What allocation is usually optimal for retirement?

On global pooled data with a guardrail or fixed strategy, broad equity-heavy mixes around 50-70% total stocks with meaningful international exposure tend to sit in the near-optimal zone for long retirements. The exact peak depends on horizon and strategy — run your own parameters.

Should I include international stocks?

For most retirement horizons, yes: international diversification cuts the left tail materially. US-only history makes home bias look free, but that is one country's unusually good draw.

What is the Pareto frontier view for?

It shows allocations where you cannot improve safety (funded ratio) without giving up upside (median final wealth), or vice versa — the efficient menu to choose from.

Retirement Asset Allocation Optimizer

Scan hundreds of domestic stock, international stock, and bond combinations to find the optimal asset allocation for your retirement portfolio. View results as heatmaps, ternary plots, and Pareto frontiers.

Example resultcomputed from the default parameters — adjust anything and hit Run to see your own numbers.

Best Funded Ratio

95.6%

Best Allocation

50/50/0/0

Dom/Global/Bond/Cash

Success Rate

88.8%

Median Final Portfolio

14.12M

Tail Value

Near-Optimal Zone

23 / 286

within ±1% of best

Asset Allocation — Funded Ratio Heatmap

Gold borders = near-optimal zone. Star = best allocation.

Cash level shown

Funded Ratio vs Median Final

Blue diamonds show the best trade-off between safety (funded ratio) and upside (median final). No other allocation beats them on both.

All Results (286 combinations)


