Quantitative Finance @ Electraphysics
At Electraphysics, algorithmic black-boxes colloquially referred to as "robots" are engineered to execute investment decisions based on adaptive quantitative models, heavily incorporating machine learning and artificial intelligence.
The use of algorithms and numerical models when managing portfolios is at the core of quantitative finance at Electraphysics.
The automated execution and management of investments based on underlying stochastic asset models offer tremendous advantages, not present when humans attempt to perform the same task.
Model design is a science of mathematically studying asset prices, macroeconomic, company, sentiment data; and new data-types to determine causal relationships. This process identifies correlated or causal effects between inputs and observed outputs that are consistent, replicable and importantly - investable.
On this website, experiment with theories in research surrounding advanced portfolio management and finance; testing postulates by using your own test data and our systems - online through our website in a convenient way.
Portfolio managers and finance professionals that do not have a strong background in advanced mathematics find the implementation of the research very challenging. Electraphysics has done that for you.
For each theory presented, we demonstrate an actual implementation of it. Including modern and research 100+ years old.
We have referenced and attached the respective paper with each theory for easy access and reading for your convenience.
Experimentation will help demonstrate how MNLSH implements, utilizes and ensembles some of these concepts for superior portfolio and risk management in our return generating systems, without interfering with or risking our intellectual property.
MNLSH utilizes 500+ non-proprietary and Electraphysics proprietary research implementations, studied over 14 years.
If you do not have test data, you may use stored historical data from MNLSH from the data-downloader.
Data Downloader
If you do not have asset data, you are welcome to use ours. MNLSH has data for thousands of companies traded in multiple markets and exchanges, available to you here for free. This data can be used to test the theories and research presented here.
Disclosed Research Implementations (113).
Absorption Ratio
Adjusted Prices
Alpha
Arithmetic Average Return
Arithmetic Return
Assets / Correlation Matrix
Assets / Covariance Matrix
Assets / Kurtosis
Assets / Monte Carlo Returns Simulation
Assets / Prices
Assets / Returns
Assets / Returns Simulation
Assets / Skewness
Assets / Variance
Assets / Volatility
Beta
Bias-Adjusted Sharpe Ratio
Bootstrap
Cornish-Fisher Distribution
Cornish-Fisher Value At Risk
Corrected Cornish-Fisher Distribution
Corrected Cornish-Fisher Value At Risk
Correlation Matrix
Correlation Matrix Bounds
Correlation Matrix Distance
Correlation Matrix Effective Rank
Correlation Matrix Informativeness
Correlation Matrix Shrinkage
Correlation Matrix Validation
Correlation Spectrum
Covariance Matrix
Covariance Matrix Effective Rank
Covariance Matrix Validation
Denoised Correlation Matrix
Diversification Ratio
Diversified Maximum Return Portfolio
Diversified Maximum Sharpe Ratio Portfolio
Diversified Mean-Variance Efficient Portfolio
Diversified Minimum Variance Portfolio
Drawdowns
Drift-weight Portfolio Rebalancing
Effective Number of Bets
Equal Risk Contributions Portfolio
Equal Sharpe Ratio Contributions Portfolio
Equal Volatility Weighted Portfolio
Equal Weighted Portfolio
Exponentially Weighted Covariance Matrix
Factor Exposures
Factors
Fast Threshold Clustering
Fixed-weight Portfolio Rebalancing
Forward-Adjusted Prices
Gaussian Distribution
Gaussian Value At Risk
Gerber Correlation Matrix
Hierarchical Clustering Risk Parity Portfolio
Hierarchical Risk Parity Portfolio
Historical Conditional Value At Risk
Historical Value At Risk
Inverse Variance Weighted Portfolio
Inverse Volatility Weighted Portfolio
Investable Portfolio
Kurtosis
Logarithmic Returns
Market Capitalization Weighted Portfolio
Maximum Decorrelation Portfolio
Maximum Return Portfolio
Maximum Sharpe Ratio Portfolio
Maximum Ulcer Performance Index Portfolio
Mean-Variance Efficient Frontier
Mean-Variance Efficient Portfolio
Mean-Variance Minimum Variance Frontier
Mimicking Portfolio
Minimum Correlation Portfolio
Minimum Track Record Length
Minimum Ulcer Index Portfolio
Minimum Variance Portfolio
Most Diversified Portfolio
Nearest Correlation Matrix
Portfolio Analysis
Portfolio Analysis / Conditional Value At Risk
Portfolio Analysis / Sharpe ratio
Portfolio Analysis / Value At Risk
Portfolio Construction
Portfolio Optimization
Portfolio Optimization / Mean-Variance
Portfolio Simulation
Probabilistic Sharpe Ratio
Random Correlation Matrix
Random Portfolio
Random-weight Portfolio Rebalancing
Residualization
Return Contributions
Risk Contributions
Sharpe Ratio
Sharpe Ratio Confidence Interval
Skewness
Spearman Correlation Matrix
Subset Resampling-Based Maximum Return Portfolio
Subset Resampling-Based Maximum Sharpe Ratio Portfolio
Subset Resampling-Based Mean-Variance Efficient Portfolio
Subset Resampling-Based Minimum Variance Portfolio
Theory-Implied Correlation Matrix
Tracking Error
Turbulence Index
Turbulence-partitioned Asset Returns
Ulcer Index
Ulcer Performance Index
Variance
Volatility
Volatility (inverse)
This area is under development.
Research and Engineering
corporate site: electraphysics.com