Relativity v1.0

Mar 10

RELATIVITY v1.0


Slide 1 — Conceptual Overview

Relativity v1.0 [Noldo] is a quantitative strategy framework designed for relative-value trading on five highly similar pair structures and for selective volatility trading on CBOE:VIX. The core design philosophy is not directional speculation in the classical sense, but the extraction of structured opportunities from instruments that are either economically close substitutes or volatility-sensitive hedging vehicles.

The strategy is built around the following five pair-trading relationships:

EEM – VWO
GOOGL – GOOG
SLV – PSLV
PHYS – IAU
UA – UAA

In addition to those pairs, the script is also designed to generate selective, high-conviction signals on CBOE:VIX, which is treated as a volatility and hedge-oriented instrument rather than a conventional directional asset.

Slide 2 — Instrument Logic

The five pair structures used in this script were selected because they represent markets with strong economic similarity, close substitution behavior, or structural linkage. In practical terms, this means the strategy is intended to operate in environments where relative dislocations may be more informative than outright market direction.

This is especially important in pair trading, because the objective is not merely to predict price direction, but to identify a divergence or tension inside a highly related structure. In that sense, the model is closer to relative-value quantitative trading than to standard single-asset momentum speculation.

For CBOE:VIX, the role is different. The strategy treats VIX as a specialized volatility instrument that can serve a hedging or convexity-oriented function within a broader trading framework. Cboe describes the VIX Index as a real-time measure derived from S&P 500 option prices, while VIX futures are distinct contracts with separate specifications.

Slide 3 — What the Strategy Claims, and What It Does Not Claim

This script is designed to seek high-probability opportunities, not to promise certainty. Its purpose is to create a disciplined decision framework under controlled execution assumptions, realistic timing conventions, and explicit risk limits.

The wording here is intentionally restrained. For TradingView publications, strategies and scripts are expected to comply with House Rules and script-publishing requirements, and it is therefore more appropriate to describe methodology, assumptions, and limitations than to imply guaranteed outcomes or fixed future profitability.

Slide 4 — Backtesting and Validation Context

The strategy has been tested in both historical backtest mode and Deep Backtesting mode. On TradingView, Deep Backtesting allows a strategy to be calculated on all historical data available for the selected symbol, rather than only the data currently loaded on the chart. TradingView also notes that Deep Backtesting and regular chart-session backtesting may differ because calculations can begin earlier in Deep Backtesting, which can affect time-series-dependent calculations.

Accordingly, the script should be interpreted as a model that has been examined across multiple validation contexts, while still respecting the fact that simulated results remain simulated results.

Slide 5 — Execution Model and Conservative Design

A central design principle of this script is to stand on the safe side. The execution logic was intentionally built under adverse-assumption discipline rather than optimistic fill assumptions.

The model assumes that:

Entry orders are evaluated on a confirmed bar close and filled on the next bar open

Exit orders that are close-based are also effectively handled on the next bar

Stop-loss orders are monitored intrabar so that adverse movement inside the same bar is not ignored

This conservative design is explicitly reflected in the strategy settings:

process_orders_on_close = false
calc_on_order_fills = false
calc_on_every_tick = false

In practical terms, this means the script avoids pretending that it can react inside the closing bar with perfect hindsight. It accepts slower entry/exit confirmation, while still allowing stop-loss protection to be checked against intrabar price movement. That asymmetry is deliberate and risk-aware.

Slide 6 — Commission and Realism Assumptions

The strategy is tested with a commission assumption of 0.045%. This is not a cosmetic parameter. It is part of the model’s viability filter and should be treated as a structural component of the strategy, especially in relative-value systems where gross edge can be compressed by fees and execution friction.

Because script is built as a TradingView strategy, its trade simulation logic operates within TradingView’s backtesting framework for historical and realtime bars.

Slide 7 — Required Chart Construction

To use the script correctly, the user should first select the relevant instrument from the script menu and then construct the TradingView chart symbol in the form(pair trading precision needs sensitivity ratios):

A / B * 100

Examples:

EEM / VWO * 100
GOOGL / GOOG * 100
SLV / PSLV * 100
PHYS / IAU * 100
UA / UAA * 100

This ratio-style construction is essential because the strategy is not designed to read the two legs independently on separate charts; it is designed to analyze the synthetic relative series itself.

For CBOE:VIX, the chart should simply be the VIX instrument.

Slide 8 — Timeframe Requirements

The script is designed to be used on the following timeframes:

EEM – VWO: 1H
GOOGL – GOOG: 1H
SLV – PSLV: 1H
PHYS – IAU: 1H
UA – UAA: 1H

CBOE:VIX: 10-minute bars

These settings are not decorative. They are part of the model definition. Changing the timeframe materially changes the statistical environment in which the strategy operates.

Slide 9 — Valid Bar Type

The strategy is intended to run only on standard candlestick bars.

It should not be used on:

Heikin Ashi
Renko
Point & Figure
Kagi

other synthetic or transformed bar constructions

The reason is straightforward: the model’s execution logic depends on standard OHLC bar behavior, and its stop, timing, and signal interpretation are all calibrated to ordinary candle data. Synthetic bars can distort bar structure, entry timing, and stop behavior, which means they will not produce realistic results for this strategy.

