Alphabet Backtesting

GOOG -- USA Stock  

USD 1,170  1.78  0.15%

With this equity back-testing module your can estimate the performance of a buy and hold strategy of Alphabet and determine expected loss or profit from investing in Alphabet over given investment horizon. Please also check Alphabet Hype Analysis, Alphabet Correlation, Alphabet Valuation, Alphabet Volatility as well as analyze Alphabet Alpha and Beta and Alphabet Performance.
 Time Horizon     30 Days    Login   to change

Alphabet 'What if' Analysis

May 21, 2018
No Change 0.00  0.0%
In 31 days
June 20, 2018
If you would invest  0.00  in Alphabet on May 21, 2018 and sell it all today you would earn a total of 0.00 from holding Alphabet or generate 0.0% return on investment in Alphabet over 30 days. Alphabet is related to or competes with Broadridge Financial, CDW, Hewlett Packard, Workday, , Salesforce, and Bank of America C. Alphabet Inc., through its subsidiaries, provides online advertising services in the United States and internationally

Alphabet Upside/Downside Indicators

Downside Deviation0.7738
Information Ratio0.3337
Maximum Drawdown4.33
Value At Risk1.15
Potential Upside1.84

Alphabet Market Premium Indicators

Risk Adjusted Performance0.01
Sortino Ratio0.4801

Alphabet Backtested Returns

Macroaxis considers Alphabet not too risky given 1 month investment horizon. Alphabet secures Sharpe Ratio (or Efficiency) of 0.3337 which signifies that Alphabet had 0.3337% of return per unit of risk over the last 1 month. Our philosophy towards foreseeing volatility of a stock is to use all available market data together with company specific technical indicators that cannot be diversified away. We have found twenty technical indicators for Alphabet which you can use to evaluate future volatility of the firm. Please makes use of Alphabet Coefficient Of Variation of 299.72, Risk Adjusted Performance of 0.01 and Mean Deviation of 0.8961 to double-check if our risk estimates are consistent with your expectations. On a scale of 0 to 100 Alphabet holds performance score of 22. The firm shows Beta (market volatility) of 0.0 which signifies that the returns on MARKET and Alphabet are completely uncorrelated. Although it is vital to follow to Alphabet historical returns, it is good to be conservative about what you can actually do with the information regarding equity current trending patterns. The philosophy towards foreseeing future performance of any stock is to evaluate the business as a whole together with its past performance including all available fundamental and technical indicators. By analyzing Alphabet technical indicators you can presently evaluate if the expected return of 0.3715% will be sustainable into the future. Please makes use of Alphabet Variance, Maximum Drawdown as well as the relationship between Maximum Drawdown and Semi Variance to make a quick decision on weather Alphabet price patterns will revert.
Advice Volatility Trend Exposure Correlations
15 days auto-correlation 0.84 

Very good predictability

Alphabet has very good predictability. Overlapping area represents the amount of predictability between Alphabet time series from May 21, 2018 to June 5, 2018 and June 5, 2018 to June 20, 2018. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Alphabet price movement. The serial correlation of 0.84 indicates that around 84.0% of current Alphabet price fluctuation can be explain by its past prices.
Correlation Coefficient 0.84
Spearman Rank Test 0.69
Price Variance 261.76
Lagged Price Variance 737.2

Alphabet lagged returns against current returns

 Current and Lagged Values 

Alphabet regressed lagged prices vs. current prices

 Current vs Lagged Prices 

Alphabet Lagged Returns

 Regressed Prices 

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Please also check Alphabet Hype Analysis, Alphabet Correlation, Alphabet Valuation, Alphabet Volatility as well as analyze Alphabet Alpha and Beta and Alphabet Performance. Please also try Watchlist Optimization module to optimize watchlists to build efficient portfolio or rebalance existing positions based on mean-variance optimization algorithm.