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SHEP does not rely solely on asset allocation and subjective rebalancing to reduce risks in client portfolios. It:
The SHEP Advantage, leading with protection, is key to delivering alpha.
Streaming live trading data is a key enabler of the SHEP® platform’s potential for delivering timely and accurate decisioning to effectuate its rules-based protection and performance objectives.
The use of technical indicators is core to rationalizing the current and anticipated market movements, supply and demand, and other market psychological factors.
Our proprietary branch of advanced analytics that assimilates historical data, momentum factors, unique smoothing analytics, and statistical modeling while attempting to formulate predictive patterns that enable The Edge to better discern anticipated future outcomes.
Our algorithmic consensus is a culmination of 63 relational rules-based parameters and customized risk threshold metrics whose outputs produce the SHEP® Advantage.
Executing SHEP® investment strategies with accuracy and speed not only reduces the chance for manual errors, but it also avoids emotional bias and subjectivity in trading decisions, benefitting from strict adherence in each strategy’s buy and sell discipline.
Our SHEP Advantage is produced by combining our powerful SHEP technology platform with our proprietary algorithm, the SHEP Edge. Together, investors can remain confident that our automation may improve their portfolios ability to respond effectively to ever-changing market environments. With each successful risk mitigation trade cycle, starting with protecting first, and then followed by successful timely reentries, investors can benefit from compounding more and more shares over time—The SHEP Advantage.
The beginning of the Modern Portfolio Theory dates back to 1952 with American economist Harry Markowitz. His position was that any given investment’s risk and return characteristics should not be viewed alone; rather, it should be analyzed by how it affects the overall portfolio’s risk and return. He discovered that by constructing portfolios using multiple asset classes that one could achieve greater returns without exposing themselves to higher levels of risk. In 1990, Dr. Harry Markowitz shared the Nobel Prize in Economics for this work.
The Modern Portfolio Theory remains the primary method in which investment portfolios are constructed today. It is foundational to how we create efficient portfolios to meet your clients’ return expectations at lower levels of risks. Yet we take it one step further, actively managing each security in client portfolios with SHEP, applying technical analysis in further pursuit of reducing risk and enhancing performance for your clients.
Technical analysis, as we know it today, was first introduced by Charles Dow and the Dow Theory in the late 1800s. Today, it has evolved to include hundreds of patterns and signals developed through years of research.
It is an investment discipline that attempts to forecast the price movement of virtually any tradable instrument that is generally subject to forces of supply and demand, including stocks, bonds, futures, and currencies. In fact, some view technical analysis as simply the study of supply and demand forces as reflected in the market price movements of a security. Professional technical analysts typically accept three general assumptions for the discipline:
Our SHEP algorithm uniquely identifies correlations between multiple momentum indicators and their respective security’s trading prices. The relationships between these two components are unique to each security in the SHEP portfolio, allowing SHEP to seek optimal returns for less risks that better protect your clients.
Goals-Based Investing (GBI) is much like it sounds. It is the development of an investment architecture specifically designed to accomplish financial goals funded within specific time frames. These constructs are generally known to rely on a combination of investments that, more specifically, minimize the probability of failing to achieve at least a minimum financial target level within a given time period.
We contend that the SHEP sell discipline, designed to anticipate and respond to market downturns by attempting to protect clients from harm, may be better positioned to accomplish their financial goals in shorter timeframes than some other conventional methods. Our defensive risk management strategy is designed to minimize downside risks. If successful, we may be able to optimize performance with significantly lower risks of shortfalls in the event of adverse market conditions.