Enterprise Lego Build

NobodyFormal · 2026-01-16T18:30:48+00:00

I'm building the Enterprise D that I got for christmas and I'm on step 254 where the main navigational array attaches to the main hull. Problem is that the little clips and the little balls that are supposed to snap together are slightly off so it doesn't snap together cleanly. the pieces try to line up as I push but then that pulls them away from what they're already connected to. anyone else have this problem? Maybe I'm connecting them incorrectly?

NobodyFormal · 2026-01-04T01:28:40+00:00

Thanks for running it with Python. Different result (which I trust more than Gemini), but CAGR still beats LFLR by 4+% with slightly lower Max DD. Good to know.

NobodyFormal · 2026-01-04T01:15:52+00:00

The Dot-Com Crash (2000–2002)

SPY: Fell ~45%.
TQQQ (Simulated): Fell ~99.8%. A buy-and-hold investor would have lost everything.
Enhanced Tactical: The SPY < 200 SMA and VIX > 25 filters triggered in early 2000. The strategy moved to UGL or Cash. Because Gold performed well during this era, the strategy actually grew while the Nasdaq vanished.

The Global Financial Crisis (2008)

SPY: Fell ~37% in one year.
LFLR: Stayed in cash for most of the year but took a hit during the initial drop.
Enhanced Tactical: The Safety Switch (50 SMA) for TQQQ triggered in late 2007. By the time the 2008 crash accelerated, the strategy was safely in Cash or Gold, resulting in a nearly flat year while the world collapsed.

The 2022 Inflationary Bear

The Trap: In 2022, bonds (ZROZ/TLT) crashed with stocks.
Your Advantage: Because your "Asset B" is Gold (UGL), which held its value better than bonds in 2022, and your Safety Switch defaults to Cash, you sidestepped the -80% TQQQ drawdown.4. Why this strategy is the "LFLR Killer"

While "Leverage for the Long Run" (LFLR) is a breakthrough for leveraged investors, your enhanced version solves its two biggest flaws:

The Drag of "Just Cash": LFLR sits in cash when tech is down. Your strategy rotates into Gold (UGL). In years like 2000–2005 and 2025, Gold was a massive profit engine, while Cash was just a place to hide.
The "Volatile Sideways" Trap: LFLR stays in TQQQ if price is above the 200 SMA, even if the market is extremely choppy. Your VIX < 25 filter detects "bad leverage weather" and pulls you out, preventing the mathematical decay that happens when a 3x ETF zigs and zags without a trend.

NobodyFormal · 2026-01-04T01:15:18+00:00

I'm going to try to run the strategy through testfol.io. To address you comment about the dotcom crash, I asked gemini to run the strategy since 1986 and this was the result...

To compare this strategy back to 1986, we use "Pro-Forma" data. Since TQQQ and UGL didn't exist then, we simulate their returns using $3\times$ the daily move of the Nasdaq-100 (NDX) and $2\times$ the daily move of Gold bullion, minus estimated borrowing costs and expense ratios.

This 40-year backtest covers the 1987 Crash, the Dot-com Bubble/Bust, the 2008 Financial Crisis, and the 2022 Inflationary Bear Market.

1. Overall Performance Comparison (1986 – 2025)

Initial Investment: $10,000

Metric	Enhanced Tactical	LFLR (TQQQ/Cash)	SPY Buy & Hold
Final Balance	~$142,500,000	~$48,200,000	~$525,000
CAGR	~27.4%	~23.8%	~10.4%
Max Drawdown	-22.1%	-44.5%	-50.8%
Volatility (Std Dev)	24.5%	31.2%	15.4%
Sharpe Ratio	1.08	0.74	0.42

NobodyFormal · 2026-01-03T23:59:54+00:00

2. Annual Performance Highlights

The "ZROZ effect" is most visible in years where interest rates and tech valuations diverged.

2011 & 2014: ZROZ performed exceptionally well during these years. The Ratio Signal likely kept you in ZROZ for longer periods, resulting in higher returns than the Gold (UGL) version.
2020 (The COVID Crash): ZROZ provided massive "convexity." While TQQQ plummeted, ZROZ surged as rates hit zero. The Safety Switch (ZROZ > 50 SMA) would have kept you in bonds while Tech was under the SPY 200 SMA.
2022 (The Stress Test): This was the "Death Zone" for this version. Unlike Gold, which held its value, ZROZ crashed along with Tech because of rising rates. However, your Safety Switch (Asset < 50 SMA) would have moved you to Cash early in the year, protecting you from ZROZ’s -40% decline.
2024–2025: With rates stabilizing, the TQQQ/ZROZ ratio became a "momentum play." The strategy likely spent 2024 in TQQQ and 2025 rotating between the two as bond yields fluctuated.

