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FI_V2: Smart Beta Investment Strategies
This lecture talks about the concept of 'Smart Beta Investment Strategies'. Examples are value, momentum, illiquidity, credit, short vol,
มุมมอง: 352

วีดีโอ

FI_V3: Factor Pricing Models
มุมมอง 2842 ปีที่แล้ว
This lecture talks about factor pricing models. Topics include: Single-factor Beta Models, Multi-factor Beta Models, Time-series Factor Models, Cross-Section Factor Models
FI_V4: Managing a Large Set of Risk Factors (Gram-Schmidt Orthogonalization)
มุมมอง 1762 ปีที่แล้ว
This lecture talks about the question on how to manage a portfolio of many, potentially correlated, risk factors. One particularly appealing approach is the Gram-Schmidt orthogonalization. That approach is often used in academic empirical research to circumvent the problem of multi-collinearity and to keep interpretation at a maximum. Simplistically speaking, each factor contains only informati...
FI_V5: Classical Linear Factor Models
มุมมอง 1732 ปีที่แล้ว
This lecture talks about classical linear factor models, using the general set-up of linear factor pricing models. Content includes: CAPM, Fama-French 3-factor model, Mertons's Intertemporal CAPM, Non-tradeable risk factors, Petkova (2006, JF),
FI_V6: Risk Management with Linear Factor Models
มุมมอง 1722 ปีที่แล้ว
This lecture talks about how linear factor models are used for managing risks. Content include 1. Risk decomposition: Total Risk = Systematic Risk Idiosyncratic Risk 2. Using factor models to compute the Covariance Matrix of Returns in a time efficient way 3. Decomposing the Covariance Matrix into Systematic Risks
FI_V7: Fama-MacBeth Approach for Estimating Market Prices of RIsk
มุมมอง 1.1K2 ปีที่แล้ว
This video talks about the seminal work of Fama, MacBeth (1973). The method is widely used to estimate the unconditional market price of risk.
FI_V1: Norway's Sovereign Wealth Fund
มุมมอง 2612 ปีที่แล้ว
Prof. Maxim Ulrich explains by example why the Sovereign Wealth Fund of Norway is a poster child for successful factor investing.
MV_V8: Diversification
มุมมอง 1742 ปีที่แล้ว
This lecture provides an introduction into the concept of "diversification".
FI_V10: Harvesting Dynamic Risk Premiums using Value, Carry, Momentum and Short Vol Strategies
มุมมอง 1843 ปีที่แล้ว
Prof. Maxim Ulrich talks about how to set-up and harvest Dynamic Risk Premium Strategies. This short overview covers the following trading strategies: value, carry, momentum, volatility.
FI_V13: Replicating Factor Anomalies
มุมมอง 1043 ปีที่แล้ว
This lecture talks about Factor Anomalies. The literature has put forward roughly 500 hundred alpha strategies, also called factor anomalies. A recent RFS publication of Hou, Xue and Zhang fails to replicate most of these 500 strategies, highlighting the danger of overfitting, p-hacking and being fooled by randomness.
FI_V9: Harvesting Static Factor Risk Premiums in Equity, Bond and Credit Markets
มุมมอง 1173 ปีที่แล้ว
Prof. Maxim Ulrich talks about static risk premiums. The premiums under consideration are the . equity risk premium . a bond's duration premium . credit premium. Empirical evidence for the US and for non-US countries is presented. The video also talks about how to rationalize static risk premiums, using the Gordon Growth Model.
FI_V8: Application for I-CAPM and Fama-MacBeth
