalytics.ai/blog/the-hidden-math-of-prop-firm-consistency-rules): Consistency rules cap your best day as a fraction of total profit — which raises the dollar target you need before payout. Here's the math.
- [The Metric That Exposes Bad Trading Disguised as Profit](https://www.imperialanalytics.ai/blog/the-metric-that-exposes-bad-trading-disguised-as-profit): Outcome bias causes traders to reinforce bad decisions that got lucky. Learn how to track decision quality vs. trade outcomes — and why P&L alone will mislead you.
- [Why 20 Winning Trades Proves Nothing (And How Many You Actually Need)](https://www.imperialanalytics.ai/blog/why-20-winning-trades-proves-nothing): Most traders declare a strategy proven after 20 wins. Statistical analysis requires 200+ trades for 90% confidence. Here's the math behind the gap.
- [The Trailing Drawdown Rule That Kills Funded Accounts](https://www.imperialanalytics.ai/blog/the-trailing-drawdown-rule-that-kills-funded-accounts): Industry data shows intraday trailing drawdowns cause 67% more failures than EOD systems. Here's the math behind the rule killing funded accounts.
- [What Is Profit Factor and Why Every Trader Should Track It](https://www.imperialanalytics.ai/blog/what-is-profit-factor): Profit factor is the ratio of gross profit to gross loss. Learn how to calculate it, what a good profit factor looks like, and why it matters more than win rate alone.
- [Revenge Trading: How to Calculate What It Actually Costs You](https://www.imperialanalytics.ai/blog/revenge-trading-the-real-cost): Revenge trading isn't just a bad habit — it has a measurable dollar cost. Learn how to identify it in your journal data and quantify the damage.
- [VWAP Explained: The Institutional Benchmark Every Day Trader Needs](https://www.imperialanalytics.ai/blog/understanding-vwap): Volume Weighted Average Price (VWAP) is the benchmark institutions use to evaluate execution quality. Learn how it works, how to read it, and how day traders apply it.