Cinemark Holdings Alpha and Beta Analysis Overview

CNK -- USA Stock  

USD 36.44  0.53  1.43%

This module allows you to check different measures of market premium for Cinemark Holdings as well as systematic risk associated with investing in Cinemark Holdings over a specified time horizon. Check also Cinemark Holdings Backtesting, Cinemark Holdings Valuation, Cinemark Holdings Correlation, Cinemark Holdings Hype Analysis, Cinemark Holdings Volatility, Cinemark Holdings History and analyze Cinemark Holdings Performance.
 Time Horizon     30 Days    Login   to change
Symbol
Run Premiums

Cinemark Holdings Market Premiums

α0.20β0.48
30 days against DJI
Risk Adjusted Performance  

0.0439

Jensen Alpha  

0.101

Total Risk Alpha  

0.0109

Sortino Ratio  

0.0452

Treynor Ratio  

0.59

Cinemark Holdings expected buy-and-hold returns

Cinemark Holdings Market Price Analysis

Cinemark Holdings Return and Market Media

The median price of Cinemark Holdings for the period between Sat, Jul 21, 2018 and Mon, Aug 20, 2018 is 35.77 with a coefficient of variation of 2.33. The daily time series for the period is distributed with a sample standard deviation of 0.83, arithmetic mean of 35.68, and mean deviation of 0.69. The Stock received substential amount of media coverage during this period.
 Price Growth (%)  
      Timeline 
1
Is Cinemark Holdings, Inc. s Proft Growth of -0.10823 Enough...07/31/2018
2
Exercise or conversion by Zuehlke Steve D of 1400 shares of ...08/03/2018
3
Cinemark 2Q Earnings Snapshot08/08/2018
4
Acquisition by Sean Gamble of 8031 shares of Cinemark Holdin...08/14/2018

Upcoming Events

Cinemark Holdings Upcoming Company Events
Upcoming Quarterly ReportMay 9, 2017
Next Earnings ReportAugust 8, 2017

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Check also Cinemark Holdings Backtesting, Cinemark Holdings Valuation, Cinemark Holdings Correlation, Cinemark Holdings Hype Analysis, Cinemark Holdings Volatility, Cinemark Holdings History and analyze Cinemark Holdings Performance. Please also try Watchlist Optimization module to optimize watchlists to build efficient portfolio or rebalance existing positions based on mean-variance optimization algorithm.