มุมมอง 2853 ปีที่แล้ว
Prof. Maxim Ulrich talks about an application to add insights into the working of the I-CAPM and the Fama-MacBeth approach of determining the market price of factor risk. The application is based on the Journal of Finance publication of Petkova (2006).
KV8: How to estimate VAR with MLE
มุมมอง 1173 ปีที่แล้ว
KV8: How to estimate VAR with MLE
KV7: How to estimate VAR with Least Squares Method
มุมมอง 1233 ปีที่แล้ว
KV7: How to estimate VAR with Least Squares Method
KV6: How to generate unique IRFs - Cholesky Decomposition
มุมมอง 3993 ปีที่แล้ว
KV6: How to generate unique IRFs - Cholesky Decomposition
KV5: Impulse- Response Functions (IRF) of a VAR(1)
มุมมอง 6343 ปีที่แล้ว
KV5: Impulse- Response Functions (IRF) of a VAR(1)
KV4: How to simulate an VAR(1) Model
มุมมอง 723 ปีที่แล้ว
KV4: How to simulate an VAR(1) Model
KV3: Recursive Forecasting of VAR(1). How to use a VAR(1) model for computing forecasts efficiently
มุมมอง 1803 ปีที่แล้ว
KV3: Recursive Forecasting of VAR(1). How to use a VAR(1) model for computing forecasts efficiently
KV2: Rewriting ARMA(p,q) as VAR(1) - Trick that allows you to focus on the VAR(1) model only
มุมมอง 1243 ปีที่แล้ว
KV2: Rewriting ARMA(p,q) as VAR(1) - Trick that allows you to focus on the VAR(1) model only
KV1: Set up empirical risk model that accounts for conditional co-variation among risk factors
มุมมอง 1983 ปีที่แล้ว
KV1: Set up empirical risk model that accounts for conditional co-variation among risk factors
NDAM_V3: How to Account for Higher Moment Risk when building Optimal Portfolios?
มุมมอง 1393 ปีที่แล้ว
NDAM_V3: How to Account for Higher Moment Risk when building Optimal Portfolios?
NDAM_V1: Why do Rule-based Portfolio Strategies beat Mean-Variance Allocations?
มุมมอง 2053 ปีที่แล้ว
NDAM_V1: Why do Rule-based Portfolio Strategies beat Mean-Variance Allocations?
Returns are usually Negatively Skewed! A T- and E-GARCH help you to capture skewness and heterosc.
มุมมอง 1973 ปีที่แล้ว
Returns are usually Negatively Skewed! A T- and E-GARCH help you to capture skewness and heterosc.
Do S&P 500 Returns follow an GARCH? Working on that, we learn how to estimate a GARCH from scratch
มุมมอง 3733 ปีที่แล้ว
Do S&P 500 Returns follow an GARCH? Working on that, we learn how to estimate a GARCH from scratch
Do S&P 500 Returns follow an ARCH(m)? Using the Application we learn how to Estimate ARCH(m) Models
มุมมอง 1263 ปีที่แล้ว
Do S&P 500 Returns follow an ARCH(m)? Using the Application we learn how to Estimate ARCH(m) Models
Do S&P 500 Returns follow an ARCH(1)? Using that application we learn how to Estimate an ARCH(1)
มุมมอง 1453 ปีที่แล้ว
Do S&P 500 Returns follow an ARCH(1)? Using that application we learn how to Estimate an ARCH(1)
ARCH(1) Model for Vol Forecasting
มุมมอง 2243 ปีที่แล้ว
ARCH(1) Model for Vol Forecasting
Test #2 for whether a Time Series has Stochastic Volatility: LM Test
มุมมอง 2253 ปีที่แล้ว
Test #2 for whether a Time Series has Stochastic Volatility: LM Test
Test #1 for whether a Time Series is Heteroscedastic (i.e. Portmanteau Test to Detect ARCH Effects)
มุมมอง 4513 ปีที่แล้ว
Test #1 for whether a Time Series is Heteroscedastic (i.e. Portmanteau Test to Detect ARCH Effects)
How do I Test whether a Time Series has Stochastic Volatility (Heteroscedasticity)?
มุมมอง 2793 ปีที่แล้ว
How do I Test whether a Time Series has Stochastic Volatility (Heteroscedasticity)?

