This is an honest, feature-by-feature comparison. No marketing fluff. Where TradingView wins, we'll say so. Where Vaanam wins, we'll back it with specifics.

TL;DR​

Side-by-Side Comparison​

Filtering & Conditions​

What this means: TradingView's screener is excellent for "show me stocks where X is above Y." Vaanam handles that too — and also "show me stocks where RSI has been below 30 for 3 consecutive days, volume is 1.5x its 20-day average, and price is above the 200-day SMA" in a single line of expression.

Asset Coverage​

Honest take: TradingView is the clear winner here. If you trade anything other than US equities, this isn't even a contest.

Universe & Watchlist Filtering​

Results & Display​

Alerts & Automation​

What Happens Next​

This is where the platforms really diverge.

This is the real story. TradingView treats screening, backtesting, and trading as separate products. Vaanam treats them as one workflow with the same query language. If you want to go from "I have an idea" to "I'm running it live" without rewriting your logic three times, that's the meaningful difference.

Where TradingView Is Better​

Let's be direct about it.

• Multi-asset coverage — forex, futures, bonds, DEX crypto. Vaanam doesn't touch these.
• Fundamentals — P/E, EPS, dividends, financials. Not in Vaanam's DSL.
• Charting — TradingView's charting is the industry benchmark. Ours is functional, not exceptional.
• Mobile apps — native iOS and Android. Vaanam is web-only.
• Community — millions of public scripts and shared ideas. Vaanam is newer.
• Mini-chart grid view of screener results.
• Pre-built column sets for fundamental and risk views.

If charting and asset breadth are what you need, TradingView is the right tool.

Where Vaanam Is Better​

• DSL expressiveness — express compound, multi-bar, technical conditions in one line.
• Same query, three outputs — screen → backtest → bot deployment without rewriting.
• Native scheduled screeners with email and webhook alerts on every plan tier (webhook from Essential).
• Custom basket as universe — native first-class feature, not a workaround.
• Strategy optimizer — sweep up to 2000 parameter combinations to find the best version of your strategy.
• AI natural language — describe what you want; we generate the query.
• Opening Range Breakout support — TODAY_HIGH_ and TODAY_LOW_ operands built into the DSL.
• Live broker execution via TradersPost — paste a webhook URL, run real trades.
• Weekly $100 championship — public leaderboard, real-time competition.

If systematic, automatable trading on US equities is what you need, Vaanam is purpose-built for that.

The Honest Conclusion​

TradingView is a charting platform that includes a screener. It serves a broad audience across every asset class, with great visuals and a huge community.

Vaanam is a strategy execution platform where the screener is a workflow step. It serves systematic traders on US equities who want their screen, backtest, and bot to share the same logic.

Different tools for different jobs. The right answer depends on what you actually do.

If you're a chart-first multi-asset trader, stay on TradingView.

If you're tired of rebuilding the same logic across three different tools, try Vaanam — free.

© 2026 Vaanam, Inc. All rights reserved.

Entry Condition​

close < (10 day high - 2.5 * (25 day avg high - 25 day avg low))
and
IBS < 0.3

What This Means​

Today's close should be less than the highest high of the last 10 bars minus 2.5 times the last 25 days average stock movement.

Additionally, IBS should be below 0.3.

What's IBS? Not irritable bowel syndrome.

IBS (Internal Bar Strength) = (close - low) / (high - low)

This gives a 0–1 range. 0 means close = low (weakness), 1 means close = high (strength). Below 0.3 = the stock closed in the bottom 30% of the day's range.

Exit Condition​

close > yesterday's high

Yep, very simple.

Backtest: SPY (2006–2026)​

Testing parameters:

• Timeframe: Daily
• Ticker: SPY
• Slippage: $0.01 per share
• Commission: $0.01 per share
• Duration: March 2006 – March 2026
• Capital: $100,000

Core Returns​

Risk Metrics​

Position and Efficiency​

Execution and Friction​

75% win rate with only 15% max drawdown is solid. The 7.75% CAGR isn't spectacular, but you're only in the market 21% of the time. The remaining 79% of time could run a different strategy or the same strategy on other instruments.

How It Performs Across Other Instruments​

I ran the same strategy on QQQ, AAPL, and ABNB. Here's how the key numbers compare:

QQQ​

The ~70% win rate holds just like it did with SPY, and a CAGR of ~9% is not bad at all. But here too the time invested is very low — only 16% of the time the capital was utilized.

