9/19/ 2012 Presidential True Vote/Election Fraud Simulation Model:Obama 320 EV; 100% Win Probability
By Richard Charnin
Sept.19, 2012
From Richard Charnin’s Blog
Posted with the permission of the author
The analysis assumes that the election is held on the latest poll date.
2012 Presidential True Vote and Monte Carlo Simulation Forecast Model
Forecast Summary
Obama has jumped to a commanding 49-44% lead in the latest state polls and has 320 expected electoral votes based on the win probabilities. The 500 trial Monte Carlo simulation indicates that if the election were held today, he would have a 100% probability of winning the electoral vote (he won all 500 election simulation trials). But it’s still too early to project him a winner. (Image)
Approximately 7% of voters are undecided and may hold the key to the election. I suspect they are mostly Democrats disillusioned with Obama but scared by Romney and Ryan. The model currently assumes an equal split of the undecided vote. If undecided voters break for Obama, he will be in a commanding position to win re-election. But look for an October surprise.
The polls are anticipating the inevitable 5% reduction in Obama’s True Vote. Immediately after the Democratic Convention, Obama moved into a 5% lead in the Gallup (RV) and Rasmussen (LV) national tracking polls, but the polls are tied once again.
The forecast model is a combination of a) a pre-election Monte Carlo Simulation Model, which is based on the latest state polls, and b) the True Vote Model, based on a feasible estimate of new and returning 2008 voters and corresponding estimated vote shares. The model will be updated periodically for the latest state and national polls.
9/19/2012
True Vote Model Obama Romney
True Vote...... 55.25% 44.75%
Expected EV.... 379.64 158.36
Snapshot EV.... 380 158
EV Win Prob.... 99.97% 0.03%
State Polls
Average........ 49.3% 44.4%
Projection..... 52.5% 47.5%
Pop. Win Prob.. 94.8% 5.2%
Expected EV.... 320.2 217.8
Snapshot EV.... 322 216
National Polls
Average..... .. 48.20% 45.30%
Projection.. .. 51.45% 48.55%
Pop. Win Prob.. 92.2% 7.8%
Gallup......... 47.0% 46.0%
Rasmussen...... 46.0% 47.0%
Simulation
Projection..... 52.5% 47.5%
Mean EV........ 320.4 217.6
Max EV......... 351 187
Min EV......... 278 260
EV Win Prob.... 100.0% 0.0%
Polling samples are based on prior election recorded votes – not the previous True Vote or unadjusted exit poll. Likely voter (LV) polls discount the pervasive systematic fraud factor. They are traditionally excellent predictors of the recorded vote – which always understate the Democratic True Vote.
In the six presidential elections from 1988-2008, the Democrats won the average recorded vote by 48-46%. But they led both state and national exit polls by 52-42%. There were approximately 375,000 respondents in the 274 state polls and 90,000 respondents in the six national polls. Overall, an extremely low margin of error.
Based on the historical record, Obama’s True Vote share is about 4-5% higher than the latest polls indicate. It is a certainty that he will lose millions of votes on Election Day to fraud. The only question is: Will he overcome the systemic fraud factor? As of today, it appears he will.
The 2008 True Vote Model (TVM) determined that Obama won in a landslide by 58-40.3%. Based on the historical red-shift, he needs at least a 55% True Vote share to overcome the systemic 5% fraud factor. The TVM was confirmed by the unadjusted state exit poll aggregate: Obama had an identical 58-40.5% margin (76,000 respondents). He won unadjusted National Exit Poll (17,836 respondents) by an even bigger 61-37% margin.
The National Exit Poll displayed on mainstream media websites (Fox, CNN, ABC, CBS, NYT, etc.) indicate that Obama had 52.9% – his recorded vote. Unadjusted state and national exit polls are always forced to match the recorded share.
The source of the polling data is the Real Clear Politics (RCP) website. The simulation uses the latest state polls. Recorded 2008 vote shares are used for states which have not yet been polled.
The True Vote Model
In projecting the national vote, the required input to the TVM are returning 2008 voter turnout rates in 2012 and estimated 2012 vote shares. The rates are applied to each state in order to derive the national aggregate turnout . A 1.25% annual voter mortality rate is assumed. There are two options for estimating returning voters. The default option assumes that 2008 voters return in proportion to the unadjusted 2008 exit poll aggregate (Obama won by 58-40.5%). In this scenario, Obama wins by 55-45% with 380 EV and has a 100% EV win probability.
It is important to note that the True Vote is never the same as the recorded vote. The 1988-2008 True Vote Model utilizes estimates of previous election returning and new voters and and adjusted state and national exit poll vote shares.
Sensitivity analysis
The TVM displays the effects of effects of incremental changes in turnout rates and shares of returning voters. Three tables are generated consisting of nine scenario combinations of a) Obama and McCain turnout rates and b) the Obama/Romney shares of returning Obama and McCain voters. The output tables display resulting vote shares, vote margins and popular vote win probabilities.
Monte Carlo Simulation: 500 election trials
There are two options for the simulation model. Both should be used and the results compared. The default option uses the TVM projected state vote shares. The second option uses projections based on the latest pre-election state polls.
The projected vote share is the sum of the poll share and the undecided voter allocation (UVA). The model uses state vote share projections as input to the Normal Distribution function to determine the state win probability.
The simulation consists of 500 election trials. The electoral vote win probability is the number of winning election trials divided by 500.
In each election trial, a random number (RND) between 0 and 1 is generated for each state and compared to Obama’s state win probability. If RND is greater than the win probability, the Republican wins the state. If RND is less than the win probability, Obama wins the state. The winner of the election trial is the candidate who has at least 270 electoral votes. The process is repeated in 500 election trials.