50	50	0	0	95.6%	88.8%	14.12M	93.46M	39.23M	Year 48
60	40	0	0	95.5%	88.4%	14.84M	96.60M	39.62M	Year 46
50	40	10	0	95.5%	87.9%	10.89M	64.18M	27.14M	Year 46
50	40	0	10	95.4%	87.5%	10.34M	61.48M	25.64M	Year 43
60	30	10	0	95.4%	87.8%	11.66M	68.06M	27.18M	Year 44
60	30	0	10	95.4%	87.8%	11.02M	64.22M	25.68M	Year 44
40	50	10	0	95.3%	87.1%	9.92M	64.30M	26.77M	Year 43
40	60	0	0	95.3%	87.5%	12.77M	89.33M	38.43M	Year 45
70	30	0	0	95.3%	88.3%	15.36M	100.92M	39.53M	Year 43
40	50	0	10	95.2%	86.6%	9.57M	60.12M	25.29M	Year 43
50	30	10	10	95.1%	85.8%	7.78M	41.95M	17.27M	Year 42
50	30	20	0	95.1%	85.6%	8.34M	43.60M	18.34M	Year 42
50	30	0	20	95.1%	85.8%	7.27M	40.54M	16.27M	Year 42
70	20	0	10	95.0%	86.8%	11.10M	64.85M	25.38M	Year 42
70	20	10	0	95.0%	87.2%	11.58M	67.24M	26.87M	Year 41
40	40	20	0	95.0%	85.6%	7.49M	43.86M	18.24M	Year 42
40	40	10	10	94.9%	85.3%	7.04M	40.56M	17.17M	Year 41
60	20	0	20	94.9%	85.0%	7.61M	41.35M	16.14M	Year 41
60	20	10	10	94.8%	85.1%	8.13M	43.40M	17.13M	Year 40
80	20	0	0	94.8%	87.3%	15.56M	99.49M	38.95M	Year 40
40	40	0	20	94.8%	84.7%	6.79M	38.68M	16.18M	Year 41
60	20	20	0	94.7%	85.3%	8.53M	45.75M	18.20M	Year 40
30	60	10	0	94.7%	85.8%	9.07M	60.55M	26.12M	Year 41
30	70	0	0	94.5%	85.8%	11.65M	85.91M	37.25M	Year 40
30	60	0	10	94.5%	85.2%	8.72M	57.11M	24.67M	Year 39
30	50	20	0	94.5%	84.5%	6.70M	42.14M	17.92M	Year 39
30	50	10	10	94.4%	84.2%	6.59M	40.74M	16.87M	Year 39
80	10	10	0	94.3%	85.5%	11.53M	69.05M	26.20M	Year 38
70	10	10	10	94.3%	84.6%	8.12M	43.85M	16.76M	Year 38
80	10	0	10	94.3%	84.9%	10.86M	64.56M	24.75M	Year 38
70	10	0	20	94.2%	83.9%	7.55M	41.43M	15.79M	Year 38
70	10	20	0	94.2%	84.4%	8.40M	47.20M	17.81M	Year 38
30	50	0	20	94.2%	83.7%	6.31M	38.99M	15.89M	Year 38
50	20	10	20	94.2%	82.3%	5.04M	26.90M	10.57M	Year 39
40	30	10	20	94.1%	81.8%	4.85M	25.54M	10.61M	Year 38
50	20	0	30	94.1%	81.7%	4.85M	24.72M	9.92M	Year 39
40	30	20	10	94.1%	82.2%	5.05M	27.27M	11.32M	Year 39
50	20	20	10	94.1%	82.4%	5.44M	28.16M	11.28M	Year 38
40	30	0	30	94.0%	81.5%	4.50M	24.25M	9.96M	Year 38
90	10	0	0	94.0%	85.4%	14.83M	98.94M	37.87M	Year 37
40	30	30	0	93.9%	81.7%	5.23M	29.50M	12.08M	Year 39
50	20	30	0	93.9%	82.0%	5.61M	29.85M	12.04M	Year 38
20	70	10	0	93.8%	84.0%	8.09M	57.48M	25.21M	Year 37
60	10	10	20	93.8%	81.7%	5.25M	26.78M	10.38M	Year 37
30	40	20	10	93.7%	81.2%	4.60M	26.68M	11.21M	Year 37
60	10	0	30	93.7%	81.2%	4.96M	25.17M	9.73M	Year 37
30	40	10	20	93.7%	80.7%	4.41M	25.60M	10.51M	Year 37
30	40	30	0	93.6%	81.3%	4.75M	28.94M	11.96M	Year 37
60	10	20	10	93.6%	81.5%	5.61M	28.38M	11.08M	Year 37
20	60	20	0	93.6%	82.2%	6.03M	40.49M	17.40M	Year 37
20	80	0	0	93.6%	84.3%	10.06M	80.66M	35.76M	Year 36
20	70	0	10	93.5%	83.2%	7.59M	54.55M	23.80M	Year 36
20	60	10	10	93.5%	82.1%	5.84M	39.23M	16.38M	Year 37
60	10	30	0	93.4%	81.3%	5.86M	30.22M	11.82M	Year 36
30	40	0	30	93.4%	80.3%	4.12M	24.36M	9.86M	Year 36