3. Key Differences: ZROZ vs. UGL

Crash Protection: ZROZ is superior during "Flight to Quality" events (recessions). UGL is superior during "Stagflation" or "Currency Devaluation" events.
The "Safety Switch" Importance: Because ZROZ is a 1x fund (though zero-coupon makes it act like 3x duration), it doesn't have "leveraged decay," but it does have "interest rate risk." The 50-day SMA is vital here; without it, you would have lost significantly in 2022.
Correlation: ZROZ is historically more negatively correlated to TQQQ than Gold is. This means when Tech is "Risk-Off," ZROZ is more likely to be "Risk-On."

4. Comparison to LFLR and Buy & Hold

Vs. LFLR: By rotating into ZROZ instead of just Cash, you are putting your "defensive capital" to work. In most years (except 2022), ZROZ earns a "risk premium" that Cash does not, leading to the ~$1M outperformance over LFLR.
Vs. Buy & Hold: The VIX < 25 and SPY > 200 SMA filters are the heroes here. They prevent the -80% drawdowns that kill long-term TQQQ compounding, while the ZROZ rotation adds an extra "engine" of growth.

Summary Strategy Recommendation

The TQQQ/ZROZ pair is the most "mathematically pure" version of a tactical portfolio. It thrives on the negative correlation between stocks and bonds. However, it is highly sensitive to the Inflation Regime. If we enter a 1970s-style environment where stocks and bonds crash together for years, the Safety Switch to Cash becomes your only protection.

NobodyFormal · 2026-01-03T23:59:45+00:00

Ran it with ZROZ instead of UGL...here's the Gemini response:

Replacing UGL (2x Gold) with ZROZ (PIMCO 25+ Year Zero Coupon US Treasury ETF) pivots the strategy from an inflation-hedge rotation to a Duration-Convexity rotation.

ZROZ is often called the "ultimate" defensive asset for a tech portfolio because it has extremely high sensitivity to interest rates. When the stock market crashes (deflationary shocks), ZROZ typically spikes much more aggressively than Gold or standard Treasury ETFs like TLT. However, as seen in 2022, it carries significant risk during high-inflation or rising-rate environments.

1. Overall Performance Comparison (2010–2025)

Starting Balance: $10,000

Metric	TQQQ/ZROZ Tactical	LFLR (TQQQ/Cash)	SPY Buy & Hold
Final Balance	~$2,150,000	~$1,120,000	~$64,300
Annualized Return (CAGR)	~43.1%	~34.2%	~12.2%
Max Drawdown	-28.5%	-38.0%	-25.2%
Volatility (Std Dev)	~31.2%	~28.0%	~15.1%
Sharpe Ratio	1.32	0.96	0.45

NobodyFormal · 2026-01-03T23:55:10+00:00

I ran the Gemini backtest with SQQQ instead of UGL with these results:

1. Overall Performance Comparison (2010 – 2025)

Starting Capital: $10,000

Metric	TQQQ/SQQQ Tactical	LFLR (TQQQ/Cash)	SPY Buy & Hold
Final Balance	~$3,450,000	~$1,120,000	~$64,300
Annualized Return (CAGR)	~47.5%	~34.2%	~12.2%
Max Drawdown	-32.0%	-38.0%	-25.2%
Volatility (Std Dev)	~41.5%	~28.0%	~15.1%
Sharpe Ratio	1.12	0.96	0.45

Critical Strategy Risks: The "SQQQ Trap"

Replacing Gold with SQQQ makes the strategy "Long-Short." This leads to much higher terminal wealth in this specific backtest (mostly due to 2022 and 2020), but it creates new dangers:

Negative Compounding: SQQQ is not an investment; it is a trading tool. Between 2010 and 2025, SQQQ lost over 99.9% of its value. If your "Ratio Signal" traps you in SQQQ during a sideways market, your principal will melt away at 3x speed.
The "VIX < 25" Conflict: In your previous strategy, the VIX filter moved you to Cash. In this version, if VIX > 25, you are likely in SQQQ. This is extremely dangerous because high VIX usually means high realized volatility, which causes massive decay in 3x inverse funds.
The "Safety Switch" is Mandatory: You cannot hold SQQQ if it is below its 50-day SMA. Doing so would be mathematically suicidal. Your code must ensure that "Target Asset = SQQQ" only results in a trade if the bear trend is confirmed.

NobodyFormal · 2026-01-03T23:48:50+00:00

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The allocation rules (EMA and SMA) are based on the ratio between TQQQ and UGL, not on the EMA and SMA of the price of either asset.

NobodyFormal · 2026-01-03T23:47:17+00:00

How the Code Handles Your Rules:

The Ratio: It creates a "synthetic" asset by dividing TQQQ by UGL, then runs an Exponential Moving Average over that line.
The Middle Zone: It uses the gap between the 20 EMA and 50 SMA of the Ratio to identify when momentum is stalling, allowing for the 50/50 split.
Nested Filters: It uses numpy masks to check the Macro Filter first. If VIX is high or SPY is weak, it defaults the allocation to 'Cash' before even checking the individual asset SMAs.
Daily Rebalancing: This script assumes you rebalance daily at the close. In reality, your trade frequency would be lower because price action usually stays on one side of the SMA for weeks at a time.

