# Assuming ‘price_data’ is a data frame with the first column as ‘Date’ and the rest as asset prices.
# Converting price data to log returns for individual assets
prices <- as.matrix(price_data[,-1]) # Exclude ‘Date’ column and convert to a matrix
log_returns <- diff(log(prices)) # Calculate log returns

# Handling missing values if present
returns_data <- na.omit(log_returns) # Remove NAs from returns data

# Calculate the index returns as the average of all asset log returns per time period
# This assumes an equally weighted index
index_log_returns <- rowMeans(returns_data, na.rm = TRUE) # Mean log return of all assets

# Adding index returns to the matrix of returns for analysis
# Ensure that ‘index_log_returns’ is properly formatted to match dimensions
# It should be a single column matrix to bind with ‘returns_data’
index_log_returns_matrix <- matrix(index_log_returns, ncol = 1)

# Adding the index returns as a new column in ‘returns_data’
all_returns_data <- cbind(returns_data, index_log_returns_matrix)

# Providing appropriate column names, especially for the newly added index
colnames(all_returns_data) <- c(colnames(returns_data), "Index Returns")

# Ensure all_returns_data is in a format acceptable by fPortfolio::basicStats
library(fPortfolio)
if (!is.timeSeries(all_returns_data)) {
    all_returns_data <- as.timeSeries(all_returns_data)
}

# Estimate Summary Statistics for the Returns (Both Individual Assets and the “Market Index”)
summary_stats <- basicStats(all_returns_data)
print(summary_stats)
Above code i have done is for Estimate the Summary Statistics for the Returns (Index and Asset) and comment on it. Note, the answer must state clearly which return measure you are using and the reason for opting that measure as an estimate for return.

Insert the code chunk below. this question 
And the case was Case Begins:
You have recently joined as a Portfolio Manager at Morgan Stanley. The first task assigned to you is to create a portfolio for a client who is interested in investing 1 million Euro in secondary markets. He wants the money to be "fully-invested", but he is not aware of weight allocation in a scientific manner. Your employer has given you the responsibility to not only select the bunch of asset class for investment, but also allocate weight so as to garner more returns with limited risk.
After analyzing the market trends, you are bullish in your approach and have narrowed down to the three asset classes for selection of Portfolio Universe.
1.	Stocks - Google, Tesla, Pfizer, Shell, AT&T
2.	Forex - USDINR, EURUSD, USDCAD, USDCHF, NZDUSD
3.	Commodities - Crude, Natural Gas, Gold, Wheat, Ethanol
Asset	Tickr
Google	GOOGL
Tesla	TSLA
Pfizer	PFE
Shell	SHEL
AT&T	T
USDINR	USDINR
EURUSD	EURUSD
USDCAD	USDCAD
USDCHF	USDCHF
NZDUSD	NZDUSD
Crude	WTI
Natural Gas	NG
Gold	XAU
Wheat	W1
Ethanol	EH
	
Note: Portfolio constraints from your supervisor
1.	Portfolio should consist of 5 assets
2.	Atleast one from Commodity and one from Forex
Now my second question is Portfolio Universe Selection

Since, you have to make a Portfolio constituting of five assets only, you select the assets based on the basis of two strategies as shared below.

Strategy 1:

Step 1: Calculate the Reward to Risk - (Median Return/Standard Deviation)

Step 2: Rank the Reward to Risk for Assets, then choose the top five asset while maintaining the constraint (Atleast one Commodity and one Forex)

Note: In case of tie, you choose the asset with higher mean return.

Strategy 2:

Based on Price/Earning Ratio while maintaining the constraint (Atleast one Commodity and one Forex)

Note: After filtering the 5 assets, export the file either as .csv or .xlsx.............................Can you please give me codes for second question