80	0	10	10	93.4%	82.8%	7.57M	43.65M	16.15M	Year 35
80	0	0	20	93.4%	82.3%	7.20M	40.32M	15.20M	Year 35
90	0	0	10	93.4%	83.4%	10.22M	63.75M	23.77M	Year 35
90	0	10	0	93.3%	83.7%	10.91M	67.32M	25.17M	Year 35
80	0	20	0	93.3%	82.5%	8.01M	45.08M	17.16M	Year 35
20	60	0	20	93.2%	81.3%	5.55M	37.56M	15.42M	Year 35
100	0	0	0	93.0%	83.3%	13.80M	95.01M	36.28M	Year 33
70	0	0	30	93.0%	79.7%	4.76M	24.93M	9.40M	Year 35
70	0	10	20	93.0%	79.8%	5.03M	26.54M	10.03M	Year 35
20	50	30	0	92.9%	79.6%	4.08M	27.74M	11.70M	Year 35
20	50	20	10	92.9%	79.2%	4.01M	26.55M	10.96M	Year 36
70	0	20	10	92.9%	80.2%	5.29M	28.47M	10.71M	Year 34
40	20	10	30	92.7%	77.3%	2.96M	16.05M	6.22M	Year 36
20	50	10	20	92.7%	78.5%	3.92M	25.93M	10.28M	Year 36
70	0	30	0	92.7%	79.8%	5.51M	29.39M	11.43M	Year 34
40	20	20	20	92.7%	78.0%	3.15M	16.87M	6.68M	Year 36
50	10	20	20	92.6%	77.5%	3.37M	17.27M	6.58M	Year 35
10	80	10	0	92.6%	81.2%	6.90M	55.24M	24.10M	Year 33
50	10	10	30	92.6%	76.8%	3.12M	15.85M	6.13M	Year 35
40	20	0	40	92.5%	76.5%	2.70M	14.79M	5.80M	Year 36
40	20	30	10	92.5%	77.5%	3.30M	18.45M	7.18M	Year 36
20	50	0	30	92.5%	78.0%	3.62M	24.31M	9.64M	Year 34
50	10	30	10	92.4%	77.8%	3.44M	18.65M	7.08M	Year 35
50	10	0	40	92.4%	76.3%	2.89M	15.01M	5.71M	Year 35
10	70	20	0	92.4%	79.5%	5.17M	38.95M	16.72M	Year 34
10	90	0	0	92.4%	81.5%	8.40M	76.77M	34.01M	Year 32
30	30	10	30	92.3%	76.4%	2.70M	15.51M	6.23M	Year 35
30	30	20	20	92.3%	76.6%	2.80M	16.76M	6.68M	Year 35
40	20	40	0	92.3%	77.4%	3.40M	19.48M	7.72M	Year 35
10	80	0	10	92.3%	80.5%	6.40M	52.53M	22.74M	Year 33
30	30	30	10	92.3%	77.1%	3.01M	17.79M	7.18M	Year 35
10	70	10	10	92.2%	79.2%	5.02M	37.47M	15.73M	Year 33
50	10	40	0	92.1%	77.4%	3.57M	19.67M	7.61M	Year 34
30	30	40	0	92.1%	76.8%	3.06M	19.16M	7.71M	Year 34
30	30	0	40	92.0%	75.4%	2.50M	14.82M	5.81M	Year 35
60	0	10	30	91.9%	75.5%	3.07M	15.75M	5.94M	Year 34
60	0	20	20	91.9%	76.3%	3.26M	16.72M	6.38M	Year 34
10	70	0	20	91.9%	78.5%	4.62M	36.79M	14.81M	Year 33
60	0	0	40	91.8%	75.2%	2.79M	14.78M	5.53M	Year 34
60	0	30	10	91.8%	76.2%	3.42M	17.57M	6.86M	Year 33
10	60	30	0	91.6%	77.0%	3.54M	26.92M	11.31M	Year 33
10	60	20	10	91.5%	76.3%	3.45M	26.02M	10.60M	Year 33
20	40	30	10	91.5%	74.9%	2.64M	17.28M	7.08M	Year 33
20	40	20	20	91.5%	74.4%	2.54M	16.41M	6.59M	Year 34
60	0	40	0	91.5%	75.9%	3.58M	19.37M	7.38M	Year 32
10	60	10	20	91.4%	75.8%	3.32M	24.44M	9.93M	Year 32
20	40	10	30	91.4%	73.9%	2.35M	15.36M	6.14M	Year 34
20	40	40	0	91.4%	75.3%	2.69M	18.75M	7.61M	Year 33
20	40	0	40	91.1%	72.6%	2.10M	14.57M	5.73M	Year 33
10	60	0	30	91.1%	74.2%	3.02M	23.71M	9.32M	Year 32
0	90	10	0	90.9%	77.0%	5.49M	52.63M	22.83M	Year 30
0	100	0	0	90.7%	77.5%	6.85M	71.42M	32.07M	Year 29
0	80	20	0	90.6%	75.4%	4.15M	37.26M	15.92M	Year 31
0	90	0	10	90.5%	76.2%	5.23M	50.08M	21.53M	Year 29
0	80	10	10	90.4%	75.3%	3.96M	35.48M	14.97M	Year 30
40	10	20	30	90.4%	69.8%	1.57M	10.05M	3.66M	Year 33
