We are well versed in using statistical tools and techniques in analyzing information to test hypothesis and draw conclusions. We have aided equity analysts, investment professionals, market researchers and corporates in their decision making through advanced correlation, regression and sensitivity techniques. Examples include:
- Stock-interest rate sensitivity analysis
- Correlations between different variables
- Single-factor and multiple-factor regressions on varied datasets
Statistical analysis to gauge effectiveness of portfolio allocation strategies
Methodology included back testing portfolio modeling and allocation strategies of a major international fund manager for its effectiveness in delivering the best relative returns. Statistical methods used included Spearman’s rank correlation, standard deviation and co-efficient of variation. Analysis was also used to comment on the stock rating policy employed by the client and the extent of correlation between stock performance and ranking/rating.
Stock Rate Sensitivity
Detailed statistical analysis of a major banking and financial services stock to establish its relationship (sensitivity) with global and local interest rates (nominal and real) and the benchmark index. Analysis included the use of correlation and regression models to explain past behavior and predict future movements.
Stock Analysis
Statistical analysis of a company’s share price to benchmark performance against its peers. Analysis entailed the construction of a bespoke index for select sector stocks to arrive at the benchmark performance rate to target above the CPI and bank rate.
Research support provided for studying the effects of El Nino on the weather, with respective to effects on US and Australian commodities
Analysis provided included single-factor regressions on time series data for select commodity and stock prices in US and Australia against temperature and precipitation anomalies in key geographical regions.