ความคิดเห็น

  • @PurohitAnkit
    @PurohitAnkit 2 หลายเดือนก่อน

    Dear Professor. Thank you for sharing your insights and knowledge with us. I have been looking at asset pricing literature for quite some time but still lacked the required clarity. Your video brought me clarity on the concepts and even the methodology

  • @SamSawClay
    @SamSawClay 3 หลายเดือนก่อน

    great work🎉

  • @tormodular
    @tormodular 3 หลายเดือนก่อน

    Hi mate, just thought you might be interested that we found this effect in Australian stocks back in 2013. The reference is Bowers, Heaton (2013) "What Does High Dimensional Factor Analysis Tell us About Risk Factors in the Australian Stock Market", and it was published in Applied Economics (I'm the Bowers part of that - Colin T Bowers). I actually also found it in US stocks almost two decades ago as part of a Masters research thesis. Interesting to see the effect is still alive and well today! I always felt like there was more to say about the fact that these methods always find the equal-weighted is a better fit than the value-weighted, which contradicts what classical portfolio theory tells us we should see. I never got around to looking in it further though.

  • @aryamankochhar
    @aryamankochhar 3 หลายเดือนก่อน

    WOw,thank you so much

  • @blackbeard9217
    @blackbeard9217 4 หลายเดือนก่อน

    Could you elaborate on the third reason the Ito integral is important in finance? Thanks. (I didn't get the part about holdings/innovations etc.)

  • @justqian2061
    @justqian2061 4 หลายเดือนก่อน

    After I finished this entire playlist does it mean I will qualify to become quant

  • @fiinanccewallah3535
    @fiinanccewallah3535 4 หลายเดือนก่อน

    respeced sir solution?

  • @prestonle8993
    @prestonle8993 4 หลายเดือนก่อน

    Why can we write Sigma tilde as P’xSigmaxP? 5:34

  • @HitAndMissLab
    @HitAndMissLab 5 หลายเดือนก่อน

    You are so bad at communicating with laymen then you will absolutely, never, never grow your channel to 100,000 subs. You have to stop explaining as if you are talking to experts. Experts wouldn't care because they already know this stuff.

  • @AminaAmina-by4oh
    @AminaAmina-by4oh 10 หลายเดือนก่อน

    Peace be upon you. Please send me books related to the subject. Thank you.

  • @AminaAmina-by4oh
    @AminaAmina-by4oh 10 หลายเดือนก่อน

    Peace be upon you. Please send me books related to the subject. Thank you.

  • @DrBluefox
    @DrBluefox 10 หลายเดือนก่อน

    This is so based

  • @richiebailey8163
    @richiebailey8163 ปีที่แล้ว

    You said that half of the financial risk management literature is written using stochastic calculus, what is the other half written using?

    • @CRAM-KIT
      @CRAM-KIT ปีที่แล้ว

      discrete time. note, the statement was a couple of years ago. recently, the ratio changed. as more and more data applications are run, most analysis is in discrete time.

    • @will-ti2qs
      @will-ti2qs 6 หลายเดือนก่อน

      @@CRAM-KITso is stochastic calculus less useful ? Is it because data is based on real observations rather than estimations?

  • @QihengFang
    @QihengFang ปีที่แล้ว

    nice

  • @abdullhafezdaoud9412
    @abdullhafezdaoud9412 ปีที่แล้ว

    Subtitle your video or enable automatic subtitles

  • @abdullhafezdaoud9412
    @abdullhafezdaoud9412 ปีที่แล้ว

    ضع ترجمة على الفيديو يا محترم

  • @bhavinmoriya9216
    @bhavinmoriya9216 ปีที่แล้ว

    Thanks very much for the wonderful videos. What is an ITO process?

  • @Daniel88santos
    @Daniel88santos ปีที่แล้ว

    Hello ... I'm an electronics engineer trying to enter in to finance. I'm exploring all the solutions that I can. So I came across with your channel, it seems great content! I've seen that you did some videos on Kalman, however this type of filter is applicable only to gaussian distributions, which is not the case for the majority of the instruments/assets. Did you know if the finance industry explored/uses Particle Filters or Sequential Monte Carlo as an alternative to Kalman filters? ... Another questions, but this one regarding Factors I've seen that you use PCA, but again for that you need to assume several things on your data and the main one is that the several parameters (factors) that you are trying to apply reduction are linearly related. Did you've tried anything rather than PCA? thanks. Regards Daniel

    • @CRAM-KIT
      @CRAM-KIT ปีที่แล้ว

      great questions. it shows you are a deep data thinker! yes, there is published research on alternative, non-linear and non-Gaussian filters. Note, KF is L2 optimal even if shocks are not Gaussian. Linearizing the system has shown some success as particle and sequential monte carlo filters have their robustness issues as well; at least in our experiments. Last, PCA is good for Gaussian data. Kernel PCA and Instrumental PCA has been recently applied to account for nonlinearities in data.