40	10	10	40	90.3%	69.0%	1.44M	9.24M	3.38M	Year 33
40	10	30	20	90.3%	70.2%	1.70M	10.73M	3.98M	Year 33
10	50	30	10	90.2%	71.5%	2.19M	17.25M	6.90M	Year 31
30	20	20	30	90.2%	69.3%	1.45M	9.84M	3.71M	Year 33
10	50	20	20	90.2%	71.1%	2.06M	16.24M	6.42M	Year 31
10	50	40	0	90.1%	72.2%	2.24M	18.19M	7.41M	Year 31
30	20	30	20	90.1%	69.5%	1.56M	10.73M	4.03M	Year 32
40	10	40	10	90.1%	70.0%	1.74M	11.83M	4.33M	Year 32
30	20	10	40	90.1%	68.5%	1.36M	9.03M	3.42M	Year 32
50	0	20	30	90.0%	69.7%	1.62M	9.77M	3.56M	Year 32
0	80	0	20	90.0%	73.5%	3.63M	34.64M	14.09M	Year 30
40	10	0	50	90.0%	67.7%	1.31M	8.62M	3.12M	Year 33
10	50	10	30	90.0%	70.3%	1.96M	15.13M	5.99M	Year 31
50	0	30	20	90.0%	69.7%	1.70M	10.77M	3.87M	Year 32
30	20	40	10	89.9%	69.3%	1.65M	11.64M	4.38M	Year 32
0	70	30	0	89.9%	72.8%	2.85M	25.90M	10.83M	Year 30
50	0	10	40	89.9%	68.5%	1.49M	9.14M	3.28M	Year 32
0	70	20	10	89.8%	72.0%	2.68M	24.55M	10.14M	Year 30
40	10	50	0	89.8%	70.3%	1.85M	12.92M	4.70M	Year 31
50	0	40	10	89.7%	69.8%	1.83M	11.56M	4.21M	Year 31
50	0	0	50	89.7%	67.7%	1.31M	8.28M	3.02M	Year 32
30	20	0	50	89.6%	66.2%	1.23M	8.47M	3.17M	Year 32
30	20	50	0	89.6%	69.3%	1.73M	12.59M	4.75M	Year 31
10	50	0	40	89.5%	69.0%	1.75M	14.27M	5.59M	Year 31
0	70	10	20	89.5%	71.1%	2.57M	23.44M	9.51M	Year 30
50	0	50	0	89.4%	69.9%	1.85M	12.49M	4.57M	Year 30
20	30	30	20	89.4%	66.9%	1.34M	10.42M	4.02M	Year 31
20	30	20	30	89.3%	66.8%	1.23M	9.77M	3.71M	Year 32
20	30	40	10	89.2%	67.5%	1.39M	11.38M	4.36M	Year 31
20	30	10	40	89.1%	66.5%	1.12M	9.19M	3.42M	Year 32
20	30	50	0	89.0%	68.0%	1.44M	12.41M	4.74M	Year 31
0	70	0	30	88.9%	69.6%	2.40M	22.42M	8.92M	Year 29
20	30	0	50	88.6%	64.5%	1.04M	8.53M	3.17M	Year 31
0	60	30	10	88.4%	67.5%	1.80M	16.65M	6.65M	Year 29
0	60	40	0	88.3%	67.6%	1.79M	17.55M	7.15M	Year 29
0	60	20	20	88.2%	66.6%	1.62M	15.67M	6.20M	Year 29
10	40	30	20	88.0%	64.1%	1.03M	10.40M	3.96M	Year 30
10	40	40	10	87.9%	64.5%	1.08M	11.17M	4.30M	Year 30
0	60	10	30	87.9%	65.4%	1.45M	14.82M	5.78M	Year 29
10	40	20	30	87.8%	63.7%	968,964	9.67M	3.66M	Year 30
10	40	50	0	87.7%	65.0%	1.15M	11.95M	4.67M	Year 30
10	40	10	40	87.5%	62.5%	877,749	9.01M	3.38M	Year 30
0	60	0	40	87.3%	64.1%	1.27M	14.03M	5.40M	Year 28
10	40	0	50	86.9%	61.1%	775,305	8.31M	3.14M	Year 30
40	0	30	30	86.7%	59.3%	491,196	6.00M	1.98M	Year 30
40	0	40	20	86.6%	60.0%	542,493	6.61M	2.19M	Year 29
30	10	30	30	86.6%	58.7%	442,917	5.88M	2.04M	Year 30
40	0	20	40	86.6%	58.3%	416,695	5.43M	1.79M	Year 30
30	10	40	20	86.6%	59.8%	532,827	6.60M	2.26M	Year 30
30	10	20	40	86.5%	57.1%	348,653	5.38M	1.85M	Year 30
40	0	50	10	86.4%	60.7%	561,420	7.19M	2.43M	Year 29
30	10	50	10	86.4%	60.3%	563,000	7.34M	2.50M	Year 29
40	0	10	50	86.3%	56.8%	325,469	4.83M	1.62M	Year 30
30	10	10	50	86.1%	55.9%	304,145	4.97M	1.68M	Year 30
40	0	60	0	86.1%	60.1%	625,941	7.84M	2.68M	Year 28
30	10	60	0	86.1%	60.7%	564,886	8.17M	2.76M	Year 28
