Equities

TST Equities Systems

A Visual Collaboration System for Equities Professionals

TST Equities Systems meet the need of equities professionals to make better decisions by systematically – yet intuitively and dynamically – managing the qualitative elements that drive stock prices. These elements include macro factors like geopolitics, social cohesion and Sunni/Shia sectarianism,  management, new technologies, government regulations, catalysts, black swans, and industry- and stock-specific risks. You can quantify your QL judgments and then synthesize them with traditional QT data, such as valuation, financial performance and technical analysis, in one seamless TST model.  This page has many examples, starting with two Morgan Stanley research reports and ending with a table that describes a sample of the model templates.

The competitive advantage is that your team can synthesize your most important information as a logical whole in a way your peers cannot using QT models only.  The benefits of this synthesis advantage are increased accuracy, transparency and efficiency which, in turn, lead to higher revenues, lower costs and higher profits.

TST Equities Systems is our most developed professional intelligence system.  It includes sub-systems for industry groups, diversified portfolios, and emerging markets. You can rank any universe of stocks by relative risk/reward under any scenarios based upon any set of QL+QT metrics using the 15+ model templates we have created as a starting point.  These sophisticated models embed multiple investment styles and were co-developed with directors of research, analysts, traders, portfolio managers & investment bankers with decades of experience.  The first Morgan Stanley report headlined below describes the TST value proposition, methodology and benefits.

First Morgan Stanley Report – 2005-6 Version 1

Morgan Stanley Snapshot

THINKSheet™ Model Structure – First Morgan Stanley Research Report

The model structure below demonstrates the importance the Morgan Stanley senior analyst attached to the qualitative factors of catalysts, risks (expectations, execution & acquisitions) and x factors. He weighted his 25 QT metrics 60% and his QL metrics 40%. He subsequently realized that it was more productive to prioritize the metrics he considered most important so he reduced the number of QT metrics from 25 to 6. You can see the 2015 version of his model below in the section entitled “TST Enabled the Morgan Stanley Analyst to Improve his Thought Process”.

MorganStanleyTSTModelStructure2

 Selected Quotes about THINKSHEET from First Morgan Stanley Report

The analyst described the THINKSheet methodology, value proposition and benefits in the above report, which is available below. The quotes below are extracts from that report.

“Truer To Life” Approach

By merging critical issues analysis with a traditional quantitative approach, we believe we are creating a robust analytical approach and one “truer to life” than that provided by a quant-based methodology alone.

Apples To Apples Comparisons

The model (employing ThinkSheet™ software and applications) relies on a number of algorithms that quantify the value of our thought process per stock and then re-computes the inputs to provide comparability.

Therefore, our thoughts on the strategy or leadership or market risks facing each individual company are comparable in measurement to the stock’s underlying P/E or earnings growth assessment.

In turn, by creating a truly apples-to- apples comparable measurement system for our entire universe, we believe, we are better able to compare seemingly different companies such as Moody’s, New York Times, or R.R. Donnelley on the same basis.

Relative Value Criteria

The aim of the exercise, as with our prior ranking system, is to identify the cheapest stocks with the best fundamentals that have a near-term, positive catalyst, low risk, and beneficial X-factors.

What’s New

In re-introducing and, we believe, enhancing our stock ranking methodology, eleven valuation inputs and fourteen financial measures (all individually ranked and scaled) represent only 60% of the weighted score for each stock.

The balance, or 40% of the weighted score, is the quantification of critical/subjective issues or catalysts, risks, and — what we call — the “X-factor” (or unique attribute per stock).

We are attempting to supplement largely efficiently priced-in valuation and financial measures for each stock by quantifying our major thoughts / concerns / expectations for each company/stock in a systematic method.

TST Reports are Shorter, More Comprehensive & Easier-To-Understand

The next six Morgan Stanley reports illustrate how TST reports are shorter, more comprehensive and easier-to-understand than traditional research reports – making the exchange of ideas with buy-side clients more productive.

Last THINKSheet Report

MorganStanleyLastReportCover

Click on cover page to enlarge

The report at left includes 2 introductory text pages and 10 TST models. The communications power of the TST models enabled the Morgan Stanley team to compare their long term ratings and short-term rankings (Exhibit 4, page 4); synthesize the most important elements of their ranking process on one page (Exhibit 5, page 5); break down the process into sub-models (Critical Issues – Exhibit 6; Valuation – Exhibit 7; and Financials – Exhibit 8); and supplement the models with snippets of text for each stock (Exhibit 10, pages 10-12).

To read last report, click: Last Report

To read first report, click: First Report

First Morgan Stanley Report: Ranking Example & Catalyst Definition

Catalysts Definition

The investment world, the buy side and sell side alike, are in constant search for the burning “catalyst” for any particular stock story. Potential catalysts can be good, bad, or non-existent depending on the time-period.  Our model weights the catalyst factor heavily or 17.5% of the entire weighted sum score. We score the catalyst factor employing seven different scores between 100% (the most positive) and “0”.

First Morgan Stanley Report, page 4

From the catalysts selected by the Morgan Stanley team for each stock, communicated and quantified using one of our proprietary Professional Language Similarity Functions, ThinkSHEET assigned a symbol for each catalyst and color-coded them to highlight their impact on the overall results.