  • @NikitaBotnakov
    @NikitaBotnakov ปีที่แล้ว

    It makes sense to say that increments of W_t are not only pairwise independent.

  • @NikitaBotnakov
    @NikitaBotnakov ปีที่แล้ว

    Thank you!

  • @samyakkandoi7626
    @samyakkandoi7626 ปีที่แล้ว

    Can you provide some examples or link for the use of fubini's trick, used for integrating stochastic integral.

  • @wajihchtiba34
    @wajihchtiba34 ปีที่แล้ว

    That is an error in the data. as simple as that. I have checked it in other sources. These jumps didn't occur in that period.

    • @CRAM-KIT
      @CRAM-KIT ปีที่แล้ว

      I agree. I was simply surprised by that finding

  • @kydkidd
    @kydkidd ปีที่แล้ว

    Is that possible to extract what is the weight of stocks for the first pc?

    • @CRAM-KIT
      @CRAM-KIT ปีที่แล้ว

      yes, that can be done

  • @junpengqiu4054
    @junpengqiu4054 ปีที่แล้ว

    and this is what's behind the algorithm of current popular AI image generative model. (I am serious)

    • @CRAM-KIT
      @CRAM-KIT ปีที่แล้ว

      please feel free to give us more insights

  • @NathanLGrossman
    @NathanLGrossman ปีที่แล้ว

    Dr. Ulrich, I really appreciate your pedagogical approach--not too theoretical but still mathematically rigorous and hands-on. Are slides you present in these videos available anywhere? Regards, Nathan

    • @CRAM-KIT
      @CRAM-KIT ปีที่แล้ว

      I might have slides. My experience is that these calculations need to be shown on the white board

    • @ua697
      @ua697 ปีที่แล้ว

      For those viewers, who are a bit rusty in linear ODEs, it can be mentioned that the application of the product rule 2:10 is based on the following calculation : dln(u)/dt = du/dt/u(t) = p(t) -> du/dt = p(t)u(t)

  • @QuantitativeDiaries
    @QuantitativeDiaries ปีที่แล้ว

    Great explanation! Thank you

  • @gieuncho3664
    @gieuncho3664 ปีที่แล้ว

    before I found this course, I was scared by "stochastic calculus" I was like what does that even mean? then I came across with this baby course, I am like ahh! it is differential equation i did in my uni course but the answer is pdf rather than a normal equation! much clearer, simpler, great introduction to stochastic calculus for a newbie like me :) thank you so much!

  • @priteshgohil7026
    @priteshgohil7026 ปีที่แล้ว

    you are speaking very low even i can't hear you properly in earbuds

    • @CRAM-KIT
      @CRAM-KIT ปีที่แล้ว

      these are old recordings with insufficient testing. sorry

    • @vp922
      @vp922 ปีที่แล้ว

      @@CRAM-KIT nevertheless nice of u to do them - thanks!

  • @DrAtomics
    @DrAtomics ปีที่แล้ว

    Hey do you know of any good books on learning stochastic calculus?

    • @CRAM-KIT
      @CRAM-KIT ปีที่แล้ว

      kerry back: asset pricing and portfolio choice. for real stoch calc, go to oksendal book on SDEs or any math fin book on financial mathematics.

    • @DrAtomics
      @DrAtomics ปีที่แล้ว

      @@CRAM-KIT thanks for the reply, I'm reading through Oksendal's book rn but find it to be so dry and stale.

  • @Chenfei00
    @Chenfei00 ปีที่แล้ว

    Very Detailed Information and video! Thank you!

  • @firstolasto1518
    @firstolasto1518 ปีที่แล้ว

    Brilliant! Thank you!