0	50	40	10	85.8%	60.4%	859,445	10.80M	4.20M	Year 28
20	20	40	20	85.8%	57.4%	393,109	6.43M	2.30M	Year 29
40	0	0	60	85.8%	56.0%	242,340	4.52M	1.47M	Year 30
20	20	30	30	85.8%	56.4%	339,297	5.81M	2.08M	Year 29
0	50	30	20	85.8%	59.3%	786,683	10.10M	3.87M	Year 28
0	50	50	0	85.8%	60.8%	848,928	11.76M	4.55M	Year 28
20	20	50	10	85.7%	58.1%	419,100	7.23M	2.53M	Year 29
30	10	0	60	85.7%	55.0%	241,574	4.58M	1.53M	Year 30
20	20	20	40	85.7%	55.5%	248,353	5.31M	1.89M	Year 30
0	50	20	30	85.6%	58.6%	694,652	9.42M	3.58M	Year 28
20	20	60	0	85.4%	58.1%	439,586	8.03M	2.79M	Year 28
20	20	10	50	85.3%	54.1%	183,572	4.85M	1.72M	Year 30
0	50	10	40	85.2%	57.7%	591,371	8.73M	3.31M	Year 28
20	20	0	60	84.8%	53.5%	168,615	4.57M	1.57M	Year 30
0	50	0	50	84.7%	57.1%	468,737	8.14M	3.08M	Year 27
10	30	30	30	84.4%	53.6%	163,407	5.75M	2.09M	Year 29
10	30	40	20	84.4%	54.6%	253,143	6.21M	2.31M	Year 28
10	30	50	10	84.2%	54.6%	293,970	7.00M	2.54M	Year 28
10	30	20	40	84.2%	52.9%	112,328	5.34M	1.90M	Year 29
10	30	60	0	84.1%	54.9%	328,548	7.82M	2.80M	Year 28
10	30	10	50	83.8%	51.8%	70,969	4.94M	1.74M	Year 29
10	30	0	60	83.3%	50.8%	8,028	4.41M	1.59M	Year 28
0	40	40	20	82.6%	51.3%	54,528	6.33M	2.29M	Year 27
0	40	50	10	82.5%	52.4%	111,483	6.83M	2.51M	Year 27
0	40	30	30	82.5%	51.0%	33,561	5.68M	2.08M	Year 27
0	40	60	0	82.3%	52.3%	144,675	7.39M	2.77M	Year 27
0	40	20	40	82.2%	50.2%	0	5.26M	1.90M	Year 27
0	40	10	50	81.8%	49.5%	0	4.82M	1.74M	Year 27
0	40	0	60	81.3%	47.7%	0	4.57M	1.60M	Year 27
30	0	40	30	81.1%	44.2%	0	3.30M	1.02M	Year 28
30	0	50	20	81.1%	44.0%	0	3.77M	1.16M	Year 27
30	0	30	40	81.0%	43.2%	0	2.94M	892,536	Year 28
30	0	60	10	80.9%	45.1%	0	4.19M	1.32M	Year 27
30	0	20	50	80.7%	41.9%	0	2.66M	781,932	Year 28
20	10	40	30	80.6%	43.1%	0	3.31M	1.07M	Year 28
20	10	50	20	80.6%	43.9%	0	3.79M	1.21M	Year 27
30	0	70	0	80.5%	45.5%	0	4.66M	1.50M	Year 26
20	10	30	40	80.5%	42.3%	0	3.03M	937,120	Year 28
20	10	60	10	80.4%	45.0%	0	4.18M	1.37M	Year 26
30	0	10	60	80.3%	40.3%	0	2.33M	686,111	Year 28
20	10	20	50	80.2%	41.9%	0	2.74M	824,922	Year 28
20	10	70	0	80.2%	45.1%	0	4.73M	1.55M	Year 26
20	10	10	60	79.8%	40.8%	0	2.44M	727,884	Year 28
30	0	0	70	79.7%	38.6%	0	2.06M	604,733	Year 28
10	20	40	30	79.6%	42.4%	0	3.34M	1.10M	Year 27
10	20	50	20	79.6%	43.1%	0	3.71M	1.24M	Year 27
10	20	30	40	79.4%	41.3%	0	2.99M	971,525	Year 27
10	20	60	10	79.4%	44.3%	0	4.27M	1.40M	Year 26
20	10	0	70	79.2%	38.9%	0	2.12M	646,148	Year 28
10	20	70	0	79.2%	44.5%	0	4.74M	1.58M	Year 26
10	20	20	50	79.1%	40.2%	0	2.67M	860,265	Year 27
10	20	10	60	78.7%	38.8%	0	2.41M	764,888	Year 27
10	20	0	70	78.2%	37.0%	0	2.19M	683,868	Year 27
0	30	40	30	78.1%	40.8%	0	3.40M	1.12M	Year 26
0	30	50	20	78.1%	42.0%	0	3.66M	1.26M	Year 26
0	30	60	10	78.0%	42.7%	0	4.10M	1.41M	Year 25
0	30	30	40	77.9%	39.7%	0	3.01M	994,845	Year 26
0	30	70	0	77.8%	43.1%	0	4.63M	1.59M	Year 25