2008 State Exit Poll and recorded vote data is displayed in the ‘2008‘ worksheet. The latest state polls are listed in the ‘Trend/Chart” worksheet, The data is displayed graphically in the ‘PollChart’ worksheet. A histogram of the Monte Carlo Simulation (500 trials) is displayed in the ‘ObamaEVChart’ worksheet.
Electoral Votes and Win Probabilities
The Electoral Vote is calculated in three ways.
1. The Snapshot EV is a simple summation of the state electoral votes. It could be misleading since there may be several very close elections which favor one candidate.
2. The Mean EV is the average electoral vote of the 500 simulated elections.
3. The Theoretical (expected) EV is the product sum of all state electoral votes and corresponding win probabilities. A simulation or meta-analysis is not required to calculate the expected EV.
The Mean EV approaches the Theoretical EV as the number of election trials increase. This is an illustration of the Law of Large Numbers.
Obama’s electoral vote win probability is his winning percentage of 500 simulated election trials.
The national popular vote win probability is calculated using the normal distribution using the national aggregate of the the projected vote shares. The national aggregate margin of error is 1-2% lower than the average MoE of the individual states. That is, if you believe the Law of Large Numbers and convergence to the mean.
The Fraud Factor
Election fraud reduced the 1988-2008 Democratic presidential unadjusted exit poll margin from 52-42% to 48-46%. View the 1988-2008 Unadjusted State and National Exit Poll Database
The combination of True Vote Model and state poll-based Monte Carlo Simulation enables the analyst to determine if the electoral and popular vote share estimates are plausible. The aggregate state poll shares can be compared to the default TVM.
The TVM can be forced to match the aggregate poll projection by…
- Adjusting vote shares by an incremental change. A red flag would be raised if the match required, if for example Obama captured 85% of returning Obama voters and Romney had 95% of returning McCain voters (a 10% net defection).
- Adjusting 2008 voter turnout in 2012. For example, if McCain voter turnout is required to be 10-15% higher than Obama’s, that would raise a red flag.
- Setting the returning voter option to the 2008 recorded vote. The implicit assumption is that the 2008 recorded vote was the True Vote. But the 2008 election was highly fraudulent. Therefore, model vote shares will closely match the likely voter polls.
Check the simulated, theoretical and snapshot electoral vote projections and corresponding win probabilities.
Election Model Projections: 2004-2010
In 2004, I created the Election Model , and posted weekly forecasts using the latest state and national polls. The model was the first one to use Monte Carlo simulation and sensitivity analysis to calculate the probability of winning the electoral vote. The final Nov.1 forecast had Kerry winning 337 electoral votes with 51.8% of the two-party vote. The forecast closely matched the unadjusted exit polls.
In 2006, the adjusted National Exit Poll indicated that the Democrats won the House by a 52-46% vote share. But the 120 Generic Poll Forecasting Regression Model indicated that they would have 56.4% – exactly matching the unadjusted exit poll.
The 2008 Election Model projection exactly matched Obama’s 365 electoral votes and was within 0.2% of his 52.9% recorded share. He won by 9.5 million votes. But the model understated his True Vote. The forecast was based on final likely voter (LV) polls that had Obama leading by 7%. Registered voter (RV) polls had him up by 13% – before undecided voter allocation. The landslide was denied. The post-election True Vote Model determined that Obama won by 23 million votes with 420 EV. His 58% share matched the unadjusted state exit poll aggregate (83,000 respondents).
Exit pollsters and media pundits have never explained the massive 11% state exit poll margin discrepancy or the impossible 17% National Exit Poll discrepancy. If they did, they would surely claim that the discrepancies were due to reluctant Republican responders. But they will not even try to explain the impossible returning voter adjustments required to force the polls to match the recorded vote in the 1988, 1992, 2004 and 2008 elections.
Pre-election RV and LV Polls
Virtually all early pre-election polls are of Registered Voters (RV). An exception is the Rasmussen poll. It uses the Likely Voter (LV) subset of the full RV sample. Rasmussen is an admitted GOP pollster.
One month prior to the election, pollsters replace the full RV sample polls with LV subsamples. The RV polls are transformed to LVs to promote an artificial “horse race” – and the poll shares invariably tighten. The Likely Voter Cutoff Model (LVCM) effectively understates the turnout of millions of new Democratic voters – and therefore increases the projected Republican share. Democrats always do better in RV polls than in the LVs.
Media pundits and pollsters are paid to project the recorded vote – not the True Vote. And they are usually right. The closer they are, the better they look. They expect there will be fraud, so they prepare the public for it by switching to LV polls which are usually excellent predictors of the recorded vote. But they never mention the fraud factor which gets them there.
Historically, RV polls have closely matched the unadjusted exit polls after undecided voters were allocated and have confirmed the True Vote Model. The loop is closed when implausible or impossible exit polls are forced to match the recorded votes predicted by LV pre-election polls that were overweighted for the Republicans.
About Richard Charnin
In 1965, I graduated from Queens College (NY) with a BA in Mathematics. I later obtained an MS in Applied Mathematics from Adelphi University and an MS in Operations Research from the Polytechnic Institute of NY. I started out as a numerical control engineer/programmer for a major defense/aerospace manufacturer and then moved to Wall Street as a manager/developer of corporate finance quantitative applications for several major investment banks. I consulted in quantitative applications development for major domestic and foreign financial institutions, investment firms and industrial corporations. In 2004 l began posting weekly “Election Model” projections based on state and national polls. As “TruthIsAll”, I have been posting election analysis to determine the True Vote ever since. View all posts by Richard Charnin