  • @giovannipaolo2137
    @giovannipaolo2137 2 ปีที่แล้ว

    Great video

  • @이성진-i3h
    @이성진-i3h 2 ปีที่แล้ว

    4:39 what the video name is? I cannot find separable Ito SDE viedo in your channel..

    • @buscxc
      @buscxc ปีที่แล้ว

      th-cam.com/video/HOH2xvvaDL0/w-d-xo.html

  • @BMAA2009
    @BMAA2009 2 ปีที่แล้ว

    The volume is way too low

    • @CRAM-KIT
      @CRAM-KIT ปีที่แล้ว

      yes; that was not our intention. any idea on how to fix is without re-recording?

    • @david-liorusa6422
      @david-liorusa6422 8 หลายเดือนก่อน

      Great explanation.

  • @SyedZahedi
    @SyedZahedi 2 ปีที่แล้ว

    That biscuit line really got me!

  • @qiguosun129
    @qiguosun129 2 ปีที่แล้ว

    Great lecture! Thanks!

    • @CRAM-KIT
      @CRAM-KIT 2 ปีที่แล้ว

      thanks.

  • @표세윤-u3w
    @표세윤-u3w 2 ปีที่แล้ว

    such a good motivation from ODE to SDE

  • @maggiechen8356
    @maggiechen8356 2 ปีที่แล้ว

    Hi

  • @tobiaskaiser669
    @tobiaskaiser669 2 ปีที่แล้ว

    Thank you Sir

  • @paolopantaleo7135
    @paolopantaleo7135 2 ปีที่แล้ว

    Very clear explanation.

  • @kevinowino6983
    @kevinowino6983 3 ปีที่แล้ว

    Thanks so much for this awesome work. Though I have a question which is abit outside this context. What is the behavior when two independent stochastic differential equations are multiplied?

    • @CRAM-KIT
      @CRAM-KIT 3 ปีที่แล้ว

      same as when multiplying two independent random numbers. For the exact answer apply Ito Lemma. makes sense?

  • @sidddddddddddddd
    @sidddddddddddddd 3 ปีที่แล้ว

    5:27 Did you mean that r_1^tilda conditioned on F_0 follows the distribution on the RHS? I'm more used to seeing ~ than a =

    • @CRAM-KIT
      @CRAM-KIT 3 ปีที่แล้ว

      yes!

  • @SoumyadeepMisra7
    @SoumyadeepMisra7 3 ปีที่แล้ว

    Thank you soo much for this, I was looking all over the internet but could not find such a simple & logical explanation of SDE...

  • @tetrusadima
    @tetrusadima 3 ปีที่แล้ว

    Subscribed, liked and appreciated. Thank you

  • @rockbobrocks
    @rockbobrocks 3 ปีที่แล้ว

    I noticed that too. Sometimes the decimal point in their data is shifted by one on some days, thus giving a huge change in one direction and on the next day an equally large change back to the original value. Other times the faulty data is a bit random. I assume you are using yfinance, which might also be the culprit and not yahoo itself. However, I still did not find a reliable method to correct for this. If you do, let me know :)

  • @miketan373
    @miketan373 3 ปีที่แล้ว

    supi tnx

  • @user-or7ji5hv8y
    @user-or7ji5hv8y 3 ปีที่แล้ว

    The fonts are really small. Might be helpful if we can get access to the notebooks.

  • @user-or7ji5hv8y
    @user-or7ji5hv8y 3 ปีที่แล้ว

    can we get access to the notebooks?

  • @shivanighodekar2112
    @shivanighodekar2112 3 ปีที่แล้ว

    May I know your references?

    • @CRAM-KIT
      @CRAM-KIT 3 ปีที่แล้ว

      Cannot remember. Yet, the following references might be useful: Kerry Back's book and the book/lecture notes of Claus Munk. Kind regards.

    • @shivanighodekar9232
      @shivanighodekar9232 3 ปีที่แล้ว

      @@CRAM-KIT many thanks

  • @user-or7ji5hv8y
    @user-or7ji5hv8y 3 ปีที่แล้ว

    The intuition was so helpful.