0	30	20	50	77.6%	38.2%	0	2.75M	887,582	Year 26
0	30	10	60	77.1%	37.0%	0	2.42M	795,306	Year 26
0	30	0	70	76.5%	35.7%	0	2.27M	715,988	Year 25
20	0	60	20	73.6%	30.3%	0	1.94M	591,453	Year 25
20	0	70	10	73.6%	31.4%	0	2.32M	696,756	Year 25
20	0	50	30	73.5%	28.6%	0	1.73M	498,798	Year 25
20	0	40	40	73.4%	27.9%	0	1.43M	416,934	Year 26
20	0	80	0	73.4%	32.8%	0	2.58M	814,140	Year 24
10	10	60	20	73.3%	30.6%	0	1.97M	617,693	Year 25
10	10	50	30	73.2%	28.9%	0	1.74M	524,405	Year 25
10	10	70	10	73.2%	31.6%	0	2.31M	723,882	Year 24
20	0	30	50	73.2%	26.5%	0	1.28M	346,137	Year 26
10	10	40	40	73.1%	27.8%	0	1.48M	443,101	Year 25
10	10	80	0	73.0%	32.3%	0	2.62M	842,089	Year 24
20	0	20	60	72.8%	24.6%	0	1.01M	286,414	Year 26
10	10	30	50	72.8%	25.9%	0	1.23M	373,487	Year 26
0	20	60	20	72.4%	29.6%	0	1.96M	641,002	Year 24
0	20	70	10	72.3%	30.9%	0	2.19M	744,679	Year 24
0	20	50	30	72.3%	28.9%	0	1.69M	548,346	Year 24
10	10	20	60	72.3%	24.6%	0	1.02M	315,137	Year 26
20	0	10	70	72.3%	23.1%	0	847,608	238,029	Year 26
0	20	80	0	72.2%	32.5%	0	2.59M	860,677	Year 23
0	20	40	40	72.1%	27.2%	0	1.48M	468,449	Year 24
0	20	30	50	71.8%	25.4%	0	1.26M	401,524	Year 25
10	10	10	70	71.7%	23.0%	0	851,006	267,273	Year 25
20	0	0	80	71.6%	20.9%	0	669,754	200,682	Year 26
0	20	20	60	71.3%	24.4%	0	1.06M	345,187	Year 24
10	10	0	80	71.1%	21.4%	0	694,056	229,084	Year 25
0	20	10	70	70.7%	22.6%	0	888,196	298,448	Year 24
0	20	0	80	70.0%	20.8%	0	753,041	260,586	Year 24
10	0	90	0	66.5%	23.2%	0	1.17M	424,163	Year 22
10	0	80	10	66.5%	22.0%	0	1.01M	350,692	Year 23
10	0	70	20	66.4%	20.2%	0	853,927	286,475	Year 23
10	0	60	30	66.1%	18.4%	0	684,693	230,331	Year 23
0	10	90	0	66.1%	23.1%	0	1.21M	442,016	Year 22
0	10	80	10	66.1%	21.6%	0	1.05M	368,385	Year 22
0	10	70	20	65.9%	19.9%	0	858,002	304,132	Year 23
10	0	50	40	65.8%	17.0%	0	460,931	182,567	Year 24
0	10	60	30	65.7%	18.5%	0	655,349	248,260	Year 23
10	0	40	50	65.4%	15.4%	0	333,647	142,523	Year 24
0	10	50	40	65.4%	16.9%	0	471,604	200,787	Year 23
0	10	40	50	65.0%	15.2%	0	324,809	161,511	Year 23
10	0	30	60	64.9%	13.6%	0	211,138	110,819	Year 24
0	10	30	60	64.5%	14.1%	0	217,154	129,154	Year 23
10	0	20	70	64.3%	12.2%	0	112,242	86,597	Year 24
0	10	20	70	63.9%	12.5%	0	102,412	103,676	Year 23
10	0	10	80	63.6%	10.5%	0	0	68,169	Year 24
0	10	10	80	63.2%	10.8%	0	134	84,494	Year 23
10	0	0	90	62.8%	8.7%	0	0	55,847	Year 24
0	10	0	90	62.5%	9.3%	0	0	70,939	Year 23
0	0	100	0	60.0%	14.0%	0	293,383	211,736	Year 20
0	0	90	10	59.8%	12.8%	0	194,174	168,596	Year 21
0	0	80	20	59.6%	11.7%	0	82,064	131,469	Year 21
0	0	70	30	59.3%	10.2%	0	0	100,375	Year 21
0	0	60	40	58.9%	8.8%	0	0	75,328	Year 21
0	0	50	50	58.5%	7.5%	0	0	55,046	Year 22
0	0	40	60	57.9%	6.0%	0	0	40,110	Year 22
0	0	30	70	57.3%	5.3%	0	0	28,963	Year 22
0	0	20	80	56.6%	4.2%	0	0	21,407	Year 22
0	0	10	90	56.0%	3.5%	0	0	16,754	Year 22
0	0	0	100	55.3%	2.9%	0	0	13,570	Year 21