AAPL​

Interestingly, the ~70% win rate holds here too, with only 25% time invested. The 11.77% CAGR looks great, but note the 29.56% max drawdown — that's nearly double what we saw with SPY.

ABNB​

Win rate dropped to 56%, which is weak for mean reversion. But ABNB only IPO'd in late 2020 and has been in a downtrend since — just 69 trades and 7% time invested. Hard to draw conclusions from such limited data. The fact that it's still slightly profitable on a falling stock is something, I guess.

Takeaways​

• ~70% win rate held across SPY, QQQ, and AAPL
• Profit factor consistently around 2.0 on ETFs
• Time invested stays low (16–25%) — capital efficient
• Individual stocks = higher returns but higher drawdowns
• Doesn't work on everything (ABNB struggled)

The low time-in-market is the real story here. You're making 7–12% CAGR while only deploying capital a fifth of the time. Stack this with another uncorrelated strategy or run it across multiple instruments and the numbers get more interesting.

The Formula​

Max Drawdown = (Trough Value - Peak Value) / Peak Value

Example: Your portfolio peaks at $150,000, then drops to $127,110 before recovering.

Max Drawdown = (127,110 - 150,000) / 150,000 = -15.26%

Why It Matters More Than You Think​

Every strategy looks great on a returns chart. But returns don't tell you what it felt like to trade it.

A 15% drawdown means watching $15,000 of every $100,000 disappear — with no guarantee it'll come back. A 30% drawdown means $30,000 gone. A 50% drawdown means you need a 100% gain just to break even.

The math gets ugly fast. This is why drawdown matters more than return for most traders — it determines whether you'll actually stick with the strategy.

What's Acceptable?​

It depends on the strategy type:

Generally, if you think your max drawdown tolerance is 20%, it's probably 10% in practice. Backtests don't capture the psychological pain of watching your money evaporate in real time.

Drawdown Duration Matters Too​

A 15% drawdown that recovers in 2 weeks is very different from one that takes 18 months. When evaluating strategies, check both the depth and duration of the worst drawdown.

Key Takeaway​

Max drawdown is the reality check for any backtest. A strategy that makes 20% a year but drops 50% along the way will be abandoned by most traders before it pays off. Always check drawdown first — if you can't survive it, the returns don't matter.

The Formula​

Calmar Ratio = CAGR / Max Drawdown

That's it. Two numbers you probably already have from any backtest.

Example: Strategy has a CAGR of 7.75% and a max drawdown of 15.26%.

Calmar = 7.75% / 15.26% = 0.51

For every 1% of max drawdown, you earned about 0.51% annually.

How to Read It​

Why Calmar Is Practical​

Unlike Sharpe and Sortino, Calmar uses max drawdown — something every trader viscerally understands. You don't need to think about "standard deviation of returns." You just ask yourself:

"Would I sit through a 15% drawdown to earn 7.75% per year?"

That's the Calmar ratio in human terms.

The Catch​

Max drawdown is a single worst-case event. If your strategy had one bad month in 20 years, that one month dominates the Calmar ratio forever. It doesn't tell you about the typical drawdown experience.

For this reason, some traders also look at the average drawdown or drawdown duration alongside Calmar.

Key Takeaway​

Calmar ratio is the most intuitive risk-adjusted metric because it directly compares return to worst-case pain. If Calmar is below 0.5, the strategy probably isn't worth the stress. Above 1.0, you're getting well-compensated for the risk.

Why Not Just Use Total Return?​

Say a strategy returns 100% over 10 years. Sounds okay, right? But another returns 100% over 3 years. Clearly different — but "100% total return" doesn't tell you that.

CAGR normalizes returns to a per-year basis so you can compare strategies across different time periods.

The Formula​

CAGR = (Final Value / Initial Value) ^ (1 / Years) - 1

Example: You start with $100,000 and end with $434,835 after 20 years.

CAGR = (434,835 / 100,000) ^ (1/20) - 1
     = 4.3483 ^ 0.05 - 1
     = 0.0775
     = 7.75%

So even though the total return is 334%, the annualized growth rate is 7.75%.

What's a Good CAGR?​

It depends on context:

But CAGR alone doesn't tell the full story. A 15% CAGR with 50% max drawdown is very different from 15% CAGR with 10% max drawdown. Always pair CAGR with risk metrics like max drawdown, Sharpe ratio, or Calmar ratio.

CAGR vs. Average Return​

These are not the same. Average return ignores compounding.