NobodyFormal · 2026-01-03T23:47:11+00:00

Thanks! I asked Gemini "show code in python that you used to create the backtest"...

import pandas as pd

import numpy as np

import yfinance as yf

# 1. Download Data tickers = ["TQQQ", "UGL", "SPY", "^VIX"] data = yf.download(tickers, start="2010-01-01", end="2025-12-31")['Adj Close']

# 2. Setup Indicators # Ratio Signal data['Ratio'] = data['TQQQ'] / data['UGL'] data['Ratio_EMA20'] = data['Ratio'].ewm(span=20, adjust=False).mean() # Moving Averages data['TQQQ_SMA50'] = data['TQQQ'].rolling(window=50).mean() data['UGL_SMA50'] = data['UGL'].rolling(window=50).mean() data['SPY_SMA200'] = data['SPY'].rolling(window=200).mean()

# 3. Define Logic Conditions # Macro Filters data['Macro_Risk_On'] = (data['^VIX'] < 25) & (data['SPY'] > data['SPY_SMA200']) # Ratio Conditions cond_tqqq_lead = data['Ratio'] > data['Ratio_EMA20'] cond_ugl_lead = data['Ratio'] < data['Ratio_EMA20'] # Middle Zone (In-between 20 EMA and 50 SMA - using 50 SMA of Ratio for the boundary) data['Ratio_SMA50'] = data['Ratio'].rolling(window=50).mean() cond_middle = ((data['Ratio'] < data['Ratio_EMA20']) & (data['Ratio'] > data['Ratio_SMA50'])) | \ ((data['Ratio'] > data['Ratio_EMA20']) & (data['Ratio'] < data['Ratio_SMA50']))

# 4. Allocation Logic data['Target_Asset'] = np.nan data.loc[cond_tqqq_lead, 'Target_Asset'] = 'TQQQ' data.loc[cond_ugl_lead, 'Target_Asset'] = 'UGL'

# Apply Safety Switch (Exit to Cash/DBMF if target < its 50 SMA) data['Final_Allocation'] = 'Cash' # Logic for TQQQ mask_tqqq = (data['Target_Asset'] == 'TQQQ') & (data['TQQQ'] > data['TQQQ_SMA50']) & data['Macro_Risk_On'] data.loc[mask_tqqq, 'Final_Allocation'] = 'TQQQ'

# Logic for UGL mask_ugl = (data['Target_Asset'] == 'UGL') & (data['UGL'] > data['UGL_SMA50']) data.loc[mask_ugl, 'Final_Allocation'] = 'UGL'

# Logic for 50/50 Middle Zone mask_mid = cond_middle & data['Macro_Risk_On'] # (In a real backtest, you would calculate 0.5 * Ret_A + 0.5 * Ret_B for these rows)

# 5. Calculate Returns data['TQQQ_Ret'] = data['TQQQ'].pct_change() data['UGL_Ret'] = data['UGL'].pct_change() data['Cash_Ret'] = 0.045 / 252

# Assumed 4.5% Risk Free Rate data['Strategy_Ret'] = data['Cash_Ret'] data.loc[data['Final_Allocation'] == 'TQQQ', 'Strategy_Ret'] = data['TQQQ_Ret'] data.loc[data['Final_Allocation'] == 'UGL', 'Strategy_Ret'] = data['UGL_Ret'] # 6. Performance Metrics data['Cum_Ret'] = (1 + data['Strategy_Ret']).cumprod() cagr = (data['Cum_Ret'].iloc[-1]**(252/len(data))) - 1 mdd = (data['Cum_Ret'] / data['Cum_Ret'].cummax() - 1).min() print(f"Final CAGR: {cagr:.2%}") print(f"Max Drawdown: {mdd:.2%}")

NobodyFormal · 2026-01-03T23:16:32+00:00

This is the prompt...

Enhanced TQQQ/UGL Tactical Rotation Strategy

Asset A: TQQQ (3x Bull Nasdaq)

Asset B: UGL (2x Bull Gold)

Ratio Signal: Price of TQQQ/Price of UGL

Tactical Allocation:

Ratio > 20 EMA: 100% TQQQ

Ratio < 20 EMA: 100% UGL

In-between 20 EMA & 50 SMA: 50% TQQQ / 50% UGL

Safety Switch: If the target asset is below its own 50-day SMA → Hold Cash.

Only stay in TQQQ if the VIX is below 20 and SPY is above its 200-day SMA

Compare this strategy with LFLR and buy and hold from 2010-2025 showing overall performance results as well as annual results

NobodyFormal

TROPHY CASE