Updates Equity Market Data (#5576)

* Updates Equity Market Data

* Updates Unit Tests

* Updates Regression Tests

In this commit we include regression tests with small changes (slightly different CAGR, Alpha, etc, but same number of trades) due to the data update.

* Updates Regression Tests 2

The following regression tests were adapt because of verification of hard-coded market data values:
- `AdjustedVolumeRegressionAlgorithm`
- `HistoryWithSymbolChangesRegressionAlgorithm`
- `OptionRenameRegressionAlgorithm`
- `RawDataRegressionAlgorithm`
- `SwitchDataModeRegressionAlgorithm`

The following regression tests have more trades since adjusted prices allowed more 1-2 shares trades that were rounded down to zero before:
- `AddUniverseSelectionModelCoarseAlgorithm` 23 -> 35
- `MeanVarianceOptimizationFrameworkAlgorithm` 12 -> 14
- `PortfolioRebalanceOnDateRulesRegressionAlgorithm` 298 -> 324
- `PortfolioRebalanceOnInsightChangesRegressionAlgorithm` 83 -> 86
- `ScheduledUniverseSelectionModelRegressionAlgorithm` 86 -> 90
- `SectorExposureRiskFrameworkAlgorithm` 17 -> 22
- `SetHoldingsMultipleTargetsRegressionAlgorithm` 8 -> 9
- `StandardDeviationExecutionModelRegressionAlgorithm` 196 -> 199
- `UniverseUnchangedRegressionAlgorithm` 11 -> 17
- `VolumeWeightedAveragePriceExecutionModelRegressionAlgorithm` 237 -> 238

Especial cases:
- `BlackLittermanPortfolioOptimizationFrameworkAlgorithm` 18 -> 17
 - BLM model sensibility
- `OptionChainedAndUniverseSelectionRegressionAlgorithm`

The following regression tests have different Capacity because of different volume from lowest capacity asset, except:
- `OptionEquityCoveredCallRegressionAlgorithm` New lowest capacity asset is underlying
- `OptionEquityCoveredPutRegressionAlgorithm` New lowest capacity asset is underlying

* Revert File Update for SPWR and SPWRA

* Fix Regression Tests

Temporarily removes python regression test for `MeanVarianceOptimizationFrameworkAlgorithm` as the `MeanVarianceOptimizationPortfolioConstructionModel` for each version are yeilding different results. If we use C# version in `MeanVarianceOptimizationPortfolioConstructionModel.py`, the results match.

* Changes Optimization Method in MinimumVariancePortfolioOptimizer [Py]

Uses `trust-constr`  method.
See https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html

Algorithm.CSharp/CustomDataUsingMapFileRegressionAlgorithm.cs

@@ -124,22 +124,22 @@ namespace QuantConnect.Algorithm.CSharp
             {"Total Trades", "1"},
             {"Average Win", "0%"},
             {"Average Loss", "0%"},
-            {"Compounding Annual Return", "-99.920%"},
-            {"Drawdown", "11.100%"},
+            {"Compounding Annual Return", "-99.907%"},
+            {"Drawdown", "11.000%"},
             {"Expectancy", "0"},
-            {"Net Profit", "-10.486%"},
-            {"Sharpe Ratio", "-1.534"},
+            {"Net Profit", "-10.343%"},
+            {"Sharpe Ratio", "-1.554"},
             {"Probabilistic Sharpe Ratio", "0.001%"},
             {"Loss Rate", "0%"},
             {"Win Rate", "0%"},
             {"Profit-Loss Ratio", "0"},
-            {"Alpha", "-0.909"},
-            {"Beta", "-5.676"},
-            {"Annual Standard Deviation", "0.651"},
-            {"Annual Variance", "0.424"},
-            {"Information Ratio", "-1.362"},
-            {"Tracking Error", "0.745"},
-            {"Treynor Ratio", "0.176"},
+            {"Alpha", "-0.91"},
+            {"Beta", "-5.602"},
+            {"Annual Standard Deviation", "0.643"},
+            {"Annual Variance", "0.413"},
+            {"Information Ratio", "-1.378"},
+            {"Tracking Error", "0.736"},
+            {"Treynor Ratio", "0.178"},
             {"Total Fees", "$0.00"},
             {"Estimated Strategy Capacity", "$0"},
             {"Lowest Capacity Asset", "NWSA.CustomDataUsingMapping T3MO1488O0H0"},
@@ -147,7 +147,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Kelly Criterion Estimate", "0"},
             {"Kelly Criterion Probability Value", "0"},
             {"Sortino Ratio", "79228162514264337593543950335"},
-            {"Return Over Maximum Drawdown", "-9.383"},
+            {"Return Over Maximum Drawdown", "-9.481"},
             {"Portfolio Turnover", "0.249"},
             {"Total Insights Generated", "0"},
             {"Total Insights Closed", "0"},
@@ -162,7 +162,7 @@ namespace QuantConnect.Algorithm.CSharp
             {"Mean Population Magnitude", "0%"},
             {"Rolling Averaged Population Direction", "0%"},
             {"Rolling Averaged Population Magnitude", "0%"},
-            {"OrderListHash", "1c319ae4b15416184a247bb47b31aabc"}
+            {"OrderListHash", "d4cf2839e74df7fa436e30f44be4cb57"}
         };
 
         /// <summary>