MorganStanleyCatalysts

You can see at a glance that the Ad turn at Times/Globe +++ catalyst for New York Times had the most positive impact, while Vocational school exposure for Washington Post the most negative impact.

TST enabled Morgan Stanley team to create QL+QT Histories of their Stocks

You can create comprehensive histories of your stock analyses and their performance. The model below shows the change in the Moody’s analysis from report to report.

Moody’s History

MoodysHistoryXXX

You can see at a glance why Moody’s ranking moved from 5th to 15th and then back to 5th over the model history. This movement was in spite of the fact that Moody’s Financials (highest weighted metric at 35%) remained “Outstanding” throughout the period. Its ranking fell from 5th to 15th in 1 month primarily due to the deterioration in the X Factor – a key factor at 17.5% weight.  The team’s X Factor judgment changed from “International Growth structured finance +++” (max positive) to “Int’l growth / Spitzer subpoena -” (slight negative), reducing the Overall Score by 52% from 51% to -1%. Moody’s then rose back to 5th with a 56% score primarily due to the X factor moving up to neutral from slightly negative.

TST Enabled Morgan Stanley Analyst to Improve his Thought Process

(2015 Model Version)

Douglas Arthur, the lead analyst at Morgan Stanley who authored the above report, improved both his thought process and his TST model over time. His 2015 model changed:

  • QT metrics from 25 to 6
  • Catalysts to Short Term Catalysts
  • X Factors to Black Swans
  • QT and QL weights from 60% & 40%, respectively, to 40% & 60%.

He also changed the 3 Risks from Expectations, Execution & Acquisitions to Quarterly Momentum, Demand and Industry Dynamics.  The updated model structure is below:

EvercoreTSTModelStructure

 

THINKSheet is a semantics-driven model that features user-driven language with the greatest meaning in the fewest words. Replacing Catalysts with Short Term Catalysts not only communicated the metric’s meaning more clearly but also the different time frames for his ratings (12 months) and TST rankings (3-6 months).  Using Short Term Catalysts saved him significant explanatory text in explaining to his readers the different time frames between his ratings & rankings.

TSTCatalystsEvercore

Catalysts Histories

A user simply enters new catalysts into the model as soon as they are identified. For example, the user entered the three catalysts for Facebook: the IPO, the WhatsApp Acquisition and the Q1 numbers for Mobile Ad Revenues in terms of language and scoring equivalents.

You can maintain a history of how stocks performed over different market cycles and time periods, viewing a specific metric or a combination of metrics, on both a sub-model and a complete model basis.

Facebook Historical Catalysts

FacebookCatalysts

The THINKSheet symbols (– – –, +++, and none = neutral) and colors highlight the user’s judgment about the catalyst’s impact on the Facebook stock price: IPO: very negative; WhatsApp Acquisition: neutral; and Mobile Ad Numbers 2014: very positive.

Evercore Partners – Weighted Risk Index

EvercorePartnersMcGrawHill

Hedge Fund Manager’s Adaptation to New Market Cycle

The difference between QT and QL models is illustrated by the contrasting ThinkSHEET™ models used before and during the 2008-2011 financial crisis by a hedge fund manager specializing in bank & thrift stocks . Prior to the financial crisis, he used an all QT model because the markets were stable and he trusted the reported numbers. During the crisis, he switched to an all-QL model because he considered the reported numbers meaningless.

All QT Model – Before 2008-10 Financial Crisis

Dale Pre-Financial Crisis
All QL Model – During Financial Crisis

Bank Risk Model

Multiple Financial Crisis Scenarios

Who believes the US is invulnerable to another financial crisis that could drive the Dow back down to 6,500 and the S&P to 650? Many events in isolation or in combination could cause it, such as the ones described by Andrew Ross Sorkin in “Too Big To Fail“.

Too Big To Fail

THINKSheet enables you to build a comprehensive set of logically consistent scenarios based on your own judgments regarding the most probable set of conditions that could result in a financial crisis.  For example, you could consider factors such as China Hard Landing, EU break-up, war in the Middle East, and/or rapid rise in global interest rates.

You then update your facts and judgments dynamically as conditions change. You can then see the impact of the scenarios on any set of global markets, sectors, industries and/or individual stocks.

TST Equities Model Template Inventory Samples

TST Equities Systems includes a large inventory of model templates co-developed with premier directors of research, sell- & buy-side analysts, portfolio managers, traders and strategists – most of whom are shareholders.  The co-developers leveraged our proprietary non-numerical algorithms to compare their judgments about their stocks using the same methods of comparison and rich language they use to speak and write in the ordinary course of business. E.g., stories, metaphors, themes, acronyms, and hierarchies.

The templates are modular, enabling us to work with you to copy sub-model, metric, rich comparison language, scenario, and logic modules and recombine them into customized TST models that meet your specific needs.  The templates embed a broad variety of asset classes, investment styles, model structures, market cycles, scenarios, and judgments in non-numerical language.  The table below summarizes the QL & QT metrics for a sample set of TST Equities templates.

QL+QT Metrics for Sample Equities Templates

MetricsSummary

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