Slide 10 — Leverage Architecture

The script uses the following leverage references:

Instrument Leverage
EEM – VWO 12
GOOGL – GOOG 12
SLV – PSLV 29
PHYS – IAU 11
UA – UAA 12
CBOE:VIX 7

These leverage values were derived from personal trading experience and practical risk judgment. They were not designed to serve curve fitting. They should be understood as operational presets, not as a claim that all users, all brokers, or all account types will receive identical margin treatment.

Further leverage customization for user-specific demands may be added in future revisions.

Slide 11 — Why Pair-Trading Leverage Can Be Structurally Different

For highly similar pair-trading structures, broker margin treatment can in practice be materially different from outright single-name exposure. Because these trades are often constructed around economically related instruments, capital usage may remain well below 100% of gross notional while still producing meaningful exposure through debit-credit mechanics, spread logic, and leverage.

This is one of the key advantages of relative-value trading: it can enable quantitative trading in instruments that are closer to market-neutral than ordinary directional trades. That does not remove risk, but it changes the type of risk being assumed.

For that reason, the panel and the position-sizing engine are extremely important. The user should not treat the script as a simple “signal light.” It is a framework in which the sizing logic is part of the strategy itself.

Slide 12 — Why Info Panel Matters

The information panel should be treated as operationally important because it exposes the strategy’s live risk geometry:

entry level
stop level
take-profit level
position size percentage per trade

effective take-profit percentage

leverage context

In other words, the panel is not merely visual decoration. It is the practical interface through which the user understands how the position sizing algorithm is interpreting the current setup.

Ignoring the panel would mean ignoring part of the system’s decision architecture.

Slide 13 — Alerts

The script contains alert logic, but alerts do not become active by themselves. They become active only after the user creates them from the TradingView interface. TradingView’s documentation explicitly states that scripts can expose alert triggers, but users must create the alerts in the Create Alert dialog or strategy alert menu.

So the correct statement is:

Alerts are present in the code; they become operational only when the user sets them up.

Slide 14 — Special Note on CBOE:VIX vs VIX Futures

The strategy uses CBOE:VIX because this is the U.S. equity-options volatility reference instrument around which the VIX ecosystem is built. Cboe defines the VIX Index using real-time SPX option prices, and this makes it especially relevant when the design goal is to interact with the options-volatility complex rather than with a generic macro proxy.

This should be distinguished from VX futures, which are separate futures contracts. Cboe lists VX as the ticker family for VIX futures contract specifications.

In practical brokerage environments, leverage available on VIX futures is often lower than what users may expect from pair-trading structures, and a low-single-digit range is commonly encountered as a rough benchmark. However, that is a broker-margin matter, not an exchange law. By contrast, in options-oriented usage, effective leverage can vary across a much wider scale because it depends on variables such as strike, implied volatility, days to expiration, and position structure.

For that reason, CBOE:VIX is used here as an options-centered volatility reference, while the script’s 7x internal leverage reference should be read as a strategy parameter, not as a universal brokerage promise.

Slide 15 — Strategic Role of the Two Components

The script combines two distinct but complementary ideas:

1. Pair-trading module
This module seeks relative-value opportunities in highly similar instrument pairs, where capital can often be deployed more efficiently than in outright directional trading and where market exposure can be closer to neutral.

2. VIX module
This module serves a different role. It is better understood within a hedge logic or volatility-allocation logic than as a standard directional long/short engine.

This separation matters. The pair section is fundamentally about dislocation inside similarity. The VIX section is fundamentally about volatility regime opportunity and protection logic.

Slide 16 — Final Positioning Statement

This is best understood as a risk-structured quantitative framework rather than a generic signal script. It is designed for users who understand that:

execution assumptions matter,
capital efficiency matters,
commission matters,
the panel matters,
and instrument construction matters.

Its pair-trading side is intended for near market-neutral relative-value opportunities under debit-credit and leverage logic. Its VIX side is intended as a hedge-aware volatility component. The strategy has been evaluated in regular historical backtesting and Deep Backtesting, while preserving conservative execution assumptions and avoiding artificially optimistic fill logic.

Traders working with the script absolutely must have access to live data.
Results can be inconsistent with delayed data.

FINAL REMARK

The most realistic success metric is the average result across all instruments, each treated with near-equal importance rather than allowing one market to dominate the evaluation. Important note: while Historical Backtesting and Deep Backtesting are encouraging, the system should still be monitored together in real time for a meaningful period before drawing stronger conclusions.

Mar 10

Release Notes

Signal messages were simplified for clarity and usability.

Mar 10

Release Notes

The script was simplified for calculation loads, focus, and ease of use.

Apr 17

Release Notes

The script optimization from Regular Trading Hours (RTH) to Full Trading Hours (FTH) is complete.

Apr 26

Release Notes

First general parameter optimization.

Apr 29

Release Notes

CBOE: VIX timeframe reduced to 5-minute timeframe :
CBOE : VIX Timeframe : 5 mins (5m) candlestick bars

CBOE: VIX operations modified to be compatible with RTH (Regular Trading Hours).

Apr 29

Release Notes

New RTH algorithm parameter optimization

5 days ago

Release Notes

Parameter Optimization update completed