TechQuant Algo System 2025 Performance Report

Introduction

This year-end report provides a clear summary of results across two views of performance: (1) realized performance from tracked live trading activity, and (2) theoretical strategy compounding for the strategies currently active in the TechQuant Algo Systems portfolio. It also documents the updated allocation going forward and introduces the new defensive strategy sleeve.

Real Account Performance (Tracked Execution)

TechQuant Algo Systems closed the year with a positive return and a stable profitability profile. The results reflect live execution and therefore represent actual trading conditions, including fills, real market volatility, and operational constraints. In addition to the annual return, the expectancy metrics (profit factor and average win/loss characteristics) provide a more complete view of performance quality.

Table 1 - Real Account Performance (Jan 01 2025 to Jan 01 2026)

Metric	Value
Net P&L	25.20%
Starting balance	$25,968.11
Ending balance (approx.)	$32,512.07
Trade win rate	46.84%
Profit factor	1.43
Day win rate	53.05%
Avg win / avg loss ratio	1.07
Average win	3.99%
Average loss	-3.74%

Performance vs Market Benchmarks

To put results into context, TechQuant Algo Systems is compared to widely followed market reference indices and ETFs over the same calendar year. The “Difference vs Account” figure represents the performance gap between the TechQuant tracked account return and each benchmark.

Table 2 — Benchmark Comparison (Calendar Year 2025 Total Return)

Benchmark	2025 Total Return	Difference vs Account (25.20%)
SPY (S&P 500 ETF, total return)	17.72%	+7.48%
QQQ (Nasdaq-100 ETF, total return)	20.77%	+4.43%
IWM (Russell 2000 ETF, NAV total return YTD)	12.69%	+12.51%
AGG (US Aggregate Bond ETF, total return)	7.20%	+18.00%
SGOV (0–3M T-Bills ETF, NAV total return YTD)	4.24%	+20.96%

Strategy Compounding Theoretical Performance (Active Strategies and Retired Set)

TechQuant Algo Systems also tracks a strategy-level model compounding view. This is used for portfolio engineering, allocation design, and monitoring of each strategy’s behavior across different market conditions. Several strategies began mid-year and therefore represent partial-year behavior. Strategies identified as “Retired/Excluded” have been removed from the forward portfolio design.

Table 3 — Strategy Model Compounding (Live + Retired Shown)

Strategy	2025 Return	Model Start ($)	Model End ($)	Status in New Portfolio
TQQQ Super ATR	52.43%	8,000.00	12,868.34	Active
SPXL Super ATR	53.83%	2,400.00	3,868.26	Active
TQQQ FomoCross Momentum	64.01%	3,000.00	5,834.86	Active
SOXL FomoCross Momentum	106.52%	3,500.00	7,226.96	Active
UDOW Super ATR	37.91%	1,000.00	1,429.75	Active
SOXL Super ATR	14.54%	1,600.00	1,836.19	Active
TQQQ Range BB	33.29%	2,000.00	2,703.36	Active
SPXL Range BB	37.28%	3,000.00	4,121.49	Active
SPXL FomoCross Momentum	18.98%	2,000.00	2,494.26	Active
SQQQ Range BB	51.07%			NEW
SPXL MR Deep Buy	-9.31%	1,500.00	1,385.12	Retired / Excluded
TQQQ Price & Volume Breakout	-9.40%	2,000.00	1,893.17	Retired / Excluded
UDOW FomoCross	-5.62%	1,500.00	1,474.80	Retired / Excluded
SOXL Range BB	3.89%	2,500.00	2,597.23	Retired / Excluded

Model Portfolio Summary (Aggregate)

At the portfolio level, the strategy compounding model finished the year materially higher. The model view is reported in two ways: return on starting cash and an exposure-adjusted view because the model includes gross exposure above 100%. This perspective is primarily used for portfolio construction and comparison across strategy baskets; realized returns may differ due to live execution effects.

Table 4 — Model Portfolio Summary

Item	Value
Model starting capital (cash)	$34,000.00
Model ending net value	$52,743.56
Model profit ($)	$18,743.56
Model return on cash	55.00%
Total model exposure	122%
Model return on exposure	45.84%

Updated Allocation Going Forward

The allocation below is the updated TechQuant Algo Systems target weighting for the next cycle. The structure combines a long sleeve (primary return engine across leveraged equity ETFs) with a defensive sleeve intended to help during risk-off regimes. Gross and net exposure are provided to make the portfolio profile explicit.

Table 5 — New Portfolio Allocation (Target Weights)

Strategy	Target Weight	Sleeve
TQQQ Super ATR	20%	Long
SPXL Super ATR	15%	Long
TQQQ FomoCross Momentum	20%	Long
SOXL FomoCross Momentum	20%	Long
UDOW Super ATR	10%	Long
SOXL Super ATR	5%	Long
TQQQ Range BB	7%	Long
SPXL Range BB	5%	Long
SPXL FomoCross Momentum	5%	Long
SQQQ Range Breakout BB	25%	Defensive / Hedge

Allocation Summary	Value
Long sleeve gross weighting	107%
Defensive sleeve gross weighting	25%

New Strategy Introduction — SQQQ Range Breakout BB

TechQuant Algo Systems is adding a new defensive strategy sleeve: SQQQ Range Breakout BB. The purpose is to introduce a systematic hedge component designed to participate during risk-off market conditions and reduce portfolio drawdown pressure during periods of market stress. The model is rule-based and is not intended to be active continuously; it is designed to activate based on defined breakout and volatility conditions.

Automation details and strategy webhook will be shared via your account in techqunt.ca.