What this optimizer does

The optimizer sweeps every combination of domestic stocks, international stocks, and bonds (at your chosen step size) and runs a Monte Carlo simulation for each. Results appear as a ternary heatmap, a sortable table, and a Pareto frontier of safety versus upside, so you can see not just the single best mix but the whole near-optimal region.

Why the near-optimal zone matters more than the peak

Allocation surfaces are flat near the top: dozens of mixes usually sit within one percentage point of the best funded ratio. Any of them is statistically defensible, so secondary preferences — home bias, simplicity, behavioral comfort — can safely decide. Chasing the exact peak of a historical backtest is curve-fitting.

Diversification across 16 countries

With global pooled data, single-country disasters (hyperinflation Germany, wartime Japan or France) enter the simulation at realistic frequency. Portfolios that look optimal on US-only history — often 90%+ equities — typically shift toward more international diversification and moderate bond allocations when judged against the broader historical record.

Frequently asked questions

What allocation is usually optimal for retirement?: On global pooled data with a guardrail or fixed strategy, broad equity-heavy mixes around 50-70% total stocks with meaningful international exposure tend to sit in the near-optimal zone for long retirements. The exact peak depends on horizon and strategy — run your own parameters.
Should I include international stocks?: For most retirement horizons, yes: international diversification cuts the left tail materially. US-only history makes home bias look free, but that is one country's unusually good draw.
What is the Pareto frontier view for?: It shows allocations where you cannot improve safety (funded ratio) without giving up upside (median final wealth), or vice versa — the efficient menu to choose from.