mathematics

Steven E. Shreve

Steven E. Shreve is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Steven E. Shreve rather than just read about it. In short: Steven Eugene Shreve is a mathematician and a University Professor Emeritus in the Department of Mathematical Sciences at Carnegie Mellon University. He was previously the Orion Hoch Professor of Mathematical Sciences, which he held from 2006 until his retirement.

Key takeaways

Steven E. Shreve belongs to mathematics; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Steven E. Shreve to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Steven E. Shreve from memory before moving on to harder problems.

Reference excerpt

Steven Eugene Shreve is a mathematician and a University Professor Emeritus in the Department of Mathematical Sciences at Carnegie Mellon University. He was previously the Orion Hoch Professor of Mathematical Sciences, which he held from 2006 until his retirement. Shreve is also the author of several major books on the mathematics of financial derivatives. His first degree, awarded in 1972 was in German from West Virginia University. He then studied mathematics at Georg-August-Universität Göttingen. He then took a Masters in Electrical Engineering at the University of Illinois, where he completed a PhD in mathematics in 1977. Shreve joined the Carnegie Mellon faculty in 1980 and helped establish the university's bachelor's, master's and doctoral programs in computational and mathematical finance. In 2013, Carnegie Mellon named him a University Professor, the university's highest faculty distinction. His textbook Stochastic Calculus for Finance is used by numerous graduate programs in quantitative finance. The book was voted "Best New Book in Quantitative Finance" in 2004 by members of Wilmott website, and has been highly praised by scholars in the field. Shreve is a Fellow of the Institute of Mathematical Statistics.

Books Stochastic Optimal Control: The Discrete Time Case with Dimitri P. Bertsekas, Academic Press, 1978. Brownian Motion and Stochastic Calculus with Ioannis Karatzas Springer-Verlag, 2nd Ed. 1991. Methods of Mathematical Finance with Ioannis Karatzas Springer-Verlag, 1998 Stochastic Calculus for Finance. Volume I: The Binomial Asset Pricing Model Volume II: Continuous-Time Models Springer-Verlag, 2004 The most recent volume was awarded "New Book of the Year" by Wilmott magazine.

References

External links Shreve's Home Page Steven E. Shreve at the Mathematics Genealogy Project Steven E. Shreve publications indexed by Google Scholar

Worked examples

Example 1 — a first encounter with Steven E. Shreve

Start with the simplest possible case. Write down what Steven E. Shreve claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Steven E. Shreve before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Steven E. Shreve ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Steven E. Shreve

In research: Steven E. Shreve appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Steven E. Shreve in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Steven E. Shreve is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1950s births, 20th-century American statisticians, 21st-century American mathematicians, so understanding it makes those chapters shorter.
In everyday life: Look for Steven E. Shreve outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Steven E. Shreve in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Steven E. Shreve means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Steven E. Shreve out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Steven E. Shreve in simple terms?

Why does Steven E. Shreve matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Steven E. Shreve?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Steven E. Shreve.