• Year 1: +50%, Year 2: -50%
• Average return: 0%
• Actual result: $100 → $150 → $75 (you lost 25%)
• CAGR: -13.4%

CAGR reflects what actually happened to your money. Average return can be misleading.

Key Takeaway​

CAGR is the single best number for comparing strategy returns across different time periods. But never look at it in isolation — pair it with drawdown and risk-adjusted metrics for the full picture.

The Formula​

Sharpe Ratio = (Strategy Return - Risk-Free Rate) / Standard Deviation of Returns

• Strategy Return: Your CAGR or average return
• Risk-Free Rate: What you'd earn doing nothing (T-bills, ~4-5%)
• Standard Deviation: How much your returns bounce around (volatility)

Example: Strategy earns 12% annually, risk-free rate is 4%, standard deviation is 15%.

Sharpe = (12% - 4%) / 15% = 0.53

How to Read It​

For context, the S&P 500's long-term Sharpe ratio is roughly 0.4–0.6.

The Problem with Sharpe​

Sharpe treats all volatility as risk — both up and down. If your strategy has occasional huge winning days, that increases standard deviation and lowers your Sharpe ratio. That feels wrong.

This is exactly why the Sortino ratio exists — it only penalizes downside volatility.

When Sharpe Is Useful​

• Comparing strategies with similar return profiles
• Evaluating how much risk you're taking for your returns
• Quick screening of backtest results

When It's Not​

• Strategies with infrequent but large gains (trend following)
• Strategies that are mostly in cash (low volatility inflates Sharpe)
• Comparing strategies with very different time-in-market

Key Takeaway​

Sharpe ratio is the most widely used risk-adjusted metric, but it punishes upside volatility the same as downside. Use it as a starting point, then check Sortino for a fairer picture.

Why Sortino Over Sharpe?​

The Sharpe ratio treats a +5% day and a -5% day as equally "risky" because both increase standard deviation. But as a trader, you don't mind upside volatility — you only care about the losses.

Sortino fixes this by only looking at negative returns when calculating risk.

The Formula​

Sortino Ratio = (Strategy Return - Risk-Free Rate) / Downside Deviation

The only difference from Sharpe: the denominator uses downside deviation (standard deviation of only negative returns) instead of total standard deviation.

Example: Strategy earns 12%, risk-free rate is 4%, downside deviation is 8%.

Sortino = (12% - 4%) / 8% = 1.0

Compare to the same strategy's Sharpe of 0.53 (from our Sharpe ratio post). Same strategy, but Sortino gives a better score because it doesn't penalize the upside moves.

How to Read It​

Sortino values are typically higher than Sharpe for the same strategy, because you're dividing by a smaller number (downside-only deviation < total deviation).

When to Use Sortino​

Sortino shines for strategies where returns are asymmetric — meaning big wins and small losses (or vice versa). Mean reversion strategies often fit this profile: frequent small wins with occasional larger losses. Sortino captures this more accurately than Sharpe.

Key Takeaway​

Sortino ratio gives you a fairer read on risk-adjusted performance than Sharpe because it only counts the volatility that actually hurts you. If you're only going to look at one risk-adjusted metric, make it Sortino.

The Formula​

Profit Factor = Gross Profits / Gross Losses

That's it. Add up all your winning trades. Add up all your losing trades (as a positive number). Divide.

Example: Your strategy made $50,000 in winning trades and lost $25,000 in losing trades.

Profit Factor = 50,000 / 25,000 = 2.0

For every $1 lost, you made $2 back.

How to Read It​

Why It's Useful​

Profit Factor combines win rate and risk-reward into a single number. Two very different strategies can have the same profit factor:

• Strategy A: 80% win rate, small wins, occasional big loss → PF 2.0
• Strategy B: 40% win rate, big wins, frequent small losses → PF 2.0

Both make $2 for every $1 lost. Profit factor doesn't care how you get there.

Watch Out For​

• Low trade count: A profit factor of 3.0 on 15 trades means almost nothing. You need enough trades for the number to be statistically meaningful.
• Very high values (5.0+): Usually a sign of curve-fitting or too few trades rather than a genuinely amazing strategy.
• Doesn't account for drawdown: A strategy can have a great profit factor but still have gut-wrenching drawdowns. Pair it with max drawdown and Calmar ratio.

Key Takeaway​

Profit Factor is the quickest sanity check for any backtest. Above 1.5 is decent, above 2.0 is strong. But always verify with enough trades and check the drawdown profile too.