Sökning: "Asset pricing"

Visar resultat 1 - 5 av 307 uppsatser innehållade orden Asset pricing.

  1. 1. Active fund management or passive index cruising?

    Kandidat-uppsats, Göteborgs universitet/Institutionen för nationalekonomi med statistik

    Författare :Joel Johansson; Gustav Osbeck; [2020-08-07]
    Nyckelord :;

    Sammanfattning : How should an investor pick funds to invest in? What is the best strategy, picking active or passive funds? It’s hard to navigate the fund landscape when there is ambiguous evidence and advice coming from different directions. Do fund managers outperform the market and passive funds? Do they bring something extra of value to the table in regards to their high management fees? The question seems almost age-old at this point, from dart throwing monkeys outperforming high profile fund managers to famous investors proclaiming that active fund management is dead, it’s hard to know what is really true about active versus passive fund management. LÄS MER

  2. 2. Downside risk: is downside risk being priced in the U.S. stock market?

    Kandidat-uppsats,

    Författare :Raouf Bahsoun; Arsalan Hakimi; [2020-07-06]
    Nyckelord :Excess kurtosis; skewness; Value-at-Risk; Expected shortfall; semi deviation; downside beta; Sortino ratio; Fama-French three-factor model; Fama French Five Factor model; Carhart four-factor model; q-four factor model; q-five factor model; asset pricing; U.S. stock market;

    Sammanfattning : This paper aims to add further research to the field of downside risk, and downside risk measures’ influence on the average returns in the U.S. stock market. LÄS MER

  3. 3. Deep Learning and the Heston Model:Calibration & Hedging

    Kandidat-uppsats, Göteborgs universitet/Institutionen för nationalekonomi med statistik

    Författare :Oliver Klingberg Malmer; Victor Tisell; [2020-07-03]
    Nyckelord :deep learning; deep hedging; deep calibration; option pricing; stochastic volatilty; Heston model; S P 500 index options; incomplete markets; transaction costs;

    Sammanfattning : The computational speedup of computers has been one of the de ning characteristicsof the 21st century. This has enabled very complex numerical methods for solving existingproblems. As a result, one area that has seen an extraordinary rise in popularity over the lastdecade is what is called deep learning. LÄS MER

  4. 4. Tidying up the factor zoo: Using machine learning to find sparse factor models that predict asset returns.

    Kandidat-uppsats, Göteborgs universitet/Institutionen för nationalekonomi med statistik

    Författare :Oliver Klingberg Malmer; Gustav Pettersson; [2020-07-01]
    Nyckelord :Asset pricing; Factor models; Machine learning; PCA; LASSO; Variable selection; Dimension reduction; Fama French Three Factor model; Fama French Five Factor model;

    Sammanfattning : There exist over 300 firm characteristics that provide significant information about average asset return. John Cochrane refers to this as a “factor zoo” and challenges researchers to find the independent characteristics which can explain average return. LÄS MER

  5. 5. Predicting Asset Prices with Machine Learning

    Kandidat-uppsats,

    Författare :Adam Eklund; Valter Trollius; [2020-06-29]
    Nyckelord :Machine learning; neural networks; OLS regression; asset pricing; financial forecasting; out-of-sample; predictability;

    Sammanfattning : This study examines whether machine learning techniques such as neural networks contain predictability when modeling asset prices and if they can improve on asset pricing prediction compared to traditional OLS-regressions. This is analyzed through measuring and comparing the out-of-sample R2 to find each models’ predictive power. LÄS MER